Practical robustness measures in multivariable control system analysis. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Lehtomaki, N. A.

1981-01-01

The robustness of the stability of multivariable linear time invariant feedback control systems with respect to model uncertainty is considered using frequency domain criteria. Available robustness tests are unified under a common framework based on the nature and structure of model errors. These results are derived using a multivariable version of Nyquist's stability theorem in which the minimum singular value of the return difference transfer matrix is shown to be the multivariable generalization of the distance to the critical point on a single input, single output Nyquist diagram. Using the return difference transfer matrix, a very general robustness theorem is presented from which all of the robustness tests dealing with specific model errors may be derived. The robustness tests that explicitly utilized model error structure are able to guarantee feedback system stability in the face of model errors of larger magnitude than those robustness tests that do not. The robustness of linear quadratic Gaussian control systems are analyzed.

Study on Fuzzy Adaptive Fractional Order PIλDμ Control for Maglev Guiding System

NASA Astrophysics Data System (ADS)

Hu, Qing; Hu, Yuwei

The mathematical model of the linear elevator maglev guiding system is analyzed in this paper. For the linear elevator needs strong stability and robustness to run, the integer order PID was expanded to the fractional order, in order to improve the steady state precision, rapidity and robustness of the system, enhance the accuracy of the parameter in fractional order PIλDμ controller, the fuzzy control is combined with the fractional order PIλDμ control, using the fuzzy logic achieves the parameters online adjustment. The simulations reveal that the system has faster response speed, higher tracking precision, and has stronger robustness to the disturbance.

Robust design of feedback feed-forward iterative learning control based on 2D system theory for linear uncertain systems

NASA Astrophysics Data System (ADS)

Li, Zhifu; Hu, Yueming; Li, Di

2016-08-01

For a class of linear discrete-time uncertain systems, a feedback feed-forward iterative learning control (ILC) scheme is proposed, which is comprised of an iterative learning controller and two current iteration feedback controllers. The iterative learning controller is used to improve the performance along the iteration direction and the feedback controllers are used to improve the performance along the time direction. First of all, the uncertain feedback feed-forward ILC system is presented by an uncertain two-dimensional Roesser model system. Then, two robust control schemes are proposed. One can ensure that the feedback feed-forward ILC system is bounded-input bounded-output stable along time direction, and the other can ensure that the feedback feed-forward ILC system is asymptotically stable along time direction. Both schemes can guarantee the system is robust monotonically convergent along the iteration direction. Third, the robust convergent sufficient conditions are given, which contains a linear matrix inequality (LMI). Moreover, the LMI can be used to determine the gain matrix of the feedback feed-forward iterative learning controller. Finally, the simulation results are presented to demonstrate the effectiveness of the proposed schemes.

Robust Control of Uncertain Systems via Dissipative LQG-Type Controllers

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2000-01-01

Optimal controller design is addressed for a class of linear, time-invariant systems which are dissipative with respect to a quadratic power function. The system matrices are assumed to be affine functions of uncertain parameters confined to a convex polytopic region in the parameter space. For such systems, a method is developed for designing a controller which is dissipative with respect to a given power function, and is simultaneously optimal in the linear-quadratic-Gaussian (LQG) sense. The resulting controller provides robust stability as well as optimal performance. Three important special cases, namely, passive, norm-bounded, and sector-bounded controllers, which are also LQG-optimal, are presented. The results give new methods for robust controller design in the presence of parametric uncertainties.

Robust Nonlinear Feedback Control of Aircraft Propulsion Systems

NASA Technical Reports Server (NTRS)

Garrard, William L.; Balas, Gary J.; Litt, Jonathan (Technical Monitor)

2001-01-01

This is the final report on the research performed under NASA Glen grant NASA/NAG-3-1975 concerning feedback control of the Pratt & Whitney (PW) STF 952, a twin spool, mixed flow, after burning turbofan engine. The research focussed on the design of linear and gain-scheduled, multivariable inner-loop controllers for the PW turbofan engine using H-infinity and linear, parameter-varying (LPV) control techniques. The nonlinear turbofan engine simulation was provided by PW within the NASA Rocket Engine Transient Simulator (ROCETS) simulation software environment. ROCETS was used to generate linearized models of the turbofan engine for control design and analysis as well as the simulation environment to evaluate the performance and robustness of the controllers. Comparison between the H-infinity, and LPV controllers are made with the baseline multivariable controller and developed by Pratt & Whitney engineers included in the ROCETS simulation. Simulation results indicate that H-infinity and LPV techniques effectively achieve desired response characteristics with minimal cross coupling between commanded values and are very robust to unmodeled dynamics and sensor noise.

Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.

Uncertainty analysis and robust trajectory linearization control of a flexible air-breathing hypersonic vehicle

NASA Astrophysics Data System (ADS)

Pu, Zhiqiang; Tan, Xiangmin; Fan, Guoliang; Yi, Jianqiang

2014-08-01

Flexible air-breathing hypersonic vehicles feature significant uncertainties which pose huge challenges to robust controller designs. In this paper, four major categories of uncertainties are analyzed, that is, uncertainties associated with flexible effects, aerodynamic parameter variations, external environmental disturbances, and control-oriented modeling errors. A uniform nonlinear uncertainty model is explored for the first three uncertainties which lumps all uncertainties together and consequently is beneficial for controller synthesis. The fourth uncertainty is additionally considered in stability analysis. Based on these analyses, the starting point of the control design is to decompose the vehicle dynamics into five functional subsystems. Then a robust trajectory linearization control (TLC) scheme consisting of five robust subsystem controllers is proposed. In each subsystem controller, TLC is combined with the extended state observer (ESO) technique for uncertainty compensation. The stability of the overall closed-loop system with the four aforementioned uncertainties and additional singular perturbations is analyzed. Particularly, the stability of nonlinear ESO is also discussed from a Liénard system perspective. At last, simulations demonstrate the great control performance and the uncertainty rejection ability of the robust scheme.

Robust, nonlinear, high angle-of-attack control design for a supermaneuverable vehicle

NASA Technical Reports Server (NTRS)

Adams, Richard J.

1993-01-01

High angle-of-attack flight control laws are developed for a supermaneuverable fighter aircraft. The methods of dynamic inversion and structured singular value synthesis are combined into an approach which addresses both the nonlinearity and robustness problems of flight at extreme operating conditions. The primary purpose of the dynamic inversion control elements is to linearize the vehicle response across the flight envelope. Structured singular value synthesis is used to design a dynamic controller which provides robust tracking to pilot commands. The resulting control system achieves desired flying qualities and guarantees a large margin of robustness to uncertainties for high angle-of-attack flight conditions. The results of linear simulation and structured singular value stability analysis are presented to demonstrate satisfaction of the design criteria. High fidelity nonlinear simulation results show that the combined dynamics inversion/structured singular value synthesis control law achieves a high level of performance in a realistic environment.

Robust control of the DC-DC boost converter based on the uncertainty and disturbance estimator

NASA Astrophysics Data System (ADS)

Oucheriah, Said

2017-11-01

In this paper, a robust non-linear controller based on the uncertainty and disturbance estimator (UDE) scheme is successfully developed and implemented for the output voltage regulation of the DC-DC boost converter. System uncertainties, external disturbances and unknown non-linear dynamics are lumped as a signal that is accurately estimated using a low-pass filter and their effects are cancelled by the controller. This methodology forms the basis of the UDE-based controller. A simple procedure is also developed that systematically determines the parameters of the controller to meet certain specifications. Using simulation, the effectiveness of the proposed controller is compared against the sliding-mode control (SMC). Experimental tests also show that the proposed controller is robust to system uncertainties, large input and load perturbations.

Robust output tracking control of a laboratory helicopter for automatic landing

NASA Astrophysics Data System (ADS)

Liu, Hao; Lu, Geng; Zhong, Yisheng

2014-11-01

In this paper, robust output tracking control problem of a laboratory helicopter for automatic landing in high seas is investigated. The motion of the helicopter is required to synchronise with that of an oscillating platform, e.g. the deck of a vessel subject to wave-induced motions. A robust linear time-invariant output feedback controller consisting of a nominal controller and a robust compensator is designed. The robust compensator is introduced to restrain the influences of parametric uncertainties, nonlinearities and external disturbances. It is shown that robust stability and robust tracking property can be achieved simultaneously. Experimental results on the laboratory helicopter for automatic landing demonstrate the effectiveness of the designed control approach.

Robustness of linear quadratic state feedback designs in the presence of system uncertainty. [application to Augmentor Wing Jet STOL Research Aircraft flare control autopilot design

NASA Technical Reports Server (NTRS)

Patel, R. V.; Toda, M.; Sridhar, B.

1977-01-01

The paper deals with the problem of expressing the robustness (stability) property of a linear quadratic state feedback (LQSF) design quantitatively in terms of bounds on the perturbations (modeling errors or parameter variations) in the system matrices so that the closed-loop system remains stable. Nonlinear time-varying and linear time-invariant perturbations are considered. The only computation required in obtaining a measure of the robustness of an LQSF design is to determine the eigenvalues of two symmetric matrices determined when solving the algebraic Riccati equation corresponding to the LQSF design problem. Results are applied to a complex dynamic system consisting of the flare control of a STOL aircraft. The design of the flare control is formulated as an LQSF tracking problem.

Robust Stability and Control of Multi-Body Ground Vehicles with Uncertain Dynamics and Failures

DTIC Science & Technology

2010-01-01

and N. Zhang, 2008. “Robust stability control of vehicle rollover subject to actuator time delay”. Proc. IMechE Part I: J. of systems and control ...Dynamic Systems and Control Conference, Boston, MA, Sept 2010 R.K. Yedavalli,”Robust Stability of Linear Interval Parameter Matrix Family Problem...for control coupled output regulation for a class of systems is presented. In section 2.1.7, the control design algorithm developed in section

Fractional representation theory - Robustness results with applications to finite dimensional control of a class of linear distributed systems

NASA Technical Reports Server (NTRS)

Nett, C. N.; Jacobson, C. A.; Balas, M. J.

1983-01-01

This paper reviews and extends the fractional representation theory. In particular, new and powerful robustness results are presented. This new theory is utilized to develop a preliminary design methodology for finite dimensional control of a class of linear evolution equations on a Banach space. The design is for stability in an input-output sense, but particular attention is paid to internal stability as well.

Regional robust stabilisation and domain-of-attraction estimation for MIMO uncertain nonlinear systems with input saturation

NASA Astrophysics Data System (ADS)

Azizi, S.; Torres, L. A. B.; Palhares, R. M.

2018-01-01

The regional robust stabilisation by means of linear time-invariant state feedback control for a class of uncertain MIMO nonlinear systems with parametric uncertainties and control input saturation is investigated. The nonlinear systems are described in a differential algebraic representation and the regional stability is handled considering the largest ellipsoidal domain-of-attraction (DOA) inside a given polytopic region in the state space. A novel set of sufficient Linear Matrix Inequality (LMI) conditions with new auxiliary decision variables are developed aiming to design less conservative linear state feedback controllers with corresponding larger DOAs, by considering the polytopic description of the saturated inputs. A few examples are presented showing favourable comparisons with recently published similar control design methodologies.

Flight control application of new stability robustness bounds for linear uncertain systems

NASA Technical Reports Server (NTRS)

Yedavalli, Rama K.

1993-01-01

This paper addresses the issue of obtaining bounds on the real parameter perturbations of a linear state-space model for robust stability. Based on Kronecker algebra, new, easily computable sufficient bounds are derived that are much less conservative than the existing bounds since the technique is meant for only real parameter perturbations (in contrast to specializing complex variation case to real parameter case). The proposed theory is illustrated with application to several flight control examples.

H∞ robust fault-tolerant controller design for an autonomous underwater vehicle's navigation control system

NASA Astrophysics Data System (ADS)

Cheng, Xiang-Qin; Qu, Jing-Yuan; Yan, Zhe-Ping; Bian, Xin-Qian

2010-03-01

In order to improve the security and reliability for autonomous underwater vehicle (AUV) navigation, an H∞ robust fault-tolerant controller was designed after analyzing variations in state-feedback gain. Operating conditions and the design method were then analyzed so that the control problem could be expressed as a mathematical optimization problem. This permitted the use of linear matrix inequalities (LMI) to solve for the H∞ controller for the system. When considering different actuator failures, these conditions were then also mathematically expressed, allowing the H∞ robust controller to solve for these events and thus be fault-tolerant. Finally, simulation results showed that the H∞ robust fault-tolerant controller could provide precise AUV navigation control with strong robustness.

Robust Stabilization of Uncertain Systems Based on Energy Dissipation Concepts

NASA Technical Reports Server (NTRS)

Gupta, Sandeep

1996-01-01

Robust stability conditions obtained through generalization of the notion of energy dissipation in physical systems are discussed in this report. Linear time-invariant (LTI) systems which dissipate energy corresponding to quadratic power functions are characterized in the time-domain and the frequency-domain, in terms of linear matrix inequalities (LMls) and algebraic Riccati equations (ARE's). A novel characterization of strictly dissipative LTI systems is introduced in this report. Sufficient conditions in terms of dissipativity and strict dissipativity are presented for (1) stability of the feedback interconnection of dissipative LTI systems, (2) stability of dissipative LTI systems with memoryless feedback nonlinearities, and (3) quadratic stability of uncertain linear systems. It is demonstrated that the framework of dissipative LTI systems investigated in this report unifies and extends small gain, passivity, and sector conditions for stability. Techniques for selecting power functions for characterization of uncertain plants and robust controller synthesis based on these stability results are introduced. A spring-mass-damper example is used to illustrate the application of these methods for robust controller synthesis.

Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

NASA Technical Reports Server (NTRS)

Burken, John J.

2005-01-01

This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

Intelligent robust control for uncertain nonlinear time-varying systems and its application to robotic systems.

PubMed

Chang, Yeong-Chan

2005-12-01

This paper addresses the problem of designing adaptive fuzzy-based (or neural network-based) robust controls for a large class of uncertain nonlinear time-varying systems. This class of systems can be perturbed by plant uncertainties, unmodeled perturbations, and external disturbances. Nonlinear H(infinity) control technique incorporated with adaptive control technique and VSC technique is employed to construct the intelligent robust stabilization controller such that an H(infinity) control is achieved. The problem of the robust tracking control design for uncertain robotic systems is employed to demonstrate the effectiveness of the developed robust stabilization control scheme. Therefore, an intelligent robust tracking controller for uncertain robotic systems in the presence of high-degree uncertainties can easily be implemented. Its solution requires only to solve a linear algebraic matrix inequality and a satisfactorily transient and asymptotical tracking performance is guaranteed. A simulation example is made to confirm the performance of the developed control algorithms.

Robustness in linear quadratic feedback design with application to an aircraft control problem

NASA Technical Reports Server (NTRS)

Patel, R. V.; Sridhar, B.; Toda, M.

1977-01-01

Some new results concerning robustness and asymptotic properties of error bounds of a linear quadratic feedback design are applied to an aircraft control problem. An autopilot for the flare control of the Augmentor Wing Jet STOL Research Aircraft (AWJSRA) is designed based on Linear Quadratic (LQ) theory and the results developed in this paper. The variation of the error bounds to changes in the weighting matrices in the LQ design is studied by computer simulations, and appropriate weighting matrices are chosen to obtain a reasonable error bound for variations in the system matrix and at the same time meet the practical constraints for the flare maneuver of the AWJSRA. Results from the computer simulation of a satisfactory autopilot design for the flare control of the AWJSRA are presented.

Projection Operator: A Step Towards Certification of Adaptive Controllers

NASA Technical Reports Server (NTRS)

Larchev, Gregory V.; Campbell, Stefan F.; Kaneshige, John T.

2010-01-01

One of the major barriers to wider use of adaptive controllers in commercial aviation is the lack of appropriate certification procedures. In order to be certified by the Federal Aviation Administration (FAA), an aircraft controller is expected to meet a set of guidelines on functionality and reliability while not negatively impacting other systems or safety of aircraft operations. Due to their inherent time-variant and non-linear behavior, adaptive controllers cannot be certified via the metrics used for linear conventional controllers, such as gain and phase margin. Projection Operator is a robustness augmentation technique that bounds the output of a non-linear adaptive controller while conforming to the Lyapunov stability rules. It can also be used to limit the control authority of the adaptive component so that the said control authority can be arbitrarily close to that of a linear controller. In this paper we will present the results of applying the Projection Operator to a Model-Reference Adaptive Controller (MRAC), varying the amount of control authority, and comparing controller s performance and stability characteristics with those of a linear controller. We will also show how adjusting Projection Operator parameters can make it easier for the controller to satisfy the certification guidelines by enabling a tradeoff between controller s performance and robustness.

Sliding Mode Control of the X-33 with an Engine Failure

NASA Technical Reports Server (NTRS)

Shtessel, Yuri B.; Hall, Charles E.

2000-01-01

Ascent flight control of the X-3 is performed using two XRS-2200 linear aerospike engines. in addition to aerosurfaces. The baseline control algorithms are PID with gain scheduling. Flight control using an innovative method. Sliding Mode Control. is presented for nominal and engine failed modes of flight. An easy to implement, robust controller. requiring no reconfiguration or gain scheduling is demonstrated through high fidelity flight simulations. The proposed sliding mode controller utilizes a two-loop structure and provides robust. de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of engine failure, bounded external disturbances (wind gusts) and uncertain matrix of inertia. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues. Conditions that restrict engine failures to robustness domain of the sliding mode controller are derived. Overall stability of a two-loop flight control system is assessed. Simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in the presence of external disturbances and vehicle inertia uncertainties, as well as the single engine failed case. The designed robust controller will significantly reduce the time and cost associated with flying new trajectory profiles or orbits, with new payloads, and with modified vehicles

Robust gaze-steering of an active vision system against errors in the estimated parameters

NASA Astrophysics Data System (ADS)

Han, Youngmo

2015-01-01

Gaze-steering is often used to broaden the viewing range of an active vision system. Gaze-steering procedures are usually based on estimated parameters such as image position, image velocity, depth and camera calibration parameters. However, there may be uncertainties in these estimated parameters because of measurement noise and estimation errors. In this case, robust gaze-steering cannot be guaranteed. To compensate for such problems, this paper proposes a gaze-steering method based on a linear matrix inequality (LMI). In this method, we first propose a proportional derivative (PD) control scheme on the unit sphere that does not use depth parameters. This proposed PD control scheme can avoid uncertainties in the estimated depth and camera calibration parameters, as well as inconveniences in their estimation process, including the use of auxiliary feature points and highly non-linear computation. Furthermore, the control gain of the proposed PD control scheme on the unit sphere is designed using LMI such that the designed control is robust in the presence of uncertainties in the other estimated parameters, such as image position and velocity. Simulation results demonstrate that the proposed method provides a better compensation for uncertainties in the estimated parameters than the contemporary linear method and steers the gaze of the camera more steadily over time than the contemporary non-linear method.

Modern CACSD using the Robust-Control Toolbox

NASA Technical Reports Server (NTRS)

Chiang, Richard Y.; Safonov, Michael G.

1989-01-01

The Robust-Control Toolbox is a collection of 40 M-files which extend the capability of PC/PRO-MATLAB to do modern multivariable robust control system design. Included are robust analysis tools like singular values and structured singular values, robust synthesis tools like continuous/discrete H(exp 2)/H infinity synthesis and Linear Quadratic Gaussian Loop Transfer Recovery methods and a variety of robust model reduction tools such as Hankel approximation, balanced truncation and balanced stochastic truncation, etc. The capabilities of the toolbox are described and illustated with examples to show how easily they can be used in practice. Examples include structured singular value analysis, H infinity loop-shaping and large space structure model reduction.

Feedback system design with an uncertain plant

NASA Technical Reports Server (NTRS)

Milich, D.; Valavani, L.; Athans, M.

1986-01-01

A method is developed to design a fixed-parameter compensator for a linear, time-invariant, SISO (single-input single-output) plant model characterized by significant structured, as well as unstructured, uncertainty. The controller minimizes the H(infinity) norm of the worst-case sensitivity function over the operating band and the resulting feedback system exhibits robust stability and robust performance. It is conjectured that such a robust nonadaptive control design technique can be used on-line in an adaptive control system.

Design and experimental validation of linear and nonlinear vehicle steering control strategies

NASA Astrophysics Data System (ADS)

Menhour, Lghani; Lechner, Daniel; Charara, Ali

2012-06-01

This paper proposes the design of three control laws dedicated to vehicle steering control, two based on robust linear control strategies and one based on nonlinear control strategies, and presents a comparison between them. The two robust linear control laws (indirect and direct methods) are built around M linear bicycle models, each of these control laws is composed of two M proportional integral derivative (PID) controllers: one M PID controller to control the lateral deviation and the other M PID controller to control the vehicle yaw angle. The indirect control law method is designed using an oscillation method and a nonlinear optimisation subject to H ∞ constraint. The direct control law method is designed using a linear matrix inequality optimisation in order to achieve H ∞ performances. The nonlinear control method used for the correction of the lateral deviation is based on a continuous first-order sliding-mode controller. The different methods are designed using a linear bicycle vehicle model with variant parameters, but the aim is to simulate the nonlinear vehicle behaviour under high dynamic demands with a four-wheel vehicle model. These steering vehicle controls are validated experimentally using the data acquired using a laboratory vehicle, Peugeot 307, developed by National Institute for Transport and Safety Research - Department of Accident Mechanism Analysis Laboratory's (INRETS-MA) and their performance results are compared. Moreover, an unknown input sliding-mode observer is introduced to estimate the road bank angle.

A new robust adaptive controller for vibration control of active engine mount subjected to large uncertainties

NASA Astrophysics Data System (ADS)

Fakhari, Vahid; Choi, Seung-Bok; Cho, Chang-Hyun

2015-04-01

This work presents a new robust model reference adaptive control (MRAC) for vibration control caused from vehicle engine using an electromagnetic type of active engine mount. Vibration isolation performances of the active mount associated with the robust controller are evaluated in the presence of large uncertainties. As a first step, an active mount with linear solenoid actuator is prepared and its dynamic model is identified via experimental test. Subsequently, a new robust MRAC based on the gradient method with σ-modification is designed by selecting a proper reference model. In designing the robust adaptive control, structured (parametric) uncertainties in the stiffness of the passive part of the mount and in damping ratio of the active part of the mount are considered to investigate the robustness of the proposed controller. Experimental and simulation results are presented to evaluate performance focusing on the robustness behavior of the controller in the face of large uncertainties. The obtained results show that the proposed controller can sufficiently provide the robust vibration control performance even in the presence of large uncertainties showing an effective vibration isolation.

Linear quadratic servo control of a reusable rocket engine

NASA Technical Reports Server (NTRS)

Musgrave, Jeffrey L.

1991-01-01

The paper deals with the development of a design method for a servo component in the frequency domain using singular values and its application to a reusable rocket engine. A general methodology used to design a class of linear multivariable controllers for intelligent control systems is presented. Focus is placed on performance and robustness characteristics, and an estimator design performed in the framework of the Kalman-filter formalism with emphasis on using a sensor set different from the commanded values is discussed. It is noted that loop transfer recovery modifies the nominal plant noise intensities in order to obtain the desired degree of robustness to uncertainty reflected at the plant input. Simulation results demonstrating the performance of the linear design on a nonlinear engine model over all power levels during mainstage operation are discussed.

Linear quadratic servo control of a reusable rocket engine

NASA Technical Reports Server (NTRS)

Musgrave, Jeffrey L.

1991-01-01

A design method for a servo compensator is developed in the frequency domain using singular values. The method is applied to a reusable rocket engine. An intelligent control system for reusable rocket engines was proposed which includes a diagnostic system, a control system, and an intelligent coordinator which determines engine control strategies based on the identified failure modes. The method provides a means of generating various linear multivariable controllers capable of meeting performance and robustness specifications and accommodating failure modes identified by the diagnostic system. Command following with set point control is necessary for engine operation. A Kalman filter reconstructs the state while loop transfer recovery recovers the required degree of robustness while maintaining satisfactory rejection of sensor noise from the command error. The approach is applied to the design of a controller for a rocket engine satisfying performance constraints in the frequency domain. Simulation results demonstrate the performance of the linear design on a nonlinear engine model over all power levels during mainstage operation.

Robust Neighboring Optimal Guidance for the Advanced Launch System

NASA Technical Reports Server (NTRS)

Hull, David G.

1993-01-01

In recent years, optimization has become an engineering tool through the availability of numerous successful nonlinear programming codes. Optimal control problems are converted into parameter optimization (nonlinear programming) problems by assuming the control to be piecewise linear, making the unknowns the nodes or junction points of the linear control segments. Once the optimal piecewise linear control (suboptimal) control is known, a guidance law for operating near the suboptimal path is the neighboring optimal piecewise linear control (neighboring suboptimal control). Research conducted under this grant has been directed toward the investigation of neighboring suboptimal control as a guidance scheme for an advanced launch system.

LMI Based Robust Blood Glucose Regulation in Type-1 Diabetes Patient with Daily Multi-meal Ingestion

NASA Astrophysics Data System (ADS)

Mandal, S.; Bhattacharjee, A.; Sutradhar, A.

2014-04-01

This paper illustrates the design of a robust output feedback H ∞ controller for the nonlinear glucose-insulin (GI) process in a type-1 diabetes patient to deliver insulin through intravenous infusion device. The H ∞ design specification have been realized using the concept of linear matrix inequality (LMI) and the LMI approach has been used to quadratically stabilize the GI process via output feedback H ∞ controller. The controller has been designed on the basis of full 19th order linearized state-space model generated from the modified Sorensen's nonlinear model of GI process. The resulting controller has been tested with the nonlinear patient model (the modified Sorensen's model) in presence of patient parameter variations and other uncertainty conditions. The performance of the controller was assessed in terms of its ability to track the normoglycemic set point of 81 mg/dl with a typical multi-meal disturbance throughout a day that yields robust performance and noise rejection.

Model based control of dynamic atomic force microscope.

PubMed

Lee, Chibum; Salapaka, Srinivasa M

2015-04-01

A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H(∞) control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.

Generalized Predictive and Neural Generalized Predictive Control of Aerospace Systems

NASA Technical Reports Server (NTRS)

Kelkar, Atul G.

2000-01-01

The research work presented in this thesis addresses the problem of robust control of uncertain linear and nonlinear systems using Neural network-based Generalized Predictive Control (NGPC) methodology. A brief overview of predictive control and its comparison with Linear Quadratic (LQ) control is given to emphasize advantages and drawbacks of predictive control methods. It is shown that the Generalized Predictive Control (GPC) methodology overcomes the drawbacks associated with traditional LQ control as well as conventional predictive control methods. It is shown that in spite of the model-based nature of GPC it has good robustness properties being special case of receding horizon control. The conditions for choosing tuning parameters for GPC to ensure closed-loop stability are derived. A neural network-based GPC architecture is proposed for the control of linear and nonlinear uncertain systems. A methodology to account for parametric uncertainty in the system is proposed using on-line training capability of multi-layer neural network. Several simulation examples and results from real-time experiments are given to demonstrate the effectiveness of the proposed methodology.

Asymptotic Linearity of Optimal Control Modification Adaptive Law with Analytical Stability Margins

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2010-01-01

Optimal control modification has been developed to improve robustness to model-reference adaptive control. For systems with linear matched uncertainty, optimal control modification adaptive law can be shown by a singular perturbation argument to possess an outer solution that exhibits a linear asymptotic property. Analytical expressions of phase and time delay margins for the outer solution can be obtained. Using the gradient projection operator, a free design parameter of the adaptive law can be selected to satisfy stability margins.

Robust H∞ output-feedback control for path following of autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Hu, Chuan; Jing, Hui; Wang, Rongrong; Yan, Fengjun; Chadli, Mohammed

2016-03-01

This paper presents a robust H∞ output-feedback control strategy for the path following of autonomous ground vehicles (AGVs). Considering the vehicle lateral velocity is usually hard to measure with low cost sensor, a robust H∞ static output-feedback controller based on the mixed genetic algorithms (GA)/linear matrix inequality (LMI) approach is proposed to realize the path following without the information of the lateral velocity. The proposed controller is robust to the parametric uncertainties and external disturbances, with the parameters including the tire cornering stiffness, vehicle longitudinal velocity, yaw rate and road curvature. Simulation results based on CarSim-Simulink joint platform using a high-fidelity and full-car model have verified the effectiveness of the proposed control approach.

Robust model predictive control for constrained continuous-time nonlinear systems

NASA Astrophysics Data System (ADS)

Sun, Tairen; Pan, Yongping; Zhang, Jun; Yu, Haoyong

2018-02-01

In this paper, a robust model predictive control (MPC) is designed for a class of constrained continuous-time nonlinear systems with bounded additive disturbances. The robust MPC consists of a nonlinear feedback control and a continuous-time model-based dual-mode MPC. The nonlinear feedback control guarantees the actual trajectory being contained in a tube centred at the nominal trajectory. The dual-mode MPC is designed to ensure asymptotic convergence of the nominal trajectory to zero. This paper extends current results on discrete-time model-based tube MPC and linear system model-based tube MPC to continuous-time nonlinear model-based tube MPC. The feasibility and robustness of the proposed robust MPC have been demonstrated by theoretical analysis and applications to a cart-damper springer system and a one-link robot manipulator.

Robustness Analysis and Optimally Robust Control Design via Sum-of-Squares

NASA Technical Reports Server (NTRS)

Dorobantu, Andrei; Crespo, Luis G.; Seiler, Peter J.

2012-01-01

A control analysis and design framework is proposed for systems subject to parametric uncertainty. The underlying strategies are based on sum-of-squares (SOS) polynomial analysis and nonlinear optimization to design an optimally robust controller. The approach determines a maximum uncertainty range for which the closed-loop system satisfies a set of stability and performance requirements. These requirements, de ned as inequality constraints on several metrics, are restricted to polynomial functions of the uncertainty. To quantify robustness, SOS analysis is used to prove that the closed-loop system complies with the requirements for a given uncertainty range. The maximum uncertainty range, calculated by assessing a sequence of increasingly larger ranges, serves as a robustness metric for the closed-loop system. To optimize the control design, nonlinear optimization is used to enlarge the maximum uncertainty range by tuning the controller gains. Hence, the resulting controller is optimally robust to parametric uncertainty. This approach balances the robustness margins corresponding to each requirement in order to maximize the aggregate system robustness. The proposed framework is applied to a simple linear short-period aircraft model with uncertain aerodynamic coefficients.

Design and Experimental Evaluation of a Robust Position Controller for an Electrohydrostatic Actuator Using Adaptive Antiwindup Sliding Mode Scheme

PubMed Central

Lee, Ji Min; Park, Sung Hwan; Kim, Jong Shik

2013-01-01

A robust control scheme is proposed for the position control of the electrohydrostatic actuator (EHA) when considering hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. To reduce overshoot due to a saturation of electric motor and to realize robustness against load disturbance and lumped system uncertainties such as varying parameters and modeling error, this paper proposes an adaptive antiwindup PID sliding mode scheme as a robust position controller for the EHA system. An optimal PID controller and an optimal anti-windup PID controller are also designed to compare control performance. An EHA prototype is developed, carrying out system modeling and parameter identification in designing the position controller. The simply identified linear model serves as the basis for the design of the position controllers, while the robustness of the control systems is compared by experiments. The adaptive anti-windup PID sliding mode controller has been found to have the desired performance and become robust against hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. PMID:23983640

An H-infinity approach to optimal control of oxygen and carbon dioxide contents in blood

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Siano, Pierluigi; Selisteanu, Dan; Precup, Radu

2016-12-01

Nonlinear H-infinity control is proposed for the regulation of the levels of oxygen and carbon dioxide in the blood of patients undergoing heart surgery and extracorporeal blood circulation. The levels of blood gases are administered through a membrane oxygenator and the control inputs are the externally supplied oxygen, the aggregate gas supply (oxygen plus nitrogen), and the blood flow which is regulated by a blood pump. The proposed control method is based on linearization of the oxygenator's dynamical model through Taylor series expansion and the computation of Jacobian matrices. The local linearization points are defined by the present value of the oxygenator's state vector and the last value of the control input that was exerted on this system. The modelling errors due to linearization are considered as disturbances which are compensated by the robustness of the control loop. Next, for the linearized model of the oxygenator an H-infinity control input is computed at each iteration of the control algorithm through the solution of an algebraic Riccati equation. With the use of Lyapunov stability analysis it is demonstrated that the control scheme satisfies the H-infinity tracking performance criterion, which signifies improved robustness against modelling uncertainty and external disturbances. Moreover, under moderate conditions the asymptotic stability of the control loop is also proven.

Robust Hinfinity position control synthesis of an electro-hydraulic servo system.

PubMed

Milić, Vladimir; Situm, Zeljko; Essert, Mario

2010-10-01

This paper focuses on the use of the techniques based on linear matrix inequalities for robust H(infinity) position control synthesis of an electro-hydraulic servo system. A nonlinear dynamic model of the hydraulic cylindrical actuator with a proportional valve has been developed. For the purpose of the feedback control an uncertain linearized mathematical model of the system has been derived. The structured (parametric) perturbations in the electro-hydraulic coefficients are taken into account. H(infinity) controller extended with an integral action is proposed. To estimate internal states of the electro-hydraulic servo system an observer is designed. Developed control algorithms have been tested experimentally in the laboratory model of an electro-hydraulic servo system. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Extensions of output variance constrained controllers to hard constraints

NASA Technical Reports Server (NTRS)

Skelton, R.; Zhu, G.

1989-01-01

Covariance Controllers assign specified matrix values to the state covariance. A number of robustness results are directly related to the covariance matrix. The conservatism in known upperbounds on the H infinity, L infinity, and L (sub 2) norms for stability and disturbance robustness of linear uncertain systems using covariance controllers is illustrated with examples. These results are illustrated for continuous and discrete time systems. **** ONLY 2 BLOCK MARKERS FOUND -- RETRY *****

Linear Quantum Systems: Non-Classical States and Robust Stability

DTIC Science & Technology

2016-06-29

quantum linear systems subject to non-classical quantum fields. The major outcomes of this project are (i) derivation of quantum filtering equations for...derivation of quantum filtering equations for systems non-classical input states including single photon states, (ii) determination of how linear...history going back some 50 years, to the birth of modern control theory with Kalman’s foundational work on filtering and LQG optimal control

Robust H ∞ Control for Spacecraft Rendezvous with a Noncooperative Target

PubMed Central

Wu, Shu-Nan; Zhou, Wen-Ya; Tan, Shu-Jun; Wu, Guo-Qiang

2013-01-01

The robust H ∞ control for spacecraft rendezvous with a noncooperative target is addressed in this paper. The relative motion of chaser and noncooperative target is firstly modeled as the uncertain system, which contains uncertain orbit parameter and mass. Then the H ∞ performance and finite time performance are proposed, and a robust H ∞ controller is developed to drive the chaser to rendezvous with the non-cooperative target in the presence of control input saturation, measurement error, and thrust error. The linear matrix inequality technology is used to derive the sufficient condition of the proposed controller. An illustrative example is finally provided to demonstrate the effectiveness of the controller. PMID:24027446

H(2)- and H(infinity)-design tools for linear time-invariant systems

NASA Technical Reports Server (NTRS)

Ly, Uy-Loi

1989-01-01

Recent advances in optimal control have brought design techniques based on optimization of H(2) and H(infinity) norm criteria, closer to be attractive alternatives to single-loop design methods for linear time-variant systems. Significant steps forward in this technology are the deeper understanding of performance and robustness issues of these design procedures and means to perform design trade-offs. However acceptance of the technology is hindered by the lack of convenient design tools to exercise these powerful multivariable techniques, while still allowing single-loop design formulation. Presented is a unique computer tool for designing arbitrary low-order linear time-invarient controllers than encompasses both performance and robustness issues via the familiar H(2) and H(infinity) norm optimization. Application to disturbance rejection design for a commercial transport is demonstrated.

Dynamic output feedback control of a flexible air-breathing hypersonic vehicle via T-S fuzzy approach

NASA Astrophysics Data System (ADS)

Hu, Xiaoxiang; Wu, Ligang; Hu, Changhua; Wang, Zhaoqiang; Gao, Huijun

2014-08-01

By utilising Takagi-Sugeno (T-S) fuzzy set approach, this paper addresses the robust H∞ dynamic output feedback control for the non-linear longitudinal model of flexible air-breathing hypersonic vehicles (FAHVs). The flight control of FAHVs is highly challenging due to the unique dynamic characteristics, and the intricate couplings between the engine and fight dynamics and external disturbance. Because of the dynamics' enormous complexity, currently, only the longitudinal dynamics models of FAHVs have been used for controller design. In this work, T-S fuzzy modelling technique is utilised to approach the non-linear dynamics of FAHVs, then a fuzzy model is developed for the output tracking problem of FAHVs. The fuzzy model contains parameter uncertainties and disturbance, which can approach the non-linear dynamics of FAHVs more exactly. The flexible models of FAHVs are difficult to measure because of the complex dynamics and the strong couplings, thus a full-order dynamic output feedback controller is designed for the fuzzy model. A robust H∞ controller is designed for the obtained closed-loop system. By utilising the Lyapunov functional approach, sufficient solvability conditions for such controllers are established in terms of linear matrix inequalities. Finally, the effectiveness of the proposed T-S fuzzy dynamic output feedback control method is demonstrated by numerical simulations.

Aircraft ride quality controller design using new robust root clustering theory for linear uncertain systems

NASA Technical Reports Server (NTRS)

Yedavalli, R. K.

1992-01-01

The aspect of controller design for improving the ride quality of aircraft in terms of damping ratio and natural frequency specifications on the short period dynamics is addressed. The controller is designed to be robust with respect to uncertainties in the real parameters of the control design model such as uncertainties in the dimensional stability derivatives, imperfections in actuator/sensor locations and possibly variations in flight conditions, etc. The design is based on a new robust root clustering theory developed by the author by extending the nominal root clustering theory of Gutman and Jury to perturbed matrices. The proposed methodology allows to get an explicit relationship between the parameters of the root clustering region and the uncertainty radius of the parameter space. The current literature available for robust stability becomes a special case of this unified theory. The bounds derived on the parameter perturbation for robust root clustering are then used in selecting the robust controller.

Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

NASA Astrophysics Data System (ADS)

Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

2018-03-01

In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

A Case Study on the Application of a Structured Experimental Method for Optimal Parameter Design of a Complex Control System

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2015-01-01

This report documents a case study on the application of Reliability Engineering techniques to achieve an optimal balance between performance and robustness by tuning the functional parameters of a complex non-linear control system. For complex systems with intricate and non-linear patterns of interaction between system components, analytical derivation of a mathematical model of system performance and robustness in terms of functional parameters may not be feasible or cost-effective. The demonstrated approach is simple, structured, effective, repeatable, and cost and time efficient. This general approach is suitable for a wide range of systems.

Multivariable control of the Space Shuttle remote manipulator system using H2 and H(infinity) optimization. M.S. Thesis - Massachusetts Inst. of Tech.

NASA Technical Reports Server (NTRS)

Prakash, OM, II

1991-01-01

Three linear controllers are desiged to regulate the end effector of the Space Shuttle Remote Manipulator System (SRMS) operating in Position Hold Mode. In this mode of operation, jet firings of the Orbiter can be treated as disturbances while the controller tries to keep the end effector stationary in an orbiter-fixed reference frame. The three design techniques used include: the Linear Quadratic Regulator (LQR), H2 optimization, and H-infinity optimization. The nonlinear SRMS is linearized by modelling the effects of the significant nonlinearities as uncertain parameters. Each regulator design is evaluated for robust stability in light of the parametric uncertanties using both the small gain theorem with an H-infinity norm and the less conservative micro-analysis test. All three regulator designs offer significant improvement over the current system on the nominal plant. Unfortunately, even after dropping performance requirements and designing exclusively for robust stability, robust stability cannot be achieved. The SRMS suffers from lightly damped poles with real parametric uncertainties. Such a system renders the micro-analysis test, which allows for complex peturbations, too conservative.

Design, test, and evaluation of three active flutter suppression controllers

NASA Technical Reports Server (NTRS)

Adams, William M., Jr.; Christhilf, David M.; Waszak, Martin R.; Mukhopadhyay, Vivek; Srinathkumar, S.

1992-01-01

Three control law design techniques for flutter suppression are presented. Each technique uses multiple control surfaces and/or sensors. The first method uses traditional tools (such as pole/zero loci and Nyquist diagrams) for producing a controller that has minimal complexity and which is sufficiently robust to handle plant uncertainty. The second procedure uses linear combinations of several accelerometer signals and dynamic compensation to synthesize the model rate of the critical mode for feedback to the distributed control surfaces. The third technique starts with a minimum-energy linear quadratic Gaussian controller, iteratively modifies intensity matrices corresponding to input and output noise, and applies controller order reduction to achieve a low-order, robust controller. The resulting designs were implemented digitally and tested subsonically on the active flexible wing wind-tunnel model in the Langley Transonic Dynamics Tunnel. Only the traditional pole/zero loci design was sufficiently robust to errors in the nominal plant to successfully suppress flutter during the test. The traditional pole/zero loci design provided simultaneous suppression of symmetric and antisymmetric flutter with a 24-percent increase in attainable dynamic pressure. Posttest analyses are shown which illustrate the problems encountered with the other laws.

Robust design optimization using the price of robustness, robust least squares and regularization methods

NASA Astrophysics Data System (ADS)

Bukhari, Hassan J.

2017-12-01

In this paper a framework for robust optimization of mechanical design problems and process systems that have parametric uncertainty is presented using three different approaches. Robust optimization problems are formulated so that the optimal solution is robust which means it is minimally sensitive to any perturbations in parameters. The first method uses the price of robustness approach which assumes the uncertain parameters to be symmetric and bounded. The robustness for the design can be controlled by limiting the parameters that can perturb.The second method uses the robust least squares method to determine the optimal parameters when data itself is subjected to perturbations instead of the parameters. The last method manages uncertainty by restricting the perturbation on parameters to improve sensitivity similar to Tikhonov regularization. The methods are implemented on two sets of problems; one linear and the other non-linear. This methodology will be compared with a prior method using multiple Monte Carlo simulation runs which shows that the approach being presented in this paper results in better performance.

Feedback linearizing control of a MIMO power system

NASA Astrophysics Data System (ADS)

Ilyes, Laszlo

Prior research has demonstrated that either the mechanical or electrical subsystem of a synchronous electric generator may be controlled using single-input single-output (SISO) nonlinear feedback linearization. This research suggests a new approach which applies nonlinear feedback linearization to a multi-input multi-output (MIMO) model of the synchronous electric generator connected to an infinite bus load model. In this way, the electrical and mechanical subsystems may be linearized and simultaneously decoupled through the introduction of a pair of auxiliary inputs. This allows well known, linear, SISO control methods to be effectively applied to the resulting systems. The derivation of the feedback linearizing control law is presented in detail, including a discussion on the use of symbolic math processing as a development tool. The linearizing and decoupling properties of the control law are validated through simulation. And finally, the robustness of the control law is demonstrated.

Robust Control Design via Linear Programming

NASA Technical Reports Server (NTRS)

Keel, L. H.; Bhattacharyya, S. P.

1998-01-01

This paper deals with the problem of synthesizing or designing a feedback controller of fixed dynamic order. The closed loop specifications considered here are given in terms of a target performance vector representing a desired set of closed loop transfer functions connecting various signals. In general these point targets are unattainable with a fixed order controller. By enlarging the target from a fixed point set to an interval set the solvability conditions with a fixed order controller are relaxed and a solution is more easily enabled. Results from the parametric robust control literature can be used to design the interval target family so that the performance deterioration is acceptable, even when plant uncertainty is present. It is shown that it is possible to devise a computationally simple linear programming approach that attempts to meet the desired closed loop specifications.

From linear to nonlinear control means: a practical progression.

PubMed

Gao, Zhiqiang

2002-04-01

With the rapid advance of digital control hardware, it is time to take the simple but effective proportional-integral-derivative (PID) control technology to the next level of performance and robustness. For this purpose, a nonlinear PID and active disturbance rejection framework are introduced in this paper. It complements the existing theory in that (1) it actively and systematically explores the use of nonlinear control mechanisms for better performance, even for linear plants; (2) it represents a control strategy that is rather independent of mathematical models of the plants, thus achieving inherent robustness and reducing design complexity. Stability analysis, as well as software/hardware test results, are presented. It is evident that the proposed framework lends itself well in seeking innovative solutions to practical problems while maintaining the simplicity and the intuitiveness of the existing technology.

Linear control of oscillator and amplifier flows*

NASA Astrophysics Data System (ADS)

Schmid, Peter J.; Sipp, Denis

2016-08-01

Linear control applied to fluid systems near an equilibrium point has important applications for many flows of industrial or fundamental interest. In this article we give an exposition of tools and approaches for the design of control strategies for globally stable or unstable flows. For unstable oscillator flows a feedback configuration and a model-based approach is proposed, while for stable noise-amplifier flows a feedforward setup and an approach based on system identification is advocated. Model reduction and robustness issues are addressed for the oscillator case; statistical learning techniques are emphasized for the amplifier case. Effective suppression of global and convective instabilities could be demonstrated for either case, even though the system-identification approach results in a superior robustness to off-design conditions.

Robust multi-model control of an autonomous wind power system

NASA Astrophysics Data System (ADS)

Cutululis, Nicolas Antonio; Ceanga, Emil; Hansen, Anca Daniela; Sørensen, Poul

2006-09-01

This article presents a robust multi-model control structure for a wind power system that uses a variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) connected to a local grid. The control problem consists in maximizing the energy captured from the wind for varying wind speeds. The VSWT-PMSG linearized model analysis reveals the resonant nature of its dynamic at points on the optimal regimes characteristic (ORC). The natural frequency of the system and the damping factor are strongly dependent on the operating point on the ORC. Under these circumstances a robust multi-model control structure is designed. The simulation results prove the viability of the proposed control structure. Copyright

Robust fast controller design via nonlinear fractional differential equations.

PubMed

Zhou, Xi; Wei, Yiheng; Liang, Shu; Wang, Yong

2017-07-01

A new method for linear system controller design is proposed whereby the closed-loop system achieves both robustness and fast response. The robustness performance considered here means the damping ratio of closed-loop system can keep its desired value under system parameter perturbation, while the fast response, represented by rise time of system output, can be improved by tuning the controller parameter. We exploit techniques from both the nonlinear systems control and the fractional order systems control to derive a novel nonlinear fractional order controller. For theoretical analysis of the closed-loop system performance, two comparison theorems are developed for a class of fractional differential equations. Moreover, the rise time of the closed-loop system can be estimated, which facilitates our controller design to satisfy the fast response performance and maintain the robustness. Finally, numerical examples are given to illustrate the effectiveness of our methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Linear Quantum Systems: Non-Classical States and Robust Stability

DTIC Science & Technology

2016-06-29

has a history going back some 50 years, to the birth of modern control theory with Kalman’s foundational work on filtering and LQG optimal control ...information   if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD...analysis and control of quantum linear systems and their interactions with non-classical quantum fields by developing control theoretic concepts exploiting

Robust synchronization control scheme of a population of nonlinear stochastic synthetic genetic oscillators under intrinsic and extrinsic molecular noise via quorum sensing.

PubMed

Chen, Bor-Sen; Hsu, Chih-Yuan

2012-10-26

Collective rhythms of gene regulatory networks have been a subject of considerable interest for biologists and theoreticians, in particular the synchronization of dynamic cells mediated by intercellular communication. Synchronization of a population of synthetic genetic oscillators is an important design in practical applications, because such a population distributed over different host cells needs to exploit molecular phenomena simultaneously in order to emerge a biological phenomenon. However, this synchronization may be corrupted by intrinsic kinetic parameter fluctuations and extrinsic environmental molecular noise. Therefore, robust synchronization is an important design topic in nonlinear stochastic coupled synthetic genetic oscillators with intrinsic kinetic parameter fluctuations and extrinsic molecular noise. Initially, the condition for robust synchronization of synthetic genetic oscillators was derived based on Hamilton Jacobi inequality (HJI). We found that if the synchronization robustness can confer enough intrinsic robustness to tolerate intrinsic parameter fluctuation and extrinsic robustness to filter the environmental noise, then robust synchronization of coupled synthetic genetic oscillators is guaranteed. If the synchronization robustness of a population of nonlinear stochastic coupled synthetic genetic oscillators distributed over different host cells could not be maintained, then robust synchronization could be enhanced by external control input through quorum sensing molecules. In order to simplify the analysis and design of robust synchronization of nonlinear stochastic synthetic genetic oscillators, the fuzzy interpolation method was employed to interpolate several local linear stochastic coupled systems to approximate the nonlinear stochastic coupled system so that the HJI-based synchronization design problem could be replaced by a simple linear matrix inequality (LMI)-based design problem, which could be solved with the help of LMI toolbox in MATLAB easily. If the synchronization robustness criterion, i.e. the synchronization robustness ≥ intrinsic robustness + extrinsic robustness, then the stochastic coupled synthetic oscillators can be robustly synchronized in spite of intrinsic parameter fluctuation and extrinsic noise. If the synchronization robustness criterion is violated, external control scheme by adding inducer can be designed to improve synchronization robustness of coupled synthetic genetic oscillators. The investigated robust synchronization criteria and proposed external control method are useful for a population of coupled synthetic networks with emergent synchronization behavior, especially for multi-cellular, engineered networks.

Robust synchronization control scheme of a population of nonlinear stochastic synthetic genetic oscillators under intrinsic and extrinsic molecular noise via quorum sensing

PubMed Central

2012-01-01

Background Collective rhythms of gene regulatory networks have been a subject of considerable interest for biologists and theoreticians, in particular the synchronization of dynamic cells mediated by intercellular communication. Synchronization of a population of synthetic genetic oscillators is an important design in practical applications, because such a population distributed over different host cells needs to exploit molecular phenomena simultaneously in order to emerge a biological phenomenon. However, this synchronization may be corrupted by intrinsic kinetic parameter fluctuations and extrinsic environmental molecular noise. Therefore, robust synchronization is an important design topic in nonlinear stochastic coupled synthetic genetic oscillators with intrinsic kinetic parameter fluctuations and extrinsic molecular noise. Results Initially, the condition for robust synchronization of synthetic genetic oscillators was derived based on Hamilton Jacobi inequality (HJI). We found that if the synchronization robustness can confer enough intrinsic robustness to tolerate intrinsic parameter fluctuation and extrinsic robustness to filter the environmental noise, then robust synchronization of coupled synthetic genetic oscillators is guaranteed. If the synchronization robustness of a population of nonlinear stochastic coupled synthetic genetic oscillators distributed over different host cells could not be maintained, then robust synchronization could be enhanced by external control input through quorum sensing molecules. In order to simplify the analysis and design of robust synchronization of nonlinear stochastic synthetic genetic oscillators, the fuzzy interpolation method was employed to interpolate several local linear stochastic coupled systems to approximate the nonlinear stochastic coupled system so that the HJI-based synchronization design problem could be replaced by a simple linear matrix inequality (LMI)-based design problem, which could be solved with the help of LMI toolbox in MATLAB easily. Conclusion If the synchronization robustness criterion, i.e. the synchronization robustness ≥ intrinsic robustness + extrinsic robustness, then the stochastic coupled synthetic oscillators can be robustly synchronized in spite of intrinsic parameter fluctuation and extrinsic noise. If the synchronization robustness criterion is violated, external control scheme by adding inducer can be designed to improve synchronization robustness of coupled synthetic genetic oscillators. The investigated robust synchronization criteria and proposed external control method are useful for a population of coupled synthetic networks with emergent synchronization behavior, especially for multi-cellular, engineered networks. PMID:23101662

The Absolute Stability Analysis in Fuzzy Control Systems with Parametric Uncertainties and Reference Inputs

NASA Astrophysics Data System (ADS)

Wu, Bing-Fei; Ma, Li-Shan; Perng, Jau-Woei

This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various reference inputs and actuator gains. The steady state errors of fuzzy control systems are also addressed in the parameter plane. The parametric robust Popov criterion for parametric absolute stability based on Lur'e systems is also applied to the stability analysis of P type fuzzy control systems with uncertain plants. The PD type fuzzy logic controller in our approach is a single-input fuzzy logic controller and is transformed into the P type for analysis. In our work, the absolute stability analysis of fuzzy control systems is given with respect to a non-zero reference input and an uncertain linear plant with the parametric robust Popov criterion unlike previous works. Moreover, a fuzzy current controlled RC circuit is designed with PSPICE models. Both numerical and PSPICE simulations are provided to verify the analytical results. Furthermore, the oscillation mechanism in fuzzy control systems is specified with various equilibrium points of view in the simulation example. Finally, the comparisons are also given to show the effectiveness of the analysis method.

Robustness of controllability and observability of linear time-varying systems with application to the emergency control of power systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sastry, S. S.; Desoer, C. A.

1980-01-01

Fixed point methods from nonlinear anaysis are used to establish conditions under which the uniform complete controllability of linear time-varying systems is preserved under non-linear perturbations in the state dynamics and the zero-input uniform complete observability of linear time-varying systems is preserved under non-linear perturbation in the state dynamics and output read out map. Algorithms for computing the specific input to steer the perturbed systems from a given initial state to a given final state are also presented. As an application, a very specific emergency control of an interconnected power system is formulated as a steering problem and it ismore » shown that this emergency control is indeed possible in finite time.« less

Robust Classification and Segmentation of Planar and Linear Features for Construction Site Progress Monitoring and Structural Dimension Compliance Control

NASA Astrophysics Data System (ADS)

Maalek, R.; Lichti, D. D.; Ruwanpura, J.

2015-08-01

The application of terrestrial laser scanners (TLSs) on construction sites for automating construction progress monitoring and controlling structural dimension compliance is growing markedly. However, current research in construction management relies on the planned building information model (BIM) to assign the accumulated point clouds to their corresponding structural elements, which may not be reliable in cases where the dimensions of the as-built structure differ from those of the planned model and/or the planned model is not available with sufficient detail. In addition outliers exist in construction site datasets due to data artefacts caused by moving objects, occlusions and dust. In order to overcome the aforementioned limitations, a novel method for robust classification and segmentation of planar and linear features is proposed to reduce the effects of outliers present in the LiDAR data collected from construction sites. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a robust clustering method. A method is also proposed to robustly extract the points belonging to the flat-slab floors and/or ceilings without performing the aforementioned stages in order to preserve computational efficiency. The applicability of the proposed method is investigated in two scenarios, namely, a laboratory with 30 million points and an actual construction site with over 150 million points. The results obtained by the two experiments validate the suitability of the proposed method for robust segmentation of planar and linear features in contaminated datasets, such as those collected from construction sites.

Sliding-Mode Control Applied for Robust Control of a Highly Unstable Aircraft

NASA Technical Reports Server (NTRS)

Vetter, Travis Kenneth

2002-01-01

An investigation into the application of an observer based sliding mode controller for robust control of a highly unstable aircraft and methods of compensating for actuator dynamics is performed. After a brief overview of some reconfigurable controllers, sliding mode control (SMC) is selected because of its invariance properties and lack of need for parameter identification. SMC is reviewed and issues with parasitic dynamics, which cause system instability, are addressed. Utilizing sliding manifold boundary layers, the nonlinear control is converted to a linear control and sliding manifold design is performed in the frequency domain. An additional feedback form of model reference hedging is employed which is similar to a prefilter and has large benefits to system performance. The effects of inclusion of actuator dynamics into the designed plant is heavily investigated. Multiple Simulink models of the full longitudinal dynamics and wing deflection modes of the forward swept aero elastic vehicle (FSAV) are constructed. Additionally a linear state space models to analyze effects from various system parameters. The FSAV has a pole at +7 rad/sec and is non-minimum phase. The use of 'model actuators' in the feedback path, and varying there design, is heavily investigated for the resulting effects on plant robustness and tolerance to actuator failure. The use of redundant actuators is also explored and improved robustness is shown. All models are simulated with severe failure and excellent tracking, and task dependent handling qualities, and low pilot induced oscillation tendency is shown.

A methodology for designing robust multivariable nonlinear control systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Grunberg, D. B.

1986-01-01

A new methodology is described for the design of nonlinear dynamic controllers for nonlinear multivariable systems providing guarantees of closed-loop stability, performance, and robustness. The methodology is an extension of the Linear-Quadratic-Gaussian with Loop-Transfer-Recovery (LQG/LTR) methodology for linear systems, thus hinging upon the idea of constructing an approximate inverse operator for the plant. A major feature of the methodology is a unification of both the state-space and input-output formulations. In addition, new results on stability theory, nonlinear state estimation, and optimal nonlinear regulator theory are presented, including the guaranteed global properties of the extended Kalman filter and optimal nonlinear regulators.

Reduced-order dynamic output feedback control of uncertain discrete-time Markov jump linear systems

NASA Astrophysics Data System (ADS)

Morais, Cecília F.; Braga, Márcio F.; Oliveira, Ricardo C. L. F.; Peres, Pedro L. D.

2017-11-01

This paper deals with the problem of designing reduced-order robust dynamic output feedback controllers for discrete-time Markov jump linear systems (MJLS) with polytopic state space matrices and uncertain transition probabilities. Starting from a full order, mode-dependent and polynomially parameter-dependent dynamic output feedback controller, sufficient linear matrix inequality based conditions are provided for the existence of a robust reduced-order dynamic output feedback stabilising controller with complete, partial or none mode dependency assuring an upper bound to the ? or the ? norm of the closed-loop system. The main advantage of the proposed method when compared to the existing approaches is the fact that the dynamic controllers are exclusively expressed in terms of the decision variables of the problem. In other words, the matrices that define the controller realisation do not depend explicitly on the state space matrices associated with the modes of the MJLS. As a consequence, the method is specially suitable to handle order reduction or cluster availability constraints in the context of ? or ? dynamic output feedback control of discrete-time MJLS. Additionally, as illustrated by means of numerical examples, the proposed approach can provide less conservative results than other conditions in the literature.

Design and test of three active flutter suppression controllers

NASA Technical Reports Server (NTRS)

Christhilf, David M.; Waszak, Martin R.; Adams, William M.; Srinathkumar, S.; Mukhopadhyay, Vivek

1991-01-01

Three flutter suppression control law design techniques are presented. Each uses multiple control surfaces and/or sensors. The first uses linear combinations of several accelerometer signals together with dynamic compensation to synthesize the modal rate of the critical mode for feedback to distributed control surfaces. The second uses traditional tools (pole/zero loci and Nyquist diagrams) to develop a good understanding of the flutter mechanism and produce a controller with minimal complexity and good robustness to plant uncertainty. The third starts with a minimum energy Linear Quadratic Gaussian controller, applies controller order reduction, and then modifies weight and noise covariance matrices to improve multi-variable robustness. The resulting designs were implemented digitally and tested subsonically on the Active Flexible Wing (AFW) wind tunnel model. Test results presented here include plant characteristics, maximum attained closed-loop dynamic pressure, and Root Mean Square control surface activity. A key result is that simultaneous symmetric and antisymmetric flutter suppression was achieved by the second control law, with a 24 percent increase in attainable dynamic pressure.

Decentralized control of large-scale systems: Fixed modes, sensitivity and parametric robustness. Ph.D. Thesis - Universite Paul Sabatier, 1985

NASA Technical Reports Server (NTRS)

Tarras, A.

1987-01-01

The problem of stabilization/pole placement under structural constraints of large scale linear systems is discussed. The existence of a solution to this problem is expressed in terms of fixed modes. The aim is to provide a bibliographic survey of the available results concerning the fixed modes (characterization, elimination, control structure selection to avoid them, control design in their absence) and to present the author's contribution to this problem which can be summarized by the use of the mode sensitivity concept to detect or to avoid them, the use of vibrational control to stabilize them, and the addition of parametric robustness considerations to design an optimal decentralized robust control.

Robust blood-glucose control using Mathematica.

PubMed

Kovács, Levente; Paláncz, Béla; Benyó, Balázs; Török, László; Benyó, Zoltán

2006-01-01

A robust control design on frequency domain using Mathematica is presented for regularization of glucose level in type I diabetes persons under intensive care. The method originally proposed under Mathematica by Helton and Merino, --now with an improved disturbance rejection constraint inequality--is employed, using a three-state minimal patient model. The robustness of the resulted high-order linear controller is demonstrated by nonlinear closed loop simulation in state-space, in case of standard meal disturbances and is compared with H infinity design implemented with the mu-toolbox of Matlab. The controller designed with model parameters represented the most favorable plant dynamics from the point of view of control purposes, can operate properly even in case of parameter values of the worst-case scenario.

Robust integrated flight/propulsion control design for a STOVL aircraft using H-infinity control design techniques

NASA Technical Reports Server (NTRS)

Garg, Sanjay

1993-01-01

Results are presented from an application of H-infinity control design methodology to a centralized integrated flight/propulsion control (IFPC) system design for a supersonic STOVL fighter aircraft in transition flight. The emphasis is on formulating the H-infinity optimal control synthesis problem such that the critical requirements for the flight and propulsion systems are adequately reflected within the linear, centralized control problem formulation and the resulting controller provides robustness to modeling uncertainties and model parameter variations with flight condition. Detailed evaluation results are presented for a reduced order controller obtained from the improved H-infinity control design showing that the control design meets the specified nominal performance objective as well as provides stability robustness for variations in plant system dynamics with changes in aircraft trim speed within the transition flight envelope.

Robust control of integrated motor-transmission powertrain system over controller area network for automotive applications

NASA Astrophysics Data System (ADS)

Zhu, Xiaoyuan; Zhang, Hui; Cao, Dongpu; Fang, Zongde

2015-06-01

Integrated motor-transmission (IMT) powertrain system with directly coupled motor and gearbox is a good choice for electric commercial vehicles (e.g., pure electric buses) due to its potential in motor size reduction and energy efficiency improvement. However, the controller design for powertrain oscillation damping becomes challenging due to the elimination of damping components. On the other hand, as controller area network (CAN) is commonly adopted in modern vehicle system, the network-induced time-varying delays that caused by bandwidth limitation will further lead to powertrain vibration or even destabilize the powertrain control system. Therefore, in this paper, a robust energy-to-peak controller is proposed for the IMT powertrain system to address the oscillation damping problem and also attenuate the external disturbance. The control law adopted here is based on a multivariable PI control, which ensures the applicability and performance of the proposed controller in engineering practice. With the linearized delay uncertainties characterized by polytopic inclusions, a delay-free closed-loop augmented system is established for the IMT powertrain system under discrete-time framework. The proposed controller design problem is then converted to a static output feedback (SOF) controller design problem where the feedback control gains are obtained by solving a set of linear matrix inequalities (LMIs). The effectiveness as well as robustness of the proposed controller is demonstrated by comparing its performance against that of a conventional PI controller.

Robust synthetic biology design: stochastic game theory approach.

PubMed

Chen, Bor-Sen; Chang, Chia-Hung; Lee, Hsiao-Ching

2009-07-15

Synthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology. A robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi-Sugeno (T-S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method. http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf.

Distribution-dependent robust linear optimization with applications to inventory control

PubMed Central

Kang, Seong-Cheol; Brisimi, Theodora S.

2014-01-01

This paper tackles linear programming problems with data uncertainty and applies it to an important inventory control problem. Each element of the constraint matrix is subject to uncertainty and is modeled as a random variable with a bounded support. The classical robust optimization approach to this problem yields a solution with guaranteed feasibility. As this approach tends to be too conservative when applications can tolerate a small chance of infeasibility, one would be interested in obtaining a less conservative solution with a certain probabilistic guarantee of feasibility. A robust formulation in the literature produces such a solution, but it does not use any distributional information on the uncertain data. In this work, we show that the use of distributional information leads to an equally robust solution (i.e., under the same probabilistic guarantee of feasibility) but with a better objective value. In particular, by exploiting distributional information, we establish stronger upper bounds on the constraint violation probability of a solution. These bounds enable us to “inject” less conservatism into the formulation, which in turn yields a more cost-effective solution (by 50% or more in some numerical instances). To illustrate the effectiveness of our methodology, we consider a discrete-time stochastic inventory control problem with certain quality of service constraints. Numerical tests demonstrate that the use of distributional information in the robust optimization of the inventory control problem results in 36%–54% cost savings, compared to the case where such information is not used. PMID:26347579

Robust consensus control with guaranteed rate of convergence using second-order Hurwitz polynomials

NASA Astrophysics Data System (ADS)

Fruhnert, Michael; Corless, Martin

2017-10-01

This paper considers homogeneous networks of general, linear time-invariant, second-order systems. We consider linear feedback controllers and require that the directed graph associated with the network contains a spanning tree and systems are stabilisable. We show that consensus with a guaranteed rate of convergence can always be achieved using linear state feedback. To achieve this, we provide a new and simple derivation of the conditions for a second-order polynomial with complex coefficients to be Hurwitz. We apply this result to obtain necessary and sufficient conditions to achieve consensus with networks whose graph Laplacian matrix may have complex eigenvalues. Based on the conditions found, methods to compute feedback gains are proposed. We show that gains can be chosen such that consensus is achieved robustly over a variety of communication structures and system dynamics. We also consider the use of static output feedback.

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

X-33 Ascent Flight Controller Design by Trajectory Linearization: A Singular Perturbational Approach

NASA Technical Reports Server (NTRS)

Zhu, J. Jim; Banker, Brad D.; Hall, Charles E.

2000-01-01

The flight control of X-33 poses a challenge to conventional gain-scheduled flight controllers due to its large attitude maneuvers from liftoff to orbit and reentry. In addition, a wide range of uncertainties in vehicle handling qualities and disturbances must be accommodated by the attitude control system. Nonlinear tracking and decoupling control by trajectory linearization can be viewed as the ideal gain-scheduling controller designed at every point on the flight trajectory. Therefore it provides robust stability and performance at all stages of flight without interpolation of controller gains and eliminates costly controller redesigns due to minor airframe alteration or mission reconfiguration. In this paper, a prototype trajectory linearization design for an X-33 ascent flight controller is presented along with 3-DOF and 6-DOF simulation results. It is noted that the 6-DOF results were obtained from the 3-DOF design with only a few hours of tuning, which demonstrates the inherent robustness of the design technique. It is this "plug-and-play" feature that is much needed by NASA for the development, test and routine operations of the RLV'S. Plans for further research are also presented, and refined 6-DOF simulation results will be presented in the final version of the paper.

Stabilization of business cycles of finance agents using nonlinear optimal control

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Ghosh, T.; Sarno, D.

2017-11-01

Stabilization of the business cycles of interconnected finance agents is performed with the use of a new nonlinear optimal control method. First, the dynamics of the interacting finance agents and of the associated business cycles is described by a modeled of coupled nonlinear oscillators. Next, this dynamic model undergoes approximate linearization round a temporary operating point which is defined by the present value of the system's state vector and the last value of the control inputs vector that was exerted on it. The linearization procedure is based on Taylor series expansion of the dynamic model and on the computation of Jacobian matrices. The modelling error, which is due to the truncation of higher-order terms in the Taylor series expansion is considered as a disturbance which is compensated by the robustness of the control loop. Next, for the linearized model of the interacting finance agents, an H-infinity feedback controller is designed. The computation of the feedback control gain requires the solution of an algebraic Riccati equation at each iteration of the control algorithm. Through Lyapunov stability analysis it is proven that the control scheme satisfies an H-infinity tracking performance criterion, which signifies elevated robustness against modelling uncertainty and external perturbations. Moreover, under moderate conditions the global asymptotic stability features of the control loop are proven.

Robust Frequency-Domain Constrained Feedback Design via a Two-Stage Heuristic Approach.

PubMed

Li, Xianwei; Gao, Huijun

2015-10-01

Based on a two-stage heuristic method, this paper is concerned with the design of robust feedback controllers with restricted frequency-domain specifications (RFDSs) for uncertain linear discrete-time systems. Polytopic uncertainties are assumed to enter all the system matrices, while RFDSs are motivated by the fact that practical design specifications are often described in restricted finite frequency ranges. Dilated multipliers are first introduced to relax the generalized Kalman-Yakubovich-Popov lemma for output feedback controller synthesis and robust performance analysis. Then a two-stage approach to output feedback controller synthesis is proposed: at the first stage, a robust full-information (FI) controller is designed, which is used to construct a required output feedback controller at the second stage. To improve the solvability of the synthesis method, heuristic iterative algorithms are further formulated for exploring the feedback gain and optimizing the initial FI controller at the individual stage. The effectiveness of the proposed design method is finally demonstrated by the application to active control of suspension systems.

Robust shrinking ellipsoid model predictive control for linear parameter varying system

PubMed Central

Yan, Yan

2017-01-01

In this paper, a new off-line model predictive control strategy is presented for a kind of linear parameter varying system with polytopic uncertainty. A nest of shrinking ellipsoids is constructed by solving linear matrix inequality. By splitting the objective function into two parts, the proposed strategy moves most computations off-line. The on-line computation is only calculating the current control to assure the system shrinking into the smaller ellipsoid. With the proposed formulation, the stability of the closed system is proved, followed with two numerical examples to demonstrate the proposed method’s effectiveness in the end. PMID:28575028

Robust reinforcement learning.

PubMed

Morimoto, Jun; Doya, Kenji

2005-02-01

This letter proposes a new reinforcement learning (RL) paradigm that explicitly takes into account input disturbance as well as modeling errors. The use of environmental models in RL is quite popular for both offline learning using simulations and for online action planning. However, the difference between the model and the real environment can lead to unpredictable, and often unwanted, results. Based on the theory of H(infinity) control, we consider a differential game in which a "disturbing" agent tries to make the worst possible disturbance while a "control" agent tries to make the best control input. The problem is formulated as finding a min-max solution of a value function that takes into account the amount of the reward and the norm of the disturbance. We derive online learning algorithms for estimating the value function and for calculating the worst disturbance and the best control in reference to the value function. We tested the paradigm, which we call robust reinforcement learning (RRL), on the control task of an inverted pendulum. In the linear domain, the policy and the value function learned by online algorithms coincided with those derived analytically by the linear H(infinity) control theory. For a fully nonlinear swing-up task, RRL achieved robust performance with changes in the pendulum weight and friction, while a standard reinforcement learning algorithm could not deal with these changes. We also applied RRL to the cart-pole swing-up task, and a robust swing-up policy was acquired.

Hierarchical design of an electro-hydraulic actuator based on robust LPV methods

NASA Astrophysics Data System (ADS)

Németh, Balázs; Varga, Balázs; Gáspár, Péter

2015-08-01

The paper proposes a hierarchical control design of an electro-hydraulic actuator, which is used to improve the roll stability of vehicles. The purpose of the control system is to generate a reference torque, which is required by the vehicle dynamic control. The control-oriented model of the actuator is formulated in two subsystems. The high-level hydromotor is described in a linear form, while the low-level spool valve is a polynomial system. These subsystems require different control strategies. At the high level, a linear parameter-varying control is used to guarantee performance specifications. At the low level, a control Lyapunov-function-based algorithm, which creates discrete control input values of the valve, is proposed. The interaction between the two subsystems is guaranteed by the spool displacement, which is control input at the high level and must be tracked at the low-level control. The spool displacement has physical constraints, which must also be incorporated into the control design. The robust design of the high-level control incorporates the imprecision of the low-level control as an uncertainty of the system.

H.264/AVC digital fingerprinting based on spatio-temporal just noticeable distortion

NASA Astrophysics Data System (ADS)

Ait Saadi, Karima; Bouridane, Ahmed; Guessoum, Abderrezak

2014-01-01

This paper presents a robust adaptive embedding scheme using a modified Spatio-Temporal noticeable distortion (JND) model that is designed for tracing the distribution of the H.264/AVC video content and protecting them from unauthorized redistribution. The Embedding process is performed during coding process in selected macroblocks type Intra 4x4 within I-Frame. The method uses spread-spectrum technique in order to obtain robustness against collusion attacks and the JND model to dynamically adjust the embedding strength and control the energy of the embedded fingerprints so as to ensure their imperceptibility. Linear and non linear collusion attacks are performed to show the robustness of the proposed technique against collusion attacks while maintaining visual quality unchanged.

Robust Gain-Scheduled Fault Tolerant Control for a Transport Aircraft

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Gregory, Irene

2007-01-01

This paper presents an application of robust gain-scheduled control concepts using a linear parameter-varying (LPV) control synthesis method to design fault tolerant controllers for a civil transport aircraft. To apply the robust LPV control synthesis method, the nonlinear dynamics must be represented by an LPV model, which is developed using the function substitution method over the entire flight envelope. The developed LPV model associated with the aerodynamic coefficient uncertainties represents nonlinear dynamics including those outside the equilibrium manifold. Passive and active fault tolerant controllers (FTC) are designed for the longitudinal dynamics of the Boeing 747-100/200 aircraft in the presence of elevator failure. Both FTC laws are evaluated in the full nonlinear aircraft simulation in the presence of the elevator fault and the results are compared to show pros and cons of each control law.

Optimal second order sliding mode control for linear uncertain systems.

PubMed

Das, Madhulika; Mahanta, Chitralekha

2014-11-01

In this paper an optimal second order sliding mode controller (OSOSMC) is proposed to track a linear uncertain system. The optimal controller based on the linear quadratic regulator method is designed for the nominal system. An integral sliding mode controller is combined with the optimal controller to ensure robustness of the linear system which is affected by parametric uncertainties and external disturbances. To achieve finite time convergence of the sliding mode, a nonsingular terminal sliding surface is added with the integral sliding surface giving rise to a second order sliding mode controller. The main advantage of the proposed OSOSMC is that the control input is substantially reduced and it becomes chattering free. Simulation results confirm superiority of the proposed OSOSMC over some existing. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

A simple attitude control of quadrotor helicopter based on Ziegler-Nichols rules for tuning PD parameters.

PubMed

He, ZeFang; Zhao, Long

2014-01-01

An attitude control strategy based on Ziegler-Nichols rules for tuning PD (proportional-derivative) parameters of quadrotor helicopters is presented to solve the problem that quadrotor tends to be instable. This problem is caused by the narrow definition domain of attitude angles of quadrotor helicopters. The proposed controller is nonlinear and consists of a linear part and a nonlinear part. The linear part is a PD controller with PD parameters tuned by Ziegler-Nichols rules and acts on the quadrotor decoupled linear system after feedback linearization; the nonlinear part is a feedback linearization item which converts a nonlinear system into a linear system. It can be seen from the simulation results that the attitude controller proposed in this paper is highly robust, and its control effect is better than the other two nonlinear controllers. The nonlinear parts of the other two nonlinear controllers are the same as the attitude controller proposed in this paper. The linear part involves a PID (proportional-integral-derivative) controller with the PID controller parameters tuned by Ziegler-Nichols rules and a PD controller with the PD controller parameters tuned by GA (genetic algorithms). Moreover, this attitude controller is simple and easy to implement.

A class of stabilizing controllers for flexible multibody systems

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.; Kelkar, Atul G.; Maghami, Peiman G.

1995-01-01

The problem of controlling a class of nonlinear multibody flexible space systems consisting of a flexible central body to which a number of articulated appendages are attached is considered. Collocated actuators and sensors are assumed, and global asymptotic stability of such systems is established under a nonlinear dissipative control law. The stability is shown to be robust to unmodeled dynamics and parametric uncertainties. For a special case in which the attitude motion of the central body is small, the system, although still nonlinear, is shown to be stabilized by linear dissipative control laws. Two types of linear controllers are considered: static dissipative (constant gain) and dynamic dissipative. The static dissipative control law is also shown to provide robust stability in the presence of certain classes of actuator and sensor nonlinearities and actuator dynamics. The results obtained for this special case can also be readily applied for controlling single-body linear flexible space structures. For this case, a synthesis technique for the design of a suboptimal dynamic dissipative controller is also presented. The results obtained in this paper are applicable to a broad class of multibody and single-body systems such as flexible multilink manipulators, multipayload space platforms, and space antennas. The stability proofs use the Lyapunov approach and exploit the inherent passivity of such systems.

Decentralized Feedback Controllers for Robust Stabilization of Periodic Orbits of Hybrid Systems: Application to Bipedal Walking.

PubMed

Hamed, Kaveh Akbari; Gregg, Robert D

2017-07-01

This paper presents a systematic algorithm to design time-invariant decentralized feedback controllers to exponentially and robustly stabilize periodic orbits for hybrid dynamical systems against possible uncertainties in discrete-time phases. The algorithm assumes a family of parameterized and decentralized nonlinear controllers to coordinate interconnected hybrid subsystems based on a common phasing variable. The exponential and [Formula: see text] robust stabilization problems of periodic orbits are translated into an iterative sequence of optimization problems involving bilinear and linear matrix inequalities. By investigating the properties of the Poincaré map, some sufficient conditions for the convergence of the iterative algorithm are presented. The power of the algorithm is finally demonstrated through designing a set of robust stabilizing local nonlinear controllers for walking of an underactuated 3D autonomous bipedal robot with 9 degrees of freedom, impact model uncertainties, and a decentralization scheme motivated by amputee locomotion with a transpelvic prosthetic leg.

Decentralized Feedback Controllers for Robust Stabilization of Periodic Orbits of Hybrid Systems: Application to Bipedal Walking

PubMed Central

Hamed, Kaveh Akbari; Gregg, Robert D.

2016-01-01

This paper presents a systematic algorithm to design time-invariant decentralized feedback controllers to exponentially and robustly stabilize periodic orbits for hybrid dynamical systems against possible uncertainties in discrete-time phases. The algorithm assumes a family of parameterized and decentralized nonlinear controllers to coordinate interconnected hybrid subsystems based on a common phasing variable. The exponential and H2 robust stabilization problems of periodic orbits are translated into an iterative sequence of optimization problems involving bilinear and linear matrix inequalities. By investigating the properties of the Poincaré map, some sufficient conditions for the convergence of the iterative algorithm are presented. The power of the algorithm is finally demonstrated through designing a set of robust stabilizing local nonlinear controllers for walking of an underactuated 3D autonomous bipedal robot with 9 degrees of freedom, impact model uncertainties, and a decentralization scheme motivated by amputee locomotion with a transpelvic prosthetic leg. PMID:28959117

Stochastic Control Synthesis of Systems with Structured Uncertainty

NASA Technical Reports Server (NTRS)

Padula, Sharon L. (Technical Monitor); Crespo, Luis G.

2003-01-01

This paper presents a study on the design of robust controllers by using random variables to model structured uncertainty for both SISO and MIMO feedback systems. Once the parameter uncertainty is prescribed with probability density functions, its effects are propagated through the analysis leading to stochastic metrics for the system's output. Control designs that aim for satisfactory performances while guaranteeing robust closed loop stability are attained by solving constrained non-linear optimization problems in the frequency domain. This approach permits not only to quantify the probability of having unstable and unfavorable responses for a particular control design but also to search for controls while favoring the values of the parameters with higher chance of occurrence. In this manner, robust optimality is achieved while the characteristic conservatism of conventional robust control methods is eliminated. Examples that admit closed form expressions for the probabilistic metrics of the output are used to elucidate the nature of the problem at hand and validate the proposed formulations.

Expendable launch vehicle studies

NASA Technical Reports Server (NTRS)

Bainum, Peter M.; Reiss, Robert

1995-01-01

Analytical support studies of expendable launch vehicles concentrate on the stability of the dynamics during launch especially during or near the region of maximum dynamic pressure. The in-plane dynamic equations of a generic launch vehicle with multiple flexible bending and fuel sloshing modes are developed and linearized. The information from LeRC about the grids, masses, and modes is incorporated into the model. The eigenvalues of the plant are analyzed for several modeling factors: utilizing diagonal mass matrix, uniform beam assumption, inclusion of aerodynamics, and the interaction between the aerodynamics and the flexible bending motion. Preliminary PID, LQR, and LQG control designs with sensor and actuator dynamics for this system and simulations are also conducted. The initial analysis for comparison of PD (proportional-derivative) and full state feedback LQR Linear quadratic regulator) shows that the split weighted LQR controller has better performance than that of the PD. In order to meet both the performance and robustness requirements, the H(sub infinity) robust controller for the expendable launch vehicle is developed. The simulation indicates that both the performance and robustness of the H(sub infinity) controller are better than that for the PID and LQG controllers. The modelling and analysis support studies team has continued development of methodology, using eigensensitivity analysis, to solve three classes of discrete eigenvalue equations. In the first class, the matrix elements are non-linear functions of the eigenvector. All non-linear periodic motion can be cast in this form. Here the eigenvector is comprised of the coefficients of complete basis functions spanning the response space and the eigenvalue is the frequency. The second class of eigenvalue problems studied is the quadratic eigenvalue problem. Solutions for linear viscously damped structures or viscoelastic structures can be reduced to this form. Particular attention is paid to Maxwell and Kelvin models. The third class of problems consists of linear eigenvalue problems in which the elements of the mass and stiffness matrices are stochastic. dynamic structural response for which the parameters are given by probabilistic distribution functions, rather than deterministic values, can be cast in this form. Solutions for several problems in each class will be presented.

Robust linear parameter-varying control of blood pressure using vasoactive drugs

NASA Astrophysics Data System (ADS)

Luspay, Tamas; Grigoriadis, Karolos

2015-10-01

Resuscitation of emergency care patients requires fast restoration of blood pressure to a target value to achieve hemodynamic stability and vital organ perfusion. A robust control design methodology is presented in this paper for regulating the blood pressure of hypotensive patients by means of the closed-loop administration of vasoactive drugs. To this end, a dynamic first-order delay model is utilised to describe the vasoactive drug response with varying parameters that represent intra-patient and inter-patient variability. The proposed framework consists of two components: first, an online model parameter estimation is carried out using a multiple-model extended Kalman-filter. Second, the estimated model parameters are used for continuously scheduling a robust linear parameter-varying (LPV) controller. The closed-loop behaviour is characterised by parameter-varying dynamic weights designed to regulate the mean arterial pressure to a target value. Experimental data of blood pressure response of anesthetised pigs to phenylephrine injection are used for validating the LPV blood pressure models. Simulation studies are provided to validate the online model estimation and the LPV blood pressure control using phenylephrine drug injection models representing patients showing sensitive, nominal and insensitive response to the drug.

Robust lateral blended-wing-body aircraft feedback control design using a parameterized LFR model and DGK-iteration

NASA Astrophysics Data System (ADS)

Schirrer, A.; Westermayer, C.; Hemedi, M.; Kozek, M.

2013-12-01

This paper shows control design results, performance, and limitations of robust lateral control law designs based on the DGK-iteration mixed-μ-synthesis procedure for a large, flexible blended wing body (BWB) passenger aircraft. The aircraft dynamics is preshaped by a low-complexity inner loop control law providing stabilization, basic response shaping, and flexible mode damping. The μ controllers are designed to further improve vibration damping of the main flexible modes by exploiting the structure of the arising significant parameter-dependent plant variations. This is achieved by utilizing parameterized Linear Fractional Representations (LFR) of the aircraft rigid and flexible dynamics. Designs with various levels of LFR complexity are carried out and discussed, showing the achieved performance improvement over the initial controller and their robustness and complexity properties.

Robust reliable sampled-data control for switched systems with application to flight control

NASA Astrophysics Data System (ADS)

Sakthivel, R.; Joby, Maya; Shi, P.; Mathiyalagan, K.

2016-11-01

This paper addresses the robust reliable stabilisation problem for a class of uncertain switched systems with random delays and norm bounded uncertainties. The main aim of this paper is to obtain the reliable robust sampled-data control design which involves random time delay with an appropriate gain control matrix for achieving the robust exponential stabilisation for uncertain switched system against actuator failures. In particular, the involved delays are assumed to be randomly time-varying which obeys certain mutually uncorrelated Bernoulli distributed white noise sequences. By constructing an appropriate Lyapunov-Krasovskii functional (LKF) and employing an average-dwell time approach, a new set of criteria is derived for ensuring the robust exponential stability of the closed-loop switched system. More precisely, the Schur complement and Jensen's integral inequality are used in derivation of stabilisation criteria. By considering the relationship among the random time-varying delay and its lower and upper bounds, a new set of sufficient condition is established for the existence of reliable robust sampled-data control in terms of solution to linear matrix inequalities (LMIs). Finally, an illustrative example based on the F-18 aircraft model is provided to show the effectiveness of the proposed design procedures.

Robust estimation for partially linear models with large-dimensional covariates

PubMed Central

Zhu, LiPing; Li, RunZe; Cui, HengJian

2014-01-01

We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon-cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of o(n), where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures. PMID:24955087

Robust estimation for partially linear models with large-dimensional covariates.

PubMed

Zhu, LiPing; Li, RunZe; Cui, HengJian

2013-10-01

We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon-cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of [Formula: see text], where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures.

A generalized Lyapunov theory for robust root clustering of linear state space models with real parameter uncertainty

NASA Technical Reports Server (NTRS)

Yedavalli, R. K.

1992-01-01

The problem of analyzing and designing controllers for linear systems subject to real parameter uncertainty is considered. An elegant, unified theory for robust eigenvalue placement is presented for a class of D-regions defined by algebraic inequalities by extending the nominal matrix root clustering theory of Gutman and Jury (1981) to linear uncertain time systems. The author presents explicit conditions for matrix root clustering for different D-regions and establishes the relationship between the eigenvalue migration range and the parameter range. The bounds are all obtained by one-shot computation in the matrix domain and do not need any frequency sweeping or parameter gridding. The method uses the generalized Lyapunov theory for getting the bounds.

Design of a robust control law for the Vega launcher ballistic phase

NASA Astrophysics Data System (ADS)

Valli, Monica; Lavagna, Michèle R.; Panozzo, Thomas

2012-02-01

This work presents the design of a robust control law, and the related control system architecture, for the Vega launcher ballistic phase, taking into account the complete six degrees of freedom dynamics. To gain robustness a non-linear control approach has been preferred: more specifically the Lyapunov's second stability theorem has been exploited, being a very powerful tool to guarantee asymptotic stability of the controlled dynamics. The dynamics of Vega's actuators has also been taken into account. The system performance has been checked and analyzed by numerical simulations run on real mission data for different operational and configuration scenarios, and the effectiveness of the synthesized control highlighted: in particular scenarios including a wide range of composite's inertial configurations performing various typologies of maneuvers have been run. The robustness of the controlled dynamics has been validated by 100 cases Monte Carlo analysis campaign: the containment of the dispersion for the controlled variables - say the composite roll, yaw and pitch angles - confirmed the wide validity and generality of the proposed control law. This paper will show the theoretical approach and discuss the obtained results.

Statistics based sampling for controller and estimator design

NASA Astrophysics Data System (ADS)

Tenne, Dirk

The purpose of this research is the development of statistical design tools for robust feed-forward/feedback controllers and nonlinear estimators. This dissertation is threefold and addresses the aforementioned topics nonlinear estimation, target tracking and robust control. To develop statistically robust controllers and nonlinear estimation algorithms, research has been performed to extend existing techniques, which propagate the statistics of the state, to achieve higher order accuracy. The so-called unscented transformation has been extended to capture higher order moments. Furthermore, higher order moment update algorithms based on a truncated power series have been developed. The proposed techniques are tested on various benchmark examples. Furthermore, the unscented transformation has been utilized to develop a three dimensional geometrically constrained target tracker. The proposed planar circular prediction algorithm has been developed in a local coordinate framework, which is amenable to extension of the tracking algorithm to three dimensional space. This tracker combines the predictions of a circular prediction algorithm and a constant velocity filter by utilizing the Covariance Intersection. This combined prediction can be updated with the subsequent measurement using a linear estimator. The proposed technique is illustrated on a 3D benchmark trajectory, which includes coordinated turns and straight line maneuvers. The third part of this dissertation addresses the design of controller which include knowledge of parametric uncertainties and their distributions. The parameter distributions are approximated by a finite set of points which are calculated by the unscented transformation. This set of points is used to design robust controllers which minimize a statistical performance of the plant over the domain of uncertainty consisting of a combination of the mean and variance. The proposed technique is illustrated on three benchmark problems. The first relates to the design of prefilters for a linear and nonlinear spring-mass-dashpot system and the second applies a feedback controller to a hovering helicopter. Lastly, the statistical robust controller design is devoted to a concurrent feed-forward/feedback controller structure for a high-speed low tension tape drive.

Overview of computational control research at UT Austin

NASA Technical Reports Server (NTRS)

Bong, Wie

1989-01-01

An overview of current research activities at UT Austin is presented to discuss certain technical issues in the following areas: (1) Computer-Aided Nonlinear Control Design: In this project, the describing function method is employed for the nonlinear control analysis and design of a flexible spacecraft equipped with pulse modulated reaction jets. INCA program has been enhanced to allow the numerical calculation of describing functions as well as the nonlinear limit cycle analysis capability in the frequency domain; (2) Robust Linear Quadratic Gaussian (LQG) Compensator Synthesis: Robust control design techniques and software tools are developed for flexible space structures with parameter uncertainty. In particular, an interactive, robust multivariable control design capability is being developed for INCA program; and (3) LQR-Based Autonomous Control System for the Space Station: In this project, real time implementation of LQR-based autonomous control system is investigated for the space station with time-varying inertias and with significant multibody dynamic interactions.

Optimal strategy analysis based on robust predictive control for inventory system with random demand

NASA Astrophysics Data System (ADS)

Saputra, Aditya; Widowati, Sutrisno

2017-12-01

In this paper, the optimal strategy for a single product single supplier inventory system with random demand is analyzed by using robust predictive control with additive random parameter. We formulate the dynamical system of this system as a linear state space with additive random parameter. To determine and analyze the optimal strategy for the given inventory system, we use robust predictive control approach which gives the optimal strategy i.e. the optimal product volume that should be purchased from the supplier for each time period so that the expected cost is minimal. A numerical simulation is performed with some generated random inventory data. We simulate in MATLAB software where the inventory level must be controlled as close as possible to a set point decided by us. From the results, robust predictive control model provides the optimal strategy i.e. the optimal product volume that should be purchased and the inventory level was followed the given set point.

Robust iterative learning control for multi-phase batch processes: an average dwell-time method with 2D convergence indexes

NASA Astrophysics Data System (ADS)

Wang, Limin; Shen, Yiteng; Yu, Jingxian; Li, Ping; Zhang, Ridong; Gao, Furong

2018-01-01

In order to cope with system disturbances in multi-phase batch processes with different dimensions, a hybrid robust control scheme of iterative learning control combined with feedback control is proposed in this paper. First, with a hybrid iterative learning control law designed by introducing the state error, the tracking error and the extended information, the multi-phase batch process is converted into a two-dimensional Fornasini-Marchesini (2D-FM) switched system with different dimensions. Second, a switching signal is designed using the average dwell-time method integrated with the related switching conditions to give sufficient conditions ensuring stable running for the system. Finally, the minimum running time of the subsystems and the control law gains are calculated by solving the linear matrix inequalities. Meanwhile, a compound 2D controller with robust performance is obtained, which includes a robust extended feedback control for ensuring the steady-state tracking error to converge rapidly. The application on an injection molding process displays the effectiveness and superiority of the proposed strategy.

Language Measure for Robust Optimal Control

DTIC Science & Technology

2006-01-01

ROBUST OPTIMAL CONTROL 6. AUTHOR(S) Asok Ray , Travis Ortogero 5. FUNDING NUMBERS C - F30602-01-2-0575 PE - 62301E PR - M414...element of Π is non-negative, so each element of kΠ is also. Thus, 0][ 1 ≥Π− −I elementwise. ■ Wang and Ray [WR02] and Ray and Phoha [RP02] have...Sell, Linear Operator Theory in Science and Engineering, Springer-Verlag, New York, 1982. [RP02] A. Ray and S. Phoha, “A language measure for

Robust stability of second-order systems

NASA Technical Reports Server (NTRS)

Chuang, C.-H.

1993-01-01

A feedback linearization technique is used in conjunction with passivity concepts to design robust controllers for space robots. It is assumed that bounded modeling uncertainties exist in the inertia matrix and the vector representing the coriolis, centripetal, and friction forces. Under these assumptions, the controller guarantees asymptotic tracking of the joint variables. A Lagrangian approach is used to develop a dynamic model for space robots. Closed-loop simulation results are illustrated for a simple case of a single link planar manipulator with freely floating base.

Stability of multiloop LQ regulators with nonlinearities. I - Regions of attraction. II - Regions of ultimate boundedness

NASA Technical Reports Server (NTRS)

Joshi, S. M.

1986-01-01

An investigation is conducted for the closed loop stability of linear time-invariant systems controlled by linear quadratic (LQ) regulators, in cases where nonlinearities exist in the control channels lying outside the stability sector in regions away from the origin. The estimate of the region of attraction thus obtained furnishes methods for the selection of performance function weights for more robust LQ designs. Attention is then given to the closed loop stability of linear time-invariant systems controlled by the LQ regulators when the nonlinearities in the loops escape the stability sector in a bounded region containing the origin.

Composite Robust $$H_\\infty$$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yunlong; Wang, Hong; Guo, Lei

Here in this note, the robust stochastic stabilization and robust H_infinity control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbancemore » rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.« less

Composite Robust $$H_\\infty$$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer

DOE PAGES

Liu, Yunlong; Wang, Hong; Guo, Lei

2018-03-26

Here in this note, the robust stochastic stabilization and robust H_infinity control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbancemore » rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.« less

Digital robust active control law synthesis for large order systems using constrained optimization

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivek

1987-01-01

This paper presents a direct digital control law synthesis procedure for a large order, sampled data, linear feedback system using constrained optimization techniques to meet multiple design requirements. A linear quadratic Gaussian type cost function is minimized while satisfying a set of constraints on the design loads and responses. General expressions for gradients of the cost function and constraints, with respect to the digital control law design variables are derived analytically and computed by solving a set of discrete Liapunov equations. The designer can choose the structure of the control law and the design variables, hence a stable classical control law as well as an estimator-based full or reduced order control law can be used as an initial starting point. Selected design responses can be treated as constraints instead of lumping them into the cost function. This feature can be used to modify a control law, to meet individual root mean square response limitations as well as minimum single value restrictions. Low order, robust digital control laws were synthesized for gust load alleviation of a flexible remotely piloted drone aircraft.

Robust stability bounds for multi-delay networked control systems

NASA Astrophysics Data System (ADS)

Seitz, Timothy; Yedavalli, Rama K.; Behbahani, Alireza

2018-04-01

In this paper, the robust stability of a perturbed linear continuous-time system is examined when controlled using a sampled-data networked control system (NCS) framework. Three new robust stability bounds on the time-invariant perturbations to the original continuous-time plant matrix are presented guaranteeing stability for the corresponding discrete closed-loop augmented delay-free system (ADFS) with multiple time-varying sensor and actuator delays. The bounds are differentiated from previous work by accounting for the sampled-data nature of the NCS and for separate communication delays for each sensor and actuator, not a single delay. Therefore, this paper expands the knowledge base in multiple inputs multiple outputs (MIMO) sampled-data time delay systems. Bounds are presented for unstructured, semi-structured, and structured perturbations.

Predictive IP controller for robust position control of linear servo system.

PubMed

Lu, Shaowu; Zhou, Fengxing; Ma, Yajie; Tang, Xiaoqi

2016-07-01

Position control is a typical application of linear servo system. In this paper, to reduce the system overshoot, an integral plus proportional (IP) controller is used in the position control implementation. To further improve the control performance, a gain-tuning IP controller based on a generalized predictive control (GPC) law is proposed. Firstly, to represent the dynamics of the position loop, a second-order linear model is used and its model parameters are estimated on-line by using a recursive least squares method. Secondly, based on the GPC law, an optimal control sequence is obtained by using receding horizon, then directly supplies the IP controller with the corresponding control parameters in the real operations. Finally, simulation and experimental results are presented to show the efficiency of proposed scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Linear Parameter Varying Control Synthesis for Actuator Failure, Based on Estimated Parameter

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Wu, N. Eva; Belcastro, Christine

2002-01-01

The design of a linear parameter varying (LPV) controller for an aircraft at actuator failure cases is presented. The controller synthesis for actuator failure cases is formulated into linear matrix inequality (LMI) optimizations based on an estimated failure parameter with pre-defined estimation error bounds. The inherent conservatism of an LPV control synthesis methodology is reduced using a scaling factor on the uncertainty block which represents estimated parameter uncertainties. The fault parameter is estimated using the two-stage Kalman filter. The simulation results of the designed LPV controller for a HiMXT (Highly Maneuverable Aircraft Technology) vehicle with the on-line estimator show that the desired performance and robustness objectives are achieved for actuator failure cases.

A Simple Attitude Control of Quadrotor Helicopter Based on Ziegler-Nichols Rules for Tuning PD Parameters

PubMed Central

He, ZeFang

2014-01-01

An attitude control strategy based on Ziegler-Nichols rules for tuning PD (proportional-derivative) parameters of quadrotor helicopters is presented to solve the problem that quadrotor tends to be instable. This problem is caused by the narrow definition domain of attitude angles of quadrotor helicopters. The proposed controller is nonlinear and consists of a linear part and a nonlinear part. The linear part is a PD controller with PD parameters tuned by Ziegler-Nichols rules and acts on the quadrotor decoupled linear system after feedback linearization; the nonlinear part is a feedback linearization item which converts a nonlinear system into a linear system. It can be seen from the simulation results that the attitude controller proposed in this paper is highly robust, and its control effect is better than the other two nonlinear controllers. The nonlinear parts of the other two nonlinear controllers are the same as the attitude controller proposed in this paper. The linear part involves a PID (proportional-integral-derivative) controller with the PID controller parameters tuned by Ziegler-Nichols rules and a PD controller with the PD controller parameters tuned by GA (genetic algorithms). Moreover, this attitude controller is simple and easy to implement. PMID:25614879

Transfer matrix method for dynamics modeling and independent modal space vibration control design of linear hybrid multibody system

NASA Astrophysics Data System (ADS)

Rong, Bao; Rui, Xiaoting; Lu, Kun; Tao, Ling; Wang, Guoping; Ni, Xiaojun

2018-05-01

In this paper, an efficient method of dynamics modeling and vibration control design of a linear hybrid multibody system (MS) is studied based on the transfer matrix method. The natural vibration characteristics of a linear hybrid MS are solved by using low-order transfer equations. Then, by constructing the brand-new body dynamics equation, augmented operator and augmented eigenvector, the orthogonality of augmented eigenvector of a linear hybrid MS is satisfied, and its state space model expressed in each independent model space is obtained easily. According to this dynamics model, a robust independent modal space-fuzzy controller is designed for vibration control of a general MS, and the genetic optimization of some critical control parameters of fuzzy tuners is also presented. Two illustrative examples are performed, which results show that this method is computationally efficient and with perfect control performance.

A Reconfiguration Scheme for Accommodating Actuator Failures in Multi-Input, Multi-Output Flight Control Systems

NASA Technical Reports Server (NTRS)

Siwakosit, W.; Hess, R. A.; Bacon, Bart (Technical Monitor); Burken, John (Technical Monitor)

2000-01-01

A multi-input, multi-output reconfigurable flight control system design utilizing a robust controller and an adaptive filter is presented. The robust control design consists of a reduced-order, linear dynamic inversion controller with an outer-loop compensation matrix derived from Quantitative Feedback Theory (QFT). A principle feature of the scheme is placement of the adaptive filter in series with the QFT compensator thus exploiting the inherent robustness of the nominal flight control system in the presence of plant uncertainties. An example of the scheme is presented in a pilot-in-the-loop computer simulation using a simplified model of the lateral-directional dynamics of the NASA F18 High Angle of Attack Research Vehicle (HARV) that included nonlinear anti-wind up logic and actuator limitations. Prediction of handling qualities and pilot-induced oscillation tendencies in the presence of these nonlinearities is included in the example.

Robust Takagi-Sugeno fuzzy control for fractional order hydro-turbine governing system.

PubMed

Wang, Bin; Xue, Jianyi; Wu, Fengjiao; Zhu, Delan

2016-11-01

A robust fuzzy control method for fractional order hydro-turbine governing system (FOHGS) in the presence of random disturbances is investigated in this paper. Firstly, the mathematical model of FOHGS is introduced, and based on Takagi-Sugeno (T-S) fuzzy rules, the generalized T-S fuzzy model of FOHGS is presented. Secondly, based on fractional order Lyapunov stability theory, a novel T-S fuzzy control method is designed for the stability control of FOHGS. Thirdly, the relatively loose sufficient stability condition is acquired, which could be transformed into a group of linear matrix inequalities (LMIs) via Schur complement as well as the strict mathematical derivation is given. Furthermore, the control method could resist random disturbances, which shows the good robustness. Simulation results indicate the designed fractional order T-S fuzzy control scheme works well compared with the existing method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A reliable algorithm for optimal control synthesis

NASA Technical Reports Server (NTRS)

Vansteenwyk, Brett; Ly, Uy-Loi

1992-01-01

In recent years, powerful design tools for linear time-invariant multivariable control systems have been developed based on direct parameter optimization. In this report, an algorithm for reliable optimal control synthesis using parameter optimization is presented. Specifically, a robust numerical algorithm is developed for the evaluation of the H(sup 2)-like cost functional and its gradients with respect to the controller design parameters. The method is specifically designed to handle defective degenerate systems and is based on the well-known Pade series approximation of the matrix exponential. Numerical test problems in control synthesis for simple mechanical systems and for a flexible structure with densely packed modes illustrate positively the reliability of this method when compared to a method based on diagonalization. Several types of cost functions have been considered: a cost function for robust control consisting of a linear combination of quadratic objectives for deterministic and random disturbances, and one representing an upper bound on the quadratic objective for worst case initial conditions. Finally, a framework for multivariable control synthesis has been developed combining the concept of closed-loop transfer recovery with numerical parameter optimization. The procedure enables designers to synthesize not only observer-based controllers but also controllers of arbitrary order and structure. Numerical design solutions rely heavily on the robust algorithm due to the high order of the synthesis model and the presence of near-overlapping modes. The design approach is successfully applied to the design of a high-bandwidth control system for a rotorcraft.

Linear Parameter Varying Control for Actuator Failure

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Wu, N. Eva; Belcastro, Christine; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

A robust linear parameter varying (LPV) control synthesis is carried out for an HiMAT vehicle subject to loss of control effectiveness. The scheduling parameter is selected to be a function of the estimates of the control effectiveness factors. The estimates are provided on-line by a two-stage Kalman estimator. The inherent conservatism of the LPV design is reducing through the use of a scaling factor on the uncertainty block that represents the estimation errors of the effectiveness factors. Simulations of the controlled system with the on-line estimator show that a superior fault-tolerance can be achieved.

Robust Control Design for Uncertain Nonlinear Dynamic Systems

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Crespo, Luis G.; Andrews, Lindsey; Giesy, Daniel P.

2012-01-01

Robustness to parametric uncertainty is fundamental to successful control system design and as such it has been at the core of many design methods developed over the decades. Despite its prominence, most of the work on robust control design has focused on linear models and uncertainties that are non-probabilistic in nature. Recently, researchers have acknowledged this disparity and have been developing theory to address a broader class of uncertainties. This paper presents an experimental application of robust control design for a hybrid class of probabilistic and non-probabilistic parametric uncertainties. The experimental apparatus is based upon the classic inverted pendulum on a cart. The physical uncertainty is realized by a known additional lumped mass at an unknown location on the pendulum. This unknown location has the effect of substantially altering the nominal frequency and controllability of the nonlinear system, and in the limit has the capability to make the system neutrally stable and uncontrollable. Another uncertainty to be considered is a direct current motor parameter. The control design objective is to design a controller that satisfies stability, tracking error, control power, and transient behavior requirements for the largest range of parametric uncertainties. This paper presents an overview of the theory behind the robust control design methodology and the experimental results.

Attitude control with realization of linear error dynamics

NASA Technical Reports Server (NTRS)

Paielli, Russell A.; Bach, Ralph E.

1993-01-01

An attitude control law is derived to realize linear unforced error dynamics with the attitude error defined in terms of rotation group algebra (rather than vector algebra). Euler parameters are used in the rotational dynamics model because they are globally nonsingular, but only the minimal three Euler parameters are used in the error dynamics model because they have no nonlinear mathematical constraints to prevent the realization of linear error dynamics. The control law is singular only when the attitude error angle is exactly pi rad about any eigenaxis, and a simple intuitive modification at the singularity allows the control law to be used globally. The forced error dynamics are nonlinear but stable. Numerical simulation tests show that the control law performs robustly for both initial attitude acquisition and attitude control.

Interval Analysis Approach to Prototype the Robust Control of the Laboratory Overhead Crane

NASA Astrophysics Data System (ADS)

Smoczek, J.; Szpytko, J.; Hyla, P.

2014-07-01

The paper describes the software-hardware equipment and control-measurement solutions elaborated to prototype the laboratory scaled overhead crane control system. The novelty approach to crane dynamic system modelling and fuzzy robust control scheme design is presented. The iterative procedure for designing a fuzzy scheduling control scheme is developed based on the interval analysis of discrete-time closed-loop system characteristic polynomial coefficients in the presence of rope length and mass of a payload variation to select the minimum set of operating points corresponding to the midpoints of membership functions at which the linear controllers are determined through desired poles assignment. The experimental results obtained on the laboratory stand are presented.

Quantitative Robust Control Engineering: Theory and Applications

DTIC Science & Technology

2006-09-01

30]. Gutman, PO., Baril , C. Neuman, L. (1994), An algorithm for computing value sets of uncertain transfer functions in factored real form...linear compensation design for saturating unstable uncertain plants. Int. J. Control, Vol. 44, pp. 1137-1146. [90]. Oldak S., Baril C. and Gutman

Adaptive Control for Autonomous Navigation of Mobile Robots Considering Time Delay and Uncertainty

NASA Astrophysics Data System (ADS)

Armah, Stephen Kofi

Autonomous control of mobile robots has attracted considerable attention of researchers in the areas of robotics and autonomous systems during the past decades. One of the goals in the field of mobile robotics is development of platforms that robustly operate in given, partially unknown, or unpredictable environments and offer desired services to humans. Autonomous mobile robots need to be equipped with effective, robust and/or adaptive, navigation control systems. In spite of enormous reported work on autonomous navigation control systems for mobile robots, achieving the goal above is still an open problem. Robustness and reliability of the controlled system can always be improved. The fundamental issues affecting the stability of the control systems include the undesired nonlinear effects introduced by actuator saturation, time delay in the controlled system, and uncertainty in the model. This research work develops robustly stabilizing control systems by investigating and addressing such nonlinear effects through analytical, simulations, and experiments. The control systems are designed to meet specified transient and steady-state specifications. The systems used for this research are ground (Dr Robot X80SV) and aerial (Parrot AR.Drone 2.0) mobile robots. Firstly, an effective autonomous navigation control system is developed for X80SV using logic control by combining 'go-to-goal', 'avoid-obstacle', and 'follow-wall' controllers. A MATLAB robot simulator is developed to implement this control algorithm and experiments are conducted in a typical office environment. The next stage of the research develops an autonomous position (x, y, and z) and attitude (roll, pitch, and yaw) controllers for a quadrotor, and PD-feedback control is used to achieve stabilization. The quadrotor's nonlinear dynamics and kinematics are implemented using MATLAB S-function to generate the state output. Secondly, the white-box and black-box approaches are used to obtain a linearized second-order altitude models for the quadrotor, AR.Drone 2.0. Proportional (P), pole placement or proportional plus velocity (PV), linear quadratic regulator (LQR), and model reference adaptive control (MRAC) controllers are designed and validated through simulations using MATLAB/Simulink. Control input saturation and time delay in the controlled systems are also studied. MATLAB graphical user interface (GUI) and Simulink programs are developed to implement the controllers on the drone. Thirdly, the time delay in the drone's control system is estimated using analytical and experimental methods. In the experimental approach, the transient properties of the experimental altitude responses are compared to those of simulated responses. The analytical approach makes use of the Lambert W function to obtain analytical solutions of scalar first-order delay differential equations (DDEs). A time-delayed P-feedback control system (retarded type) is used in estimating the time delay. Then an improved system performance is obtained by incorporating the estimated time delay in the design of the PV control system (neutral type) and PV-MRAC control system. Furthermore, the stability of a parametric perturbed linear time-invariant (LTI) retarded-type system is studied. This is done by analytically calculating the stability radius of the system. Simulation of the control system is conducted to confirm the stability. This robust control design and uncertainty analysis are conducted for first-order and second-order quadrotor models. Lastly, the robustly designed PV and PV-MRAC control systems are used to autonomously track multiple waypoints. Also, the robustness of the PV-MRAC controller is tested against a baseline PV controller using the payload capability of the drone. It is shown that the PV-MRAC offers several benefits over the fixed-gain approach of the PV controller. The adaptive control is found to offer enhanced robustness to the payload fluctuations.

Non-Static error tracking control for near space airship loading platform

NASA Astrophysics Data System (ADS)

Ni, Ming; Tao, Fei; Yang, Jiandong

2018-01-01

A control scheme based on internal model with non-static error is presented against the uncertainty of the near space airship loading platform system. The uncertainty in the tracking table is represented as interval variations in stability and control derivatives. By formulating the tracking problem of the uncertainty system as a robust state feedback stabilization problem of an augmented system, sufficient condition for the existence of robust tracking controller is derived in the form of linear matrix inequality (LMI). Finally, simulation results show that the new method not only has better anti-jamming performance, but also improves the dynamic performance of the high-order systems.

Robust control for spacecraft rendezvous system with actuator unsymmetrical saturation: a gain scheduling approach

NASA Astrophysics Data System (ADS)

Wang, Qian; Xue, Anke

2018-06-01

This paper has proposed a robust control for the spacecraft rendezvous system by considering the parameter uncertainties and actuator unsymmetrical saturation based on the discrete gain scheduling approach. By changing of variables, we transform the actuator unsymmetrical saturation control problem into a symmetrical one. The main advantage of the proposed method is improving the dynamic performance of the closed-loop system with a region of attraction as large as possible. By the Lyapunov approach and the scheduling technology, the existence conditions for the admissible controller are formulated in the form of linear matrix inequalities. The numerical simulation illustrates the effectiveness of the proposed method.

Flight Test of Composite Model Reference Adaptive Control (CMRAC) Augmentation Using NASA AirSTAR Infrastructure

NASA Technical Reports Server (NTRS)

Gregory, Irene M.; Gadient, ROss; Lavretsky, Eugene

2011-01-01

This paper presents flight test results of a robust linear baseline controller with and without composite adaptive control augmentation. The flight testing was conducted using the NASA Generic Transport Model as part of the Airborne Subscale Transport Aircraft Research system at NASA Langley Research Center.

Linear and nonlinear schemes applied to pitch control of wind turbines.

PubMed

Geng, Hua; Yang, Geng

2014-01-01

Linear controllers have been employed in industrial applications for many years, but sometimes they are noneffective on the system with nonlinear characteristics. This paper discusses the structure, performance, implementation cost, advantages, and disadvantages of different linear and nonlinear schemes applied to the pitch control of the wind energy conversion systems (WECSs). The linear controller has the simplest structure and is easily understood by the engineers and thus is widely accepted by the industry. In contrast, nonlinear schemes are more complicated, but they can provide better performance. Although nonlinear algorithms can be implemented in a powerful digital processor nowadays, they need time to be accepted by the industry and their reliability needs to be verified in the commercial products. More information about the system nonlinear feature is helpful to simplify the controller design. However, nonlinear schemes independent of the system model are more robust to the uncertainties or deviations of the system parameters.

Nonlinear stability and control study of highly maneuverable high performance aircraft, phase 2

NASA Technical Reports Server (NTRS)

Mohler, R. R.

1992-01-01

Research leading to the development of new nonlinear methodologies for the adaptive control and stability analysis of high angle of attack aircraft such as the F-18 is discussed. The emphasis has been on nonlinear adaptive control, but associated model development, system identification, stability analysis, and simulation were studied in some detail as well. Studies indicated that nonlinear adaptive control can outperform linear adaptive control for rapid maneuvers with large changes in angle of attack. Included here are studies on nonlinear model algorithmic controller design and an analysis of nonlinear system stability using robust stability analysis for linear systems.

Optimal and robust control of transition

NASA Technical Reports Server (NTRS)

Bewley, T. R.; Agarwal, R.

1996-01-01

Optimal and robust control theories are used to determine feedback control rules that effectively stabilize a linearly unstable flow in a plane channel. Wall transpiration (unsteady blowing/suction) with zero net mass flux is used as the control. Control algorithms are considered that depend both on full flowfield information and on estimates of that flowfield based on wall skin-friction measurements only. The development of these control algorithms accounts for modeling errors and measurement noise in a rigorous fashion; these disturbances are considered in both a structured (Gaussian) and unstructured ('worst case') sense. The performance of these algorithms is analyzed in terms of the eigenmodes of the resulting controlled systems, and the sensitivity of individual eigenmodes to both control and observation is quantified.

Robust H(infinity) tracking control of boiler-turbine systems.

PubMed

Wu, J; Nguang, S K; Shen, J; Liu, G; Li, Y G

2010-07-01

In this paper, the problem of designing a fuzzy H(infinity) state feedback tracking control of a boiler-turbine is solved. First, the Takagi and Sugeno fuzzy model is used to model a boiler-turbine system. Next, based on the Takagi and Sugeno fuzzy model, sufficient conditions for the existence of a fuzzy H(infinity) nonlinear state feedback tracking control are derived in terms of linear matrix inequalities. The advantage of the proposed tracking control design is that it does not involve feedback linearization technique and complicated adaptive scheme. An industrial boiler-turbine system is used to illustrate the effectiveness of the proposed design as compared with a linearized approach. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Reusable Launch Vehicle Control In Multiple Time Scale Sliding Modes

NASA Technical Reports Server (NTRS)

Shtessel, Yuri; Hall, Charles; Jackson, Mark

2000-01-01

A reusable launch vehicle control problem during ascent is addressed via multiple-time scaled continuous sliding mode control. The proposed sliding mode controller utilizes a two-loop structure and provides robust, de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of bounded external disturbances and plant uncertainties. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues placement. Overall stability of a two-loop control system is addressed. An optimal control allocation algorithm is designed that allocates torque commands into end-effector deflection commands, which are executed by the actuators. The dual-time scale sliding mode controller was designed for the X-33 technology demonstration sub-orbital launch vehicle in the launch mode. Simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in presence of external disturbances and vehicle inertia uncertainties. This is a significant advancement in performance over that achieved with linear, gain scheduled control systems currently being used for launch vehicles.

Robust control of seismically excited cable stayed bridges with MR dampers

NASA Astrophysics Data System (ADS)

YeganehFallah, Arash; Khajeh Ahamd Attari, Nader

2017-03-01

In recent decades active and semi-active structural control are becoming attractive alternatives for enhancing performance of civil infrastructures subjected to seismic and winds loads. However, in order to have reliable active and semi-active control, there is a need to include information of uncertainties in design of the controller. In real world for civil structures, parameters such as loading places, stiffness, mass and damping are time variant and uncertain. These uncertainties in many cases model as parametric uncertainties. The motivation of this research is to design a robust controller for attenuating the vibrational responses of civil infrastructures, regarding their dynamical uncertainties. Uncertainties in structural dynamic’s parameters are modeled as affine uncertainties in state space modeling. These uncertainties are decoupled from the system through Linear Fractional Transformation (LFT) and are assumed to be unknown input to the system but norm bounded. The robust H ∞ controller is designed for the decoupled system to regulate the evaluation outputs and it is robust to effects of uncertainties, disturbance and sensors noise. The cable stayed bridge benchmark which is equipped with MR damper is considered for the numerical simulation. The simulated results show that the proposed robust controller can effectively mitigate undesired uncertainties effects on systems’ responds under seismic loading.

Controller Synthesis for Periodically Forced Chaotic Systems

NASA Astrophysics Data System (ADS)

Basso, Michele; Genesio, Roberto; Giovanardi, Lorenzo

Delayed feedback controllers are an appealing tool for stabilization of periodic orbits in chaotic systems. Despite their conceptual simplicity, specific and reliable design procedures are difficult to obtain, partly also because of their inherent infinite-dimensional structure. This chapter considers the use of finite dimensional linear time invariant controllers for stabilization of periodic solutions in a general class of sinusoidally forced nonlinear systems. For such controllers — which can be interpreted as rational approximations of the delayed ones — we provide a computationally attractive synthesis technique based on Linear Matrix Inequalities (LMIs), by mixing results concerning absolute stability of nonlinear systems and robustness of uncertain linear systems. The resulting controllers prove to be effective for chaos suppression in electronic circuits and systems, as shown by two different application examples.

High-Alpha Research Vehicle Lateral-Directional Control Law Description, Analyses, and Simulation Results

NASA Technical Reports Server (NTRS)

Davidson, John B.; Murphy, Patrick C.; Lallman, Frederick J.; Hoffler, Keith D.; Bacon, Barton J.

1998-01-01

This report contains a description of a lateral-directional control law designed for the NASA High-Alpha Research Vehicle (HARV). The HARV is a F/A-18 aircraft modified to include a research flight computer, spin chute, and thrust-vectoring in the pitch and yaw axes. Two separate design tools, CRAFT and Pseudo Controls, were integrated to synthesize the lateral-directional control law. This report contains a description of the lateral-directional control law, analyses, and nonlinear simulation (batch and piloted) results. Linear analysis results include closed-loop eigenvalues, stability margins, robustness to changes in various plant parameters, and servo-elastic frequency responses. Step time responses from nonlinear batch simulation are presented and compared to design guidelines. Piloted simulation task scenarios, task guidelines, and pilot subjective ratings for the various maneuvers are discussed. Linear analysis shows that the control law meets the stability margin guidelines and is robust to stability and control parameter changes. Nonlinear batch simulation analysis shows the control law exhibits good performance and meets most of the design guidelines over the entire range of angle-of-attack. This control law (designated NASA-1A) was flight tested during the Summer of 1994 at NASA Dryden Flight Research Center.

Fractional Order PIλDμ Control for Maglev Guiding System

NASA Astrophysics Data System (ADS)

Hu, Qing; Hu, Yuwei

To effectively suppress the external disturbances and parameter perturbation problem of the maglev guiding system, and improve speed and robustness, the electromagnetic guiding system is exactly linearized using state feedback method, Fractional calculus theory is introduced, the order of integer order PID control was extended to the field of fractional, then fractional order PIλDμ Controller was presented, Due to the extra two adjustable parameters compared with traditional PID controller, fractional order PIλDμ controllers were expected to show better control performance. The results of the computer simulation show that the proposed controller suppresses the external disturbances and parameter perturbation of the system effectively; the system response speed was increased; at the same time, it had flexible structure and stronger robustness.

Robust Finite-Dimensional LQG (Linear Quadric Gaussian)-Based Controllers for a Class of Distributed Parameter Systems.

DTIC Science & Technology

1988-06-01

abilities when I lost confidence. Without her help I would not have completed the program. Next, I wish to thank Dr. Peter Maybeck, my research ...being not only a resource for my research . but also for being a friend who listened when I needed a shoulder to cry on. Finally, I wish to give thanks...considered in this research are assumed to be linear quadratic Gaussian (LQG) based controllers. This research first uses a direct approach to

Distributed Time-Varying Formation Robust Tracking for General Linear Multiagent Systems With Parameter Uncertainties and External Disturbances.

PubMed

Hua, Yongzhao; Dong, Xiwang; Li, Qingdong; Ren, Zhang

2017-05-18

This paper investigates the time-varying formation robust tracking problems for high-order linear multiagent systems with a leader of unknown control input in the presence of heterogeneous parameter uncertainties and external disturbances. The followers need to accomplish an expected time-varying formation in the state space and track the state trajectory produced by the leader simultaneously. First, a time-varying formation robust tracking protocol with a totally distributed form is proposed utilizing the neighborhood state information. With the adaptive updating mechanism, neither any global knowledge about the communication topology nor the upper bounds of the parameter uncertainties, external disturbances and leader's unknown input are required in the proposed protocol. Then, in order to determine the control parameters, an algorithm with four steps is presented, where feasible conditions for the followers to accomplish the expected time-varying formation tracking are provided. Furthermore, based on the Lyapunov-like analysis theory, it is proved that the formation tracking error can converge to zero asymptotically. Finally, the effectiveness of the theoretical results is verified by simulation examples.

SUBOPT: A CAD program for suboptimal linear regulators

NASA Technical Reports Server (NTRS)

Fleming, P. J.

1985-01-01

An interactive software package which provides design solutions for both standard linear quadratic regulator (LQR) and suboptimal linear regulator problems is described. Intended for time-invariant continuous systems, the package is easily modified to include sampled-data systems. LQR designs are obtained by established techniques while the large class of suboptimal problems containing controller and/or performance index options is solved using a robust gradient minimization technique. Numerical examples demonstrate features of the package and recent developments are described.

Large planar maneuvers for articulated flexible manipulators

NASA Technical Reports Server (NTRS)

Huang, Jen-Kuang; Yang, Li-Farn

1988-01-01

An articulated flexible manipulator carried on a translational cart is maneuvered by an active controller to perform certain position control tasks. The nonlinear dynamics of the articulated flexible manipulator are derived and a transformation matrix is formulated to localize the nonlinearities within the inertia matrix. Then a feedback linearization scheme is introduced to linearize the dynamic equations for controller design. Through a pole placement technique, a robust controller design is obtained by properly assigning a set of closed-loop desired eigenvalues to meet performance requirements. Numerical simulations for the articulated flexible manipulators are given to demonstrate the feasibility and effectiveness of the proposed position control algorithms.

An LMI approach to design H(infinity) controllers for discrete-time nonlinear systems based on unified models.

PubMed

Liu, Meiqin; Zhang, Senlin

2008-10-01

A unified neural network model termed standard neural network model (SNNM) is advanced. Based on the robust L(2) gain (i.e. robust H(infinity) performance) analysis of the SNNM with external disturbances, a state-feedback control law is designed for the SNNM to stabilize the closed-loop system and eliminate the effect of external disturbances. The control design constraints are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms (e.g. interior-point algorithms) to determine the control law. Most discrete-time recurrent neural network (RNNs) and discrete-time nonlinear systems modelled by neural networks or Takagi and Sugeno (T-S) fuzzy models can be transformed into the SNNMs to be robust H(infinity) performance analyzed or robust H(infinity) controller synthesized in a unified SNNM's framework. Finally, some examples are presented to illustrate the wide application of the SNNMs to the nonlinear systems, and the proposed approach is compared with related methods reported in the literature.

Mixed H2/H∞ distributed robust model predictive control for polytopic uncertain systems subject to actuator saturation and missing measurements

NASA Astrophysics Data System (ADS)

Song, Yan; Fang, Xiaosheng; Diao, Qingda

2016-03-01

In this paper, we discuss the mixed H2/H∞ distributed robust model predictive control problem for polytopic uncertain systems subject to randomly occurring actuator saturation and packet loss. The global system is decomposed into several subsystems, and all the subsystems are connected by a fixed topology network, which is the definition for the packet loss among the subsystems. To better use the successfully transmitted information via Internet, both the phenomena of actuator saturation and packet loss resulting from the limitation of the communication bandwidth are taken into consideration. A novel distributed controller model is established to account for the actuator saturation and packet loss in a unified representation by using two sets of Bernoulli distributed white sequences with known conditional probabilities. With the nonlinear feedback control law represented by the convex hull of a group of linear feedback laws, the distributed controllers for subsystems are obtained by solving an linear matrix inequality (LMI) optimisation problem. Finally, numerical studies demonstrate the effectiveness of the proposed techniques.

A neural network controller of a flotation process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Durao, F.; Cortez, L.

1995-12-31

The dynamic control of a froth flotation section is simulated through a neural network feedback controller, trained in order to stabilize the concentrate metal grade and recovery by applying random step changes to the feed metal grade. The results of the application example show that this controller seems to be sufficiently robust and a good alternative to handle a non-linear process.

Incremental Adaptive Fuzzy Control for Sensorless Stroke Control of A Halbach-type Linear Oscillatory Motor

NASA Astrophysics Data System (ADS)

Lei, Meizhen; Wang, Liqiang

2018-01-01

The halbach-type linear oscillatory motor (HT-LOM) is multi-variable, highly coupled, nonlinear and uncertain, and difficult to get a satisfied result by conventional PID control. An incremental adaptive fuzzy controller (IAFC) for stroke tracking was presented, which combined the merits of PID control, the fuzzy inference mechanism and the adaptive algorithm. The integral-operation is added to the conventional fuzzy control algorithm. The fuzzy scale factor can be online tuned according to the load force and stroke command. The simulation results indicate that the proposed control scheme can achieve satisfied stroke tracking performance and is robust with respect to parameter variations and external disturbance.

A Comparison of Multivariable Control Design Techniques for a Turbofan Engine Control

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Watts, Stephen R.

1995-01-01

This paper compares two previously published design procedures for two different multivariable control design techniques for application to a linear engine model of a jet engine. The two multivariable control design techniques compared were the Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) and the H-Infinity synthesis. The two control design techniques were used with specific previously published design procedures to synthesize controls which would provide equivalent closed loop frequency response for the primary control loops while assuring adequate loop decoupling. The resulting controllers were then reduced in order to minimize the programming and data storage requirements for a typical implementation. The reduced order linear controllers designed by each method were combined with the linear model of an advanced turbofan engine and the system performance was evaluated for the continuous linear system. Included in the performance analysis are the resulting frequency and transient responses as well as actuator usage and rate capability for each design method. The controls were also analyzed for robustness with respect to structured uncertainties in the unmodeled system dynamics. The two controls were then compared for performance capability and hardware implementation issues.

Modeling and comparative study of linear and nonlinear controllers for rotary inverted pendulum

NASA Astrophysics Data System (ADS)

Lima, Byron; Cajo, Ricardo; Huilcapi, Víctor; Agila, Wilton

2017-01-01

The rotary inverted pendulum (RIP) is a problem difficult to control, several studies have been conducted where different control techniques have been applied. Literature reports that, although problem is nonlinear, classical PID controllers presents appropriate performances when applied to the system. In this paper, a comparative study of the performances of linear and nonlinear PID structures is carried out. The control algorithms are evaluated in the RIP system, using indices of performance and power consumption, which allow the categorization of control strategies according to their performance. This article also presents the modeling system, which has been estimated some of the parameters involved in the RIP system, using computer-aided design tools (CAD) and experimental methods or techniques proposed by several authors attended. The results indicate a better performance of the nonlinear controller with an increase in the robustness and faster response than the linear controller.

Sliding Mode Control of a Thermal Mixing Process

NASA Technical Reports Server (NTRS)

Richter, Hanz; Figueroa, Fernando

2004-01-01

In this paper we consider the robust control of a thermal mixer using multivariable Sliding Mode Control (SMC). The mixer consists of a mixing chamber, hot and cold fluid valves, and an exit valve. The commanded positions of the three valves are the available control inputs, while the controlled variables are total mass flow rate, chamber pressure and the density of the mixture inside the chamber. Unsteady thermodynamics and linear valve models are used in deriving a 5th order nonlinear system with three inputs and three outputs, An SMC controller is designed to achieve robust output tracking in the presence of unknown energy losses between the chamber and the environment. The usefulness of the technique is illustrated with a simulation.

Robust energy-absorbing compensators for the ACTEX II test article

NASA Astrophysics Data System (ADS)

Blaurock, Carl A.; Miller, David W.; Nye, Ted

1995-05-01

The paper addresses the problem of satellite solar panel vibration. A multi-layer vibration control scheme is investigated using a flight test article. Key issues in the active control portion are presented in the paper. The paper discusses the primary control design drivers, which are the time variations in modal frequencies due to configuration and thermal changes. A local control design approach is investigated, but found to be unworkable due to sensor/actuator non-collocation. An alternate design process uses linear robust control techniques, by describing the modal shifts as uncertainties. Multiple modal design, alpha- shifted multiple model, and a feedthrough compensation scheme are examined. Ground and simulation tests demonstrate that the resulting controllers provide significant vibration reduction in the presence of expected system variations.

Robust adaptive sliding mode control for uncertain systems with unknown time-varying delay input.

PubMed

Benamor, Anouar; Messaoud, Hassani

2018-05-02

This article focuses on robust adaptive sliding mode control law for uncertain discrete systems with unknown time-varying delay input, where the uncertainty is assumed unknown. The main results of this paper are divided into three phases. In the first phase, we propose a new sliding surface is derived within the Linear Matrix Inequalities (LMIs). In the second phase, using the new sliding surface, the novel Robust Sliding Mode Control (RSMC) is proposed where the upper bound of uncertainty is supposed known. Finally, the novel approach of Robust Adaptive Sliding ModeControl (RASMC) has been defined for this type of systems, where the upper limit of uncertainty which is assumed unknown. In this new approach, we have estimate the upper limit of uncertainties and we have determined the control law based on a sliding surface that will converge to zero. This novel control laws are been validated in simulation on an uncertain numerical system with good results and comparative study. This efficiency is emphasized through the application of the new controls on the two physical systems which are the process trainer PT326 and hydraulic system two tanks. Published by Elsevier Ltd.

Stability margin of linear systems with parameters described by fuzzy numbers.

PubMed

Husek, Petr

2011-10-01

This paper deals with the linear systems with uncertain parameters described by fuzzy numbers. The problem of determining the stability margin of those systems with linear affine dependence of the coefficients of a characteristic polynomial on system parameters is studied. Fuzzy numbers describing the system parameters are allowed to be characterized by arbitrary nonsymmetric membership functions. An elegant solution, graphical in nature, based on generalization of the Tsypkin-Polyak plot is presented. The advantage of the presented approach over the classical robust concept is demonstrated on a control of the Fiat Dedra engine model and a control of the quarter car suspension model.

Linear-parameter-varying gain-scheduled control of aerospace systems

NASA Astrophysics Data System (ADS)

Barker, Jeffrey Michael

The dynamics of many aerospace systems vary significantly as a function of flight condition. Robust control provides methods of guaranteeing performance and stability goals across flight conditions. In mu-syntthesis, changes to the dynamical system are primarily treated as uncertainty. This method has been successfully applied to many control problems, and here is applied to flutter control. More recently, two techniques for generating robust gain-scheduled controller have been developed. Linear fractional transformation (LFT) gain-scheduled control is an extension of mu-synthesis in which the plant and controller are explicit functions of parameters measurable in real-time. This LFT gain-scheduled control technique is applied to the Benchmark Active Control Technology (BACT) wing, and compared with mu-synthesis control. Linear parameter-varying (LPV) gain-scheduled control is an extension of Hinfinity control to parameter varying systems. LPV gain-scheduled control directly incorporates bounds on the rate of change of the scheduling parameters, and often reduces conservatism inherent in LFT gain-scheduled control. Gain-scheduled LPV control of the BACT wing compares very favorably with the LFT controller. Gain-scheduled LPV controllers are generated for the lateral-directional and longitudinal axes of the Innovative Control Effectors (ICE) aircraft and implemented in nonlinear simulations and real-time piloted nonlinear simulations. Cooper-Harper and pilot-induced oscillation ratings were obtained for an initial design, a reference aircraft and a redesign. Piloted simulation results for the initial LPV gain-scheduled control of the ICE aircraft are compared with results for a conventional fighter aircraft in discrete pitch and roll angle tracking tasks. The results for the redesigned controller are significantly better than both the previous LPV controller and the conventional aircraft.

Technical notes and correspondence: Stochastic robustness of linear time-invariant control systems

NASA Technical Reports Server (NTRS)

Stengel, Robert F.; Ray, Laura R.

1991-01-01

A simple numerical procedure for estimating the stochastic robustness of a linear time-invariant system is described. Monte Carlo evaluations of the system's eigenvalues allows the probability of instability and the related stochastic root locus to be estimated. This analysis approach treats not only Gaussian parameter uncertainties but non-Gaussian cases, including uncertain-but-bounded variation. Confidence intervals for the scalar probability of instability address computational issues inherent in Monte Carlo simulation. Trivial extensions of the procedure admit consideration of alternate discriminants; thus, the probabilities that stipulated degrees of instability will be exceeded or that closed-loop roots will leave desirable regions can also be estimated. Results are particularly amenable to graphical presentation.

Robust cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain dynamics

NASA Astrophysics Data System (ADS)

Li, Keqiang; Gao, Feng; Li, Shengbo Eben; Zheng, Yang; Gao, Hongbo

2017-12-01

This study presents a distributed H-infinity control method for uncertain platoons with dimensionally and structurally unknown interaction topologies provided that the associated topological eigenvalues are bounded by a predesigned range.With an inverse model to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertain systems with bounded disturbances. On the basis of the eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertain part and a diagonally structured certain part by applying linear transformation. We then use a common Lyapunov method to design a distributed H-infinity controller. Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should be solved. The resulting controller can tolerate interaction topologies with eigenvalues located in a certain range. The proposed method can also ensure robustness performance and disturbance attenuation ability for the closed-loop platoon system. Hardware-in-the-loop tests are performed to validate the effectiveness of our method.

Fuzzy logic-based flight control system design

NASA Astrophysics Data System (ADS)

Nho, Kyungmoon

The application of fuzzy logic to aircraft motion control is studied in this dissertation. The self-tuning fuzzy techniques are developed by changing input scaling factors to obtain a robust fuzzy controller over a wide range of operating conditions and nonlinearities for a nonlinear aircraft model. It is demonstrated that the properly adjusted input scaling factors can meet the required performance and robustness in a fuzzy controller. For a simple demonstration of the easy design and control capability of a fuzzy controller, a proportional-derivative (PD) fuzzy control system is compared to the conventional controller for a simple dynamical system. This thesis also describes the design principles and stability analysis of fuzzy control systems by considering the key features of a fuzzy control system including the fuzzification, rule-base and defuzzification. The wing-rock motion of slender delta wings, a linear aircraft model and the six degree of freedom nonlinear aircraft dynamics are considered to illustrate several self-tuning methods employing change in input scaling factors. Finally, this dissertation is concluded with numerical simulation of glide-slope capture in windshear demonstrating the robustness of the fuzzy logic based flight control system.

Robust control of speed and temperature in a power plant gas turbine.

PubMed

Najimi, Ebrahim; Ramezani, Mohammad Hossein

2012-03-01

In this paper, an H(∞) robust controller has been designed for an identified model of MONTAZER GHAEM power plant gas turbine (GE9001E). In design phase, a linear model (ARX model) which is obtained using real data has been applied. Since the turbine has been used in a combined cycle power plant, its speed and also the exhaust gas temperature should be adjusted simultaneously by controlling fuel signals and compressor inlet guide vane (IGV) position. Considering the limitations on the system inputs, the aim of the control is to maintain the turbine speed and the exhaust gas temperature within desired interval under uncertainties and load demand disturbances. Simulation results of applying the proposed robust controller on the nonlinear model of the system (NARX model), fairly fulfilled the predefined aims. Simulations also show the improvement in the performance compared to MPC and PID controllers for the same conditions. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

A nonlinear H-infinity approach to optimal control of the depth of anaesthesia

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Rigatou, Efthymia; Zervos, Nikolaos

2016-12-01

Controlling the level of anaesthesia is important for improving the success rate of surgeries and for reducing the risks to which operated patients are exposed. This paper proposes a nonlinear H-infinity approach to optimal control of the level of anaesthesia. The dynamic model of the anaesthesia, which describes the concentration of the anaesthetic drug in different parts of the body, is subjected to linearization at local operating points. These are defined at each iteration of the control algorithm and consist of the present value of the system's state vector and of the last control input that was exerted on it. For this linearization Taylor series expansion is performed and the system's Jacobian matrices are computed. For the linearized model an H-infinity controller is designed. The feedback control gains are found by solving at each iteration of the control algorithm an algebraic Riccati equation. The modelling errors due to this approximate linearization are considered as disturbances which are compensated by the robustness of the control loop. The stability of the control loop is confirmed through Lyapunov analysis.

Joint Services Electronics Program.

DTIC Science & Technology

1983-09-30

environment. The research is under three interrelated heads: (1) algebraic Methodologies for Control Systems design , both linear and non -linear, (2) robust...properties of the device. After study of these experimental results, we plan to design a millimeter- wave version of the Gunn device. This will...appropriate dose discretization level for an adju- stable width beam. 2) Experimental Device Fabrication In a collaborative effort with the IC design group

A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear Optimization

PubMed Central

Li, Zukui; Ding, Ran; Floudas, Christodoulos A.

2011-01-01

Robust counterpart optimization techniques for linear optimization and mixed integer linear optimization problems are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. For uncertainty in the left hand side, right hand side, and objective function of the optimization problems, robust counterpart optimization formulations induced by those different uncertainty sets are derived. Numerical studies are performed to compare the solutions of the robust counterpart optimization models and applications in refinery production planning and batch process scheduling problem are presented. PMID:21935263

Missile Guidance Law Based on Robust Model Predictive Control Using Neural-Network Optimization.

PubMed

Li, Zhijun; Xia, Yuanqing; Su, Chun-Yi; Deng, Jun; Fu, Jun; He, Wei

2015-08-01

In this brief, the utilization of robust model-based predictive control is investigated for the problem of missile interception. Treating the target acceleration as a bounded disturbance, novel guidance law using model predictive control is developed by incorporating missile inside constraints. The combined model predictive approach could be transformed as a constrained quadratic programming (QP) problem, which may be solved using a linear variational inequality-based primal-dual neural network over a finite receding horizon. Online solutions to multiple parametric QP problems are used so that constrained optimal control decisions can be made in real time. Simulation studies are conducted to illustrate the effectiveness and performance of the proposed guidance control law for missile interception.

Applications of Nonlinear Control Using the State-Dependent Riccati Equation.

DTIC Science & Technology

1995-12-01

method, and do not address noise rejection or robustness issues. xi Applications of Nonlinear Control Using the State-Dependent Riccati Equation I...construct a stabilizing nonlinear feedback controller. This method will be referred to as nonlinear quadratic regulation (NQR). The original intention...involves nding a state-dependent coe- cient (SDC) linear structure for which a stabilizing nonlinear feedback controller can be constructed. The

Robust hopping based on virtual pendulum posture control.

PubMed

Sharbafi, Maziar A; Maufroy, Christophe; Ahmadabadi, Majid Nili; Yazdanpanah, Mohammad J; Seyfarth, Andre

2013-09-01

A new control approach to achieve robust hopping against perturbations in the sagittal plane is presented in this paper. In perturbed hopping, vertical body alignment has a significant role for stability. Our approach is based on the virtual pendulum concept, recently proposed, based on experimental findings in human and animal locomotion. In this concept, the ground reaction forces are pointed to a virtual support point, named virtual pivot point (VPP), during motion. This concept is employed in designing the controller to balance the trunk during the stance phase. New strategies for leg angle and length adjustment besides the virtual pendulum posture control are proposed as a unified controller. This method is investigated by applying it on an extension of the spring loaded inverted pendulum (SLIP) model. Trunk, leg mass and damping are added to the SLIP model in order to make the model more realistic. The stability is analyzed by Poincaré map analysis. With fixed VPP position, stability, disturbance rejection and moderate robustness are achieved, but with a low convergence speed. To improve the performance and attain higher robustness, an event-based control of the VPP position is introduced, using feedback of the system states at apexes. Discrete linear quartic regulator is used to design the feedback controller. Considerable enhancements with respect to stability, convergence speed and robustness against perturbations and parameter changes are achieved.

Multivariable control of a twin lift helicopter system using the LQG/LTR design methodology

NASA Technical Reports Server (NTRS)

Rodriguez, A. A.; Athans, M.

1986-01-01

Guidelines for developing a multivariable centralized automatic flight control system (AFCS) for a twin lift helicopter system (TLHS) are presented. Singular value ideas are used to formulate performance and stability robustness specifications. A linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) design is obtained and evaluated.

Robust Adaptive Flight Control Design of Air-breathing Hypersonic Vehicles

DTIC Science & Technology

2016-12-07

dynamic inversion controller design for a non -minimum phase hypersonic vehicle is derived by Kuipers et al. [2008]. Moreover, integrated guidance and...stabilization time for inner loop variables is lesser than the intermediate loop variables because of the three-loop-control design methodology . The control...adaptive design . Control Engineering Practice, 2016. Michael A Bolender and David B Doman. A non -linear model for the longitudinal dynamics of a

Resilient guaranteed cost control of a power system.

PubMed

Soliman, Hisham M; Soliman, Mostafa H; Hassan, Mohammad F

2014-05-01

With the development of power system interconnection, the low-frequency oscillation is becoming more and more prominent which may cause system separation and loss of energy to consumers. This paper presents an innovative robust control for power systems in which the operating conditions are changing continuously due to load changes. However, practical implementation of robust control can be fragile due to controller inaccuracies (tolerance of resistors used with operational amplifiers). A new design of resilient (non-fragile) robust control is given that takes into consideration both model and controller uncertainties by an iterative solution of a set of linear matrix inequalities (LMI). Both uncertainties are cast into a norm-bounded structure. A sufficient condition is derived to achieve the desired settling time for damping power system oscillations in face of plant and controller uncertainties. Furthermore, an improved controller design, resilient guaranteed cost controller, is derived to achieve oscillations damping in a guaranteed cost manner. The effectiveness of the algorithm is shown for a single machine infinite bus system, and then, it is extended to multi-area power system.

A nonlinear optimal control approach for chaotic finance dynamics

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.

2017-11-01

A new nonlinear optimal control approach is proposed for stabilization of the dynamics of a chaotic finance model. The dynamic model of the financial system, which expresses interaction between the interest rate, the investment demand, the price exponent and the profit margin, undergoes approximate linearization round local operating points. These local equilibria are defined at each iteration of the control algorithm and consist of the present value of the systems state vector and the last value of the control inputs vector that was exerted on it. The approximate linearization makes use of Taylor series expansion and of the computation of the associated Jacobian matrices. The truncation of higher order terms in the Taylor series expansion is considered to be a modelling error that is compensated by the robustness of the control loop. As the control algorithm runs, the temporary equilibrium is shifted towards the reference trajectory and finally converges to it. The control method needs to compute an H-infinity feedback control law at each iteration, and requires the repetitive solution of an algebraic Riccati equation. Through Lyapunov stability analysis it is shown that an H-infinity tracking performance criterion holds for the control loop. This implies elevated robustness against model approximations and external perturbations. Moreover, under moderate conditions the global asymptotic stability of the control loop is proven.

A robust momentum management and attitude control system for the space station

NASA Technical Reports Server (NTRS)

Speyer, J. L.; Rhee, Ihnseok

1991-01-01

A game theoretic controller is synthesized for momentum management and attitude control of the Space Station in the presence of uncertainties in the moments of inertia. Full state information is assumed since attitude rates are assumed to be very assurately measured. By an input-output decomposition of the uncertainty in the system matrices, the parameter uncertainties in the dynamic system are represented as an unknown gain associated with an internal feedback loop (IFL). The input and output matrices associated with the IFL form directions through which the uncertain parameters affect system response. If the quadratic form of the IFL output augments the cost criterion, then enhanced parameter robustness is anticipated. By considering the input and the input disturbance from the IFL as two noncooperative players, a linear-quadratic differential game is constructed. The solution in the form of a linear controller is used for synthesis. Inclusion of the external disturbance torques results in a dynamic feedback controller which consists of conventional PID (proportional integral derivative) control and cyclic disturbance rejection filters. It is shown that the game theoretic design allows large variations in the inertias in directions of importance.

Robust momentum management and attitude control system for the Space Station

NASA Technical Reports Server (NTRS)

Rhee, Ihnseok; Speyer, Jason L.

1992-01-01

A game theoretic controller is synthesized for momentum management and attitude control of the Space Station in the presence of uncertainties in the moments of inertia. Full state information is assumed since attitude rates are assumed to be very accurately measured. By an input-output decomposition of the uncertainty in the system matrices, the parameter uncertainties in the dynamic system are represented as an unknown gain associated with an internal feedback loop (IFL). The input and output matrices associated with the IFL form directions through which the uncertain parameters affect system response. If the quadratic form of the IFL output augments the cost criterion, then enhanced parameter robustness is anticipated. By considering the input and the input disturbance from the IFL as two noncooperative players, a linear-quadratic differential game is constructed. The solution in the form of a linear controller is used for synthesis. Inclusion of the external disturbance torques results in a dynamic feedback controller which consists of conventional PID (proportional integral derivative) control and cyclic disturbance rejection filters. It is shown that the game theoretic design allows large variations in the inertias in directions of importance.

Passivity-based Robust Control of Aerospace Systems

NASA Technical Reports Server (NTRS)

Kelkar, Atul G.; Joshi, Suresh M. (Technical Monitor)

2000-01-01

This report provides a brief summary of the research work performed over the duration of the cooperative research agreement between NASA Langley Research Center and Kansas State University. The cooperative agreement which was originally for the duration the three years was extended by another year through no-cost extension in order to accomplish the goals of the project. The main objective of the research was to develop passivity-based robust control methodology for passive and non-passive aerospace systems. The focus of the first-year's research was limited to the investigation of passivity-based methods for the robust control of Linear Time-Invariant (LTI) single-input single-output (SISO), open-loop stable, minimum-phase non-passive systems. The second year's focus was mainly on extending the passivity-based methodology to a larger class of non-passive LTI systems which includes unstable and nonminimum phase SISO systems. For LTI non-passive systems, five different passification. methods were developed. The primary effort during the years three and four was on the development of passification methodology for MIMO systems, development of methods for checking robustness of passification, and developing synthesis techniques for passifying compensators. For passive LTI systems optimal synthesis procedure was also developed for the design of constant-gain positive real controllers. For nonlinear passive systems, numerical optimization-based technique was developed for the synthesis of constant as well as time-varying gain positive-real controllers. The passivity-based control design methodology developed during the duration of this project was demonstrated by its application to various benchmark examples. These example systems included longitudinal model of an F-18 High Alpha Research Vehicle (HARV) for pitch axis control, NASA's supersonic transport wind tunnel model, ACC benchmark model, 1-D acoustic duct model, piezo-actuated flexible link model, and NASA's Benchmark Active Controls Technology (BACT) Wing model. Some of the stability results for linear passive systems were also extended to nonlinear passive systems. Several publications and conference presentations resulted from this research.

The Stability Region for Feedback Control of the Wake Behind Twin Oscillating Cylinders

NASA Astrophysics Data System (ADS)

Borggaard, Jeff; Gugercin, Serkan; Zietsman, Lizette

2016-11-01

Linear feedback control has the ability to stabilize vortex shedding behind twin cylinders where cylinder rotation is the actuation mechanism. Complete elimination of the wake is only possible for certain Reynolds numbers and cylinder spacing. This is related to the presence of asymmetric unstable modes in the linearized system. We investigate this region of parameter space using a number of closed-loop simulations that bound this region. We then consider the practical issue of designing feedback controls based on limited state measurements by building a nonlinear compensator using linear robust control theory with and incorporating the nonlinear terms in the compensator (e.g., using the extended Kalman filter). Interpolatory model reduction methods are applied to the large discretized, linearized Navier-Stokes system and used for computing the control laws and compensators. Preliminary closed-loop simulations of a three-dimensional version of this problem will also be presented. Supported in part by the National Science Foundation.

Control method for physical systems and devices

DOEpatents

Guckenheimer, John

1997-01-01

A control method for stabilizing systems or devices that are outside the control domain of a linear controller is provided. When applied to nonlinear systems, the effectiveness of this method depends upon the size of the domain of stability that is produced for the stabilized equilibrium. If this domain is small compared to the accuracy of measurements or the size of disturbances within the system, then the linear controller is likely to fail within a short period. Failure of the system or device can be catastrophic: the system or device can wander far from the desired equilibrium. The method of the invention presents a general procedure to recapture the stability of a linear controller, when the trajectory of a system or device leaves its region of stability. By using a hybrid strategy based upon discrete switching events within the state space of the system or device, the system or device will return from a much larger domain to the region of stability utilized by the linear controller. The control procedure is robust and remains effective under large classes of perturbations of a given underlying system or device.

Decoupling control of vehicle chassis system based on neural network inverse system

NASA Astrophysics Data System (ADS)

Wang, Chunyan; Zhao, Wanzhong; Luan, Zhongkai; Gao, Qi; Deng, Ke

2018-06-01

Steering and suspension are two important subsystems affecting the handling stability and riding comfort of the chassis system. In order to avoid the interference and coupling of the control channels between active front steering (AFS) and active suspension subsystems (ASS), this paper presents a composite decoupling control method, which consists of a neural network inverse system and a robust controller. The neural network inverse system is composed of a static neural network with several integrators and state feedback of the original chassis system to approach the inverse system of the nonlinear systems. The existence of the inverse system for the chassis system is proved by the reversibility derivation of Interactor algorithm. The robust controller is based on the internal model control (IMC), which is designed to improve the robustness and anti-interference of the decoupled system by adding a pre-compensation controller to the pseudo linear system. The results of the simulation and vehicle test show that the proposed decoupling controller has excellent decoupling performance, which can transform the multivariable system into a number of single input and single output systems, and eliminate the mutual influence and interference. Furthermore, it has satisfactory tracking capability and robust performance, which can improve the comprehensive performance of the chassis system.

Active disturbance rejection control based robust output feedback autopilot design for airbreathing hypersonic vehicles.

PubMed

Tian, Jiayi; Zhang, Shifeng; Zhang, Yinhui; Li, Tong

2018-03-01

Since motion control plant (y (n) =f(⋅)+d) was repeatedly used to exemplify how active disturbance rejection control (ADRC) works when it was proposed, the integral chain system subject to matched disturbances is always regarded as a canonical form and even misconstrued as the only form that ADRC is applicable to. In this paper, a systematic approach is first presented to apply ADRC to a generic nonlinear uncertain system with mismatched disturbances and a robust output feedback autopilot for an airbreathing hypersonic vehicle (AHV) is devised based on that. The key idea is to employ the feedback linearization (FL) and equivalent input disturbance (EID) technique to decouple nonlinear uncertain system into several subsystems in canonical form, thus it would be much easy to directly design classical/improved linear/nonlinear ADRC controller for each subsystem. It is noticed that all disturbances are taken into account when implementing FL rather than just omitting that in previous research, which greatly enhances controllers' robustness against external disturbances. For autopilot design, ADRC strategy enables precise tracking for velocity and altitude reference command in the presence of severe parametric perturbations and atmospheric disturbances only using measurable output information. Bounded-input-bounded-output (BIBO) stable is analyzed for closed-loop system. To illustrate the feasibility and superiority of this novel design, a series of comparative simulations with some prominent and representative methods are carried out on a benchmark longitudinal AHV model. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Decentralized Control of Sound Radiation using a High-Authority/Low-Authority Control Strategy with Anisotropic Actuators

NASA Technical Reports Server (NTRS)

Schiller, Noah H.; Cabell, Randolph H.; Fuller, Chris R.

2008-01-01

This paper describes a combined control strategy designed to reduce sound radiation from stiffened aircraft-style panels. The control architecture uses robust active damping in addition to high-authority linear quadratic Gaussian (LQG) control. Active damping is achieved using direct velocity feedback with triangularly shaped anisotropic actuators and point velocity sensors. While active damping is simple and robust, stability is guaranteed at the expense of performance. Therefore the approach is often referred to as low-authority control. In contrast, LQG control strategies can achieve substantial reductions in sound radiation. Unfortunately, the unmodeled interaction between neighboring control units can destabilize decentralized control systems. Numerical simulations show that combining active damping and decentralized LQG control can be beneficial. In particular, augmenting the in-bandwidth damping supplements the performance of the LQG control strategy and reduces the destabilizing interaction between neighboring control units.

Robust dynamic inversion controller design and analysis (using the X-38 vehicle as a case study)

NASA Astrophysics Data System (ADS)

Ito, Daigoro

A new way to approach robust Dynamic Inversion controller synthesis is addressed in this paper. A Linear Quadratic Gaussian outer-loop controller improves the robustness of a Dynamic Inversion inner-loop controller in the presence of uncertainties. Desired dynamics are given by the dynamic compensator, which shapes the loop. The selected dynamics are based on both performance and stability robustness requirements. These requirements are straightforwardly formulated as frequency-dependent singular value bounds during synthesis of the controller. Performance and robustness of the designed controller is tested using a worst case time domain quadratic index, which is a simple but effective way to measure robustness due to parameter variation. Using this approach, a lateral-directional controller for the X-38 vehicle is designed and its robustness to parameter variations and disturbances is analyzed. It is found that if full state measurements are available, the performance of the designed lateral-directional control system, measured by the chosen cost function, improves by approximately a factor of four. Also, it is found that the designed system is stable up to a parametric variation of 1.65 standard deviation with the set of uncertainty considered. The system robustness is determined to be highly sensitive to the dihedral derivative and the roll damping coefficients. The controller analysis is extended to the nonlinear system where both control input displacements and rates are bounded. In this case, the considered nonlinear system is stable up to 48.1° in bank angle and 1.59° in sideslip angle variations, indicating it is more sensitive to variations in sideslip angle than in bank angle. This nonlinear approach is further extended for the actuator failure mode analysis. The results suggest that the designed system maintains a high level of stability in the event of aileron failure. However, only 35% or less of the original stability range is maintained for the rudder failure case. Overall, this combination of controller synthesis and robustness criteria compares well with the mu-synthesis technique. It also is readily accessible to the practicing engineer, in terms of understanding and use.

Linear-quadratic-Gaussian synthesis with reduced parameter sensitivity

NASA Technical Reports Server (NTRS)

Lin, J. Y.; Mingori, D. L.

1992-01-01

We present a method for improving the tolerance of a conventional LQG controller to parameter errors in the plant model. The improvement is achieved by introducing additional terms reflecting the structure of the parameter errors into the LQR cost function, and also the process and measurement noise models. Adjusting the sizes of these additional terms permits a trade-off between robustness and nominal performance. Manipulation of some of the additional terms leads to high gain controllers while other terms lead to low gain controllers. Conditions are developed under which the high-gain approach asymptotically recovers the robustness of the corresponding full-state feedback design, and the low-gain approach makes the closed-loop poles asymptotically insensitive to parameter errors.

Preliminary assessment of the robustness of dynamic inversion based flight control laws

NASA Technical Reports Server (NTRS)

Snell, S. A.

1992-01-01

Dynamic-inversion-based flight control laws present an attractive alternative to conventional gain-scheduled designs for high angle-of-attack maneuvering, where nonlinearities dominate the dynamics. Dynamic inversion is easily applied to the aircraft dynamics requiring a knowledge of the nonlinear equations of motion alone, rather than an extensive set of linearizations. However, the robustness properties of the dynamic inversion are questionable especially when considering the uncertainties involved with the aerodynamic database during post-stall flight. This paper presents a simple analysis and some preliminary results of simulations with a perturbed database. It is shown that incorporating integrators into the control loops helps to improve the performance in the presence of these perturbations.

New nonlinear control algorithms for multiple robot arms

NASA Technical Reports Server (NTRS)

Tarn, T. J.; Bejczy, A. K.; Yun, X.

1988-01-01

Multiple coordinated robot arms are modeled by considering the arms as closed kinematic chains and as a force-constrained mechanical system working on the same object simultaneously. In both formulations, a novel dynamic control method is discussed. It is based on feedback linearization and simultaneous output decoupling technique. By applying a nonlinear feedback and a nonlinear coordinate transformation, the complicated model of the multiple robot arms in either formulation is converted into a linear and output decoupled system. The linear system control theory and optimal control theory are used to design robust controllers in the task space. The first formulation has the advantage of automatically handling the coordination and load distribution among the robot arms. In the second formulation, it was found that by choosing a general output equation it became possible simultaneously to superimpose the position and velocity error feedback with the force-torque error feedback in the task space.

Variable structure control of nonlinear systems through simplified uncertain models

NASA Technical Reports Server (NTRS)

Sira-Ramirez, Hebertt

1986-01-01

A variable structure control approach is presented for the robust stabilization of feedback equivalent nonlinear systems whose proposed model lies in the same structural orbit of a linear system in Brunovsky's canonical form. An attempt to linearize exactly the nonlinear plant on the basis of the feedback control law derived for the available model results in a nonlinearly perturbed canonical system for the expanded class of possible equivalent control functions. Conservatism tends to grow as modeling errors become larger. In order to preserve the internal controllability structure of the plant, it is proposed that model simplification be carried out on the open-loop-transformed system. As an example, a controller is developed for a single link manipulator with an elastic joint.

Robust synergetic control design under inputs and states constraints

NASA Astrophysics Data System (ADS)

Rastegar, Saeid; Araújo, Rui; Sadati, Jalil

2018-03-01

In this paper, a novel robust-constrained control methodology for discrete-time linear parameter-varying (DT-LPV) systems is proposed based on a synergetic control theory (SCT) approach. It is shown that in DT-LPV systems without uncertainty, and for any unmeasured bounded additive disturbance, the proposed controller accomplishes the goal of stabilising the system by asymptotically driving the error of the controlled variable to a bounded set containing the origin and then maintaining it there. Moreover, given an uncertain DT-LPV system jointly subject to unmeasured and constrained additive disturbances, and constraints in states, input commands and reference signals (set points), then invariant set theory is used to find an appropriate polyhedral robust invariant region in which the proposed control framework is guaranteed to robustly stabilise the closed-loop system. Furthermore, this is achieved even for the case of varying non-zero control set points in such uncertain DT-LPV systems. The controller is characterised to have a simple structure leading to an easy implementation, and a non-complex design process. The effectiveness of the proposed method and the implications of the controller design on feasibility and closed-loop performance are demonstrated through application examples on the temperature control on a continuous-stirred tank reactor plant, on the control of a real-coupled DC motor plant, and on an open-loop unstable system example.

Design of a candidate flutter suppression control law for DAST ARW-2. [Drones for Aerodynamic and Structural Testing Aeroelastic Research Wing

NASA Technical Reports Server (NTRS)

Adams, W. M., Jr.; Tiffany, S. H.

1983-01-01

A control law is developed to suppress symmetric flutter for a mathematical model of an aeroelastic research vehicle. An implementable control law is attained by including modified LQG (linear quadratic Gaussian) design techniques, controller order reduction, and gain scheduling. An alternate (complementary) design approach is illustrated for one flight condition wherein nongradient-based constrained optimization techniques are applied to maximize controller robustness.

Sliding Mode Thermal Control System for Space Station Furnace Facility

NASA Technical Reports Server (NTRS)

Jackson Mark E.; Shtessel, Yuri B.

1998-01-01

The decoupled control of the nonlinear, multiinput-multioutput, and highly coupled space station furnace facility (SSFF) thermal control system is addressed. Sliding mode control theory, a subset of variable-structure control theory, is employed to increase the performance, robustness, and reliability of the SSFF's currently designed control system. This paper presents the nonlinear thermal control system description and develops the sliding mode controllers that cause the interconnected subsystems to operate in their local sliding modes, resulting in control system invariance to plant uncertainties and external and interaction disturbances. The desired decoupled flow-rate tracking is achieved by optimization of the local linear sliding mode equations. The controllers are implemented digitally and extensive simulation results are presented to show the flow-rate tracking robustness and invariance to plant uncertainties, nonlinearities, external disturbances, and variations of the system pressure supplied to the controlled subsystems.

Bellman Continuum (3rd) International Workshop (13-14 June 1988)

DTIC Science & Technology

1988-06-01

Modelling Uncertain Problem ................. 53 David Bensoussan ,---,>Asymptotic Linearization of Uncertain Multivariable Systems by Sliding Modes...K. Ghosh .-. Robust Model Tracking for a Class of Singularly Perturbed Nonlinear Systems via Composite Control ....... 93 F. Garofalo and L. Glielmo...MODELISATION ET COMMANDE EN ECONOMIE MODELS AND CONTROL POLICIES IN ECONOMICS Qualitative Differential Games : A Viability Approach ............. 117

Smith predictor based-sliding mode controller for integrating processes with elevated deadtime.

PubMed

Camacho, Oscar; De la Cruz, Francisco

2004-04-01

An approach to control integrating processes with elevated deadtime using a Smith predictor sliding mode controller is presented. A PID sliding surface and an integrating first-order plus deadtime model have been used to synthesize the controller. Since the performance of existing controllers with a Smith predictor decrease in the presence of modeling errors, this paper presents a simple approach to combining the Smith predictor with the sliding mode concept, which is a proven, simple, and robust procedure. The proposed scheme has a set of tuning equations as a function of the characteristic parameters of the model. For implementation of our proposed approach, computer based industrial controllers that execute PID algorithms can be used. The performance and robustness of the proposed controller are compared with the Matausek-Micić scheme for linear systems using simulations.

Design and implementation of a new modified sliding mode controller for grid-connected inverter to controlling the voltage and frequency.

PubMed

Ghanbarian, Mohammad Mehdi; Nayeripour, Majid; Rajaei, Amirhossein; Mansouri, Mohammad Mahdi

2016-03-01

As the output power of a microgrid with renewable energy sources should be regulated based on the grid conditions, using robust controllers to share and balance the power in order to regulate the voltage and frequency of microgrid is critical. Therefore a proper control system is necessary for updating the reference signals and determining the proportion of each inverter in the microgrid control. This paper proposes a new adaptive method which is robust while the conditions are changing. This controller is based on a modified sliding mode controller which provides adapting conditions in linear and nonlinear loads. The performance of the proposed method is validated by representing the simulation results and experimental lab results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

A Nonlinear Physics-Based Optimal Control Method for Magnetostrictive Actuators

NASA Technical Reports Server (NTRS)

Smith, Ralph C.

1998-01-01

This paper addresses the development of a nonlinear optimal control methodology for magnetostrictive actuators. At moderate to high drive levels, the output from these actuators is highly nonlinear and contains significant magnetic and magnetomechanical hysteresis. These dynamics must be accommodated by models and control laws to utilize the full capabilities of the actuators. A characterization based upon ferromagnetic mean field theory provides a model which accurately quantifies both transient and steady state actuator dynamics under a variety of operating conditions. The control method consists of a linear perturbation feedback law used in combination with an optimal open loop nonlinear control. The nonlinear control incorporates the hysteresis and nonlinearities inherent to the transducer and can be computed offline. The feedback control is constructed through linearization of the perturbed system about the optimal system and is efficient for online implementation. As demonstrated through numerical examples, the combined hybrid control is robust and can be readily implemented in linear PDE-based structural models.

Linear dark field control: simulation for implementation and testing on the UA wavefront control testbed

NASA Astrophysics Data System (ADS)

Miller, Kelsey; Guyon, Olivier

2016-07-01

This paper presents the early-stage simulation results of linear dark field control (LDFC) as a new approach to maintaining a stable dark hole within a stellar post-coronagraphic PSF. In practice, conventional speckle nulling is used to create a dark hole in the PSF, and LDFC is then employed to maintain the dark field by using information from the bright speckle field. The concept exploits the linear response of the bright speckle intensity to wavefront variations in the pupil, and therefore has many advantages over conventional speckle nulling as a method for stabilizing the dark hole. In theory, LDFC is faster, more sensitive, and more robust than using conventional speckle nulling techniques, like electric field conjugation, to maintain the dark hole. In this paper, LDFC theory, linear bright speckle characterization, and first results in simulation are presented as an initial step toward the deployment of LDFC on the UA Wavefront Control testbed in the coming year.

Design and experimental evaluation of robust controllers for a two-wheeled robot

NASA Astrophysics Data System (ADS)

Kralev, J.; Slavov, Ts.; Petkov, P.

2016-11-01

The paper presents the design and experimental evaluation of two alternative μ-controllers for robust vertical stabilisation of a two-wheeled self-balancing robot. The controllers design is based on models derived by identification from closed-loop experimental data. In the first design, a signal-based uncertainty representation obtained directly from the identification procedure is used, which leads to a controller of order 29. In the second design the signal uncertainty is approximated by an input multiplicative uncertainty, which leads to a controller of order 50, subsequently reduced to 30. The performance of the two μ-controllers is compared with the performance of a conventional linear quadratic controller with 17th-order Kalman filter. A proportional-integral controller of the rotational motion around the vertical axis is implemented as well. The control code is generated using Simulink® controller models and is embedded in a digital signal processor. Results from the simulation of the closed-loop system as well as experimental results obtained during the real-time implementation of the designed controllers are given. The theoretical investigation and experimental results confirm that the closed-loop system achieves robust performance in respect to the uncertainties related to the identified robot model.

Dissipative rendering and neural network control system design

NASA Technical Reports Server (NTRS)

Gonzalez, Oscar R.

1995-01-01

Model-based control system designs are limited by the accuracy of the models of the plant, plant uncertainty, and exogenous signals. Although better models can be obtained with system identification, the models and control designs still have limitations. One approach to reduce the dependency on particular models is to design a set of compensators that will guarantee robust stability to a set of plants. Optimization over the compensator parameters can then be used to get the desired performance. Conservativeness of this approach can be reduced by integrating fundamental properties of the plant models. This is the approach of dissipative control design. Dissipative control designs are based on several variations of the Passivity Theorem, which have been proven for nonlinear/linear and continuous-time/discrete-time systems. These theorems depend not on a specific model of a plant, but on its general dissipative properties. Dissipative control design has found wide applicability in flexible space structures and robotic systems that can be configured to be dissipative. Currently, there is ongoing research to improve the performance of dissipative control designs. For aircraft systems that are not dissipative active control may be used to make them dissipative and then a dissipative control design technique can be used. It is also possible that rendering a system dissipative and dissipative control design may be combined into one step. Furthermore, the transformation of a non-dissipative system to dissipative can be done robustly. One sequential design procedure for finite dimensional linear time-invariant systems has been developed. For nonlinear plants that cannot be controlled adequately with a single linear controller, model-based techniques have additional problems. Nonlinear system identification is still a research topic. Lacking analytical models for model-based design, artificial neural network algorithms have recently received considerable attention. Using their universal approximation property, neural networks have been introduced into nonlinear control designs in several ways. Unfortunately, little work has appeared that analyzes neural network control systems and establishes margins for stability and performance. One approach for this analysis is to set up neural network control systems in the framework presented above. For example, one neural network could be used to render a system to be dissipative, a second strictly dissipative neural network controller could be used to guarantee robust stability.

A linear programming approach to characterizing norm bounded uncertainty from experimental data

NASA Technical Reports Server (NTRS)

Scheid, R. E.; Bayard, D. S.; Yam, Y.

1991-01-01

The linear programming spectral overbounding and factorization (LPSOF) algorithm, an algorithm for finding a minimum phase transfer function of specified order whose magnitude tightly overbounds a specified nonparametric function of frequency, is introduced. This method has direct application to transforming nonparametric uncertainty bounds (available from system identification experiments) into parametric representations required for modern robust control design software (i.e., a minimum-phase transfer function multiplied by a norm-bounded perturbation).

Decoupling control of a five-phase fault-tolerant permanent magnet motor by radial basis function neural network inverse

NASA Astrophysics Data System (ADS)

Chen, Qian; Liu, Guohai; Xu, Dezhi; Xu, Liang; Xu, Gaohong; Aamir, Nazir

2018-05-01

This paper proposes a new decoupled control for a five-phase in-wheel fault-tolerant permanent magnet (IW-FTPM) motor drive, in which radial basis function neural network inverse (RBF-NNI) and internal model control (IMC) are combined. The RBF-NNI system is introduced into original system to construct a pseudo-linear system, and IMC is used as a robust controller. Hence, the newly proposed control system incorporates the merits of the IMC and RBF-NNI methods. In order to verify the proposed strategy, an IW-FTPM motor drive is designed based on dSPACE real-time control platform. Then, the experimental results are offered to verify that the d-axis current and the rotor speed are successfully decoupled. Besides, the proposed motor drive exhibits strong robustness even under load torque disturbance.

Robust output feedback H∞ control for networked control systems based on the occurrence probabilities of time delays

NASA Astrophysics Data System (ADS)

Guo, Chenyu; Zhang, Weidong; Bao, Jie

2012-02-01

This article is concerned with the problem of robust H ∞ output feedback control for a kind of networked control systems with time-varying network-induced delays. Instead of using boundaries of time delays to represent all time delays, the occurrence probability of each time delay is considered in H∞ stability analysis and stabilisation. The problem addressed is the design of an output feedback controller such that, for all admissible uncertainties, the resulting closed-loop system is stochastically stable for the zero disturbance input and also simultaneously achieves a prescribed H∞ performance level. It is shown that less conservativeness is obtained. A set of linear matrix inequalities is given to solve the corresponding controller design problem. An example is provided to show the effectiveness and applicability of the proposed method.

Pilot Evaluation of Adaptive Control in Motion-Based Flight Simulator

NASA Technical Reports Server (NTRS)

Kaneshige, John T.; Campbell, Stefan Forrest

2009-01-01

The objective of this work is to assess the strengths, weaknesses, and robustness characteristics of several MRAC (Model-Reference Adaptive Control) based adaptive control technologies garnering interest from the community as a whole. To facilitate this, a control study using piloted and unpiloted simulations to evaluate sensitivities and handling qualities was conducted. The adaptive control technologies under consideration were ALR (Adaptive Loop Recovery), BLS (Bounded Linear Stability), Hybrid Adaptive Control, L1, OCM (Optimal Control Modification), PMRAC (Predictor-based MRAC), and traditional MRAC

A Novel Approach to Noise-Filtering Based on a Gain-Scheduling Neural Network Architecture

NASA Technical Reports Server (NTRS)

Troudet, T.; Merrill, W.

1994-01-01

A gain-scheduling neural network architecture is proposed to enhance the noise-filtering efficiency of feedforward neural networks, in terms of both nominal performance and robustness. The synergistic benefits of the proposed architecture are demonstrated and discussed in the context of the noise-filtering of signals that are typically encountered in aerospace control systems. The synthesis of such a gain-scheduled neurofiltering provides the robustness of linear filtering, while preserving the nominal performance advantage of conventional nonlinear neurofiltering. Quantitative performance and robustness evaluations are provided for the signal processing of pitch rate responses to typical pilot command inputs for a modern fighter aircraft model.

Structure Computation of Quiet Spike[Trademark] Flight-Test Data During Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2008-01-01

System identification or mathematical modeling is used in the aerospace community for development of simulation models for robust control law design. These models are often described as linear time-invariant processes. Nevertheless, it is well known that the underlying process is often nonlinear. The reason for using a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades, the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B Quiet Spike(TradeMark) aeroservoelastic flight-test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description that may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance for the development of robust parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion, which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B Quiet Spike aeroservoelastic flight-test data for several flight conditions that 1) linear models are inefficient for modeling aeroservoelastic data, 2) nonlinear identification provides a parsimonious model description while providing a high percent fit for cross-validated data, and 3) the model structure and parameters vary as the flight condition is altered.

Control optimization, stabilization and computer algorithms for aircraft applications

NASA Technical Reports Server (NTRS)

1975-01-01

Research related to reliable aircraft design is summarized. Topics discussed include systems reliability optimization, failure detection algorithms, analysis of nonlinear filters, design of compensators incorporating time delays, digital compensator design, estimation for systems with echoes, low-order compensator design, descent-phase controller for 4-D navigation, infinite dimensional mathematical programming problems and optimal control problems with constraints, robust compensator design, numerical methods for the Lyapunov equations, and perturbation methods in linear filtering and control.

Feedback control of combustion instabilities from within limit cycle oscillations using H∞ loop-shaping and the ν-gap metric

PubMed Central

Morgans, Aimee S.

2016-01-01

Combustion instabilities arise owing to a two-way coupling between acoustic waves and unsteady heat release. Oscillation amplitudes successively grow, until nonlinear effects cause saturation into limit cycle oscillations. Feedback control, in which an actuator modifies some combustor input in response to a sensor measurement, can suppress combustion instabilities. Linear feedback controllers are typically designed, using linear combustor models. However, when activated from within limit cycle, the linear model is invalid, and such controllers are not guaranteed to stabilize. This work develops a feedback control strategy guaranteed to stabilize from within limit cycle oscillations. A low-order model of a simple combustor, exhibiting the essential features of more complex systems, is presented. Linear plane acoustic wave modelling is combined with a weakly nonlinear describing function for the flame. The latter is determined numerically using a level set approach. Its implication is that the open-loop transfer function (OLTF) needed for controller design varies with oscillation level. The difference between the mean and the rest of the OLTFs is characterized using the ν-gap metric, providing the minimum required ‘robustness margin’ for an H∞ loop-shaping controller. Such controllers are designed and achieve stability both for linear fluctuations and from within limit cycle oscillations. PMID:27493558

Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

NASA Technical Reports Server (NTRS)

Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

1992-01-01

A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

A new class of energy based control laws for revolute robot arms - Tracking control, robustness enhancement and adaptive control

NASA Technical Reports Server (NTRS)

Wen, John T.; Kreutz, Kenneth; Bayard, David S.

1988-01-01

A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.

Polarization control of isolated high-harmonic pulses

NASA Astrophysics Data System (ADS)

Huang, Pei-Chi; Hernández-García, Carlos; Huang, Jen-Ting; Huang, Po-Yao; Lu, Chih-Hsuan; Rego, Laura; Hickstein, Daniel D.; Ellis, Jennifer L.; Jaron-Becker, Agnieszka; Becker, Andreas; Yang, Shang-Da; Durfee, Charles G.; Plaja, Luis; Kapteyn, Henry C.; Murnane, Margaret M.; Kung, A. H.; Chen, Ming-Chang

2018-06-01

High-harmonic generation driven by femtosecond lasers makes it possible to capture the fastest dynamics in molecules and materials. However, thus far, the shortest isolated attosecond pulses have only been produced with linear polarization, which limits the range of physics that can be explored. Here, we demonstrate robust polarization control of isolated extreme-ultraviolet pulses by exploiting non-collinear high-harmonic generation driven by two counter-rotating few-cycle laser beams. The circularly polarized supercontinuum is produced at a central photon energy of 33 eV with a transform limit of 190 as and a predicted linear chirp of 330 as. By adjusting the ellipticity of the two counter-rotating driving pulses simultaneously, we control the polarization state of isolated extreme-ultraviolet pulses—from circular through elliptical to linear polarization—without sacrificing conversion efficiency. Access to the purely circularly polarized supercontinuum, combined with full helicity and ellipticity control, paves the way towards attosecond metrology of circular dichroism.

Geometry Modeling and Adaptive Control of Air-Breathing Hypersonic Vehicles

NASA Astrophysics Data System (ADS)

Vick, Tyler Joseph

Air-breathing hypersonic vehicles have the potential to provide global reach and affordable access to space. Recent technological advancements have made scramjet-powered flight achievable, as evidenced by the successes of the X-43A and X-51A flight test programs over the last decade. Air-breathing hypersonic vehicles present unique modeling and control challenges in large part due to the fact that scramjet propulsion systems are highly integrated into the airframe, resulting in strongly coupled and often unstable dynamics. Additionally, the extreme flight conditions and inability to test fully integrated vehicle systems larger than X-51 before flight leads to inherent uncertainty in hypersonic flight. This thesis presents a means to design vehicle geometries, simulate vehicle dynamics, and develop and analyze control systems for hypersonic vehicles. First, a software tool for generating three-dimensional watertight vehicle surface meshes from simple design parameters is developed. These surface meshes are compatible with existing vehicle analysis tools, with which databases of aerodynamic and propulsive forces and moments can be constructed. A six-degree-of-freedom nonlinear dynamics simulation model which incorporates this data is presented. Inner-loop longitudinal and lateral control systems are designed and analyzed utilizing the simulation model. The first is an output feedback proportional-integral linear controller designed using linear quadratic regulator techniques. The second is a model reference adaptive controller (MRAC) which augments this baseline linear controller with an adaptive element. The performance and robustness of each controller are analyzed through simulated time responses to angle-of-attack and bank angle commands, while various uncertainties are introduced. The MRAC architecture enables the controller to adapt in a nonlinear fashion to deviations from the desired response, allowing for improved tracking performance, stability, and robustness.

Nonlinear control of linear parameter varying systems with applications to hypersonic vehicles

NASA Astrophysics Data System (ADS)

Wilcox, Zachary Donald

The focus of this dissertation is to design a controller for linear parameter varying (LPV) systems, apply it specifically to air-breathing hypersonic vehicles, and examine the interplay between control performance and the structural dynamics design. Specifically a Lyapunov-based continuous robust controller is developed that yields exponential tracking of a reference model, despite the presence of bounded, nonvanishing disturbances. The hypersonic vehicle has time varying parameters, specifically temperature profiles, and its dynamics can be reduced to an LPV system with additive disturbances. Since the HSV can be modeled as an LPV system the proposed control design is directly applicable. The control performance is directly examined through simulations. A wide variety of applications exist that can be effectively modeled as LPV systems. In particular, flight systems have historically been modeled as LPV systems and associated control tools have been applied such as gain-scheduling, linear matrix inequalities (LMIs), linear fractional transformations (LFT), and mu-types. However, as the type of flight environments and trajectories become more demanding, the traditional LPV controllers may no longer be sufficient. In particular, hypersonic flight vehicles (HSVs) present an inherently difficult problem because of the nonlinear aerothermoelastic coupling effects in the dynamics. HSV flight conditions produce temperature variations that can alter both the structural dynamics and flight dynamics. Starting with the full nonlinear dynamics, the aerothermoelastic effects are modeled by a temperature dependent, parameter varying state-space representation with added disturbances. The model includes an uncertain parameter varying state matrix, an uncertain parameter varying non-square (column deficient) input matrix, and an additive bounded disturbance. In this dissertation, a robust dynamic controller is formulated for a uncertain and disturbed LPV system. The developed controller is then applied to a HSV model, and a Lyapunov analysis is used to prove global exponential reference model tracking in the presence of uncertainty in the state and input matrices and exogenous disturbances. Simulations with a spectrum of gains and temperature profiles on the full nonlinear dynamic model of the HSV is used to illustrate the performance and robustness of the developed controller. In addition, this work considers how the performance of the developed controller varies over a wide variety of control gains and temperature profiles and are optimized with respect to different performance metrics. Specifically, various temperature profile models and related nonlinear temperature dependent disturbances are used to characterize the relative control performance and effort for each model. Examining such metrics as a function of temperature provides a potential inroad to examine the interplay between structural/thermal protection design and control development and has application for future HSV design and control implementation.

Robust and real-time control of magnetic bearings for space engines

NASA Technical Reports Server (NTRS)

Sinha, Alok; Wang, Kon-Well; Mease, K.; Lewis, S.

1991-01-01

Currently, NASA Lewis Research Center is developing magnetic bearings for Space Shuttle Main Engine (SSME) turbopumps. The control algorithms which have been used are based on either the proportional-intergral-derivative control (PID) approach or the linear quadratic (LQ) state space approach. These approaches lead to an acceptable performance only when the system model is accurately known, which is seldom true in practice. For example, the rotor eccentricity, which is a major source of vibration at high speeds, cannot be predicted accurately. Furthermore, the dynamics of a rotor shaft, which must be treated as a flexible system to model the elastic rotor shaft, is infinite dimensional in theory and the controller can only be developed on the basis of a finite number of modes. Therefore, the development of the control system is further complicated by the possibility of closed loop system instability because of residual or uncontrolled modes, the so called spillover problem. Consequently, novel control algorithms for magnetic bearings are being developed to be robust to inevitable parametric uncertainties, external disturbances, spillover phenomenon and noise. Also, as pointed out earlier, magnetic bearings must exhibit good performance at a speed over 30,000 rpm. This implies that the sampling period available for the design of a digital control system has to be of the order of 0.5 milli-seconds. Therefore, feedback coefficients and other required controller parameters have to be computed off-line so that the on-line computational burden is extremely small. The development of the robust and real-time control algorithms is based on the sliding mode control theory. In this method, a dynamic system is made to move along a manifold of sliding hyperplanes to the origin of the state space. The number of sliding hyperplanes equals that of actuators. The sliding mode controller has two parts; linear state feedback and nonlinear terms. The nonlinear terms guarantee that the systems would reach the intersection of all sliding hyperplanes and remain on it when bounds on the errors in the system parameters and external disturbances are known. The linear part of the control drives the system to the origin of state space. Another important feature is that the controller parameter can be computed off-line. Consequently, on-line computational burden is small.

Application of the LQG/LTR technique to robust controller synthesis for a large flexible space antenna

NASA Technical Reports Server (NTRS)

Joshi, S. M.; Armstrong, E. S.; Sundararajan, N.

1986-01-01

The problem of synthesizing a robust controller is considered for a large, flexible space-based antenna by using the linear-quadratic-Gaussian (LQG)/loop transfer recovery (LTR) method. The study is based on a finite-element model of the 122-m hoop/column antenna, which consists of three rigid-body rotational modes and the first 10 elastic modes. A robust compensator design for achieving the required performance bandwidth in the presence of modeling uncertainties is obtained using the LQG/LTR method for loop-shaping in the frequency domain. Different sensor actuator locations are analyzed in terms of the pole/zero locations of the multivariable systems and possible best locations are indicated. The computations are performed by using the LQG design package ORACLS augmented with frequency domain singular value analysis software.

Robust Flight Path Determination for Mars Precision Landing Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Bayard, David S.; Kohen, Hamid

1997-01-01

This paper documents the application of genetic algorithms (GAs) to the problem of robust flight path determination for Mars precision landing. The robust flight path problem is defined here as the determination of the flight path which delivers a low-lift open-loop controlled vehicle to its desired final landing location while minimizing the effect of perturbations due to uncertainty in the atmospheric model and entry conditions. The genetic algorithm was capable of finding solutions which reduced the landing error from 111 km RMS radial (open-loop optimal) to 43 km RMS radial (optimized with respect to perturbations) using 200 hours of computation on an Ultra-SPARC workstation. Further reduction in the landing error is possible by going to closed-loop control which can utilize the GA optimized paths as nominal trajectories for linearization.

Robust model predictive control of nonlinear systems with unmodeled dynamics and bounded uncertainties based on neural networks.

PubMed

Yan, Zheng; Wang, Jun

2014-03-01

This paper presents a neural network approach to robust model predictive control (MPC) for constrained discrete-time nonlinear systems with unmodeled dynamics affected by bounded uncertainties. The exact nonlinear model of underlying process is not precisely known, but a partially known nominal model is available. This partially known nonlinear model is first decomposed to an affine term plus an unknown high-order term via Jacobian linearization. The linearization residue combined with unmodeled dynamics is then modeled using an extreme learning machine via supervised learning. The minimax methodology is exploited to deal with bounded uncertainties. The minimax optimization problem is reformulated as a convex minimization problem and is iteratively solved by a two-layer recurrent neural network. The proposed neurodynamic approach to nonlinear MPC improves the computational efficiency and sheds a light for real-time implementability of MPC technology. Simulation results are provided to substantiate the effectiveness and characteristics of the proposed approach.

Robust Stabilization of T-S Fuzzy Stochastic Descriptor Systems via Integral Sliding Modes.

PubMed

Li, Jinghao; Zhang, Qingling; Yan, Xing-Gang; Spurgeon, Sarah K

2017-09-19

This paper addresses the robust stabilization problem for T-S fuzzy stochastic descriptor systems using an integral sliding mode control paradigm. A classical integral sliding mode control scheme and a nonparallel distributed compensation (Non-PDC) integral sliding mode control scheme are presented. It is shown that two restrictive assumptions previously adopted developing sliding mode controllers for Takagi-Sugeno (T-S) fuzzy stochastic systems are not required with the proposed framework. A unified framework for sliding mode control of T-S fuzzy systems is formulated. The proposed Non-PDC integral sliding mode control scheme encompasses existing schemes when the previously imposed assumptions hold. Stability of the sliding motion is analyzed and the sliding mode controller is parameterized in terms of the solutions of a set of linear matrix inequalities which facilitates design. The methodology is applied to an inverted pendulum model to validate the effectiveness of the results presented.

Advanced rotorcraft control using parameter optimization

NASA Technical Reports Server (NTRS)

Vansteenwyk, Brett; Ly, Uy-Loi

1991-01-01

A reliable algorithm for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters is presented. The algorithm is part of a design algorithm for an optimal linear dynamic output feedback controller that minimizes a finite time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed loop eigensystem. This approach through the use of a accurate Pade series approximation does not require the closed loop system matrix to be diagonalizable. The algorithm has been included in a control design package for optimal robust low order controllers. Usefulness of the proposed numerical algorithm has been demonstrated using numerous practical design cases where degeneracies occur frequently in the closed loop system under an arbitrary controller design initialization and during the numerical search.

A comparative robustness evaluation of feedforward neurofilters

NASA Technical Reports Server (NTRS)

Troudet, Terry; Merrill, Walter

1993-01-01

A comparative performance and robustness analysis is provided for feedforward neurofilters trained with back propagation to filter additive white noise. The signals used in this analysis are simulated pitch rate responses to typical pilot command inputs for a modern fighter aircraft model. Various configurations of nonlinear and linear neurofilters are trained to estimate exact signal values from input sequences of noisy sampled signal values. In this application, nonlinear neurofiltering is found to be more efficient than linear neurofiltering in removing the noise from responses of the nominal vehicle model, whereas linear neurofiltering is found to be more robust in the presence of changes in the vehicle dynamics. The possibility of enhancing neurofiltering through hybrid architectures based on linear and nonlinear neuroprocessing is therefore suggested as a way of taking advantage of the robustness of linear neurofiltering, while maintaining the nominal performance advantage of nonlinear neurofiltering.

Robust set-point regulation for ecological models with multiple management goals.

PubMed

Guiver, Chris; Mueller, Markus; Hodgson, Dave; Townley, Stuart

2016-05-01

Population managers will often have to deal with problems of meeting multiple goals, for example, keeping at specific levels both the total population and population abundances in given stage-classes of a stratified population. In control engineering, such set-point regulation problems are commonly tackled using multi-input, multi-output proportional and integral (PI) feedback controllers. Building on our recent results for population management with single goals, we develop a PI control approach in a context of multi-objective population management. We show that robust set-point regulation is achieved by using a modified PI controller with saturation and anti-windup elements, both described in the paper, and illustrate the theory with examples. Our results apply more generally to linear control systems with positive state variables, including a class of infinite-dimensional systems, and thus have broader appeal.

Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems.

PubMed

Chang, Yeong-Chan

2009-02-01

This paper addresses the problem of designing robust tracking controls for a large class of strict-feedback nonlinear systems involving plant uncertainties and external disturbances. The input and virtual input weighting matrices are perturbed by bounded time-varying uncertainties. An adaptive fuzzy-based (or neural-network-based) dynamic feedback tracking controller will be developed such that all the states and signals of the closed-loop system are bounded and the trajectory tracking error should be as small as possible. First, the adaptive approximators with linearly parameterized models are designed, and a partitioned procedure with respect to the developed adaptive approximators is proposed such that the implementation of the fuzzy (or neural network) basis functions depends only on the state variables but does not depend on the tuning approximation parameters. Furthermore, we extend to design the nonlinearly parameterized adaptive approximators. Consequently, the intelligent robust tracking control schemes developed in this paper possess the properties of computational simplicity and easy implementation. Finally, simulation examples are presented to demonstrate the effectiveness of the proposed control algorithms.

Comparisons of Robustness and Sensitivity between Cancer and Normal Cells by Microarray Data

PubMed Central

Chu, Liang-Hui; Chen, Bor-Sen

2008-01-01

Robustness is defined as the ability to uphold performance in face of perturbations and uncertainties, and sensitivity is a measure of the system deviations generated by perturbations to the system. While cancer appears as a robust but fragile system, few computational and quantitative evidences demonstrate robustness tradeoffs in cancer. Microarrays have been widely applied to decipher gene expression signatures in human cancer research, and quantification of global gene expression profiles facilitates precise prediction and modeling of cancer in systems biology. We provide several efficient computational methods based on system and control theory to compare robustness and sensitivity between cancer and normal cells by microarray data. Measurement of robustness and sensitivity by linear stochastic model is introduced in this study, which shows oscillations in feedback loops of p53 and demonstrates robustness tradeoffs that cancer is a robust system with some extreme fragilities. In addition, we measure sensitivity of gene expression to perturbations in other gene expression and kinetic parameters, discuss nonlinear effects in feedback loops of p53 and extend our method to robustness-based cancer drug design. PMID:19259409

Linear Covariance Analysis for a Lunar Lander

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; Bhatt, Sagar; Fritz, Matthew; Woffinden, David; May, Darryl; Braden, Ellen; Hannan, Michael

2017-01-01

A next-generation lunar lander Guidance, Navigation, and Control (GNC) system, which includes a state-of-the-art optical sensor suite, is proposed in a concept design cycle. The design goal is to allow the lander to softly land within the prescribed landing precision. The achievement of this precision landing requirement depends on proper selection of the sensor suite. In this paper, a robust sensor selection procedure is demonstrated using a Linear Covariance (LinCov) analysis tool developed by Draper.

Design of Linear Control System for Wind Turbine Blade Fatigue Testing

NASA Astrophysics Data System (ADS)

Toft, Anders; Roe-Poulsen, Bjarke; Christiansen, Rasmus; Knudsen, Torben

2016-09-01

This paper proposes a linear method for wind turbine blade fatigue testing at Siemens Wind Power. The setup consists of a blade, an actuator (motor and load mass) that acts on the blade with a sinusoidal moment, and a distribution of strain gauges to measure the blade flexure. Based on the frequency of the sinusoidal input, the blade will start oscillating with a given gain, hence the objective of the fatigue test is to make the blade oscillate with a controlled amplitude. The system currently in use is based on frequency control, which involves some non-linearities that make the system difficult to control. To make a linear controller, a different approach has been chosen, namely making a controller which is not regulating on the input frequency, but on the input amplitude. A non-linear mechanical model for the blade and the motor has been constructed. This model has been simplified based on the desired output, namely the amplitude of the blade. Furthermore, the model has been linearised to make it suitable for linear analysis and control design methods. The controller is designed based on a simplified and linearised model, and its gain parameter determined using pole placement. The model variants have been simulated in the MATLAB toolbox Simulink, which shows that the controller design based on the simple model performs adequately with the non-linear model. Moreover, the developed controller solves the robustness issue found in the existent solution and also reduces the needed energy for actuation as it always operates at the blade eigenfrequency.

Adaptive robust fault-tolerant control for linear MIMO systems with unmatched uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Kangkang; Jiang, Bin; Yan, Xing-Gang; Mao, Zehui

2017-10-01

In this paper, two novel fault-tolerant control design approaches are proposed for linear MIMO systems with actuator additive faults, multiplicative faults and unmatched uncertainties. For time-varying multiplicative and additive faults, new adaptive laws and additive compensation functions are proposed. A set of conditions is developed such that the unmatched uncertainties are compensated by actuators in control. On the other hand, for unmatched uncertainties with their projection in unmatched space being not zero, based on a (vector) relative degree condition, additive functions are designed to compensate for the uncertainties from output channels in the presence of actuator faults. The developed fault-tolerant control schemes are applied to two aircraft systems to demonstrate the efficiency of the proposed approaches.

Adaptive integral dynamic surface control of a hypersonic flight vehicle

NASA Astrophysics Data System (ADS)

Aslam Butt, Waseem; Yan, Lin; Amezquita S., Kendrick

2015-07-01

In this article, non-linear adaptive dynamic surface air speed and flight path angle control designs are presented for the longitudinal dynamics of a flexible hypersonic flight vehicle. The tracking performance of the control design is enhanced by introducing a novel integral term that caters to avoiding a large initial control signal. To ensure feasibility, the design scheme incorporates magnitude and rate constraints on the actuator commands. The uncertain non-linear functions are approximated by an efficient use of the neural networks to reduce the computational load. A detailed stability analysis shows that all closed-loop signals are uniformly ultimately bounded and the ? tracking performance is guaranteed. The robustness of the design scheme is verified through numerical simulations of the flexible flight vehicle model.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites.

PubMed

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-03-08

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites

PubMed Central

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-01-01

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites. PMID:29518062

Robust H∞ control of active vehicle suspension under non-stationary running

NASA Astrophysics Data System (ADS)

Guo, Li-Xin; Zhang, Li-Ping

2012-12-01

Due to complexity of the controlled objects, the selection of control strategies and algorithms in vehicle control system designs is an important task. Moreover, the control problem of automobile active suspensions has been become one of the important relevant investigations due to the constrained peculiarity and parameter uncertainty of mathematical models. In this study, after establishing the non-stationary road surface excitation model, a study on the active suspension control for non-stationary running condition was conducted using robust H∞ control and linear matrix inequality optimization. The dynamic equation of a two-degree-of-freedom quarter car model with parameter uncertainty was derived. The H∞ state feedback control strategy with time-domain hard constraints was proposed, and then was used to design the active suspension control system of the quarter car model. Time-domain analysis and parameter robustness analysis were carried out to evaluate the proposed controller stability. Simulation results show that the proposed control strategy has high systemic stability on the condition of non-stationary running and parameter uncertainty (including suspension mass, suspension stiffness and tire stiffness). The proposed control strategy can achieve a promising improvement on ride comfort and satisfy the requirements of dynamic suspension deflection, dynamic tire loads and required control forces within given constraints, as well as non-stationary running condition.

Wing Shaping and Gust Load Controls of Flexible Aircraft: An LPV Approach

NASA Technical Reports Server (NTRS)

Hammerton, Jared R.; Su, Weihua; Zhu, Guoming; Swei, Sean Shan-Min

2018-01-01

In the proposed paper, the optimum wing shape of a highly flexible aircraft under varying flight conditions will be controlled by a linear parameter-varying approach. The optimum shape determined under multiple objectives, including flight performance, ride quality, and control effort, will be determined as well. This work is an extension of work done previously by the authors, and updates the existing optimization and utilizes the results to generate a robust flight controller.

Lateral control system design for VTOL landing on a DD963 in high sea states. M.S. Thesis

NASA Technical Reports Server (NTRS)

Bodson, M.

1982-01-01

The problem of designing lateral control systems for the safe landing of VTOL aircraft on small ships is addressed. A ship model is derived. The issues of estimation and prediction of ship motions are discussed, using optimal linear linear estimation techniques. The roll motion is the most important of the lateral motions, and it is found that it can be predicted for up to 10 seconds in perfect conditions. The automatic landing of the VTOL aircraft is considered, and a lateral controller, defined as a ship motion tracker, is designed, using optimal control techniqes. The tradeoffs between the tracking errors and the control authority are obtained. The important couplings between the lateral motions and controls are demonstrated, and it is shown that the adverse couplings between the sway and the roll motion at the landing pad are significant constraints in the tracking of the lateral ship motions. The robustness of the control system, including the optimal estimator, is studied, using the singular values analysis. Through a robustification procedure, a robust control system is obtained, and the usefulness of the singular values to define stability margins that take into account general types of unstructured modelling errors is demonstrated. The minimal destabilizing perturbations indicated by the singular values analysis are interpreted and related to the multivariable Nyquist diagrams.

Fixed order dynamic compensation for multivariable linear systems

NASA Technical Reports Server (NTRS)

Kramer, F. S.; Calise, A. J.

1986-01-01

This paper considers the design of fixed order dynamic compensators for multivariable time invariant linear systems, minimizing a linear quadratic performance cost functional. Attention is given to robustness issues in terms of multivariable frequency domain specifications. An output feedback formulation is adopted by suitably augmenting the system description to include the compensator states. Either a controller or observer canonical form is imposed on the compensator description to reduce the number of free parameters to its minimal number. The internal structure of the compensator is prespecified by assigning a set of ascending feedback invariant indices, thus forming a Brunovsky structure for the nominal compensator.

Multivariable robust adaptive sliding mode control of an industrial boiler-turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller.

PubMed

Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza

2015-09-01

To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Reliable numerical computation in an optimal output-feedback design

NASA Technical Reports Server (NTRS)

Vansteenwyk, Brett; Ly, Uy-Loi

1991-01-01

A reliable algorithm is presented for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters. The algorithm is a part of a design algorithm for optimal linear dynamic output-feedback controller that minimizes a finite-time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control-law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed-loop eigensystem. This approach through the use of an accurate Pade series approximation does not require the closed-loop system matrix to be diagonalizable. The algorithm was included in a control design package for optimal robust low-order controllers. Usefulness of the proposed numerical algorithm was demonstrated using numerous practical design cases where degeneracies occur frequently in the closed-loop system under an arbitrary controller design initialization and during the numerical search.

Robust fuzzy output feedback controller for affine nonlinear systems via T-S fuzzy bilinear model: CSTR benchmark.

PubMed

Hamdy, M; Hamdan, I

2015-07-01

In this paper, a robust H∞ fuzzy output feedback controller is designed for a class of affine nonlinear systems with disturbance via Takagi-Sugeno (T-S) fuzzy bilinear model. The parallel distributed compensation (PDC) technique is utilized to design a fuzzy controller. The stability conditions of the overall closed loop T-S fuzzy bilinear model are formulated in terms of Lyapunov function via linear matrix inequality (LMI). The control law is robustified by H∞ sense to attenuate external disturbance. Moreover, the desired controller gains can be obtained by solving a set of LMI. A continuous stirred tank reactor (CSTR), which is a benchmark problem in nonlinear process control, is discussed in detail to verify the effectiveness of the proposed approach with a comparative study. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Switching State-Feedback LPV Control with Uncertain Scheduling Parameters

NASA Technical Reports Server (NTRS)

He, Tianyi; Al-Jiboory, Ali Khudhair; Swei, Sean Shan-Min; Zhu, Guoming G.

2017-01-01

This paper presents a new method to design Robust Switching State-Feedback Gain-Scheduling (RSSFGS) controllers for Linear Parameter Varying (LPV) systems with uncertain scheduling parameters. The domain of scheduling parameters are divided into several overlapped subregions to undergo hysteresis switching among a family of simultaneously designed LPV controllers over the corresponding subregion with the guaranteed H-infinity performance. The synthesis conditions are given in terms of Parameterized Linear Matrix Inequalities that guarantee both stability and performance at each subregion and associated switching surfaces. The switching stability is ensured by descent parameter-dependent Lyapunov function on switching surfaces. By solving the optimization problem, RSSFGS controller can be obtained for each subregion. A numerical example is given to illustrate the effectiveness of the proposed approach over the non-switching controllers.

A linear quadratic regulator approach to the stabilization of uncertain linear systems

NASA Technical Reports Server (NTRS)

Shieh, L. S.; Sunkel, J. W.; Wang, Y. J.

1990-01-01

This paper presents a linear quadratic regulator approach to the stabilization of uncertain linear systems. The uncertain systems under consideration are described by state equations with the presence of time-varying unknown-but-bounded uncertainty matrices. The method is based on linear quadratic regulator (LQR) theory and Liapunov stability theory. The robust stabilizing control law for a given uncertain system can be easily constructed from the symmetric positive-definite solution of the associated augmented Riccati equation. The proposed approach can be applied to matched and/or mismatched systems with uncertainty matrices in which only their matrix norms are bounded by some prescribed values and/or their entries are bounded by some prescribed constraint sets. Several numerical examples are presented to illustrate the results.

An H(∞) control approach to robust learning of feedforward neural networks.

PubMed

Jing, Xingjian

2011-09-01

A novel H(∞) robust control approach is proposed in this study to deal with the learning problems of feedforward neural networks (FNNs). The analysis and design of a desired weight update law for the FNN is transformed into a robust controller design problem for a discrete dynamic system in terms of the estimation error. The drawbacks of some existing learning algorithms can therefore be revealed, especially for the case that the output data is fast changing with respect to the input or the output data is corrupted by noise. Based on this approach, the optimal learning parameters can be found by utilizing the linear matrix inequality (LMI) optimization techniques to achieve a predefined H(∞) "noise" attenuation level. Several existing BP-type algorithms are shown to be special cases of the new H(∞)-learning algorithm. Theoretical analysis and several examples are provided to show the advantages of the new method. Copyright © 2011 Elsevier Ltd. All rights reserved.

Orbit control of a stratospheric satellite with parameter uncertainties

NASA Astrophysics Data System (ADS)

Xu, Ming; Huo, Wei

2016-12-01

When a stratospheric satellite travels by prevailing winds in the stratosphere, its cross-track displacement needs to be controlled to keep a constant latitude orbital flight. To design the orbit control system, a 6 degree-of-freedom (DOF) model of the satellite is established based on the second Lagrangian formulation, it is proven that the input/output feedback linearization theory cannot be directly implemented for the orbit control with this model, thus three subsystem models are deduced from the 6-DOF model to develop a sequential nonlinear control strategy. The control strategy includes an adaptive controller for the balloon-tether subsystem with uncertain balloon parameters, a PD controller based on feedback linearization for the tether-sail subsystem, and a sliding mode controller for the sail-rudder subsystem with uncertain sail parameters. Simulation studies demonstrate that the proposed control strategy is robust to uncertainties and satisfies high precision requirements for the orbit flight of the satellite.

Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks.

PubMed

Flassig, R J; Sundmacher, K

2012-12-01

Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. flassig@mpi-magdeburg.mpg.de Supplementary data are are available at Bioinformatics online.

Improved Continuous-Time Higher Harmonic Control Using Hinfinity Methods

NASA Astrophysics Data System (ADS)

Fan, Frank H.

The helicopter is a versatile aircraft that can take-off and land vertically, hover efficiently, and maneuver in confined space. This versatility is enabled by the main rotor, which also causes undesired harmonic vibration during operation. This unwanted vibration has a negative impact on the practicality of the helicopter and also increases its operational cost. Passive control techniques have been applied to helicopter vibration suppression, but these methods are generally heavy and are not robust to changes in operating conditions. Feedback control offers the advantages of robustness and potentially higher performance over passive control techniques, and amongst the various feedback schemes, Shaw's higher harmonic control algorithm has been shown to be an effective method for attenuating harmonic disturbance in helicopters. In this thesis, the higher harmonic disturbance algorithm is further developed to achieve improved performance. One goal in this thesis is to determine the importance of periodicity in the helicopter rotor dynamics for control synthesis. Based on the analysis of wind tunnel data and simulation results, we conclude the helicopter rotor can be modeled reasonably well as linear and time-invariant for control design purposes. Modeling the helicopter rotor as linear time-invariant allows us to apply linear control theory concepts to the higher harmonic control problem. Another goal in this thesis is to find the limits of performance in harmonic disturbance rejection. To achieve this goal, we first define the metrics to measure the performance of the controller in terms of response speed and robustness to changes in the plant dynamics. The performance metrics are incorporated into an Hinfinity control problem. For a given plant, the resulting Hinfinity controller achieves the maximum performance, thus allowing us to identify the performance limitation in harmonic disturbance rejection. However, the Hinfinity controllers are of high order, and may have unstable poles, leading us to develop a design method to generate stable, fixed-order, and high performance controllers. Both the Hinfinity and the fixed-order controllers are designed for constant flight conditions. A gain-scheduled control law is used to reduce the vibration throughout the flight envelope. The gain-scheduling is accomplished by blending the outputs from fixed-order controllers designed for different flight conditions. The structure of the fixed-order controller allows the usage of a previously developed anti-windup scheme, and the blending function results in a bumpless full flight envelope control law. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)

Structural robustness with suboptimal responses for linear state space model

NASA Technical Reports Server (NTRS)

Keel, L. H.; Lim, Kyong B.; Juang, Jer-Nan

1989-01-01

A relationship between the closed-loop eigenvalues and the amount of perturbations in the open-loop matrix is addressed in the context of performance robustness. If the allowable perturbation ranges of elements of the open-loop matrix A and the desired tolerance of the closed-loop eigenvalues are given such that max(j) of the absolute value of Delta-lambda(j) (A+BF) should be less than some prescribed value, what is a state feedback controller F which satisfies the closed-loop eigenvalue perturbation-tolerance requirement for a class of given perturbation in A? The paper gives an algorithm to design such a controller. Numerical examples are included for illustration.

Least median of squares and iteratively re-weighted least squares as robust linear regression methods for fluorimetric determination of α-lipoic acid in capsules in ideal and non-ideal cases of linearity.

PubMed

Korany, Mohamed A; Gazy, Azza A; Khamis, Essam F; Ragab, Marwa A A; Kamal, Miranda F

2018-06-01

This study outlines two robust regression approaches, namely least median of squares (LMS) and iteratively re-weighted least squares (IRLS) to investigate their application in instrument analysis of nutraceuticals (that is, fluorescence quenching of merbromin reagent upon lipoic acid addition). These robust regression methods were used to calculate calibration data from the fluorescence quenching reaction (∆F and F-ratio) under ideal or non-ideal linearity conditions. For each condition, data were treated using three regression fittings: Ordinary Least Squares (OLS), LMS and IRLS. Assessment of linearity, limits of detection (LOD) and quantitation (LOQ), accuracy and precision were carefully studied for each condition. LMS and IRLS regression line fittings showed significant improvement in correlation coefficients and all regression parameters for both methods and both conditions. In the ideal linearity condition, the intercept and slope changed insignificantly, but a dramatic change was observed for the non-ideal condition and linearity intercept. Under both linearity conditions, LOD and LOQ values after the robust regression line fitting of data were lower than those obtained before data treatment. The results obtained after statistical treatment indicated that the linearity ranges for drug determination could be expanded to lower limits of quantitation by enhancing the regression equation parameters after data treatment. Analysis results for lipoic acid in capsules, using both fluorimetric methods, treated by parametric OLS and after treatment by robust LMS and IRLS were compared for both linearity conditions. Copyright © 2018 John Wiley & Sons, Ltd.

A feedback linearization approach to spacecraft control using momentum exchange devices. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Dzielski, John Edward

1988-01-01

Recent developments in the area of nonlinear control theory have shown how coordiante changes in the state and input spaces can be used with nonlinear feedback to transform certain nonlinear ordinary differential equations into equivalent linear equations. These feedback linearization techniques are applied to resolve two problems arising in the control of spacecraft equipped with control moment gyroscopes (CMGs). The first application involves the computation of rate commands for the gimbals that rotate the individual gyroscopes to produce commanded torques on the spacecraft. The second application is to the long-term management of stored momentum in the system of control moment gyroscopes using environmental torques acting on the vehicle. An approach to distributing control effort among a group of redundant actuators is described that uses feedback linearization techniques to parameterize sets of controls which influence a specified subsystem in a desired way. The approach is adapted for use in spacecraft control with double-gimballed gyroscopes to produce an algorithm that avoids problematic gimbal configurations by approximating sets of gimbal rates that drive CMG rotors into desirable configurations. The momentum management problem is stated as a trajectory optimization problem with a nonlinear dynamical constraint. Feedback linearization and collocation are used to transform this problem into an unconstrainted nonlinear program. The approach to trajectory optimization is fast and robust. A number of examples are presented showing applications to the proposed NASA space station.

Identification and Control of Non-Linear Time-Varying Dynamical Systems Using Artificial Neural Networks

DTIC Science & Technology

1992-09-01

finding an inverse plant such as was done by Bertrand [BD91] and by Levin, Gewirtzman and Inbar in a binary type inverse controller [LGI91], to self tuning...gain robust control. 2) Self oscillating adaptive controller. 3) Gain scheduling. 4) Self tuning. 5) Model-reference adaptive systems. Although the...of multidimensional systems (CS881 as well as aircraft [HG90]. The self oscillating method is also a feedback based mechanism, utilizing a relay in the

Improving power and robustness for detecting genetic association with extreme-value sampling design.

PubMed

Chen, Hua Yun; Li, Mingyao

2011-12-01

Extreme-value sampling design that samples subjects with extremely large or small quantitative trait values is commonly used in genetic association studies. Samples in such designs are often treated as "cases" and "controls" and analyzed using logistic regression. Such a case-control analysis ignores the potential dose-response relationship between the quantitative trait and the underlying trait locus and thus may lead to loss of power in detecting genetic association. An alternative approach to analyzing such data is to model the dose-response relationship by a linear regression model. However, parameter estimation from this model can be biased, which may lead to inflated type I errors. We propose a robust and efficient approach that takes into consideration of both the biased sampling design and the potential dose-response relationship. Extensive simulations demonstrate that the proposed method is more powerful than the traditional logistic regression analysis and is more robust than the linear regression analysis. We applied our method to the analysis of a candidate gene association study on high-density lipoprotein cholesterol (HDL-C) which includes study subjects with extremely high or low HDL-C levels. Using our method, we identified several SNPs showing a stronger evidence of association with HDL-C than the traditional case-control logistic regression analysis. Our results suggest that it is important to appropriately model the quantitative traits and to adjust for the biased sampling when dose-response relationship exists in extreme-value sampling designs. © 2011 Wiley Periodicals, Inc.

Robust passive control for a class of uncertain neutral systems based on sliding mode observer.

PubMed

Liu, Zhen; Zhao, Lin; Kao, Yonggui; Gao, Cunchen

2017-01-01

The passivity-based sliding mode control (SMC) problem for a class of uncertain neutral systems with unmeasured states is investigated. Firstly, a particular non-fragile state observer is designed to generate the estimations of the system states, based upon which a novel integral-type sliding surface function is established for the control process. Secondly, a new sufficient condition for robust asymptotic stability and passivity of the resultant sliding mode dynamics (SMDs) is obtained in terms of linear matrix inequalities (LMIs). Thirdly, the finite-time reachability of the predesigned sliding surface is ensured by resorting to a novel adaptive SMC law. Finally, the validity and superiority of the scheme are justified via several examples. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A variable structure approach to robust control of VTOL aircraft

NASA Technical Reports Server (NTRS)

Calise, A. J.; Kramer, F.

1982-01-01

This paper examines the application of variable structure control theory to the design of a flight control system for the AV-8A Harrier in a hover mode. The objective in variable structure design is to confine the motion to a subspace of the total state space. The motion in this subspace is insensitive to system parameter variations and external disturbances that lie in the range space of the control. A switching type of control law results from the design procedure. The control system was designed to track a vector velocity command defined in the body frame. For comparison purposes, a proportional controller was designed using optimal linear regulator theory. Both control designs were first evaluated for transient response performance using a linearized model, then a nonlinear simulation study of a hovering approach to landing was conducted. Wind turbulence was modeled using a 1052 destroyer class air wake model.

A Study on Application of Fuzzy Adaptive Unscented Kalman Filter to Nonlinear Turbojet Engine Control

NASA Astrophysics Data System (ADS)

Han, Dongju

2018-05-01

Safe and efficient flight powered by an aircraft turbojet engine relies on the performance of the engine controller preventing compressor surge with robustness from noises or disturbances. This paper proposes the effective nonlinear controller associated with the nonlinear filter for the real turbojet engine with highly nonlinear dynamics. For the feasible controller study the nonlinearity of the engine dynamics was investigated by comparing the step responses from the linearized model with the original nonlinear dynamics. The fuzzy-based PID control logic is introduced to control the engine efficiently and FAUKF is applied for robustness from noises. The simulation results prove the effectiveness of FAUKF applied to the proposed controller such that the control performances are superior over the conventional controller and the filer performance using FAUKF indicates the satisfactory results such as clearing the defects by reducing the distortions without compressor surge, whereas the conventional UKF is not fully effective as occurring some distortions with compressor surge due to a process noise.

Design Criteria for the Future of Flight Controls. Proceedings of the Flight Dynamics Laboratory Flying Qualities and Flight Control Symposium 2-5 March 1982.

DTIC Science & Technology

1982-07-01

robustness of the closed-loop system as compared to state feedback. The observer theory of Luenberger specifies the conditions that must be satisfied for...No. ID-17SI-F-l, October 1963. 8. Rynaski, E. G. and Whitbeck, R. F.: "The Theory and Application of Linear Optimal Control," Calspan Report No. IH...pilots tend to control them open-loop. Frequencies much beyond 10 rad/sec are generally beyond pilots’ control capability. Control theory indicates a need

Robust fault tolerant control based on sliding mode method for uncertain linear systems with quantization.

PubMed

Hao, Li-Ying; Yang, Guang-Hong

2013-09-01

This paper is concerned with the problem of robust fault-tolerant compensation control problem for uncertain linear systems subject to both state and input signal quantization. By incorporating novel matrix full-rank factorization technique with sliding surface design successfully, the total failure of certain actuators can be coped with, under a special actuator redundancy assumption. In order to compensate for quantization errors, an adjustment range of quantization sensitivity for a dynamic uniform quantizer is given through the flexible choices of design parameters. Comparing with the existing results, the derived inequality condition leads to the fault tolerance ability stronger and much wider scope of applicability. With a static adjustment policy of quantization sensitivity, an adaptive sliding mode controller is then designed to maintain the sliding mode, where the gain of the nonlinear unit vector term is updated automatically to compensate for the effects of actuator faults, quantization errors, exogenous disturbances and parameter uncertainties without the need for a fault detection and isolation (FDI) mechanism. Finally, the effectiveness of the proposed design method is illustrated via a model of a rocket fairing structural-acoustic. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Non-linear control of the output stage of a solar microinverter

NASA Astrophysics Data System (ADS)

Lopez-Santos, Oswaldo; Garcia, Germain; Martinez-Salamero, Luis; Avila-Martinez, Juan C.; Seguier, Lionel

2017-01-01

This paper presents a proposal to control the output stage of a two-stage solar microinverter to inject real power into the grid. The input stage of the microinverter is used to extract the maximum available power of a photovoltaic module enforcing a power source behavior in the DC-link to feed the output stage. The work here reported is devoted to control a grid-connected power source inverter with a high power quality level at the grid side ensuring the power balance of the microinverter regulating the voltage of the DC-link. The proposed control is composed of a sinusoidal current reference generator and a cascade type controller composed by a current tracking loop and a voltage regulation loop. The current reference is obtained using a synchronized generator based on phase locked loop (PLL) which gives the shape, the frequency and phase of the current signal. The amplitude of the reference is obtained from a simple controller regulating the DC-link voltage. The tracking of the current reference is accomplished by means of a first-order sliding mode control law. The solution takes advantage of the rapidity and inherent robustness of the sliding mode current controller allowing a robust behavior in the regulation of the DC-link using a simple linear controller. The analytical expression to determine the power quality indicators of the micro-inverter's output is theoretically solved giving expressions relating the converter parameters. The theoretical approach is validated using simulation and experimental results.

Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust stability and controller robustness.

PubMed

Precup, Radu-Emil; David, Radu-Codrut; Petriu, Emil M; Radac, Mircea-Bogdan; Preitl, Stefan

2014-11-01

This paper suggests a new generation of optimal PI controllers for a class of servo systems characterized by saturation and dead zone static nonlinearities and second-order models with an integral component. The objective functions are expressed as the integral of time multiplied by absolute error plus the weighted sum of the integrals of output sensitivity functions of the state sensitivity models with respect to two process parametric variations. The PI controller tuning conditions applied to a simplified linear process model involve a single design parameter specific to the extended symmetrical optimum (ESO) method which offers the desired tradeoff to several control system performance indices. An original back-calculation and tracking anti-windup scheme is proposed in order to prevent the integrator wind-up and to compensate for the dead zone nonlinearity of the process. The minimization of the objective functions is carried out in the framework of optimization problems with inequality constraints which guarantee the robust stability with respect to the process parametric variations and the controller robustness. An adaptive gravitational search algorithm (GSA) solves the optimization problems focused on the optimal tuning of the design parameter specific to the ESO method and of the anti-windup tracking gain. A tuning method for PI controllers is proposed as an efficient approach to the design of resilient control systems. The tuning method and the PI controllers are experimentally validated by the adaptive GSA-based tuning of PI controllers for the angular position control of a laboratory servo system.

Decentralized robust nonlinear model predictive controller for unmanned aerial systems

NASA Astrophysics Data System (ADS)

Garcia Garreton, Gonzalo A.

The nonlinear and unsteady nature of aircraft aerodynamics together with limited practical range of controls and state variables make the use of the linear control theory inadequate especially in the presence of external disturbances, such as wind. In the classical approach, aircraft are controlled by multiple inner and outer loops, designed separately and sequentially. For unmanned aerial systems in particular, control technology must evolve to a point where autonomy is extended to the entire mission flight envelope. This requires advanced controllers that have sufficient robustness, track complex trajectories, and use all the vehicles control capabilities at higher levels of accuracy. In this work, a robust nonlinear model predictive controller is designed to command and control an unmanned aerial system to track complex tight trajectories in the presence of internal and external perturbance. The Flight System developed in this work achieves the above performance by using: 1. A nonlinear guidance algorithm that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2. A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3. An artificial neural network, designed to adaptively estimate and provide aerodynamic and propulsive forces in real-time; and 4. A mixed sensitivity approach that enhances the robustness for a nonlinear model predictive controller overcoming the effect of un-modeled dynamics, external disturbances such as wind, and measurement additive perturbations, such as noise and biases. These elements have been integrated and tested in simulation and with previously stored flight test data and shown to be feasible.

Neural network application to aircraft control system design

NASA Technical Reports Server (NTRS)

Troudet, Terry; Garg, Sanjay; Merrill, Walter C.

1991-01-01

The feasibility of using artificial neural networks as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research are identified to enhance the practical applicability of neural networks to flight control design.

Neural network application to aircraft control system design

NASA Technical Reports Server (NTRS)

Troudet, Terry; Garg, Sanjay; Merrill, Walter C.

1991-01-01

The feasibility of using artificial neural network as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research identified to enhance the practical applicability of neural networks to flight control design.

Robust control of systems with real parameter uncertainty and unmodelled dynamics

NASA Technical Reports Server (NTRS)

Chang, Bor-Chin; Fischl, Robert

1991-01-01

During this research period we have made significant progress in the four proposed areas: (1) design of robust controllers via H infinity optimization; (2) design of robust controllers via mixed H2/H infinity optimization; (3) M-delta structure and robust stability analysis for structured uncertainties; and (4) a study on controllability and observability of perturbed plant. It is well known now that the two-Riccati-equation solution to the H infinity control problem can be used to characterize all possible stabilizing optimal or suboptimal H infinity controllers if the optimal H infinity norm or gamma, an upper bound of a suboptimal H infinity norm, is given. In this research, we discovered some useful properties of these H infinity Riccati solutions. Among them, the most prominent one is that the spectral radius of the product of these two Riccati solutions is a continuous, nonincreasing, convex function of gamma in the domain of interest. Based on these properties, quadratically convergent algorithms are developed to compute the optimal H infinity norm. We also set up a detailed procedure for applying the H infinity theory to robust control systems design. The desire to design controllers with H infinity robustness but H(exp 2) performance has recently resulted in mixed H(exp 2) and H infinity control problem formulation. The mixed H(exp 2)/H infinity problem have drawn the attention of many investigators. However, solution is only available for special cases of this problem. We formulated a relatively realistic control problem with H(exp 2) performance index and H infinity robustness constraint into a more general mixed H(exp 2)/H infinity problem. No optimal solution yet is available for this more general mixed H(exp 2)/H infinity problem. Although the optimal solution for this mixed H(exp 2)/H infinity control has not yet been found, we proposed a design approach which can be used through proper choice of the available design parameters to influence both robustness and performance. For a large class of linear time-invariant systems with real parametric perturbations, the coefficient vector of the characteristic polynomial is a multilinear function of the real parameter vector. Based on this multilinear mapping relationship together with the recent developments for polytopic polynomials and parameter domain partition technique, we proposed an iterative algorithm for coupling the real structured singular value.

Model based design of electronic throttle control

NASA Astrophysics Data System (ADS)

Cherian, Fenin; Ranjan, Ashish; Bhowmick, Pathikrit; Rammohan, A.

2017-11-01

With the advent of torque based Engine Management Systems, the precise control and robust performance of the throttle body becomes a key factor in the overall performance of the vehicle. Electronic Throttle Control provides benefits such as improved air-fuel ratio for improving the vehicle performance and lower exhausts emissions to meet the stringent emission norms. Modern vehicles facilitate various features such as Cruise Control, Traction Control, Electronic Stability Program and Pre-crash systems. These systems require control over engine power without driver intervention, which is not possible with conventional mechanical throttle system. Thus these systems are integrated to function with the electronic throttle control. However, due to inherent non-linearities in the throttle body, the control becomes a difficult task. In order to eliminate the influence of this hysteresis at the initial operation of the butterfly valve, a control to compensate the shortage must be added to the duty required for starting throttle operation when the initial operation is detected. Therefore, a lot of work is being done in this field to incorporate the various nonlinearities to achieve robust control. In our present work, the ETB was tested to verify the working of the system. Calibration of the TPS sensors was carried out in order to acquire accurate throttle opening angle. The response of the calibrated system was then plotted against a step input signal. A linear model of the ETB was prepared using Simulink and its response was compared with the experimental data to find out the initial deviation of the model from the actual system. To reduce this deviation, non-linearities from existing literature were introduced to the system and a response analysis was performed to check the deviation from the actual system. Based on this investigation, an introduction of a new nonlinearity parameter can be used in future to reduce the deviation further making the control of the ETB more precise and accurate.

Nonlinear gearshifts control of dual-clutch transmissions during inertia phase.

PubMed

Hu, Yunfeng; Tian, Lu; Gao, Bingzhao; Chen, Hong

2014-07-01

In this paper, a model-based nonlinear gearshift controller is designed by the backstepping method to improve the shift quality of vehicles with a dual-clutch transmission (DCT). Considering easy-implementation, the controller is rearranged into a concise structure which contains a feedforward control and a feedback control. Then, robustness of the closed-loop error system is discussed in the framework of the input to state stability (ISS) theory, where model uncertainties are considered as the additive disturbance inputs. Furthermore, due to the application of the backstepping method, the closed-loop error system is ordered as a linear system. Using the linear system theory, a guideline for selecting the controller parameters is deduced which could reduce the workload of parameters tuning. Finally, simulation results and Hardware in the Loop (HiL) simulation are presented to validate the effectiveness of the designed controller. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alvarez-Ramirez, J.; Aguilar, R.; Lopez-Isunza, F.

FCC processes involve complex interactive dynamics which are difficult to operate and control as well as poorly known reaction kinetics. This work concerns the synthesis of temperature controllers for FCC units. The problem is addressed first for the case where perfect knowledge of the reaction kinetics is assumed, leading to an input-output linearizing state feedback. However, in most industrial FCC units, perfect knowledge of reaction kinetics and composition measurements is not available. To address the problem of robustness against uncertainties in the reaction kinetics, an adaptive model-based nonlinear controller with simplified reaction models is presented. The adaptive strategy makes usemore » of estimates of uncertainties derived from calorimetric (energy) balances. The resulting controller is similar in form to standard input-output linearizing controllers and can be tuned analogously. Alternatively, the controller can be tuned using a single gain parameter and is computationally efficient. The performance of the closed-loop system and the controller design procedure are shown with simulations.« less

Reusable Launch Vehicle Control in Multiple Time Scale Sliding Modes

NASA Technical Reports Server (NTRS)

Shtessel, Yuri

1999-01-01

A reusable launch vehicle control problem during ascent is addressed via multiple-time scaled continuous sliding mode control. The proposed sliding mode controller utilizes a two-loop structure and provides robust, de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of bounded external disturbances and plant uncertainties. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues placement. The dual-time scale sliding mode controller was designed for the X-33 technology demonstration sub-orbital launch vehicle in the launch mode. 6DOF simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in presence of external disturbances and vehicle inertia uncertainties. It creates possibility to operate the X-33 vehicle in an aircraft-like mode with reduced pre-launch adjustment of the control system.

Sliding Mode Control Applied to Reconfigurable Flight Control Design

NASA Technical Reports Server (NTRS)

Hess, R. A.; Wells, S. R.; Bacon, Barton (Technical Monitor)

2002-01-01

Sliding mode control is applied to the design of a flight control system capable of operating with limited bandwidth actuators and in the presence of significant damage to the airframe and/or control effector actuators. Although inherently robust, sliding mode control algorithms have been hampered by their sensitivity to the effects of parasitic unmodeled dynamics, such as those associated with actuators and structural modes. It is known that asymptotic observers can alleviate this sensitivity while still allowing the system to exhibit significant robustness. This approach is demonstrated. The selection of the sliding manifold as well as the interpretation of the linear design that results after introduction of a boundary layer is accomplished in the frequency domain. The design technique is exercised on a pitch-axis controller for a simple short-period model of the High Angle of Attack F-18 vehicle via computer simulation. Stability and performance is compared to that of a system incorporating a controller designed by classical loop-shaping techniques.

Robust lane detection and tracking using multiple visual cues under stochastic lane shape conditions

NASA Astrophysics Data System (ADS)

Huang, Zhi; Fan, Baozheng; Song, Xiaolin

2018-03-01

As one of the essential components of environment perception techniques for an intelligent vehicle, lane detection is confronted with challenges including robustness against the complicated disturbance and illumination, also adaptability to stochastic lane shapes. To overcome these issues, we proposed a robust lane detection method named classification-generation-growth-based (CGG) operator to the detected lines, whereby the linear lane markings are identified by synergizing multiple visual cues with the a priori knowledge and spatial-temporal information. According to the quality of linear lane fitting, the linear and linear-parabolic models are dynamically switched to describe the actual lane. The Kalman filter with adaptive noise covariance and the region of interests (ROI) tracking are applied to improve the robustness and efficiency. Experiments were conducted with images covering various challenging scenarios. The experimental results evaluate the effectiveness of the presented method for complicated disturbances, illumination, and stochastic lane shapes.

Robust coordinated control of a dual-arm space robot

NASA Astrophysics Data System (ADS)

Shi, Lingling; Kayastha, Sharmila; Katupitiya, Jay

2017-09-01

Dual-arm space robots are more capable of implementing complex space tasks compared with single arm space robots. However, the dynamic coupling between the arms and the base will have a serious impact on the spacecraft attitude and the hand motion of each arm. Instead of considering one arm as the mission arm and the other as the balance arm, in this work two arms of the space robot perform as mission arms aimed at accomplishing secure capture of a floating target. The paper investigates coordinated control of the base's attitude and the arms' motion in the task space in the presence of system uncertainties. Two types of controllers, i.e. a Sliding Mode Controller (SMC) and a nonlinear Model Predictive Controller (MPC) are verified and compared with a conventional Computed-Torque Controller (CTC) through numerical simulations in terms of control accuracy and system robustness. Both controllers eliminate the need to linearly parameterize the dynamic equations. The MPC has been shown to achieve performance with higher accuracy than CTC and SMC in the absence of system uncertainties under the condition that they consume comparable energy. When the system uncertainties are included, SMC and CTC present advantageous robustness than MPC. Specifically, in a case where system inertia increases, SMC delivers higher accuracy than CTC and costs the least amount of energy.

An adaptive robust controller for time delay maglev transportation systems

NASA Astrophysics Data System (ADS)

Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza

2012-12-01

For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.

Robust control design with real parameter uncertainty using absolute stability theory. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

How, Jonathan P.; Hall, Steven R.

1993-01-01

The purpose of this thesis is to investigate an extension of mu theory for robust control design by considering systems with linear and nonlinear real parameter uncertainties. In the process, explicit connections are made between mixed mu and absolute stability theory. In particular, it is shown that the upper bounds for mixed mu are a generalization of results from absolute stability theory. Both state space and frequency domain criteria are developed for several nonlinearities and stability multipliers using the wealth of literature on absolute stability theory and the concepts of supply rates and storage functions. The state space conditions are expressed in terms of Riccati equations and parameter-dependent Lyapunov functions. For controller synthesis, these stability conditions are used to form an overbound of the H2 performance objective. A geometric interpretation of the equivalent frequency domain criteria in terms of off-axis circles clarifies the important role of the multiplier and shows that both the magnitude and phase of the uncertainty are considered. A numerical algorithm is developed to design robust controllers that minimize the bound on an H2 cost functional and satisfy an analysis test based on the Popov stability multiplier. The controller and multiplier coefficients are optimized simultaneously, which avoids the iteration and curve-fitting procedures required by the D-K procedure of mu synthesis. Several benchmark problems and experiments on the Middeck Active Control Experiment at M.I.T. demonstrate that these controllers achieve good robust performance and guaranteed stability bounds.

The analysis on nonlinear control of the aircraft arresting system

NASA Astrophysics Data System (ADS)

Song, Jinchun; Du, Tianrong

2005-12-01

The aircraft arresting system is a complicated nonlinear system. This paper analyzes the mechanical-hydraulic structure of aircraft arresting system composed of electro hydraulic valve and establishes the dynamic equation of the aircraft arresting system. Based on the state-feedback linearization of nonlinear system, a PD-based controller is synthesized. Simulation studies indicate, while arresting the different type aircraft, the proposed controller has fast response, good tracking performance and strong robustness. By tuning the parameters of the PD controller, a satisfactory control performance can be guaranteed.

An approach to multivariable control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

The paper presents simple schemes for multivariable control of multiple-joint robot manipulators in joint and Cartesian coordinates. The joint control scheme consists of two independent multivariable feedforward and feedback controllers. The feedforward controller is the minimal inverse of the linearized model of robot dynamics and contains only proportional-double-derivative (PD2) terms - implying feedforward from the desired position, velocity and acceleration. This controller ensures that the manipulator joint angles track any reference trajectories. The feedback controller is of proportional-integral-derivative (PID) type and is designed to achieve pole placement. This controller reduces any initial tracking error to zero as desired and also ensures that robust steady-state tracking of step-plus-exponential trajectories is achieved by the joint angles. Simple and explicit expressions of computation of the feedforward and feedback gains are obtained based on the linearized model of robot dynamics. This leads to computationally efficient schemes for either on-line gain computation or off-line gain scheduling to account for variations in the linearized robot model due to changes in the operating point. The joint control scheme is extended to direct control of the end-effector motion in Cartesian space. Simulation results are given for illustration.

A novel single thruster control strategy for spacecraft attitude stabilization

NASA Astrophysics Data System (ADS)

Godard; Kumar, Krishna Dev; Zou, An-Min

2013-05-01

Feasibility of achieving three axis attitude stabilization using a single thruster is explored in this paper. Torques are generated using a thruster orientation mechanism with which the thrust vector can be tilted on a two axis gimbal. A robust nonlinear control scheme is developed based on the nonlinear kinematic and dynamic equations of motion of a rigid body spacecraft in the presence of gravity gradient torque and external disturbances. The spacecraft, controlled using the proposed concept, constitutes an underactuated system (a system with fewer independent control inputs than degrees of freedom) with nonlinear dynamics. Moreover, using thruster gimbal angles as control inputs make the system non-affine (control terms appear nonlinearly in the state equation). This necessitates the control algorithms to be developed based on nonlinear control theory since linear control methods are not directly applicable. The stability conditions for the spacecraft attitude motion for robustness against uncertainties and disturbances are derived to establish the regions of asymptotic 3-axis attitude stabilization. Several numerical simulations are presented to demonstrate the efficacy of the proposed controller and validate the theoretical results. The control algorithm is shown to compensate for time-varying external disturbances including solar radiation pressure, aerodynamic forces, and magnetic disturbances; and uncertainties in the spacecraft inertia parameters. The numerical results also establish the robustness of the proposed control scheme to negate disturbances caused by orbit eccentricity.

A robust H∞-tracking design for uncertain Takagi-Sugeno fuzzy systems with unknown premise variables using descriptor redundancy approach

NASA Astrophysics Data System (ADS)

Hassan Asemani, Mohammad; Johari Majd, Vahid

2015-12-01

This paper addresses a robust H∞ fuzzy observer-based tracking design problem for uncertain Takagi-Sugeno fuzzy systems with external disturbances. To have a practical observer-based controller, the premise variables of the system are assumed to be not measurable in general, which leads to a more complex design process. The tracker is synthesised based on a fuzzy Lyapunov function approach and non-parallel distributed compensation (non-PDC) scheme. Using the descriptor redundancy approach, the robust stability conditions are derived in the form of strict linear matrix inequalities (LMIs) even in the presence of uncertainties in the system, input, and output matrices simultaneously. Numerical simulations are provided to show the effectiveness of the proposed method.

Robust optical sensors for safety critical automotive applications

NASA Astrophysics Data System (ADS)

De Locht, Cliff; De Knibber, Sven; Maddalena, Sam

2008-02-01

Optical sensors for the automotive industry need to be robust, high performing and low cost. This paper focuses on the impact of automotive requirements on optical sensor design and packaging. Main strategies to lower optical sensor entry barriers in the automotive market include: Perform sensor calibration and tuning by the sensor manufacturer, sensor test modes on chip to guarantee functional integrity at operation, and package technology is key. As a conclusion, optical sensor applications are growing in automotive. Optical sensor robustness matured to the level of safety critical applications like Electrical Power Assisted Steering (EPAS) and Drive-by-Wire by optical linear arrays based systems and Automated Cruise Control (ACC), Lane Change Assist and Driver Classification/Smart Airbag Deployment by camera imagers based systems.

Nonlinear SVM-DTC for induction motor drive using input-output feedback linearization and high order sliding mode control.

PubMed

Ammar, Abdelkarim; Bourek, Amor; Benakcha, Abdelhamid

2017-03-01

This paper presents a nonlinear Direct Torque Control (DTC) strategy with Space Vector Modulation (SVM) for an induction motor. A nonlinear input-output feedback linearization (IOFL) is implemented to achieve a decoupled torque and flux control and the SVM is employed to reduce high torque and flux ripples. Furthermore, the control scheme performance is improved by inserting a super twisting speed controller in the outer loop and a load torque observer to enhance the speed regulation. The combining of dual nonlinear strategies ensures a good dynamic and robustness against parameters variation and disturbance. The system stability has been analyzed using Lyapunov stability theory. The effectiveness of the control algorithm is investigated by simulation and experimental validation using Matlab/Simulink software with real-time interface based on dSpace 1104. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Integral Sliding Mode Fault-Tolerant Control for Uncertain Linear Systems Over Networks With Signals Quantization.

PubMed

Hao, Li-Ying; Park, Ju H; Ye, Dan

2017-09-01

In this paper, a new robust fault-tolerant compensation control method for uncertain linear systems over networks is proposed, where only quantized signals are assumed to be available. This approach is based on the integral sliding mode (ISM) method where two kinds of integral sliding surfaces are constructed. One is the continuous-state-dependent surface with the aim of sliding mode stability analysis and the other is the quantization-state-dependent surface, which is used for ISM controller design. A scheme that combines the adaptive ISM controller and quantization parameter adjustment strategy is then proposed. Through utilizing H ∞ control analytical technique, once the system is in the sliding mode, the nature of performing disturbance attenuation and fault tolerance from the initial time can be found without requiring any fault information. Finally, the effectiveness of our proposed ISM control fault-tolerant schemes against quantization errors is demonstrated in the simulation.

Developpement d'une plateforme de simulation et d'un pilote automatique - Application aux Cessna Citation X et Hawker 800XP

NASA Astrophysics Data System (ADS)

Ghazi, Georges

This report presents several methodologies for the design of tools intended to the analysis of the stability and the control of a business aircraft. At first, a generic flight dynamic model was developed to predict the behavior of the aircraft further to a movement on the control surfaces or further to any disturbance. For that purpose, different categories of winds were considered in the module of simulation to generate various scenarios and conclude about the efficiency of the autopilot. Besides being realistic, the flight model takes into account the variation of the mass parameters according to fuel consumption. A comparison with a simulator of the company CAE Inc. and certified level D allowed to validate this first stage with an acceptable success rate. Once the dynamics is validated, the next stage deals with the stability around a flight condition. For that purpose, a first static analysis is established to find the trim conditions inside the flight envelop. Then, two algorithms of linearization generate the state space models which approximate the decoupled dynamics (longitudinal and lateral) of the aircraft. Then to test the viability of the linear models, 1,500 comparisons with the nonlinear dynamics have been done with a 100% rate of success. The study of stability allowed to highlight the need of control systems to improve first the performances of the plane, then to control its different axes. A methodology based on a coupling between a modern control technique (LQR) and a genetic algorithm is presented. This methodology allowed to find optimal and successful controllers which satisfy a large number of specifications. Besides being successful, they have to be robust to uncertainties owed to the variation of mass. Thus, an analysis of robustness using the theory of the guardian maps was applied to uncertain dynamics. However, because of a too sensitive region of the flight envelop, some analyses are biased. Nevertheless, a validation with the nonlinear dynamics allowed to prove the robustness of the controllers over the entire flight envelope. Finally, the last stage of this project concerned the control laws for the autopilot. Once again, the proposed methodology, bases itself on the association of flight mechanic equations, control theory and a metaheuristic optimization method. Afterward, four detailed test scenarios are presented to illustrate the efficiency and the robustness of the entire autopilot.

Robust pinning control of heterogeneous complex networks with jointly connected topologies and time-varying parametric uncertainty

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2018-05-01

The pinning/leader control problems provide the design of the leader or pinning controller in order to guide a complex network to a desired trajectory or target (synchronisation or consensus). Let a time-invariant complex network, pinning/leader control problems include the design of the leader or pinning controller gain and number of nodes to pin in order to guide a network to a desired trajectory (synchronization or consensus). Usually, lower is the number of pinned nodes larger is the pinning gain required to assess network synchronisation. On the other side, realistic application scenario of complex networks is characterised by switching topologies, time-varying node coupling strength and link weight that make hard to solve the pinning/leader control problem. Additionally, the system dynamics at nodes can be heterogeneous. In this paper, we derive robust stabilisation conditions of time-varying heterogeneous complex networks with jointly connected topologies when coupling strength and link weight interactions are affected by time-varying uncertainties. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, we formulate low computationally demanding stabilisability conditions to design a pinning/leader control gain for robust network synchronisation. The effectiveness of the proposed approach is shown by several design examples applied to a paradigmatic well-known complex network composed of heterogeneous Chua's circuits.

F-15B QuietSpike(TradeMark) Aeroservoelastic Flight Test Data Analysis

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

System identification or mathematical modelling is utilised in the aerospace community for the development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. The reason for utilising a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance for the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data for several flight conditions (Mach number) that (i) linear models are inefficient for modelling aeroservoelastic data, (ii) nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data and (iii) the model structure and parameters vary as the flight condition is altered.

Development of An Intelligent Flight Propulsion Control System

NASA Technical Reports Server (NTRS)

Calise, A. J.; Rysdyk, R. T.; Leonhardt, B. K.

1999-01-01

The initial design and demonstration of an Intelligent Flight Propulsion and Control System (IFPCS) is documented. The design is based on the implementation of a nonlinear adaptive flight control architecture. This initial design of the IFPCS enhances flight safety by using propulsion sources to provide redundancy in flight control. The IFPCS enhances the conventional gain scheduled approach in significant ways: (1) The IFPCS provides a back up flight control system that results in consistent responses over a wide range of unanticipated failures. (2) The IFPCS is applicable to a variety of aircraft models without redesign and,(3) significantly reduces the laborious research and design necessary in a gain scheduled approach. The control augmentation is detailed within an approximate Input-Output Linearization setting. The availability of propulsion only provides two control inputs, symmetric and differential thrust. Earlier Propulsion Control Augmentation (PCA) work performed by NASA provided for a trajectory controller with pilot command input of glidepath and heading. This work is aimed at demonstrating the flexibility of the IFPCS in providing consistency in flying qualities under a variety of failure scenarios. This report documents the initial design phase where propulsion only is used. Results confirm that the engine dynamics and associated hard nonlineaaities result in poor handling qualities at best. However, as demonstrated in simulation, the IFPCS is capable of results similar to the gain scheduled designs of the NASA PCA work. The IFPCS design uses crude estimates of aircraft behaviour. The adaptive control architecture demonstrates robust stability and provides robust performance. In this work, robust stability means that all states, errors, and adaptive parameters remain bounded under a wide class of uncertainties and input and output disturbances. Robust performance is measured in the quality of the tracking. The results demonstrate the flexibility of the IFPCS architecture and the ability to provide robust performance under a broad range of uncertainty. Robust stability is proved using Lyapunov like analysis. Future development of the IFPCS will include integration of conventional control surfaces with the use of propulsion augmentation, and utilization of available lift and drag devices, to demonstrate adaptive control capability under a greater variety of failure scenarios. Further work will specifically address the effects of actuator saturation.

Preliminary demonstration of a robust controller design method

NASA Technical Reports Server (NTRS)

Anderson, L. R.

1980-01-01

Alternative computational procedures for obtaining a feedback control law which yields a control signal based on measurable quantitites are evaluated. The three methods evaluated are: (1) the standard linear quadratic regulator design model; (2) minimization of the norm of the feedback matrix, k via nonlinear programming subject to the constraint that the closed loop eigenvalues be in a specified domain in the complex plane; and (3) maximize the angles between the closed loop eigenvectors in combination with minimizing the norm of K also via the constrained nonlinear programming. The third or robust design method was chosen to yield a closed loop system whose eigenvalues are insensitive to small changes in the A and B matrices. The relationship between orthogonality of closed loop eigenvectors and the sensitivity of closed loop eigenvalues is described. Computer programs are described.

Parameterized LMI Based Diagonal Dominance Compensator Study for Polynomial Linear Parameter Varying System

NASA Astrophysics Data System (ADS)

Han, Xiaobao; Li, Huacong; Jia, Qiusheng

2017-12-01

For dynamic decoupling of polynomial linear parameter varying(PLPV) system, a robust dominance pre-compensator design method is given. The parameterized precompensator design problem is converted into an optimal problem constrained with parameterized linear matrix inequalities(PLMI) by using the conception of parameterized Lyapunov function(PLF). To solve the PLMI constrained optimal problem, the precompensator design problem is reduced into a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a new constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator is achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation on a turbofan engine PLPV model.

A Flight Control System for Small Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Tunik, A. A.; Nadsadnaya, O. I.

2018-03-01

The program adaptation of the controller for the flight control system (FCS) of an unmanned aerial vehicle (UAV) is considered. Linearized flight dynamic models depend mainly on the true airspeed of the UAV, which is measured by the onboard air data system. This enables its use for program adaptation of the FCS over the full range of altitudes and velocities, which define the flight operating range. FCS with program adaptation, based on static feedback (SF), is selected. The SF parameters for every sub-range of the true airspeed are determined using the linear matrix inequality approach in the case of discrete systems for synthesis of a suboptimal robust H ∞-controller. The use of the Lagrange interpolation between true airspeed sub-ranges provides continuous adaptation. The efficiency of the proposed approach is shown against an example of the heading stabilization system.

Trajectory control of robot manipulators with closed-kinematic chain mechanism

NASA Technical Reports Server (NTRS)

Nguyen, Charles C.; Pooran, Farhad J.; Premack, Timothy

1987-01-01

The problem of Cartesian trajectory control of a closed-kinematic chain mechanism robot manipulator, recently built at CAIR to study the assembly of NASA hardware for the future Space Station, is considered. The study is performed by both computer simulation and experimentation for tracking of three different paths: a straight line, a sinusoid, and a circle. Linearization and pole placement methods are employed to design controller gains. Results show that the controllers are robust and there are good agreements between simulation and experimentation. The results also show excellent tracking quality and small overshoots.

On decentralized control of large-scale systems

NASA Technical Reports Server (NTRS)

Siljak, D. D.

1978-01-01

A scheme is presented for decentralized control of large-scale linear systems which are composed of a number of interconnected subsystems. By ignoring the interconnections, local feedback controls are chosen to optimize each decoupled subsystem. Conditions are provided to establish compatibility of the individual local controllers and achieve stability of the overall system. Besides computational simplifications, the scheme is attractive because of its structural features and the fact that it produces a robust decentralized regulator for large dynamic systems, which can tolerate a wide range of nonlinearities and perturbations among the subsystems.

An Analysis of the Optimal Control Modification Method Applied to Flutter Suppression

NASA Technical Reports Server (NTRS)

Drew, Michael; Nguyen, Nhan T.; Hashemi, Kelley E.; Ting, Eric; Chaparro, Daniel

2017-01-01

Unlike basic Model Reference Adaptive Control (MRAC)l, Optimal Control Modification (OCM) has been shown to be a promising MRAC modification with robustness and analytical properties not present in other adaptive control methods. This paper presents an analysis of the OCM method, and how the asymptotic property of OCM is useful for analyzing and tuning the controller. We begin with a Lyapunov stability proof of an OCM controller having two adaptive gain terms, then the less conservative and easily analyzed OCM asymptotic property is presented. Two numerical examples are used to show how this property can accurately predict steady state stability and quantitative robustness in the presence of time delay, and relative to linear plant perturbations, and nominal Loop Transfer Recovery (LTR) tuning. The asymptotic property of the OCM controller is then used as an aid in tuning the controller applied to a large scale aeroservoelastic longitudinal aircraft model for flutter suppression. Control with OCM adaptive augmentation is shown to improve performance over that of the nominal non-adaptive controller when significant disparities exist between the controller/observer model and the true plant model.

Active fault tolerant control based on interval type-2 fuzzy sliding mode controller and non linear adaptive observer for 3-DOF laboratory helicopter.

PubMed

Zeghlache, Samir; Benslimane, Tarak; Bouguerra, Abderrahmen

2017-11-01

In this paper, a robust controller for a three degree of freedom (3 DOF) helicopter control is proposed in presence of actuator and sensor faults. For this purpose, Interval type-2 fuzzy logic control approach (IT2FLC) and sliding mode control (SMC) technique are used to design a controller, named active fault tolerant interval type-2 Fuzzy Sliding mode controller (AFTIT2FSMC) based on non-linear adaptive observer to estimate and detect the system faults for each subsystem of the 3-DOF helicopter. The proposed control scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller. Exponential stability of the closed loop is guaranteed by using the Lyapunov method. The simulation results show that the AFTIT2FSMC can greatly alleviate the chattering effect, providing good tracking performance, even in presence of actuator and sensor faults. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A portable integrated system to control an active needle

NASA Astrophysics Data System (ADS)

Konh, Bardia; Motalleb, Mahdi; Ashrafiuon, Hashem

2017-04-01

The primary objective of this work is to introduce an integrated portable system to operate a flexible active surgical needle with actuation capabilities. The smart needle uses the robust actuation capabilities of the shape memory alloy wires to drastically improve the accuracy of in medical procedures such as brachytherapy. This, however, requires an integrated system aimed to control the insertion of the needle via a linear motor and its deflection by the SMA wire in real-time. The integrated system includes a flexible needle prototype, a Raspberry Pi computer, a linear stage motor, an SMA wire actuator, a power supply, electromagnetic tracking system, and various communication supplies. The linear stage motor guides the needle into tissue. The power supply provides appropriate current to the SMA actuator. The tracking system measures tip movement for feedback, The Raspberry Pi is the central tool that receives the tip movement feedback and controls the linear stage motor and the SMA actuator via the power supply. The implemented algorithms required for communication and feedback control are also described. This paper demonstrates that the portable integrated system may be a viable solution for more effective procedures requiring surgical needles.

Robust Damage-Mitigating Control of Aircraft for High Performance and Structural Durability

NASA Technical Reports Server (NTRS)

Caplin, Jeffrey; Ray, Asok; Joshi, Suresh M.

1999-01-01

This paper presents the concept and a design methodology for robust damage-mitigating control (DMC) of aircraft. The goal of DMC is to simultaneously achieve high performance and structural durability. The controller design procedure involves consideration of damage at critical points of the structure, as well as the performance requirements of the aircraft. An aeroelastic model of the wings has been formulated and is incorporated into a nonlinear rigid-body model of aircraft flight-dynamics. Robust damage-mitigating controllers are then designed using the H(infinity)-based structured singular value (mu) synthesis method based on a linearized model of the aircraft. In addition to penalizing the error between the ideal performance and the actual performance of the aircraft, frequency-dependent weights are placed on the strain amplitude at the root of each wing. Using each controller in turn, the control system is put through an identical sequence of maneuvers, and the resulting (varying amplitude cyclic) stress profiles are analyzed using a fatigue crack growth model that incorporates the effects of stress overload. Comparisons are made to determine the impact of different weights on the resulting fatigue crack damage in the wings. The results of simulation experiments show significant savings in fatigue life of the wings while retaining the dynamic performance of the aircraft.

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen; Zhu, J. Jim; Adami, Tony; Berry, Kyle; Grammar, Alex; Orr, Jeb S.; Best, Eric A.

2014-01-01

Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a generalized stability metric for time-varying loop=gain perturbations is needed for the AAC.

Finite-time robust passive control for a class of switched reaction-diffusion stochastic complex dynamical networks with coupling delays and impulsive control

NASA Astrophysics Data System (ADS)

Syed Ali, M.; Yogambigai, J.; Kwon, O. M.

2018-03-01

Finite-time boundedness and finite-time passivity for a class of switched stochastic complex dynamical networks (CDNs) with coupling delays, parameter uncertainties, reaction-diffusion term and impulsive control are studied. Novel finite-time synchronisation criteria are derived based on passivity theory. This paper proposes a CDN consisting of N linearly and diffusively coupled identical reaction- diffusion neural networks. By constructing of a suitable Lyapunov-Krasovskii's functional and utilisation of Jensen's inequality and Wirtinger's inequality, new finite-time passivity criteria for the networks are established in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Finally, two interesting numerical examples are given to show the effectiveness of the theoretical results.

Robust Power Management Control for Stand-Alone Hybrid Power Generation System

NASA Astrophysics Data System (ADS)

Kamal, Elkhatib; Adouane, Lounis; Aitouche, Abdel; Mohammed, Walaa

2017-01-01

This paper presents a new robust fuzzy control of energy management strategy for the stand-alone hybrid power systems. It consists of two levels named centralized fuzzy supervisory control which generates the power references for each decentralized robust fuzzy control. Hybrid power systems comprises: a photovoltaic panel and wind turbine as renewable sources, a micro turbine generator and a battery storage system. The proposed control strategy is able to satisfy the load requirements based on a fuzzy supervisor controller and manage power flows between the different energy sources and the storage unit by respecting the state of charge and the variation of wind speed and irradiance. Centralized controller is designed based on If-Then fuzzy rules to manage and optimize the hybrid power system production by generating the reference power for photovoltaic panel and wind turbine. Decentralized controller is based on the Takagi-Sugeno fuzzy model and permits us to stabilize each photovoltaic panel and wind turbine in presence of disturbances and parametric uncertainties and to optimize the tracking reference which is given by the centralized controller level. The sufficient conditions stability are formulated in the format of linear matrix inequalities using the Lyapunov stability theory. The effectiveness of the proposed Strategy is finally demonstrated through a SAHPS (stand-alone hybrid power systems) to illustrate the effectiveness of the overall proposed method.

Closed-Loop Evaluation of an Integrated Failure Identification and Fault Tolerant Control System for a Transport Aircraft

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Belcastro, Christine; Khong, thuan

2006-01-01

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. Such systems developed for failure detection, identification, and reconfiguration, as well as upset recovery, need to be evaluated over broad regions of the flight envelope or under extreme flight conditions, and should include various sources of uncertainty. To apply formal robustness analysis, formulation of linear fractional transformation (LFT) models of complex parameter-dependent systems is required, which represent system uncertainty due to parameter uncertainty and actuator faults. This paper describes a detailed LFT model formulation procedure from the nonlinear model of a transport aircraft by using a preliminary LFT modeling software tool developed at the NASA Langley Research Center, which utilizes a matrix-based computational approach. The closed-loop system is evaluated over the entire flight envelope based on the generated LFT model which can cover nonlinear dynamics. The robustness analysis results of the closed-loop fault tolerant control system of a transport aircraft are presented. A reliable flight envelope (safe flight regime) is also calculated from the robust performance analysis results, over which the closed-loop system can achieve the desired performance of command tracking and failure detection.

Time-delay control of a magnetic levitated linear positioning system

NASA Technical Reports Server (NTRS)

Tarn, J. H.; Juang, K. Y.; Lin, C. E.

1994-01-01

In this paper, a high accuracy linear positioning system with a linear force actuator and magnetic levitation is proposed. By locating a permanently magnetized rod inside a current-carrying solenoid, the axial force is achieved by the boundary effect of magnet poles and utilized to power the linear motion, while the force for levitation is governed by Ampere's Law supplied with the same solenoid. With the levitation in a radial direction, there is hardly any friction between the rod and the solenoid. The high speed motion can hence be achieved. Besides, the axial force acting on the rod is a smooth function of rod position, so the system can provide nanometer resolution linear positioning to the molecule size. Since the force-position relation is highly nonlinear, and the mathematical model is derived according to some assumptions, such as the equivalent solenoid of the permanently magnetized rod, so there exists unknown dynamics in practical application. Thus 'robustness' is an important issue in controller design. Meanwhile the load effect reacts directly on the servo system without transmission elements, so the capability of 'disturbance rejection; is also required. With the above consideration, a time-delay control scheme is chosen and applied. By comparing the input-output relation and the mathematical model, the time-delay controller calculates an estimation of unmodeled dynamics and disturbances and then composes the desired compensation into the system. Effectiveness of the linear positioning system and control scheme are illustrated with simulation results.

Comparison of adaptive critic-based and classical wide-area controllers for power systems.

PubMed

Ray, Swakshar; Venayagamoorthy, Ganesh Kumar; Chaudhuri, Balarko; Majumder, Rajat

2008-08-01

An adaptive critic design (ACD)-based damping controller is developed for a thyristor-controlled series capacitor (TCSC) installed in a power system with multiple poorly damped interarea modes. The performance of this ACD computational intelligence-based method is compared with two classical techniques, which are observer-based state-feedback (SF) control and linear matrix inequality LMI-H(infinity) robust control. Remote measurements are used as feedback signals to the wide-area damping controller for modulating the compensation of the TCSC. The classical methods use a linearized model of the system whereas the ACD method is purely measurement-based, leading to a nonlinear controller with fixed parameters. A comparative analysis of the controllers' performances is carried out under different disturbance scenarios. The ACD-based design has shown promising performance with very little knowledge of the system compared to classical model-based controllers. This paper also discusses the advantages and disadvantages of ACDs, SF, and LMI-H(infinity).

Influence of a high vacuum on the precise positioning using an ultrasonic linear motor.

PubMed

Kim, Wan-Soo; Lee, Dong-Jin; Lee, Sun-Kyu

2011-01-01

This paper presents an investigation of the ultrasonic linear motor stage for use in a high vacuum environment. The slider table is driven by the hybrid bolt-clamped Langevin-type ultrasonic linear motor, which is excited with its different modes of natural frequencies in both lateral and longitudinal directions. In general, the friction behavior in a vacuum environment becomes different from that in an environment of atmospheric pressure and this difference significantly affects the performance of the ultrasonic linear motor. In this paper, to consistently provide stable and high power of output in a high vacuum, frequency matching was conducted. Moreover, to achieve the fine control performance in the vacuum environment, a modified nominal characteristic trajectory following control method was adopted. Finally, the stage was operated under high vacuum condition, and the operating performances were investigated compared with that of a conventional PI compensator. As a result, robustness of positioning was accomplished in a high vacuum condition with nanometer-level accuracy.

LPV control for the full region operation of a wind turbine integrated with synchronous generator.

PubMed

Cao, Guoyan; Grigoriadis, Karolos M; Nyanteh, Yaw D

2015-01-01

Wind turbine conversion systems require feedback control to achieve reliable wind turbine operation and stable current supply. A robust linear parameter varying (LPV) controller is proposed to reduce the structural loads and improve the power extraction of a horizontal axis wind turbine operating in both the partial load and the full load regions. The LPV model is derived from the wind turbine state space models extracted by FAST (fatigue, aerodynamics, structural, and turbulence) code linearization at different operating points. In order to assure a smooth transition between the two regions, appropriate frequency-dependent varying scaling parametric weighting functions are designed in the LPV control structure. The solution of a set of linear matrix inequalities (LMIs) leads to the LPV controller. A synchronous generator model is connected with the closed LPV control loop for examining the electrical subsystem performance obtained by an inner speed control loop. Simulation results of a 1.5 MW horizontal axis wind turbine model on the FAST platform illustrates the benefit of the LPV control and demonstrates the advantages of this proposed LPV controller, when compared with a traditional gain scheduling PI control and prior LPV control configurations. Enhanced structural load mitigation, improved power extraction, and good current performance were obtained from the proposed LPV control.

LPV Control for the Full Region Operation of a Wind Turbine Integrated with Synchronous Generator

PubMed Central

Grigoriadis, Karolos M.; Nyanteh, Yaw D.

2015-01-01

Wind turbine conversion systems require feedback control to achieve reliable wind turbine operation and stable current supply. A robust linear parameter varying (LPV) controller is proposed to reduce the structural loads and improve the power extraction of a horizontal axis wind turbine operating in both the partial load and the full load regions. The LPV model is derived from the wind turbine state space models extracted by FAST (fatigue, aerodynamics, structural, and turbulence) code linearization at different operating points. In order to assure a smooth transition between the two regions, appropriate frequency-dependent varying scaling parametric weighting functions are designed in the LPV control structure. The solution of a set of linear matrix inequalities (LMIs) leads to the LPV controller. A synchronous generator model is connected with the closed LPV control loop for examining the electrical subsystem performance obtained by an inner speed control loop. Simulation results of a 1.5 MW horizontal axis wind turbine model on the FAST platform illustrates the benefit of the LPV control and demonstrates the advantages of this proposed LPV controller, when compared with a traditional gain scheduling PI control and prior LPV control configurations. Enhanced structural load mitigation, improved power extraction, and good current performance were obtained from the proposed LPV control. PMID:25884036

Tail mean and related robust solution concepts

NASA Astrophysics Data System (ADS)

Ogryczak, Włodzimierz

2014-01-01

Robust optimisation might be viewed as a multicriteria optimisation problem where objectives correspond to the scenarios although their probabilities are unknown or imprecise. The simplest robust solution concept represents a conservative approach focused on the worst-case scenario results optimisation. A softer concept allows one to optimise the tail mean thus combining performances under multiple worst scenarios. We show that while considering robust models allowing the probabilities to vary only within given intervals, the tail mean represents the robust solution for only upper bounded probabilities. For any arbitrary intervals of probabilities the corresponding robust solution may be expressed by the optimisation of appropriately combined mean and tail mean criteria thus remaining easily implementable with auxiliary linear inequalities. Moreover, we use the tail mean concept to develope linear programming implementable robust solution concepts related to risk averse optimisation criteria.

Digital robust control law synthesis using constrained optimization

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivekananda

1989-01-01

Development of digital robust control laws for active control of high performance flexible aircraft and large space structures is a research area of significant practical importance. The flexible system is typically modeled by a large order state space system of equations in order to accurately represent the dynamics. The active control law must satisy multiple conflicting design requirements and maintain certain stability margins, yet should be simple enough to be implementable on an onboard digital computer. Described here is an application of a generic digital control law synthesis procedure for such a system, using optimal control theory and constrained optimization technique. A linear quadratic Gaussian type cost function is minimized by updating the free parameters of the digital control law, while trying to satisfy a set of constraints on the design loads, responses and stability margins. Analytical expressions for the gradients of the cost function and the constraints with respect to the control law design variables are used to facilitate rapid numerical convergence. These gradients can be used for sensitivity study and may be integrated into a simultaneous structure and control optimization scheme.

Full quaternion based finite-time cascade attitude control approach via pulse modulation synthesis for a spacecraft.

PubMed

Mazinan, A H; Pasand, M; Soltani, B

2015-09-01

In the aspect of further development of investigations in the area of spacecraft modeling and analysis of the control scheme, a new hybrid finite-time robust three-axis cascade attitude control approach is proposed via pulse modulation synthesis. The full quaternion based control approach proposed here is organized in association with both the inner and the outer closed loops. It is shown that the inner closed loop, which consists of the sliding mode finite-time control approach, the pulse width pulse frequency modulator, the control allocation and finally the dynamics of the spacecraft is realized to track the three-axis referenced commands of the angular velocities. The pulse width pulse frequency modulators are in fact employed in the inner closed loop to accommodate the control signals to a number of on-off thrusters, while the control allocation algorithm provides the commanded firing times for the reaction control thrusters in the overactuated spacecraft. Hereinafter, the outer closed loop, which consists of the proportional linear control approach and the kinematics of the spacecraft is correspondingly designed to deal with the attitude angles that are presented by quaternion vector. It should be noted that the main motivation of the present research is to realize a hybrid control method by using linear and nonlinear terms and to provide a reliable and robust control structure, which is able to track time varying three-axis referenced commands. Subsequently, a stability analysis is presented to verify the performance of the overall proposed cascade attitude control approach. To prove the effectiveness of the presented approach, a thorough investigation is presented compared to a number of recent corresponding benchmarks. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

NASA Astrophysics Data System (ADS)

Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

2018-04-01

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

On the Numerical Formulation of Parametric Linear Fractional Transformation (LFT) Uncertainty Models for Multivariate Matrix Polynomial Problems

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.

1998-01-01

Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form.

Robust model reference adaptive output feedback tracking for uncertain linear systems with actuator fault based on reinforced dead-zone modification.

PubMed

Bagherpoor, H M; Salmasi, Farzad R

2015-07-01

In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Wind Turbine Load Mitigation based on Multivariable Robust Control and Blade Root Sensors

NASA Astrophysics Data System (ADS)

Díaz de Corcuera, A.; Pujana-Arrese, A.; Ezquerra, J. M.; Segurola, E.; Landaluze, J.

2014-12-01

This paper presents two H∞ multivariable robust controllers based on blade root sensors' information for individual pitch angle control. The wind turbine of 5 MW defined in the Upwind European project is the reference non-linear model used in this research work, which has been modelled in the GH Bladed 4.0 software package. The main objective of these controllers is load mitigation in different components of wind turbines during power production in the above rated control zone. The first proposed multi-input multi-output (MIMO) individual pitch H" controller mitigates the wind effect on the tower side-to-side acceleration and reduces the asymmetrical loads which appear in the rotor due to its misalignment. The second individual pitch H" multivariable controller mitigates the loads on the three blades reducing the wind effect on the bending flapwise and edgewise momentums in the blades. The designed H" controllers have been validated in GH Bladed and an exhaustive analysis has been carried out to calculate fatigue load reduction on wind turbine components, as well as to analyze load mitigation in some extreme cases.

Robust PI and PID design for first- and second-order processes with zeros, time-delay and structured uncertainties

NASA Astrophysics Data System (ADS)

Parada, M.; Sbarbaro, D.; Borges, R. A.; Peres, P. L. D.

2017-01-01

The use of robust design techniques such as the one based on ? and ? for tuning proportional integral (PI) and proportional integral derivative (PID) controllers have been limited to address a small set of processes. This work addresses the problem by considering a wide set of possible plants, both first- and second-order continuous-time systems with time delays and zeros, leading to PI and PID controllers. The use of structured uncertainties to handle neglected dynamics allows to expand the range of processes to be considered. The proposed approach takes into account the robustness of the controller with respect to these structured uncertainties by using the small-gain theorem. In addition, improved performance is sought through the minimisation of an upper bound to the closed-loop system ? norm. A Lyapunov-Krasovskii-type functional is used to obtain delay-dependent design conditions. The controller design is accomplished by means of a convex optimisation procedure formulated using linear matrix inequalities. In order to illustrate the flexibility of the approach, several examples considering recycle compensation, reduced-order controller design and a practical implementation are addressed. Numerical experiments are provided in each case to highlight the main characteristics of the proposed design method.

Deterministic implementations of single-photon multi-qubit Deutsch-Jozsa algorithms with linear optics

NASA Astrophysics Data System (ADS)

Wei, Hai-Rui; Liu, Ji-Zhen

2017-02-01

It is very important to seek an efficient and robust quantum algorithm demanding less quantum resources. We propose one-photon three-qubit original and refined Deutsch-Jozsa algorithms with polarization and two linear momentums degrees of freedom (DOFs). Our schemes are constructed by solely using linear optics. Compared to the traditional ones with one DOF, our schemes are more economic and robust because the necessary photons are reduced from three to one. Our linear-optic schemes are working in a determinate way, and they are feasible with current experimental technology.

Deterministic implementations of single-photon multi-qubit Deutsch–Jozsa algorithms with linear optics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Hai-Rui, E-mail: hrwei@ustb.edu.cn; Liu, Ji-Zhen

2017-02-15

It is very important to seek an efficient and robust quantum algorithm demanding less quantum resources. We propose one-photon three-qubit original and refined Deutsch–Jozsa algorithms with polarization and two linear momentums degrees of freedom (DOFs). Our schemes are constructed by solely using linear optics. Compared to the traditional ones with one DOF, our schemes are more economic and robust because the necessary photons are reduced from three to one. Our linear-optic schemes are working in a determinate way, and they are feasible with current experimental technology.

Virtual Constraint Control of a Powered Prosthetic Leg: From Simulation to Experiments with Transfemoral Amputees.

PubMed

Gregg, Robert D; Lenzi, Tommaso; Hargrove, Levi J; Sensinger, Jonathon W

2014-12-01

Recent powered (or robotic) prosthetic legs independently control different joints and time periods of the gait cycle, resulting in control parameters and switching rules that can be difficult to tune by clinicians. This challenge might be addressed by a unifying control model used by recent bipedal robots, in which virtual constraints define joint patterns as functions of a monotonic variable that continuously represents the gait cycle phase. In the first application of virtual constraints to amputee locomotion, this paper derives exact and approximate control laws for a partial feedback linearization to enforce virtual constraints on a prosthetic leg. We then encode a human-inspired invariance property called effective shape into virtual constraints for the stance period. After simulating the robustness of the partial feedback linearization to clinically meaningful conditions, we experimentally implement this control strategy on a powered transfemoral leg. We report the results of three amputee subjects walking overground and at variable cadences on a treadmill, demonstrating the clinical viability of this novel control approach.

Virtual Constraint Control of a Powered Prosthetic Leg: From Simulation to Experiments with Transfemoral Amputees

PubMed Central

Lenzi, Tommaso; Hargrove, Levi J.; Sensinger, Jonathon W.

2014-01-01

Recent powered (or robotic) prosthetic legs independently control different joints and time periods of the gait cycle, resulting in control parameters and switching rules that can be difficult to tune by clinicians. This challenge might be addressed by a unifying control model used by recent bipedal robots, in which virtual constraints define joint patterns as functions of a monotonic variable that continuously represents the gait cycle phase. In the first application of virtual constraints to amputee locomotion, this paper derives exact and approximate control laws for a partial feedback linearization to enforce virtual constraints on a prosthetic leg. We then encode a human-inspired invariance property called effective shape into virtual constraints for the stance period. After simulating the robustness of the partial feedback linearization to clinically meaningful conditions, we experimentally implement this control strategy on a powered transfemoral leg. We report the results of three amputee subjects walking overground and at variable cadences on a treadmill, demonstrating the clinical viability of this novel control approach. PMID:25558185

Active disturbance rejection controller for chemical reactor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Both, Roxana; Dulf, Eva H.; Muresan, Cristina I., E-mail: roxana.both@aut.utcluj.ro

2015-03-10

In the petrochemical industry, the synthesis of 2 ethyl-hexanol-oxo-alcohols (plasticizers alcohol) is of high importance, being achieved through hydrogenation of 2 ethyl-hexenal inside catalytic trickle bed three-phase reactors. For this type of processes the use of advanced control strategies is suitable due to their nonlinear behavior and extreme sensitivity to load changes and other disturbances. Due to the complexity of the mathematical model an approach was to use a simple linear model of the process in combination with an advanced control algorithm which takes into account the model uncertainties, the disturbances and command signal limitations like robust control. However themore » resulting controller is complex, involving cost effective hardware. This paper proposes a simple integer-order control scheme using a linear model of the process, based on active disturbance rejection method. By treating the model dynamics as a common disturbance and actively rejecting it, active disturbance rejection control (ADRC) can achieve the desired response. Simulation results are provided to demonstrate the effectiveness of the proposed method.« less

Fast and robust control of nanopositioning systems: Performance limits enabled by field programmable analog arrays.

PubMed

Baranwal, Mayank; Gorugantu, Ram S; Salapaka, Srinivasa M

2015-08-01

This paper aims at control design and its implementation for robust high-bandwidth precision (nanoscale) positioning systems. Even though modern model-based control theoretic designs for robust broadband high-resolution positioning have enabled orders of magnitude improvement in performance over existing model independent designs, their scope is severely limited by the inefficacies of digital implementation of the control designs. High-order control laws that result from model-based designs typically have to be approximated with reduced-order systems to facilitate digital implementation. Digital systems, even those that have very high sampling frequencies, provide low effective control bandwidth when implementing high-order systems. In this context, field programmable analog arrays (FPAAs) provide a good alternative to the use of digital-logic based processors since they enable very high implementation speeds, moreover with cheaper resources. The superior flexibility of digital systems in terms of the implementable mathematical and logical functions does not give significant edge over FPAAs when implementing linear dynamic control laws. In this paper, we pose the control design objectives for positioning systems in different configurations as optimal control problems and demonstrate significant improvements in performance when the resulting control laws are applied using FPAAs as opposed to their digital counterparts. An improvement of over 200% in positioning bandwidth is achieved over an earlier digital signal processor (DSP) based implementation for the same system and same control design, even when for the DSP-based system, the sampling frequency is about 100 times the desired positioning bandwidth.

A Convex Approach to Fault Tolerant Control

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Cox, David E.; Bauer, Frank (Technical Monitor)

2002-01-01

The design of control laws for dynamic systems with the potential for actuator failures is considered in this work. The use of Linear Matrix Inequalities allows more freedom in controller design criteria than typically available with robust control. This work proposes an extension of fault-scheduled control design techniques that can find a fixed controller with provable performance over a set of plants. Through convexity of the objective function, performance bounds on this set of plants implies performance bounds on a range of systems defined by a convex hull. This is used to incorporate performance bounds for a variety of soft and hard failures into the control design problem.

Phase and speed synchronization control of four eccentric rotors driven by induction motors in a linear vibratory feeder with unknown time-varying load torques using adaptive sliding mode control algorithm

NASA Astrophysics Data System (ADS)

Kong, Xiangxi; Zhang, Xueliang; Chen, Xiaozhe; Wen, Bangchun; Wang, Bo

2016-05-01

In this paper, phase and speed synchronization control of four eccentric rotors (ERs) driven by induction motors in a linear vibratory feeder with unknown time-varying load torques is studied. Firstly, the electromechanical coupling model of the linear vibratory feeder is established by associating induction motor's model with the dynamic model of the system, which is a typical under actuated model. According to the characteristics of the linear vibratory feeder, the complex control problem of the under actuated electromechanical coupling model converts to phase and speed synchronization control of four ERs. In order to keep the four ERs operating synchronously with zero phase differences, phase and speed synchronization controllers are designed by employing adaptive sliding mode control (ASMC) algorithm via a modified master-slave structure. The stability of the controllers is proved by Lyapunov stability theorem. The proposed controllers are verified by simulation via Matlab/Simulink program and compared with the conventional sliding mode control (SMC) algorithm. The results show the proposed controllers can reject the time-varying load torques effectively and four ERs can operate synchronously with zero phase differences. Moreover, the control performance is better than the conventional SMC algorithm and the chattering phenomenon is attenuated. Furthermore, the effects of reference speed and parametric perturbations are discussed to show the strong robustness of the proposed controllers. Finally, experiments on a simple vibratory test bench are operated by using the proposed controllers and without control, respectively, to validate the effectiveness of the proposed controllers further.

Soft x-ray spectromicroscopy using compact scanning transmission x-ray microscope at the photon factory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Takeichi, Yasuo, E-mail: yasuo.takeichi@kek.jp; Inami, Nobuhito; Ono, Kanta

We report the stability and recent performances of a new type of scanning transmission X-ray microscopy. The optics and compact design of the microscope realized mobility and robust performance. Detailed consideration to the vibration control will be described. The insertion device upgraded to elliptical polarization undulator enabled linear dichroism and circular dichroism experiments.

Fractional order fuzzy control of hybrid power system with renewable generation using chaotic PSO.

PubMed

Pan, Indranil; Das, Saptarshi

2016-05-01

This paper investigates the operation of a hybrid power system through a novel fuzzy control scheme. The hybrid power system employs various autonomous generation systems like wind turbine, solar photovoltaic, diesel engine, fuel-cell, aqua electrolyzer etc. Other energy storage devices like the battery, flywheel and ultra-capacitor are also present in the network. A novel fractional order (FO) fuzzy control scheme is employed and its parameters are tuned with a particle swarm optimization (PSO) algorithm augmented with two chaotic maps for achieving an improved performance. This FO fuzzy controller shows better performance over the classical PID, and the integer order fuzzy PID controller in both linear and nonlinear operating regimes. The FO fuzzy controller also shows stronger robustness properties against system parameter variation and rate constraint nonlinearity, than that with the other controller structures. The robustness is a highly desirable property in such a scenario since many components of the hybrid power system may be switched on/off or may run at lower/higher power output, at different time instants. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Sliding mode control of electromagnetic tethered satellite formation

NASA Astrophysics Data System (ADS)

Hallaj, Mohammad Amin Alandi; Assadian, Nima

2016-08-01

This paper investigates the control of tethered satellite formation actuated by electromagnetic dipoles and reaction wheels using the robust sliding mode control technique. Generating electromagnetic forces and moments by electric current coils provides an attractive control actuation alternative for tethered satellite system due to the advantages of no propellant consumption and no obligatory rotational motion. Based on a dumbbell model of tethered satellite in which the flexibility and mass of the tether is neglected, the equations of motion in Cartesian coordinate are derived. In this model, the J2 perturbation is taken into account. The far-field and mid-field models of electromagnetic forces and moments of two satellites on each other and the effect of the Earth's magnetic field are presented. A robust sliding mode controller is designed for precise trajectory tracking purposes and to deal with the electromagnetic force and moment uncertainties and external disturbances due to the Earth's gravitational and magnetic fields inaccuracy. Numerical simulation results are presented to validate the effectiveness of the developed controller and its superiority over the linear controller.

Robustness Analysis of Integrated LPV-FDI Filters and LTI-FTC System for a Transport Aircraft

NASA Technical Reports Server (NTRS)

Khong, Thuan H.; Shin, Jong-Yeob

2007-01-01

This paper proposes an analysis framework for robustness analysis of a nonlinear dynamics system that can be represented by a polynomial linear parameter varying (PLPV) system with constant bounded uncertainty. The proposed analysis framework contains three key tools: 1) a function substitution method which can convert a nonlinear system in polynomial form into a PLPV system, 2) a matrix-based linear fractional transformation (LFT) modeling approach, which can convert a PLPV system into an LFT system with the delta block that includes key uncertainty and scheduling parameters, 3) micro-analysis, which is a well known robust analysis tool for linear systems. The proposed analysis framework is applied to evaluating the performance of the LPV-fault detection and isolation (FDI) filters of the closed-loop system of a transport aircraft in the presence of unmodeled actuator dynamics and sensor gain uncertainty. The robustness analysis results are compared with nonlinear time simulations.

Robust linear discriminant analysis with distance based estimators

NASA Astrophysics Data System (ADS)

Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Ali, Hazlina

2017-11-01

Linear discriminant analysis (LDA) is one of the supervised classification techniques concerning relationship between a categorical variable and a set of continuous variables. The main objective of LDA is to create a function to distinguish between populations and allocating future observations to previously defined populations. Under the assumptions of normality and homoscedasticity, the LDA yields optimal linear discriminant rule (LDR) between two or more groups. However, the optimality of LDA highly relies on the sample mean and pooled sample covariance matrix which are known to be sensitive to outliers. To alleviate these conflicts, a new robust LDA using distance based estimators known as minimum variance vector (MVV) has been proposed in this study. The MVV estimators were used to substitute the classical sample mean and classical sample covariance to form a robust linear discriminant rule (RLDR). Simulation and real data study were conducted to examine on the performance of the proposed RLDR measured in terms of misclassification error rates. The computational result showed that the proposed RLDR is better than the classical LDR and was comparable with the existing robust LDR.

A fuzzy call admission control scheme in wireless networks

NASA Astrophysics Data System (ADS)

Ma, Yufeng; Gong, Shenguang; Hu, Xiulin; Zhang, Yunyu

2007-11-01

Scarcity of the spectrum resource and mobility of users make quality of service (QoS) provision a critical issue in wireless networks. This paper presents a fuzzy call admission control scheme to meet the requirement of the QoS. A performance measure is formed as a weighted linear function of new call and handoff call blocking probabilities. Simulation compares the proposed fuzzy scheme with an adaptive channel reservation scheme. Simulation results show that fuzzy scheme has a better robust performance in terms of average blocking criterion.

Turbofan engine control system design using the LQG/LTR methodology

NASA Technical Reports Server (NTRS)

Garg, Sanjay

1989-01-01

Application of the linear-quadratic-Gaussian with loop-transfer-recovery methodology to design of a control system for a simplified turbofan engine model is considered. The importance of properly scaling the plant to achieve the desired target feedback loop is emphasized. The steps involved in the application of the methodology are discussed via an example, and evaluation results are presented for a reduced-order compensator. The effect of scaling the plant on the stability robustness evaluation of the closed-loop system is studied in detail.

Turbofan engine control system design using the LQG/LTR methodology

NASA Technical Reports Server (NTRS)

Garg, Sanjay

1989-01-01

Application of the Linear-Quadratic-Gaussian with Loop-Transfer-Recovery methodology to design of a control system for a simplified turbofan engine model is considered. The importance of properly scaling the plant to achieve the desired Target-Feedback-Loop is emphasized. The steps involved in the application of the methodology are discussed via an example, and evaluation results are presented for a reduced-order compensator. The effect of scaling the plant on the stability robustness evaluation of the closed-loop system is studied in detail.

Unified control/structure design and modeling research

NASA Technical Reports Server (NTRS)

Mingori, D. L.; Gibson, J. S.; Blelloch, P. A.; Adamian, A.

1986-01-01

To demonstrate the applicability of the control theory for distributed systems to large flexible space structures, research was focused on a model of a space antenna which consists of a rigid hub, flexible ribs, and a mesh reflecting surface. The space antenna model used is discussed along with the finite element approximation of the distributed model. The basic control problem is to design an optimal or near-optimal compensator to suppress the linear vibrations and rigid-body displacements of the structure. The application of an infinite dimensional Linear Quadratic Gaussian (LQG) control theory to flexible structure is discussed. Two basic approaches for robustness enhancement were investigated: loop transfer recovery and sensitivity optimization. A third approach synthesized from elements of these two basic approaches is currently under development. The control driven finite element approximation of flexible structures is discussed. Three sets of finite element basic vectors for computing functional control gains are compared. The possibility of constructing a finite element scheme to approximate the infinite dimensional Hamiltonian system directly, instead of indirectly is discussed.

A robust optimization methodology for preliminary aircraft design

NASA Astrophysics Data System (ADS)

Prigent, S.; Maréchal, P.; Rondepierre, A.; Druot, T.; Belleville, M.

2016-05-01

This article focuses on a robust optimization of an aircraft preliminary design under operational constraints. According to engineers' know-how, the aircraft preliminary design problem can be modelled as an uncertain optimization problem whose objective (the cost or the fuel consumption) is almost affine, and whose constraints are convex. It is shown that this uncertain optimization problem can be approximated in a conservative manner by an uncertain linear optimization program, which enables the use of the techniques of robust linear programming of Ben-Tal, El Ghaoui, and Nemirovski [Robust Optimization, Princeton University Press, 2009]. This methodology is then applied to two real cases of aircraft design and numerical results are presented.

Doubly robust estimation of generalized partial linear models for longitudinal data with dropouts.

PubMed

Lin, Huiming; Fu, Bo; Qin, Guoyou; Zhu, Zhongyi

2017-12-01

We develop a doubly robust estimation of generalized partial linear models for longitudinal data with dropouts. Our method extends the highly efficient aggregate unbiased estimating function approach proposed in Qu et al. (2010) to a doubly robust one in the sense that under missing at random (MAR), our estimator is consistent when either the linear conditional mean condition is satisfied or a model for the dropout process is correctly specified. We begin with a generalized linear model for the marginal mean, and then move forward to a generalized partial linear model, allowing for nonparametric covariate effect by using the regression spline smoothing approximation. We establish the asymptotic theory for the proposed method and use simulation studies to compare its finite sample performance with that of Qu's method, the complete-case generalized estimating equation (GEE) and the inverse-probability weighted GEE. The proposed method is finally illustrated using data from a longitudinal cohort study. © 2017, The International Biometric Society.

Architecture and robustness tradeoffs in speed-scaled queues with application to energy management

NASA Astrophysics Data System (ADS)

Dinh, Tuan V.; Andrew, Lachlan L. H.; Nazarathy, Yoni

2014-08-01

We consider single-pass, lossless, queueing systems at steady-state subject to Poisson job arrivals at an unknown rate. Service rates are allowed to depend on the number of jobs in the system, up to a fixed maximum, and power consumption is an increasing function of speed. The goal is to control the state dependent service rates such that both energy consumption and delay are kept low. We consider a linear combination of the mean job delay and energy consumption as the performance measure. We examine both the 'architecture' of the system, which we define as a specification of the number of speeds that the system can choose from, and the 'design' of the system, which we define as the actual speeds available. Previous work has illustrated that when the arrival rate is precisely known, there is little benefit in introducing complex (multi-speed) architectures, yet in view of parameter uncertainty, allowing a variable number of speeds improves robustness. We quantify the tradeoffs of architecture specification with respect to robustness, analysing both global robustness and a newly defined measure which we call local robustness.

Adaptive nonlinear robust relative pose control of spacecraft autonomous rendezvous and proximity operations.

PubMed

Sun, Liang; Huo, Wei; Jiao, Zongxia

2017-03-01

This paper studies relative pose control for a rigid spacecraft with parametric uncertainties approaching to an unknown tumbling target in disturbed space environment. State feedback controllers for relative translation and relative rotation are designed in an adaptive nonlinear robust control framework. The element-wise and norm-wise adaptive laws are utilized to compensate the parametric uncertainties of chaser and target spacecraft, respectively. External disturbances acting on two spacecraft are treated as a lumped and bounded perturbation input for system. To achieve the prescribed disturbance attenuation performance index, feedback gains of controllers are designed by solving linear matrix inequality problems so that lumped disturbance attenuation with respect to the controlled output is ensured in the L 2 -gain sense. Moreover, in the absence of lumped disturbance input, asymptotical convergence of relative pose are proved by using the Lyapunov method. Numerical simulations are performed to show that position tracking and attitude synchronization are accomplished in spite of the presence of couplings and uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Review of LFTs, LMIs, and mu. [Linear Fractional Transformations, Linear Matrix Inequalities

NASA Technical Reports Server (NTRS)

Doyle, John; Packard, Andy; Zhou, Kemin

1991-01-01

The authors present a tutorial overview of linear fractional transformations (LFTs) and the role of the structured singular value, mu, and linear matrix inequalities (LMIs) in solving LFT problems. The authors first introduce the notation for LFTs and briefly discuss some of their properties. They then describe mu and its connections with LFTs. They focus on two standard notions of robust stability and performance, mu stability and performance and Q stability and performance, and their relationship is discussed. Comparisons with the L1 theory of robust performance with structured uncertainty are considered.

A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: II. Probabilistic Guarantees on Constraint Satisfaction

PubMed Central

Li, Zukui; Floudas, Christodoulos A.

2012-01-01

Probabilistic guarantees on constraint satisfaction for robust counterpart optimization are studied in this paper. The robust counterpart optimization formulations studied are derived from box, ellipsoidal, polyhedral, “interval+ellipsoidal” and “interval+polyhedral” uncertainty sets (Li, Z., Ding, R., and Floudas, C.A., A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear and Robust Mixed Integer Linear Optimization, Ind. Eng. Chem. Res, 2011, 50, 10567). For those robust counterpart optimization formulations, their corresponding probability bounds on constraint satisfaction are derived for different types of uncertainty characteristic (i.e., bounded or unbounded uncertainty, with or without detailed probability distribution information). The findings of this work extend the results in the literature and provide greater flexibility for robust optimization practitioners in choosing tighter probability bounds so as to find less conservative robust solutions. Extensive numerical studies are performed to compare the tightness of the different probability bounds and the conservatism of different robust counterpart optimization formulations. Guiding rules for the selection of robust counterpart optimization models and for the determination of the size of the uncertainty set are discussed. Applications in production planning and process scheduling problems are presented. PMID:23329868

Robust decentralised stabilisation of uncertain large-scale interconnected nonlinear descriptor systems via proportional plus derivative feedback

NASA Astrophysics Data System (ADS)

Li, Jian; Zhang, Qingling; Ren, Junchao; Zhang, Yanhao

2017-10-01

This paper studies the problem of robust stability and stabilisation for uncertain large-scale interconnected nonlinear descriptor systems via proportional plus derivative state feedback or proportional plus derivative output feedback. The basic idea of this work is to use the well-known differential mean value theorem to deal with the nonlinear model such that the considered nonlinear descriptor systems can be transformed into linear parameter varying systems. By using a parameter-dependent Lyapunov function, a decentralised proportional plus derivative state feedback controller and decentralised proportional plus derivative output feedback controller are designed, respectively such that the closed-loop system is quadratically normal and quadratically stable. Finally, a hypersonic vehicle practical simulation example and numerical example are given to illustrate the effectiveness of the results obtained in this paper.

Attitude and vibration control of a large flexible space-based antenna

NASA Technical Reports Server (NTRS)

Joshi, S. M.

1982-01-01

Control systems synthesis is considered for controlling the rigid body attitude and elastic motion of a large deployable space-based antenna. Two methods for control systems synthesis are considered. The first method utilizes the stability and robustness properties of the controller consisting of torque actuators and collocated attitude and rate sensors. The second method is based on the linear-quadratic-Gaussian control theory. A combination of the two methods, which results in a two level hierarchical control system, is also briefly discussed. The performance of the controllers is analyzed by computing the variances of pointing errors, feed misalignment errors and surface contour errors in the presence of sensor and actuator noise.

Using spatial information about recurrence risk for robust optimization of dose-painting prescription functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bender, Edward T.

Purpose: To develop a robust method for deriving dose-painting prescription functions using spatial information about the risk for disease recurrence. Methods: Spatial distributions of radiobiological model parameters are derived from distributions of recurrence risk after uniform irradiation. These model parameters are then used to derive optimal dose-painting prescription functions given a constant mean biologically effective dose. Results: An estimate for the optimal dose distribution can be derived based on spatial information about recurrence risk. Dose painting based on imaging markers that are moderately or poorly correlated with recurrence risk are predicted to potentially result in inferior disease control when comparedmore » the same mean biologically effective dose delivered uniformly. A robust optimization approach may partially mitigate this issue. Conclusions: The methods described here can be used to derive an estimate for a robust, patient-specific prescription function for use in dose painting. Two approximate scaling relationships were observed: First, the optimal choice for the maximum dose differential when using either a linear or two-compartment prescription function is proportional to R, where R is the Pearson correlation coefficient between a given imaging marker and recurrence risk after uniform irradiation. Second, the predicted maximum possible gain in tumor control probability for any robust optimization technique is nearly proportional to the square of R.« less

Design of robust iterative learning control schemes for systems with polytopic uncertainties and sector-bounded nonlinearities

NASA Astrophysics Data System (ADS)

Boski, Marcin; Paszke, Wojciech

2017-01-01

This paper deals with designing of iterative learning control schemes for uncertain systems with static nonlinearities. More specifically, the nonlinear part is supposed to be sector bounded and system matrices are assumed to range in the polytope of matrices. For systems with such nonlinearities and uncertainties the repetitive process setting is exploited to develop a linear matrix inequality based conditions for computing the feedback and feedforward (learning) controllers. These controllers guarantee acceptable dynamics along the trials and ensure convergence of the trial-to-trial error dynamics, respectively. Numerical examples illustrate the theoretical results and confirm effectiveness of the designed control scheme.

Explicit asymmetric bounds for robust stability of continuous and discrete-time systems

NASA Technical Reports Server (NTRS)

Gao, Zhiqiang; Antsaklis, Panos J.

1993-01-01

The problem of robust stability in linear systems with parametric uncertainties is considered. Explicit stability bounds on uncertain parameters are derived and expressed in terms of linear inequalities for continuous systems, and inequalities with quadratic terms for discrete-times systems. Cases where system parameters are nonlinear functions of an uncertainty are also examined.

Localized modelling and feedback control of linear instabilities in 2-D wall bounded shear flows

NASA Astrophysics Data System (ADS)

Tol, Henry; Kotsonis, Marios; de Visser, Coen

2016-11-01

A new approach is presented for control of instabilities in 2-D wall bounded shear flows described by the linearized Navier-Stokes equations (LNSE). The control design accounts both for spatially localized actuators/sensors and the dominant perturbation dynamics in an optimal control framework. An inflow disturbance model is proposed for streamwise instabilities that drive laminar-turbulent transition. The perturbation modes that contribute to the transition process can be selected and are included in the control design. A reduced order model is derived from the LNSE that captures the input-output behavior and the dominant perturbation dynamics. This model is used to design an optimal controller for suppressing the instability growth. A 2-D channel flow and a 2-D boundary layer flow over a flat plate are considered as application cases. Disturbances are generated upstream of the control domain and the resulting flow perturbations are estimated/controlled using wall shear measurements and localized unsteady blowing and suction at the wall. It will be shown that the controller is able to cancel the perturbations and is robust to unmodelled disturbances.

Digital control of magnetic bearings in a cryogenic cooler

NASA Technical Reports Server (NTRS)

Feeley, J.; Law, A.; Lind, F.

1990-01-01

This paper describes the design of a digital control system for control of magnetic bearings used in a spaceborne cryogenic cooler. The cooler was developed by Philips Laboratories for the NASA Goddard Space Flight Center. Six magnetic bearing assemblies are used to levitate the piston, displacer, and counter-balance of the cooler. The piston and displacer are driven by linear motors in accordance with Stirling cycle thermodynamic principles to produce the desired cooling effect. The counter-balance is driven by a third linear motor to cancel motion induced forces that would otherwise be transmitted to the spacecraft. An analog control system is currently used for bearing control. The purpose of this project is to investigate the possibilities for improved performance using digital control. Areas for potential improvement include transient and steady state control characteristics, robustness, reliability, adaptability, alternate control modes, size, weight, and cost. The present control system is targeted for the Intel 80196 microcontroller family. The eventual introduction of application specific integrated circuit (ASIC) technology to this problem may produce a unique and elegant solution both here and in related industrial problems.

A method to stabilize linear systems using eigenvalue gradient information

NASA Technical Reports Server (NTRS)

Wieseman, C. D.

1985-01-01

Formal optimization methods and eigenvalue gradient information are used to develop a stabilizing control law for a closed loop linear system that is initially unstable. The method was originally formulated by using direct, constrained optimization methods with the constraints being the real parts of the eigenvalues. However, because of problems in trying to achieve stabilizing control laws, the problem was reformulated to be solved differently. The method described uses the Davidon-Fletcher-Powell minimization technique to solve an indirect, constrained minimization problem in which the performance index is the Kreisselmeier-Steinhauser function of the real parts of all the eigenvalues. The method is applied successfully to solve two different problems: the determination of a fourth-order control law stabilizes a single-input single-output active flutter suppression system and the determination of a second-order control law for a multi-input multi-output lateral-directional flight control system. Various sets of design variables and initial starting points were chosen to show the robustness of the method.

Robust Computation of Linear Models, or How to Find a Needle in a Haystack

DTIC Science & Technology

2012-02-17

robustly, project it onto a sphere, and then apply standard PCA. This approach is due to [LMS+99]. Maronna et al . [MMY06] recommend it as a preferred...of this form is due to Chandrasekaran et al . [CSPW11]. Given an observed matrix X, they propose to solve the semidefinite problem minimize ‖P ‖S1 + γ...regularization parameter γ negotiates a tradeoff between the two goals. Candès et al . [CLMW11] study the performance of (2.1) for robust linear

Design of Distributed Engine Control Systems with Uncertain Delay.

PubMed

Liu, Xiaofeng; Li, Yanxi; Sun, Xu

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method.

Design of Distributed Engine Control Systems with Uncertain Delay

PubMed Central

Li, Yanxi; Sun, Xu

2016-01-01

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method. PMID:27669005

Model-Based Battery Management Systems: From Theory to Practice

NASA Astrophysics Data System (ADS)

Pathak, Manan

Lithium-ion batteries are now extensively being used as the primary storage source. Capacity and power fade, and slow recharging times are key issues that restrict its use in many applications. Battery management systems are critical to address these issues, along with ensuring its safety. This dissertation focuses on exploring various control strategies using detailed physics-based electrochemical models developed previously for lithium-ion batteries, which could be used in advanced battery management systems. Optimal charging profiles for minimizing capacity fade based on SEI-layer formation are derived and the benefits of using such control strategies are shown by experimentally testing them on a 16 Ah NMC-based pouch cell. This dissertation also explores different time-discretization strategies for non-linear models, which gives an improved order of convergence for optimal control problems. Lastly, this dissertation also explores a physics-based model for predicting the linear impedance of a battery, and develops a freeware that is extremely robust and computationally fast. Such a code could be used for estimating transport, kinetic and material properties of the battery based on the linear impedance spectra.

Method validation for control determination of mercury in fresh fish and shrimp samples by solid sampling thermal decomposition/amalgamation atomic absorption spectrometry.

PubMed

Torres, Daiane Placido; Martins-Teixeira, Maristela Braga; Cadore, Solange; Queiroz, Helena Müller

2015-01-01

A method for the determination of total mercury in fresh fish and shrimp samples by solid sampling thermal decomposition/amalgamation atomic absorption spectrometry (TDA AAS) has been validated following international foodstuff protocols in order to fulfill the Brazilian National Residue Control Plan. The experimental parameters have been previously studied and optimized according to specific legislation on validation and inorganic contaminants in foodstuff. Linearity, sensitivity, specificity, detection and quantification limits, precision (repeatability and within-laboratory reproducibility), robustness as well as accuracy of the method have been evaluated. Linearity of response was satisfactory for the two range concentrations available on the TDA AAS equipment, between approximately 25.0 and 200.0 μg kg(-1) (square regression) and 250.0 and 2000.0 μg kg(-1) (linear regression) of mercury. The residues for both ranges were homoscedastic and independent, with normal distribution. Correlation coefficients obtained for these ranges were higher than 0.995. Limits of quantification (LOQ) and of detection of the method (LDM), based on signal standard deviation (SD) for a low-in-mercury sample, were 3.0 and 1.0 μg kg(-1), respectively. Repeatability of the method was better than 4%. Within-laboratory reproducibility achieved a relative SD better than 6%. Robustness of the current method was evaluated and pointed sample mass as a significant factor. Accuracy (assessed as the analyte recovery) was calculated on basis of the repeatability, and ranged from 89% to 99%. The obtained results showed the suitability of the present method for direct mercury measurement in fresh fish and shrimp samples and the importance of monitoring the analysis conditions for food control purposes. Additionally, the competence of this method was recognized by accreditation under the standard ISO/IEC 17025.

Supervised linear dimensionality reduction with robust margins for object recognition

NASA Astrophysics Data System (ADS)

Dornaika, F.; Assoum, A.

2013-01-01

Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.

Digital robust active control law synthesis for large order flexible structure using parameter optimization

NASA Technical Reports Server (NTRS)

Mukhopadhyay, V.

1988-01-01

A generic procedure for the parameter optimization of a digital control law for a large-order flexible flight vehicle or large space structure modeled as a sampled data system is presented. A linear quadratic Guassian type cost function was minimized, while satisfying a set of constraints on the steady-state rms values of selected design responses, using a constrained optimization technique to meet multiple design requirements. Analytical expressions for the gradients of the cost function and the design constraints on mean square responses with respect to the control law design variables are presented.

Analysis and design of a 3rd order velocity-controlled closed-loop for MEMS vibratory gyroscopes.

PubMed

Wu, Huan-ming; Yang, Hai-gang; Yin, Tao; Jiao, Ji-wei

2013-09-18

The time-average method currently available is limited to analyzing the specific performance of the automatic gain control-proportional and integral (AGC-PI) based velocity-controlled closed-loop in a micro-electro-mechanical systems (MEMS) vibratory gyroscope, since it is hard to solve nonlinear functions in the time domain when the control loop reaches to 3rd order. In this paper, we propose a linearization design approach to overcome this limitation by establishing a 3rd order linear model of the control loop and transferring the analysis to the frequency domain. Order reduction is applied on the built linear model's transfer function by constructing a zero-pole doublet, and therefore mathematical expression of each control loop's performance specification is obtained. Then an optimization methodology is summarized, which reveals that a robust, stable and swift control loop can be achieved by carefully selecting the system parameters following a priority order. Closed-loop drive circuits are designed and implemented using 0.35 μm complementary metal oxide semiconductor (CMOS) process, and experiments carried out on a gyroscope prototype verify the optimization methodology that an optimized stability of the control loop can be achieved by constructing the zero-pole doublet, and disturbance rejection capability (D.R.C) of the control loop can be improved by increasing the integral term.

Run-off-road and recovery - state estimation and vehicle control strategies

NASA Astrophysics Data System (ADS)

Freeman, P.; Wagner, J.; Alexander, K.

2016-09-01

Despite many advances in vehicle safety technology, traffic fatalities remain a devastating burden on society. With over two-thirds of all fatal single-vehicle crashes occurring off the roadway, run-off-road (ROR) crashes have become the focus of much roadway safety research. Current countermeasures, including roadway infrastructure modifications and some on-board vehicle safety systems, remain limited in their approach as they do not directly address the critical factor of driver behaviour. It has been shown that ROR crashes are often the result of poor driver performance leading up to the crash. In this study, the performance of two control algorithms, sliding control and linear quadratic control, was investigated for use in an autonomous ROR vehicle recovery system. The two controllers were simulated amongst a variety of ROR conditions where typical driver performance was inadequate to safely operate the vehicle. The sliding controller recovered the fastest within the nominal conditions but exhibited large variability in performance amongst the more extreme ROR scenarios. Despite some small sacrifices in lateral error and yaw rate, the linear quadratic controller demonstrated a higher level of consistency and stability amongst the various conditions examined. Overall, the linear quadratic controller recovered the vehicle 25% faster than the sliding controller while using 70% less steering, which combined with its robust performance, indicates its high potential as an autonomous ROR countermeasure.

Multi-model predictive control based on LMI: from the adaptation of the state-space model to the analytic description of the control law

NASA Astrophysics Data System (ADS)

Falugi, P.; Olaru, S.; Dumur, D.

2010-08-01

This article proposes an explicit robust predictive control solution based on linear matrix inequalities (LMIs). The considered predictive control strategy uses different local descriptions of the system dynamics and uncertainties and thus allows the handling of less conservative input constraints. The computed control law guarantees constraint satisfaction and asymptotic stability. The technique is effective for a class of nonlinear systems embedded into polytopic models. A detailed discussion of the procedures which adapt the partition of the state space is presented. For the practical implementation the construction of suitable (explicit) descriptions of the control law are described upon concrete algorithms.

Ares I Flight Control System Overview

NASA Technical Reports Server (NTRS)

Hall, Charles; Lee, Chong; Jackson, Mark; Whorton, Mark; West, mark; Brandon, Jay; Hall, Rob A.; Jang, Jimmy; Bedrossian, Naz; Compton, Jimmy;

Robust L1-norm two-dimensional linear discriminant analysis.

PubMed

Li, Chun-Na; Shao, Yuan-Hai; Deng, Nai-Yang

2015-05-01

In this paper, we propose an L1-norm two-dimensional linear discriminant analysis (L1-2DLDA) with robust performance. Different from the conventional two-dimensional linear discriminant analysis with L2-norm (L2-2DLDA), where the optimization problem is transferred to a generalized eigenvalue problem, the optimization problem in our L1-2DLDA is solved by a simple justifiable iterative technique, and its convergence is guaranteed. Compared with L2-2DLDA, our L1-2DLDA is more robust to outliers and noises since the L1-norm is used. This is supported by our preliminary experiments on toy example and face datasets, which show the improvement of our L1-2DLDA over L2-2DLDA. Copyright © 2015 Elsevier Ltd. All rights reserved.

A game theoretic controller for a linear time-invariant system with parameter uncertainty and its application to the Space Station

NASA Technical Reports Server (NTRS)

Rhee, Ihnseok; Speyer, Jason L.

1990-01-01

A game theoretic controller is developed for a linear time-invariant system with parameter uncertainties in system and input matrices. The input-output decomposition modeling for the plant uncertainty is adopted. The uncertain dynamic system is represented as an internal feedback loop in which the system is assumed forced by fictitious disturbance caused by the parameter uncertainty. By considering the input and the fictitious disturbance as two noncooperative players, a differential game problem is constructed. It is shown that the resulting time invariant controller stabilizes the uncertain system for a prescribed uncertainty bound. This game theoretic controller is applied to the momentum management and attitude control of the Space Station in the presence of uncertainties in the moments of inertia. Inclusion of the external disturbance torque to the design procedure results in a dynamical feedback controller which consists of conventional PID control and cyclic disturbance rejection filter. It is shown that the game theoretic design, comparing to the LQR design or pole placement design, improves the stability robustness with respect to inertia variations.

Robust preview control for a class of uncertain discrete-time systems with time-varying delay.

PubMed

Li, Li; Liao, Fucheng

2018-02-01

This paper proposes a concept of robust preview tracking control for uncertain discrete-time systems with time-varying delay. Firstly, a model transformation is employed for an uncertain discrete system with time-varying delay. Then, the auxiliary variables related to the system state and input are introduced to derive an augmented error system that includes future information on the reference signal. This leads to the tracking problem being transformed into a regulator problem. Finally, for the augmented error system, a sufficient condition of asymptotic stability is derived and the preview controller design method is proposed based on the scaled small gain theorem and linear matrix inequality (LMI) technique. The method proposed in this paper not only solves the difficulty problem of applying the difference operator to the time-varying matrices but also simplifies the structure of the augmented error system. The numerical simulation example also illustrates the effectiveness of the results presented in the paper. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

FPGA-Based Efficient Hardware/Software Co-Design for Industrial Systems with Consideration of Output Selection

NASA Astrophysics Data System (ADS)

Deliparaschos, Kyriakos M.; Michail, Konstantinos; Zolotas, Argyrios C.; Tzafestas, Spyros G.

2016-05-01

This work presents a field programmable gate array (FPGA)-based embedded software platform coupled with a software-based plant, forming a hardware-in-the-loop (HIL) that is used to validate a systematic sensor selection framework. The systematic sensor selection framework combines multi-objective optimization, linear-quadratic-Gaussian (LQG)-type control, and the nonlinear model of a maglev suspension. A robustness analysis of the closed-loop is followed (prior to implementation) supporting the appropriateness of the solution under parametric variation. The analysis also shows that quantization is robust under different controller gains. While the LQG controller is implemented on an FPGA, the physical process is realized in a high-level system modeling environment. FPGA technology enables rapid evaluation of the algorithms and test designs under realistic scenarios avoiding heavy time penalty associated with hardware description language (HDL) simulators. The HIL technique facilitates significant speed-up in the required execution time when compared to its software-based counterpart model.

Speed synchronization control for integrated automotive motor-transmission powertrain system with random delays

NASA Astrophysics Data System (ADS)

Zhu, Xiaoyuan; Zhang, Hui; Fang, Zongde

2015-12-01

This paper presents a robust speed synchronization controller design for an integrated motor-transmission powertrain system in which the driving motor and multi-gearbox are directly coupled. As the controller area network (CAN) is commonly used in the vehicle powertrain system, the possible network-induced random delays in both feedback and forward channel are considered and modeled by using two Markov chains in the controller design process. For the application perspective, the control law adopted here is a generalized proportional-integral (PI) control. By employing the system-augmentation technique, a delay-free stochastic closed-loop system is obtained and the generalized PI controller design problem is converted to a static output feedback (SOF) controller design problem. Since there are external disturbances involved in the closed-loop system, the energy-to-peak performance is considered to guarantee the robustness of the controller. And the controlled output is chosen as the speed synchronization error. To further improve the transient response of the closed-loop system, the pole placement is also employed in the energy-to-peak performance based speed synchronization control. The mode-dependent control gains are obtained by using an iterative linear matrix inequality (LMI) algorithm. Simulation results show the effectiveness of the proposed control approach.

F-15B Quiet Spike(TradeMark) Aeroservoelastic Flight-Test Data Analysis

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

System identification is utilized in the aerospace community for development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlin ear systems. In this report, we show the application of one such nonlinear system identification technique, structure detection, for the an alysis of Quiet Spike(TradeMark)(Gulfstream Aerospace Corporation, Savannah, Georgia) aeroservoelastic flight-test data. Structure detectio n is concerned with the selection of a subset of candidate terms that best describe the observed output. Structure computation as a tool fo r black-box modeling may be of critical importance for the development of robust, parsimonious models for the flight-test community. The ob jectives of this study are to demonstrate via analysis of Quiet Spike(TradeMark) aeroservoelastic flight-test data for several flight conditions that: linear models are inefficient for modelling aeroservoelast ic data, nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data an d the model structure and parameters vary as the flight condition is altered.

Robust extraction of basis functions for simultaneous and proportional myoelectric control via sparse non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Lin, Chuang; Wang, Binghui; Jiang, Ning; Farina, Dario

2018-04-01

Objective. This paper proposes a novel simultaneous and proportional multiple degree of freedom (DOF) myoelectric control method for active prostheses. Approach. The approach is based on non-negative matrix factorization (NMF) of surface EMG signals with the inclusion of sparseness constraints. By applying a sparseness constraint to the control signal matrix, it is possible to extract the basis information from arbitrary movements (quasi-unsupervised approach) for multiple DOFs concurrently. Main Results. In online testing based on target hitting, able-bodied subjects reached a greater throughput (TP) when using sparse NMF (SNMF) than with classic NMF or with linear regression (LR). Accordingly, the completion time (CT) was shorter for SNMF than NMF or LR. The same observations were made in two patients with unilateral limb deficiencies. Significance. The addition of sparseness constraints to NMF allows for a quasi-unsupervised approach to myoelectric control with superior results with respect to previous methods for the simultaneous and proportional control of multi-DOF. The proposed factorization algorithm allows robust simultaneous and proportional control, is superior to previous supervised algorithms, and, because of minimal supervision, paves the way to online adaptation in myoelectric control.

Stabilization strategies of a general nonlinear car-following model with varying reaction-time delay of the drivers.

PubMed

Li, Shukai; Yang, Lixing; Gao, Ziyou; Li, Keping

2014-11-01

In this paper, the stabilization strategies of a general nonlinear car-following model with reaction-time delay of the drivers are investigated. The reaction-time delay of the driver is time varying and bounded. By using the Lyapunov stability theory, the sufficient condition for the existence of the state feedback control strategy for the stability of the car-following model is given in the form of linear matrix inequality, under which the traffic jam can be well suppressed with respect to the varying reaction-time delay. Moreover, by considering the external disturbance for the running cars, the robust state feedback control strategy is designed, which ensures robust stability and a smaller prescribed H∞ disturbance attenuation level for the traffic flow. Numerical examples are given to illustrate the effectiveness of the proposed methods. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Approach to method development and validation in capillary electrophoresis for enantiomeric purity testing of active basic pharmaceutical ingredients.

PubMed

Sokoliess, Torsten; Köller, Gerhard

2005-06-01

A chiral capillary electrophoresis system allowing the determination of the enantiomeric purity of an investigational new drug was developed using a generic method development approach for basic analytes. The method was optimized in terms of type and concentration of both cyclodextrin (CD) and electrolyte, buffer pH, temperature, voltage, and rinsing procedure. Optimal chiral separation of the analyte was obtained using an electrolyte with 2.5% carboxymethyl-beta-CD in 25 mM NaH2PO4 (pH 4.0). Interchanging the inlet and outlet vials after each run improved the method's precision. To assure the method's suitability for the control of enantiomeric impurities in pharmaceutical quality control, its specificity, linearity, precision, accuracy, and robustness were validated according to the requirements of the International Conference on Harmonization. The usefulness of our generic method development approach for the validation of robustness was demonstrated.

Toward a Model-Based Predictive Controller Design in Brain–Computer Interfaces

PubMed Central

Kamrunnahar, M.; Dias, N. S.; Schiff, S. J.

2013-01-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain–computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8–23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications. PMID:21267657

Fault-tolerant optimised tracking control for unknown discrete-time linear systems using a combined reinforcement learning and residual compensation methodology

NASA Astrophysics Data System (ADS)

Han, Ke-Zhen; Feng, Jian; Cui, Xiaohong

2017-10-01

This paper considers the fault-tolerant optimised tracking control (FTOTC) problem for unknown discrete-time linear system. A research scheme is proposed on the basis of data-based parity space identification, reinforcement learning and residual compensation techniques. The main characteristic of this research scheme lies in the parity-space-identification-based simultaneous tracking control and residual compensation. The specific technical line consists of four main contents: apply subspace aided method to design observer-based residual generator; use reinforcement Q-learning approach to solve optimised tracking control policy; rely on robust H∞ theory to achieve noise attenuation; adopt fault estimation triggered by residual generator to perform fault compensation. To clarify the design and implementation procedures, an integrated algorithm is further constructed to link up these four functional units. The detailed analysis and proof are subsequently given to explain the guaranteed FTOTC performance of the proposed conclusions. Finally, a case simulation is provided to verify its effectiveness.

Toward a model-based predictive controller design in brain-computer interfaces.

PubMed

Kamrunnahar, M; Dias, N S; Schiff, S J

2011-05-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.

Wiener sliding-mode control for artificial pancreas: a new nonlinear approach to glucose regulation.

PubMed

Abu-Rmileh, Amjad; Garcia-Gabin, Winston

2012-08-01

Type 1 diabetic patients need insulin therapy to keep their blood glucose close to normal. In this paper an attempt is made to show how nonlinear control-oriented model may be used to improve the performance of closed-loop control of blood glucose in diabetic patients. The nonlinear Wiener model is used as a novel modeling approach to be applied to the glucose control problem. The identified Wiener model is used in the design of a robust nonlinear sliding mode control strategy. Two configurations of the nonlinear controller are tested and compared to a controller designed with a linear model. The controllers are designed in a Smith predictor structure to reduce the effect of system time delay. To improve the meal compensation features, the controllers are provided with a simple feedforward controller to inject an insulin bolus at meal time. Different simulation scenarios have been used to evaluate the proposed controllers. The obtained results show that the new approach outperforms the linear control scheme, and regulates the glucose level within safe limits in the presence of measurement and modeling errors, meal uncertainty and patient variations. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Adding flexibility to the search for robust portfolios in non-linear water resource planning

NASA Astrophysics Data System (ADS)

Tomlinson, James; Harou, Julien

2017-04-01

To date robust optimisation of water supply systems has sought to find portfolios or strategies that are robust to a range of uncertainties or scenarios. The search for a single portfolio that is robust in all scenarios is necessarily suboptimal compared to portfolios optimised for a single scenario deterministic future. By contrast establishing a separate portfolio for each future scenario is unhelpful to the planner who must make a single decision today under deep uncertainty. In this work we show that a middle ground is possible by allowing a small number of different portfolios to be found that are each robust to a different subset of the global scenarios. We use evolutionary algorithms and a simple water resource system model to demonstrate this approach. The primary contribution is to demonstrate that flexibility can be added to the search for portfolios, in complex non-linear systems, at the expense of complete robustness across all future scenarios. In this context we define flexibility as the ability to design a portfolio in which some decisions are delayed, but those decisions that are not delayed are themselves shown to be robust to the future. We recognise that some decisions in our portfolio are more important than others. An adaptive portfolio is found by allowing no flexibility for these near-term "important" decisions, but maintaining flexibility in the remaining longer term decisions. In this sense we create an effective 2-stage decision process for a non-linear water resource supply system. We show how this reduces a measure of regret versus the inflexible robust solution for the same system.

Hexacopter trajectory control using a neural network

NASA Astrophysics Data System (ADS)

Artale, V.; Collotta, M.; Pau, G.; Ricciardello, A.

2013-10-01

The modern flight control systems are complex due to their non-linear nature. In fact, modern aerospace vehicles are expected to have non-conventional flight envelopes and, then, they must guarantee a high level of robustness and adaptability in order to operate in uncertain environments. Neural Networks (NN), with real-time learning capability, for flight control can be used in applications with manned or unmanned aerial vehicles. Indeed, using proven lower level control algorithms with adaptive elements that exhibit long term learning could help in achieving better adaptation performance while performing aggressive maneuvers. In this paper we show a mathematical modeling and a Neural Network for a hexacopter dynamics in order to develop proper methods for stabilization and trajectory control.

Adaptive attitude control and momentum management for large-angle spacecraft maneuvers

NASA Technical Reports Server (NTRS)

Parlos, Alexander G.; Sunkel, John W.

1992-01-01

The fully coupled equations of motion are systematically linearized around an equilibrium point of a gravity gradient stabilized spacecraft, controlled by momentum exchange devices. These equations are then used for attitude control system design of an early Space Station Freedom flight configuration, demonstrating the errors caused by the improper approximation of the spacecraft dynamics. A full state feedback controller, incorporating gain-scheduled adaptation of the attitude gains, is developed for use during spacecraft on-orbit assembly or operations characterized by significant mass properties variations. The feasibility of the gain adaptation is demonstrated via a Space Station Freedom assembly sequence case study. The attitude controller stability robustness and transient performance during gain adaptation appear satisfactory.

A robust multi-objective global supplier selection model under currency fluctuation and price discount

NASA Astrophysics Data System (ADS)

Zarindast, Atousa; Seyed Hosseini, Seyed Mohamad; Pishvaee, Mir Saman

2017-06-01

Robust supplier selection problem, in a scenario-based approach has been proposed, when the demand and exchange rates are subject to uncertainties. First, a deterministic multi-objective mixed integer linear programming is developed; then, the robust counterpart of the proposed mixed integer linear programming is presented using the recent extension in robust optimization theory. We discuss decision variables, respectively, by a two-stage stochastic planning model, a robust stochastic optimization planning model which integrates worst case scenario in modeling approach and finally by equivalent deterministic planning model. The experimental study is carried out to compare the performances of the three models. Robust model resulted in remarkable cost saving and it illustrated that to cope with such uncertainties, we should consider them in advance in our planning. In our case study different supplier were selected due to this uncertainties and since supplier selection is a strategic decision, it is crucial to consider these uncertainties in planning approach.

Approximate analytical relationships for linear optimal aeroelastic flight control laws

NASA Astrophysics Data System (ADS)

Kassem, Ayman Hamdy

1998-09-01

This dissertation introduces new methods to uncover functional relationships between design parameters of a contemporary control design technique and the resulting closed-loop properties. Three new methods are developed for generating such relationships through analytical expressions: the Direct Eigen-Based Technique, the Order of Magnitude Technique, and the Cost Function Imbedding Technique. Efforts concentrated on the linear-quadratic state-feedback control-design technique applied to an aeroelastic flight control task. For this specific application, simple and accurate analytical expressions for the closed-loop eigenvalues and zeros in terms of basic parameters such as stability and control derivatives, structural vibration damping and natural frequency, and cost function weights are generated. These expressions explicitly indicate how the weights augment the short period and aeroelastic modes, as well as the closed-loop zeros, and by what physical mechanism. The analytical expressions are used to address topics such as damping, nonminimum phase behavior, stability, and performance with robustness considerations, and design modifications. This type of knowledge is invaluable to the flight control designer and would be more difficult to formulate when obtained from numerical-based sensitivity analysis.

Robust estimation for ordinary differential equation models.

PubMed

Cao, J; Wang, L; Xu, J

2011-12-01

Applied scientists often like to use ordinary differential equations (ODEs) to model complex dynamic processes that arise in biology, engineering, medicine, and many other areas. It is interesting but challenging to estimate ODE parameters from noisy data, especially when the data have some outliers. We propose a robust method to address this problem. The dynamic process is represented with a nonparametric function, which is a linear combination of basis functions. The nonparametric function is estimated by a robust penalized smoothing method. The penalty term is defined with the parametric ODE model, which controls the roughness of the nonparametric function and maintains the fidelity of the nonparametric function to the ODE model. The basis coefficients and ODE parameters are estimated in two nested levels of optimization. The coefficient estimates are treated as an implicit function of ODE parameters, which enables one to derive the analytic gradients for optimization using the implicit function theorem. Simulation studies show that the robust method gives satisfactory estimates for the ODE parameters from noisy data with outliers. The robust method is demonstrated by estimating a predator-prey ODE model from real ecological data. © 2011, The International Biometric Society.

Robustness Analysis and Reliable Flight Regime Estimation of an Integrated Resilent Control System for a Transport Aircraft

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Belcastro, Christine

2008-01-01

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. As a part of the validation process, this paper describes an analysis method for determining a reliable flight regime in the flight envelope within which an integrated resilent control system can achieve the desired performance of tracking command signals and detecting additive faults in the presence of parameter uncertainty and unmodeled dynamics. To calculate a reliable flight regime, a structured singular value analysis method is applied to analyze the closed-loop system over the entire flight envelope. To use the structured singular value analysis method, a linear fractional transform (LFT) model of a transport aircraft longitudinal dynamics is developed over the flight envelope by using a preliminary LFT modeling software tool developed at the NASA Langley Research Center, which utilizes a matrix-based computational approach. The developed LFT model can capture original nonlinear dynamics over the flight envelope with the ! block which contains key varying parameters: angle of attack and velocity, and real parameter uncertainty: aerodynamic coefficient uncertainty and moment of inertia uncertainty. Using the developed LFT model and a formal robustness analysis method, a reliable flight regime is calculated for a transport aircraft closed-loop system.

Model-based design and experimental verification of a monitoring concept for an active-active electromechanical aileron actuation system

NASA Astrophysics Data System (ADS)

Arriola, David; Thielecke, Frank

2017-09-01

Electromechanical actuators have become a key technology for the onset of power-by-wire flight control systems in the next generation of commercial aircraft. The design of robust control and monitoring functions for these devices capable to mitigate the effects of safety-critical faults is essential in order to achieve the required level of fault tolerance. A primary flight control system comprising two electromechanical actuators nominally operating in active-active mode is considered. A set of five signal-based monitoring functions are designed using a detailed model of the system under consideration which includes non-linear parasitic effects, measurement and data acquisition effects, and actuator faults. Robust detection thresholds are determined based on the analysis of parametric and input uncertainties. The designed monitoring functions are verified experimentally and by simulation through the injection of faults in the validated model and in a test-rig suited to the actuation system under consideration, respectively. They guarantee a robust and efficient fault detection and isolation with a low risk of false alarms, additionally enabling the correct reconfiguration of the system for an enhanced operational availability. In 98% of the performed experiments and simulations, the correct faults were detected and confirmed within the time objectives set.

A methodology for formulating a minimal uncertainty model for robust control system design and analysis

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.; Chang, B.-C.; Fischl, Robert

1989-01-01

In the design and analysis of robust control systems for uncertain plants, the technique of formulating what is termed an M-delta model has become widely accepted and applied in the robust control literature. The M represents the transfer function matrix M(s) of the nominal system, and delta represents an uncertainty matrix acting on M(s). The uncertainty can arise from various sources, such as structured uncertainty from parameter variations or multiple unstructured uncertainties from unmodeled dynamics and other neglected phenomena. In general, delta is a block diagonal matrix, and for real parameter variations the diagonal elements are real. As stated in the literature, this structure can always be formed for any linear interconnection of inputs, outputs, transfer functions, parameter variations, and perturbations. However, very little of the literature addresses methods for obtaining this structure, and none of this literature addresses a general methodology for obtaining a minimal M-delta model for a wide class of uncertainty. Since have a delta matrix of minimum order would improve the efficiency of structured singular value (or multivariable stability margin) computations, a method of obtaining a minimal M-delta model would be useful. A generalized method of obtaining a minimal M-delta structure for systems with real parameter variations is given.

Structured Uncertainty Bound Determination From Data for Control and Performance Validation

NASA Technical Reports Server (NTRS)

Lim, Kyong B.

2003-01-01

This report attempts to document the broad scope of issues that must be satisfactorily resolved before one can expect to methodically obtain, with a reasonable confidence, a near-optimal robust closed loop performance in physical applications. These include elements of signal processing, noise identification, system identification, model validation, and uncertainty modeling. Based on a recently developed methodology involving a parameterization of all model validating uncertainty sets for a given linear fractional transformation (LFT) structure and noise allowance, a new software, Uncertainty Bound Identification (UBID) toolbox, which conveniently executes model validation tests and determine uncertainty bounds from data, has been designed and is currently available. This toolbox also serves to benchmark the current state-of-the-art in uncertainty bound determination and in turn facilitate benchmarking of robust control technology. To help clarify the methodology and use of the new software, two tutorial examples are provided. The first involves the uncertainty characterization of a flexible structure dynamics, and the second example involves a closed loop performance validation of a ducted fan based on an uncertainty bound from data. These examples, along with other simulation and experimental results, also help describe the many factors and assumptions that determine the degree of success in applying robust control theory to practical problems.

Extended state observer based robust adaptive control on SE(3) for coupled spacecraft tracking maneuver with actuator saturation and misalignment

NASA Astrophysics Data System (ADS)

Zhang, Jianqiao; Ye, Dong; Sun, Zhaowei; Liu, Chuang

2018-02-01

This paper presents a robust adaptive controller integrated with an extended state observer (ESO) to solve coupled spacecraft tracking maneuver in the presence of model uncertainties, external disturbances, actuator uncertainties including magnitude deviation and misalignment, and even actuator saturation. More specifically, employing the exponential coordinates on the Lie group SE(3) to describe configuration tracking errors, the coupled six-degrees-of-freedom (6-DOF) dynamics are developed for spacecraft relative motion, in which a generic fully actuated thruster distribution is considered and the lumped disturbances are reconstructed by using anti-windup technique. Then, a novel ESO, developed via second order sliding mode (SOSM) technique and adding linear correction terms to improve the performance, is designed firstly to estimate the disturbances in finite time. Based on the estimated information, an adaptive fast terminal sliding mode (AFTSM) controller is developed to guarantee the almost global asymptotic stability of the resulting closed-loop system such that the trajectory can be tracked with all the aforementioned drawbacks addressed simultaneously. Finally, the effectiveness of the controller is illustrated through numerical examples.

Fault-tolerant control of large space structures using the stable factorization approach

NASA Technical Reports Server (NTRS)

Razavi, H. C.; Mehra, R. K.; Vidyasagar, M.

1986-01-01

Large space structures are characterized by the following features: they are in general infinite-dimensional systems, and have large numbers of undamped or lightly damped poles. Any attempt to apply linear control theory to large space structures must therefore take into account these features. Phase I consisted of an attempt to apply the recently developed Stable Factorization (SF) design philosophy to problems of large space structures, with particular attention to the aspects of robustness and fault tolerance. The final report on the Phase I effort consists of four sections, each devoted to one task. The first three sections report theoretical results, while the last consists of a design example. Significant results were obtained in all four tasks of the project. More specifically, an innovative approach to order reduction was obtained, stabilizing controller structures for plants with an infinite number of unstable poles were determined under some conditions, conditions for simultaneous stabilizability of an infinite number of plants were explored, and a fault tolerance controller design that stabilizes a flexible structure model was obtained which is robust against one failure condition.

Design of sewage treatment system by applying fuzzy adaptive PID controller

NASA Astrophysics Data System (ADS)

Jin, Liang-Ping; Li, Hong-Chan

2013-03-01

In the sewage treatment system, the dissolved oxygen concentration control, due to its nonlinear, time-varying, large time delay and uncertainty, is difficult to establish the exact mathematical model. While the conventional PID controller only works with good linear not far from its operating point, it is difficult to realize the system control when the operating point far off. In order to solve the above problems, the paper proposed a method which combine fuzzy control with PID methods and designed a fuzzy adaptive PID controller based on S7-300 PLC .It employs fuzzy inference method to achieve the online tuning for PID parameters. The control algorithm by simulation and practical application show that the system has stronger robustness and better adaptability.

A Piloted Evaluation of Damage Accommodating Flight Control Using a Remotely Piloted Vehicle

NASA Technical Reports Server (NTRS)

Cunningham, Kevin; Cox, David E.; Murri, Daniel G.; Riddick, Stephen E.

2011-01-01

Toward the goal of reducing the fatal accident rate of large transport airplanes due to loss of control, the NASA Aviation Safety Program has conducted research into flight control technologies that can provide resilient control of airplanes under adverse flight conditions, including damage and failure. As part of the safety program s Integrated Resilient Aircraft Control Project, the NASA Airborne Subscale Transport Aircraft Research system was designed to address the challenges associated with the safe and efficient subscale flight testing of research control laws under adverse flight conditions. This paper presents the results of a series of pilot evaluations of several flight control algorithms used during an offset-to-landing task conducted at altitude. The purpose of this investigation was to assess the ability of various flight control technologies to prevent loss of control as stability and control characteristics were degraded. During the course of 8 research flights, data were recorded while one task was repeatedly executed by a single evaluation pilot. Two generic failures, which degraded stability and control characteristics, were simulated inflight for each of the 9 different flight control laws that were tested. The flight control laws included three different adaptive control methodologies, several linear multivariable designs, a linear robust design, a linear stability augmentation system, and a direct open-loop control mode. Based on pilot Cooper-Harper Ratings obtained for this test, the adaptive flight control laws provided the greatest overall benefit for the stability and control degradation scenarios that were considered. Also, all controllers tested provided a significant improvement in handling qualities over the direct open-loop control mode.

Periodic-disturbance accommodating control of the space station for asymptotic momentum management

NASA Technical Reports Server (NTRS)

Warren, Wayne; Wie, Bong; Geller, David

1989-01-01

Periodic-disturbance accommodating control is investigated for asymptotic momentum management of control moment gyros used as primary actuating devices for the Space Station. The proposed controller utilizes the concepts of quaternion feedback control and periodic-disturbance accommodation to achieve oscillations about the constant torque equilibrium attitude, while minimizing the control effort required. Three-axis coupled equations of motion, written in terms of quaternions, are derived for roll/yaw controller design and stability analysis. The quaternion feedback controller designed using the linear-quadratic regulator synthesis technique is shown to be robust for a wide range of pitch angles. It is also shown that the proposed controller tunes the open-loop unstable vehicle to a stable oscillatory motion which minimizes the control effort needed for steady-state operations.

Quantitative fault tolerant control design for a hydraulic actuator with a leaking piston seal

NASA Astrophysics Data System (ADS)

Karpenko, Mark

Hydraulic actuators are complex fluid power devices whose performance can be degraded in the presence of system faults. In this thesis a linear, fixed-gain, fault tolerant controller is designed that can maintain the positioning performance of an electrohydraulic actuator operating under load with a leaking piston seal and in the presence of parametric uncertainties. Developing a control system tolerant to this class of internal leakage fault is important since a leaking piston seal can be difficult to detect, unless the actuator is disassembled. The designed fault tolerant control law is of low-order, uses only the actuator position as feedback, and can: (i) accommodate nonlinearities in the hydraulic functions, (ii) maintain robustness against typical uncertainties in the hydraulic system parameters, and (iii) keep the positioning performance of the actuator within prescribed tolerances despite an internal leakage fault that can bypass up to 40% of the rated servovalve flow across the actuator piston. Experimental tests verify the functionality of the fault tolerant control under normal and faulty operating conditions. The fault tolerant controller is synthesized based on linear time-invariant equivalent (LTIE) models of the hydraulic actuator using the quantitative feedback theory (QFT) design technique. A numerical approach for identifying LTIE frequency response functions of hydraulic actuators from acceptable input-output responses is developed so that linearizing the hydraulic functions can be avoided. The proposed approach can properly identify the features of the hydraulic actuator frequency response that are important for control system design and requires no prior knowledge about the asymptotic behavior or structure of the LTIE transfer functions. A distributed hardware-in-the-loop (HIL) simulation architecture is constructed that enables the performance of the proposed fault tolerant control law to be further substantiated, under realistic operating conditions. Using the HIL framework, the fault tolerant hydraulic actuator is operated as a flight control actuator against the real-time numerical simulation of a high-performance jet aircraft. A robust electrohydraulic loading system is also designed using QFT so that the in-flight aerodynamic load can be experimentally replicated. The results of the HIL experiments show that using the fault tolerant controller to compensate the internal leakage fault at the actuator level can benefit the flight performance of the airplane.

Fuzzy – PI controller to control the velocity parameter of Induction Motor

NASA Astrophysics Data System (ADS)

Malathy, R.; Balaji, V.

2018-04-01

The major application of Induction motor includes the usage of the same in industries because of its high robustness, reliability, low cost, highefficiency and good self-starting capability. Even though it has the above mentioned advantages, it also have some limitations: (1) the standard motor is not a true constant-speed machine, itsfull-load slip varies less than 1 % (in high-horsepower motors).And (2) it is not inherently capable of providing variable-speedoperation. In order to solve the above mentioned problem smart motor controls and variable speed controllers are used. Motor applications involve non linearity features, which can be controlled by Fuzzy logic controller as it is capable of handling those features with high efficiency and it act similar to human operator. This paper presents individuality of the plant modelling. The fuzzy logic controller (FLC)trusts on a set of linguistic if-then rules, a rule-based Mamdani for closed loop Induction Motor model. Themotor model is designed and membership functions are chosenaccording to the parameters of the motor model. Simulation results contains non linearity in induction motor model. A conventional PI controller iscompared practically to fuzzy logic controller using Simulink.

Closed-loop regulation of arterial pressure after acute brain death.

PubMed

Soltesz, Kristian; Sjöberg, Trygve; Jansson, Tomas; Johansson, Rolf; Robertsson, Anders; Paskevicius, Audrius; Liao, Quiming; Qin, Guangqi; Steen, Stig

2018-06-01

The purpose of this concept study was to investigate the possibility of automatic mean arterial pressure (MAP) regulation in a porcine heart-beating brain death (BD) model. Hemodynamic stability of BD donors is necessary for maintaining acceptable quality of donated organs for transplantation. Manual stabilization is challenging, due to the lack of vasomotor function in BD donors. Closed-loop stabilization therefore has the potential of increasing availability of acceptable donor organs, and serves to indicate feasibility within less demanding patient groups. A dynamic model of nitroglycerine pharmacology, suitable for controller synthesis, was identified from an experiment involving an anesthetized pig, using a gradient-based output error method. The model was used to synthesize a robust PID controller for hypertension prevention, evaluated in a second experiment, on a second, brain dead, pig. Hypotension was simultaneously prevented using closed-loop controlled infusion of noradrenaline, by means of a previously published controller. A linear model of low order, with variable (uncertain) gain, was sufficient to describe the dynamics to be controlled. The robustly tuned PID controller utilized in the second experiment kept the MAP within a user-defined range. The system was able to prevent hypertension, exceeding a reference of 100 mmHg by more than 10%, during 98% of a 12 h experiment. This early work demonstrates feasibility of the investigated modelling and control synthesis approach, for the purpose of maintaining normotension in a porcine BD model. There remains a need to characterize individual variability, in order to ensure robust performance over the expected population.

Robust Weak Chimeras in Oscillator Networks with Delayed Linear and Quadratic Interactions

NASA Astrophysics Data System (ADS)

Bick, Christian; Sebek, Michael; Kiss, István Z.

2017-10-01

We present an approach to generate chimera dynamics (localized frequency synchrony) in oscillator networks with two populations of (at least) two elements using a general method based on a delayed interaction with linear and quadratic terms. The coupling design yields robust chimeras through a phase-model-based design of the delay and the ratio of linear and quadratic components of the interactions. We demonstrate the method in the Brusselator model and experiments with electrochemical oscillators. The technique opens the way to directly bridge chimera dynamics in phase models and real-world oscillator networks.

Predictive functional control for active queue management in congested TCP/IP networks.

PubMed

Bigdeli, N; Haeri, M

2009-01-01

Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison.

Transonic Flutter Suppression Control Law Design, Analysis and Wind Tunnel Results

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivek

1999-01-01

The benchmark active controls technology and wind tunnel test program at NASA Langley Research Center was started with the objective to investigate the nonlinear, unsteady aerodynamics and active flutter suppression of wings in transonic flow. The paper will present the flutter suppression control law design process, numerical nonlinear simulation and wind tunnel test results for the NACA 0012 benchmark active control wing model. The flutter suppression control law design processes using (1) classical, (2) linear quadratic Gaussian (LQG), and (3) minimax techniques are described. A unified general formulation and solution for the LQG and minimax approaches, based on the steady state differential game theory is presented. Design considerations for improving the control law robustness and digital implementation are outlined. It was shown that simple control laws when properly designed based on physical principles, can suppress flutter with limited control power even in the presence of transonic shocks and flow separation. In wind tunnel tests in air and heavy gas medium, the closed-loop flutter dynamic pressure was increased to the tunnel upper limit of 200 psf The control law robustness and performance predictions were verified in highly nonlinear flow conditions, gain and phase perturbations, and spoiler deployment. A non-design plunge instability condition was also successfully suppressed.

Transonic Flutter Suppression Control Law Design, Analysis and Wind-Tunnel Results

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivek

1999-01-01

The benchmark active controls technology and wind tunnel test program at NASA Langley Research Center was started with the objective to investigate the nonlinear, unsteady aerodynamics and active flutter suppression of wings in transonic flow. The paper will present the flutter suppression control law design process, numerical nonlinear simulation and wind tunnel test results for the NACA 0012 benchmark active control wing model. The flutter suppression control law design processes using (1) classical, (2) linear quadratic Gaussian (LQG), and (3) minimax techniques are described. A unified general formulation and solution for the LQG and minimax approaches, based on the steady state differential game theory is presented. Design considerations for improving the control law robustness and digital implementation are outlined. It was shown that simple control laws when properly designed based on physical principles, can suppress flutter with limited control power even in the presence of transonic shocks and flow separation. In wind tunnel tests in air and heavy gas medium, the closed-loop flutter dynamic pressure was increased to the tunnel upper limit of 200 psf. The control law robustness and performance predictions were verified in highly nonlinear flow conditions, gain and phase perturbations, and spoiler deployment. A non-design plunge instability condition was also successfully suppressed.

Transonic Flutter Suppression Control Law Design Using Classical and Optimal Techniques with Wind-Tunnel Results

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivek

1999-01-01

The benchmark active controls technology and wind tunnel test program at NASA Langley Research Center was started with the objective to investigate the nonlinear, unsteady aerodynamics and active flutter suppression of wings in transonic flow. The paper will present the flutter suppression control law design process, numerical nonlinear simulation and wind tunnel test results for the NACA 0012 benchmark active control wing model. The flutter suppression control law design processes using (1) classical, (2) linear quadratic Gaussian (LQG), and (3) minimax techniques are described. A unified general formulation and solution for the LQG and minimax approaches, based on the steady state differential game theory is presented. Design considerations for improving the control law robustness and digital implementation are outlined. It was shown that simple control laws when properly designed based on physical principles, can suppress flutter with limited control power even in the presence of transonic shocks and flow separation. In wind tunnel tests in air and heavy gas medium, the closed-loop flutter dynamic pressure was increased to the tunnel upper limit of 200 psf. The control law robustness and performance predictions were verified in highly nonlinear flow conditions, gain and phase perturbations, and spoiler deployment. A non-design plunge instability condition was also successfully suppressed.

Control of nonlinear flexible space structures

NASA Astrophysics Data System (ADS)

Shi, Jianjun

With the advances made in computer technology and efficiency of numerical algorithms over last decade, the MPC strategies have become quite popular among control community. However, application of MPC or GPC to flexible space structure control has not been explored adequately in the literature. The work presented in this thesis primarily focuses on application of GPC to control of nonlinear flexible space structures. This thesis is particularly devoted to the development of various approximate dynamic models, design and assessment of candidate controllers, and extensive numerical simulations for a realistic multibody flexible spacecraft, namely, Jupiter Icy Moons Orbiter (JIMO)---a Prometheus class of spacecraft proposed by NASA for deep space exploratory missions. A stable GPC algorithm is developed for Multi-Input-Multi-Output (MIMO) systems. An end-point weighting (penalty) is used in the GPC cost function to guarantee the nominal stability of the closed-loop system. A method is given to compute the desired end-point state from the desired output trajectory. The methodologies based on Fake Algebraic Riccati Equation (FARE) and constrained nonlinear optimization, are developed for synthesis of state weighting matrix. This makes this formulation more practical. A stable reconfigurable GPC architecture is presented and its effectiveness is demonstrated on both aircraft as well as spacecraft model. A representative in-orbit maneuver is used for assessing the performance of various control strategies using various design models. Different approximate dynamic models used for analysis include linear single body flexible structure, nonlinear single body flexible structure, and nonlinear multibody flexible structure. The control laws evaluated include traditional GPC, feedback linearization-based GPC (FLGPC), reconfigurable GPC, and nonlinear dissipative control. These various control schemes are evaluated for robust stability and robust performance in the presence of parametric uncertainties and input disturbances. Finally, the conclusions are made with regard to the efficacy of these controllers and potential directions for future research.

Microgravity vibration isolation: Optimal preview and feedback control

NASA Technical Reports Server (NTRS)

Hampton, R. D.; Knospe, C. R.; Grodsinsky, C. M.; Allaire, P. E.; Lewis, D. W.

1992-01-01

In order to achieve adequate low-frequency vibration isolation for certain space experiments an active control is needed, due to inherent passive-isolator limitations. Proposed here are five possible state-space models for a one-dimensional vibration isolation system with a quadratic performance index. The five models are subsets of a general set of nonhomogeneous state space equations which includes disturbance terms. An optimal control is determined, using a differential equations approach, for this class of problems. This control is expressed in terms of constant, Linear Quadratic Regulator (LQR) feedback gains and constant feedforward (preview) gains. The gains can be easily determined numerically. They result in a robust controller and offers substantial improvements over a control that uses standard LQR feedback alone.

A blood pressure monitor with robust noise reduction system under linear cuff inflation and deflation.

PubMed

Usuda, Takashi; Kobayashi, Naoki; Takeda, Sunao; Kotake, Yoshifumi

2010-01-01

We have developed the non-invasive blood pressure monitor which can measure the blood pressure quickly and robustly. This monitor combines two measurement mode: the linear inflation and the linear deflation. On the inflation mode, we realized a faster measurement with rapid inflation rate. On the deflation mode, we realized a robust noise reduction. When there is neither noise nor arrhythmia, the inflation mode incorporated on this monitor provides precise, quick and comfortable measurement. Once the inflation mode fails to calculate appropriate blood pressure due to body movement or arrhythmia, then the monitor switches automatically to the deflation mode and measure blood pressure by using digital signal processing as wavelet analysis, filter bank, filter combined with FFT and Inverse FFT. The inflation mode succeeded 2440 measurements out of 3099 measurements (79%) in an operating room and a rehabilitation room. The new designed blood pressure monitor provides the fastest measurement for patient with normal circulation and robust measurement for patients with body movement or severe arrhythmia. Also this fast measurement method provides comfortableness for patients.

Common spatial pattern combined with kernel linear discriminate and generalized radial basis function for motor imagery-based brain computer interface applications

NASA Astrophysics Data System (ADS)

Hekmatmanesh, Amin; Jamaloo, Fatemeh; Wu, Huapeng; Handroos, Heikki; Kilpeläinen, Asko

2018-04-01

Brain Computer Interface (BCI) can be a challenge for developing of robotic, prosthesis and human-controlled systems. This work focuses on the implementation of a common spatial pattern (CSP) base algorithm to detect event related desynchronization patterns. Utilizing famous previous work in this area, features are extracted by filter bank with common spatial pattern (FBCSP) method, and then weighted by a sensitive learning vector quantization (SLVQ) algorithm. In the current work, application of the radial basis function (RBF) as a mapping kernel of linear discriminant analysis (KLDA) method on the weighted features, allows the transfer of data into a higher dimension for more discriminated data scattering by RBF kernel. Afterwards, support vector machine (SVM) with generalized radial basis function (GRBF) kernel is employed to improve the efficiency and robustness of the classification. Averagely, 89.60% accuracy and 74.19% robustness are achieved. BCI Competition III, Iva data set is used to evaluate the algorithm for detecting right hand and foot imagery movement patterns. Results show that combination of KLDA with SVM-GRBF classifier makes 8.9% and 14.19% improvements in accuracy and robustness, respectively. For all the subjects, it is concluded that mapping the CSP features into a higher dimension by RBF and utilization GRBF as a kernel of SVM, improve the accuracy and reliability of the proposed method.

Linear parameter varying representations for nonlinear control design

NASA Astrophysics Data System (ADS)

Carter, Lance Huntington

Linear parameter varying (LPV) systems are investigated as a framework for gain-scheduled control design and optimal hybrid control. An LPV system is defined as a linear system whose dynamics depend upon an a priori unknown but measurable exogenous parameter. A gain-scheduled autopilot design is presented for a bank-to-turn (BTT) missile. The method is novel in that the gain-scheduled design does not involve linearizations about operating points. Instead, the missile dynamics are brought to LPV form via a state transformation. This idea is applied to the design of a coupled longitudinal/lateral BTT missile autopilot. The pitch and yaw/roll dynamics are separately transformed to LPV form, where the cross axis states are treated as "exogenous" parameters. These are actually endogenous variables, so such a plant is called "quasi-LPV." Once in quasi-LPV form, a family of robust controllers using mu synthesis is designed for both the pitch and yaw/roll channels, using angle-of-attack and roll rate as the scheduling variables. The closed-loop time response is simulated using the original nonlinear model and also using perturbed aerodynamic coefficients. Modeling and control of engine idle speed is investigated using LPV methods. It is shown how generalized discrete nonlinear systems may be transformed into quasi-LPV form. A discrete nonlinear engine model is developed and expressed in quasi-LPV form with engine speed as the scheduling variable. An example control design is presented using linear quadratic methods. Simulations are shown comparing the LPV based controller performance to that using PID control. LPV representations are also shown to provide a setting for hybrid systems. A hybrid system is characterized by control inputs consisting of both analog signals and discrete actions. A solution is derived for the optimal control of hybrid systems with generalized cost functions. This is shown to be computationally intensive, so a suboptimal strategy is proposed that neglects a subset of possible parameter trajectories. A computational algorithm is constructed for this suboptimal solution applied to a class of linear non-quadratic cost functions.

Method and apparatus for adaptive force and position control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1989-01-01

The present invention discloses systematic methods and apparatus for the design of real time controllers. Real-time control employs adaptive force/position by use of feedforward and feedback controllers, with the feedforward controller being the inverse of the linearized model of robot dynamics and containing only proportional-double-derivative terms is disclosed. The feedback controller, of the proportional-integral-derivative type, ensures that manipulator joints follow reference trajectories and the feedback controller achieves robust tracking of step-plus-exponential trajectories, all in real time. The adaptive controller includes adaptive force and position control within a hybrid control architecture. The adaptive controller, for force control, achieves tracking of desired force setpoints, and the adaptive position controller accomplishes tracking of desired position trajectories. Circuits in the adaptive feedback and feedforward controllers are varied by adaptation laws.

Variational and robust density fitting of four-center two-electron integrals in local metrics

NASA Astrophysics Data System (ADS)

Reine, Simen; Tellgren, Erik; Krapp, Andreas; Kjærgaard, Thomas; Helgaker, Trygve; Jansik, Branislav; Høst, Stinne; Salek, Paweł

2008-09-01

Density fitting is an important method for speeding up quantum-chemical calculations. Linear-scaling developments in Hartree-Fock and density-functional theories have highlighted the need for linear-scaling density-fitting schemes. In this paper, we present a robust variational density-fitting scheme that allows for solving the fitting equations in local metrics instead of the traditional Coulomb metric, as required for linear scaling. Results of fitting four-center two-electron integrals in the overlap and the attenuated Gaussian damped Coulomb metric are presented, and we conclude that density fitting can be performed in local metrics at little loss of chemical accuracy. We further propose to use this theory in linear-scaling density-fitting developments.

Variational and robust density fitting of four-center two-electron integrals in local metrics.

PubMed

Reine, Simen; Tellgren, Erik; Krapp, Andreas; Kjaergaard, Thomas; Helgaker, Trygve; Jansik, Branislav; Host, Stinne; Salek, Paweł

2008-09-14

Density fitting is an important method for speeding up quantum-chemical calculations. Linear-scaling developments in Hartree-Fock and density-functional theories have highlighted the need for linear-scaling density-fitting schemes. In this paper, we present a robust variational density-fitting scheme that allows for solving the fitting equations in local metrics instead of the traditional Coulomb metric, as required for linear scaling. Results of fitting four-center two-electron integrals in the overlap and the attenuated Gaussian damped Coulomb metric are presented, and we conclude that density fitting can be performed in local metrics at little loss of chemical accuracy. We further propose to use this theory in linear-scaling density-fitting developments.

Integrated structural control design of large space structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allen, J.J.; Lauffer, J.P.

1995-01-01

Active control of structures has been under intensive development for the last ten years. Reference 2 reviews much of the identification and control technology for structural control developed during this time. The technology was initially focused on space structure and weapon applications; however, recently the technology is also being directed toward applications in manufacturing and transportation. Much of this technology focused on multiple-input/multiple-output (MIMO) identification and control methodology because many of the applications require a coordinated control involving multiple disturbances and control objectives where multiple actuators and sensors are necessary for high performance. There have been many optimal robust controlmore » methods developed for the design of MIMO robust control laws; however, there appears to be a significant gap between the theoretical development and experimental evaluation of control and identification methods to address structural control applications. Many methods have been developed for MIMO identification and control of structures, such as the Eigensystem Realization Algorithm (ERA), Q-Markov Covariance Equivalent Realization (Q-Markov COVER) for identification; and, Linear Quadratic Gaussian (LQG), Frequency Weighted LQG and H-/ii-synthesis methods for control. Upon implementation, many of the identification and control methods have shown limitations such as the excitation of unmodelled dynamics and sensitivity to system parameter variations. As a result, research on methods which address these problems have been conducted.« less

Physical origins of current and temperature controlled negative differential resistances in NbO 2

DOE PAGES

Kumar, Suhas; Wang, Ziwen; Davila, Noraica; ...

2017-09-22

Negative differential resistance behavior in oxide memristors, especially those using NbO 2, is gaining renewed interest because of its potential utility in neuromorphic computing. However, there has been a decade-long controversy over whether the negative differential resistance is caused by a relatively low-temperature non-linear transport mechanism or a high-temperature Mott transition. Resolving this issue will enable consistent and robust predictive modeling of this phenomenon for different applications. Here in this paper, we examine NbO 2 memristors that exhibit both a current-controlled and a temperature-controlled negative differential resistance. Through thermal and chemical spectromicroscopy and numerical simulations, we confirm that the formermore » is caused by a ~400 K non-linear-transport-driven instability and the latter is caused by the ~1000 K Mott metal-insulator transition, for which the thermal conductance counter-intuitively decreases in the metallic state relative to the insulating state.« less

Physical origins of current and temperature controlled negative differential resistances in NbO 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Suhas; Wang, Ziwen; Davila, Noraica

Negative differential resistance behavior in oxide memristors, especially those using NbO 2, is gaining renewed interest because of its potential utility in neuromorphic computing. However, there has been a decade-long controversy over whether the negative differential resistance is caused by a relatively low-temperature non-linear transport mechanism or a high-temperature Mott transition. Resolving this issue will enable consistent and robust predictive modeling of this phenomenon for different applications. Here in this paper, we examine NbO 2 memristors that exhibit both a current-controlled and a temperature-controlled negative differential resistance. Through thermal and chemical spectromicroscopy and numerical simulations, we confirm that the formermore » is caused by a ~400 K non-linear-transport-driven instability and the latter is caused by the ~1000 K Mott metal-insulator transition, for which the thermal conductance counter-intuitively decreases in the metallic state relative to the insulating state.« less

Simultaneous fault detection and control design for switched systems with two quantized signals.

PubMed

Li, Jian; Park, Ju H; Ye, Dan

2017-01-01

The problem of simultaneous fault detection and control design for switched systems with two quantized signals is presented in this paper. Dynamic quantizers are employed, respectively, before the output is passed to fault detector, and before the control input is transmitted to the switched system. Taking the quantized errors into account, the robust performance for this kind of system is given. Furthermore, sufficient conditions for the existence of fault detector/controller are presented in the framework of linear matrix inequalities, and fault detector/controller gains and the supremum of quantizer range are derived by a convex optimized method. Finally, two illustrative examples demonstrate the effectiveness of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

MIMO Sliding Mode Control for a Tailless Fighter Aircraft, An Alternative to Reconfigurable Architectures

NASA Technical Reports Server (NTRS)

Wells, S. R.; Hess, R. A.

2002-01-01

A frequency-domain procedure for the design of sliding mode controllers for multi-input, multi-output (MIMO) systems is presented. The methodology accommodates the effects of parasitic dynamics such as those introduced by unmodeled actuators through the introduction of multiple asymptotic observers and model reference hedging. The design procedure includes a frequency domain approach to specify the sliding manifold, the observer eigenvalues, and the hedge model. The procedure is applied to the development of a flight control system for a linear model of the Innovative Control Effector (ICE) fighter aircraft. The stability and performance robustness of the resulting design is demonstrated through the introduction of significant degradation in the control effector actuators and variation in vehicle dynamics.

Decoupling suspension controller based on magnetic flux feedback.

PubMed

Zhang, Wenqing; Li, Jie; Zhang, Kun; Cui, Peng

2013-01-01

The suspension module control system model has been established based on MIMO (multiple input and multiple output) state feedback linearization. We have completed decoupling between double suspension points, and the new decoupling method has been applied to CMS04 magnetic suspension vehicle in national mid-low-speed maglev experiment field of Tangshan city in China. Double suspension system model is very accurate for investigating stability property of maglev control system. When magnetic flux signal is taken back to the suspension control system, the suspension module's antijamming capacity for resisting suspension load variety has been proved. Also, the external force interference has been enhanced. As a result, the robustness and stability properties of double-electromagnet suspension control system have been enhanced.

Decoupling Suspension Controller Based on Magnetic Flux Feedback

PubMed Central

Zhang, Wenqing; Li, Jie; Zhang, Kun; Cui, Peng

2013-01-01

The suspension module control system model has been established based on MIMO (multiple input and multiple output) state feedback linearization. We have completed decoupling between double suspension points, and the new decoupling method has been applied to CMS04 magnetic suspension vehicle in national mid-low-speed maglev experiment field of Tangshan city in China. Double suspension system model is very accurate for investigating stability property of maglev control system. When magnetic flux signal is taken back to the suspension control system, the suspension module's antijamming capacity for resisting suspension load variety has been proved. Also, the external force interference has been enhanced. As a result, the robustness and stability properties of double-electromagnet suspension control system have been enhanced. PMID:23844415

Intelligent call admission control for multi-class services in mobile cellular networks

NASA Astrophysics Data System (ADS)

Ma, Yufeng; Hu, Xiulin; Zhang, Yunyu

2005-11-01

Scarcity of the spectrum resource and mobility of users make quality of service (QoS) provision a critical issue in mobile cellular networks. This paper presents a fuzzy call admission control scheme to meet the requirement of the QoS. A performance measure is formed as a weighted linear function of new call and handoff call blocking probabilities of each service class. Simulation compares the proposed fuzzy scheme with complete sharing and guard channel policies. Simulation results show that fuzzy scheme has a better robust performance in terms of average blocking criterion.

Application of Design Methodologies for Feedback Compensation Associated with Linear Systems

NASA Technical Reports Server (NTRS)

Smith, Monty J.

1996-01-01

The work that follows is concerned with the application of design methodologies for feedback compensation associated with linear systems. In general, the intent is to provide a well behaved closed loop system in terms of stability and robustness (internal signals remain bounded with a certain amount of uncertainty) and simultaneously achieve an acceptable level of performance. The approach here has been to convert the closed loop system and control synthesis problem into the interpolation setting. The interpolation formulation then serves as our mathematical representation of the design process. Lifting techniques have been used to solve the corresponding interpolation and control synthesis problems. Several applications using this multiobjective design methodology have been included to show the effectiveness of these techniques. In particular, the mixed H 2-H performance criteria with algorithm has been used on several examples including an F-18 HARV (High Angle of Attack Research Vehicle) for sensitivity performance.

The comparison of robust partial least squares regression with robust principal component regression on a real

NASA Astrophysics Data System (ADS)

Polat, Esra; Gunay, Suleyman

2013-10-01

One of the problems encountered in Multiple Linear Regression (MLR) is multicollinearity, which causes the overestimation of the regression parameters and increase of the variance of these parameters. Hence, in case of multicollinearity presents, biased estimation procedures such as classical Principal Component Regression (CPCR) and Partial Least Squares Regression (PLSR) are then performed. SIMPLS algorithm is the leading PLSR algorithm because of its speed, efficiency and results are easier to interpret. However, both of the CPCR and SIMPLS yield very unreliable results when the data set contains outlying observations. Therefore, Hubert and Vanden Branden (2003) have been presented a robust PCR (RPCR) method and a robust PLSR (RPLSR) method called RSIMPLS. In RPCR, firstly, a robust Principal Component Analysis (PCA) method for high-dimensional data on the independent variables is applied, then, the dependent variables are regressed on the scores using a robust regression method. RSIMPLS has been constructed from a robust covariance matrix for high-dimensional data and robust linear regression. The purpose of this study is to show the usage of RPCR and RSIMPLS methods on an econometric data set, hence, making a comparison of two methods on an inflation model of Turkey. The considered methods have been compared in terms of predictive ability and goodness of fit by using a robust Root Mean Squared Error of Cross-validation (R-RMSECV), a robust R2 value and Robust Component Selection (RCS) statistic.

Real time control for NASA robotic gripper

NASA Technical Reports Server (NTRS)

Salter, Carole A.; Baras, John S.

1990-01-01

The ability to easily manipulate objects in a zero gravity environment will pay a key role in future space activities. Emphasis will be placed on robotic manipulation. This will serve to increase astronaut safety and utility in addition to several other benefits. The aim is to develop control laws for the zero gravity robotic end effectors. A hybrid force/position controller will be used. Sensory data available to the controller are obtained from an array of strain gauges and a linear potentiometer. Applying well known optimal control theoretical principles, the control which minimizes the transition time between positions is obtained. A robust force control scheme is developed which allows the desired holding force to be achieved smoothly without oscillation. In addition, an algorithm is found to determine contact force and contact location.

Adaptive control of large space structures using recursive lattice filters

NASA Technical Reports Server (NTRS)

Sundararajan, N.; Goglia, G. L.

1985-01-01

The use of recursive lattice filters for identification and adaptive control of large space structures is studied. Lattice filters were used to identify the structural dynamics model of the flexible structures. This identification model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures is control engaged. This type of validation scheme prevents instability when the overall loop is closed. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods. The method uses the Linear Quadratic Guassian/Loop Transfer Recovery (LQG/LTR) approach to ensure stability against unmodeled higher frequency modes and achieves the desired performance.

Impact of Cross-Axis Structural Dynamics on Validation of Linear Models for Space Launch System

NASA Technical Reports Server (NTRS)

Pei, Jing; Derry, Stephen D.; Zhou Zhiqiang; Newsom, Jerry R.

2014-01-01

A feasibility study was performed to examine the advisability of incorporating a set of Programmed Test Inputs (PTIs) during the Space Launch System (SLS) vehicle flight. The intent of these inputs is to provide validation to the preflight models for control system stability margins, aerodynamics, and structural dynamics. During October 2009, Ares I-X program was successful in carrying out a series of PTI maneuvers which provided a significant amount of valuable data for post-flight analysis. The resulting data comparisons showed excellent agreement with the preflight linear models across the frequency spectrum of interest. However unlike Ares I-X, the structural dynamics associated with the SLS boost phase configuration are far more complex and highly coupled in all three axes. This presents a challenge when implementing this similar system identification technique to SLS. Preliminary simulation results show noticeable mismatches between PTI validation and analytical linear models in the frequency range of the structural dynamics. An alternate approach was examined which demonstrates the potential for better overall characterization of the system frequency response as well as robustness of the control design.

Myostatin inhibitors in sports drug testing: Detection of myostatin-neutralizing antibodies in plasma/serum by affinity purification and Western blotting.

PubMed

Walpurgis, Katja; Thomas, Andreas; Schänzer, Wilhelm; Thevis, Mario

2016-02-01

Myostatin is a key regulator of skeletal muscle growth and inhibition of its signaling pathway results in an increased muscle mass and function. The aim of this study was to develop a qualitative detection assay for myostatin-neutralizing antibodies for doping control purposes by using immunological approaches. To detect different types of myostatin-neutralizing antibodies irrespective of their amino acid sequence, an immunological assay specific for antibodies directed against myostatin and having a human Fc domain was established. Affinity purification and Western blotting strategies were combined to allow extracting and identifying relevant analytes from 200 μL of plasma/serum in a non-targeted approach. The assay was characterized regarding specificity, linearity, precision, robustness, and recovery. The assay was found to be highly specific, robust, and linear from 0.1 to 1 μg/mL. The precision was successfully specified at three different concentrations and the recovery of the affinity purification was 58%. Within this study, an immunological detection assay for myostatin-neutralizing antibodies present in plasma/serum specimens was developed and successfully characterized. The presented approach can easily be modified to include other therapeutic antibodies and serves as proof-of-concept for the detection of antibody-based myostatin inhibitors in doping control samples. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Does a crouched leg posture enhance running stability and robustness?

PubMed

Blum, Yvonne; Birn-Jeffery, Aleksandra; Daley, Monica A; Seyfarth, Andre

2011-07-21

Humans and birds both walk and run bipedally on compliant legs. However, differences in leg architecture may result in species-specific leg control strategies as indicated by the observed gait patterns. In this work, control strategies for stable running are derived based on a conceptual model and compared with experimental data on running humans and pheasants (Phasianus colchicus). From a model perspective, running with compliant legs can be represented by the planar spring mass model and stabilized by applying swing leg control. Here, linear adaptations of the three leg parameters, leg angle, leg length and leg stiffness during late swing phase are assumed. Experimentally observed kinematic control parameters (leg rotation and leg length change) of human and avian running are compared, and interpreted within the context of this model, with specific focus on stability and robustness characteristics. The results suggest differences in stability characteristics and applied control strategies of human and avian running, which may relate to differences in leg posture (straight leg posture in humans, and crouched leg posture in birds). It has been suggested that crouched leg postures may improve stability. However, as the system of control strategies is overdetermined, our model findings suggest that a crouched leg posture does not necessarily enhance running stability. The model also predicts different leg stiffness adaptation rates for human and avian running, and suggests that a crouched avian leg posture, which is capable of both leg shortening and lengthening, allows for stable running without adjusting leg stiffness. In contrast, in straight-legged human running, the preparation of the ground contact seems to be more critical, requiring leg stiffness adjustment to remain stable. Finally, analysis of a simple robustness measure, the normalized maximum drop, suggests that the crouched leg posture may provide greater robustness to changes in terrain height. Copyright © 2011 Elsevier Ltd. All rights reserved.

Robust Bounded Influence Tests in Linear Models

DTIC Science & Technology

1988-11-01

sensitivity analysis and bounded influence estimation. In: Evaluation of Econometric Models, J. Kmenta and J.B. Ramsey (eds.) Academic Press, New York...1R’OBUST bOUNDED INFLUENCE TESTS IN LINEA’ MODELS and( I’homas P. [lettmansperger* Tim [PennsylvanLa State UJniversity A M i0d fix pu111 rsos.p JJ 1 0...November 1988 ROBUST BOUNDED INFLUENCE TESTS IN LINEAR MODELS Marianthi Markatou The University of Iowa and Thomas P. Hettmansperger* The Pennsylvania

Robust linear discriminant models to solve financial crisis in banking sectors

NASA Astrophysics Data System (ADS)

Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Idris, Faoziah; Ali, Hazlina; Omar, Zurni

2014-12-01

Linear discriminant analysis (LDA) is a widely-used technique in patterns classification via an equation which will minimize the probability of misclassifying cases into their respective categories. However, the performance of classical estimators in LDA highly depends on the assumptions of normality and homoscedasticity. Several robust estimators in LDA such as Minimum Covariance Determinant (MCD), S-estimators and Minimum Volume Ellipsoid (MVE) are addressed by many authors to alleviate the problem of non-robustness of the classical estimates. In this paper, we investigate on the financial crisis of the Malaysian banking institutions using robust LDA and classical LDA methods. Our objective is to distinguish the "distress" and "non-distress" banks in Malaysia by using the LDA models. Hit ratio is used to validate the accuracy predictive of LDA models. The performance of LDA is evaluated by estimating the misclassification rate via apparent error rate. The results and comparisons show that the robust estimators provide a better performance than the classical estimators for LDA.

Effect of motor dynamics on nonlinear feedback robot arm control

NASA Technical Reports Server (NTRS)

Tarn, Tzyh-Jong; Li, Zuofeng; Bejczy, Antal K.; Yun, Xiaoping

1991-01-01

A nonlinear feedback robot controller that incorporates the robot manipulator dynamics and the robot joint motor dynamics is proposed. The manipulator dynamics and the motor dynamics are coupled to obtain a third-order-dynamic model, and differential geometric control theory is applied to produce a linearized and decoupled robot controller. The derived robot controller operates in the robot task space, thus eliminating the need for decomposition of motion commands into robot joint space commands. Computer simulations are performed to verify the feasibility of the proposed robot controller. The controller is further experimentally evaluated on the PUMA 560 robot arm. The experiments show that the proposed controller produces good trajectory tracking performances and is robust in the presence of model inaccuracies. Compared with a nonlinear feedback robot controller based on the manipulator dynamics only, the proposed robot controller yields conspicuously improved performance.

A methodology for the synthesis of robust feedback systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Milich, David Albert

1988-01-01

A new methodology is developed for the synthesis of linear, time-variant (LTI) controllers for multivariable LTI systems. The resulting closed-loop system is nominally stable and exhibits a known level of performance. In addition, robustness of the feedback system is guaranteed, i.e., stability and performance are retained in the presence of multiple unstructured uncertainty blocks located at various points in the feedback loop. The design technique is referred to as the Causality Recovery Methodology (CRM). The CRM relies on the Youla parameterization of all stabilizing compensators to ensure nominal stability of the feedback system. A frequency-domain inequality in terms of the structured singular value mu defines the robustness specification. The optimal compensator, with respect to the mu condition, is shown to be noncausal in general. The aim of the CRM is to find a stable, causal transfer function matrix that approximates the robustness characteristics of the optimal solution. The CRM, via a series of infinite-dimensional convex programs, produces a closed-loop system whose performance robustness is at least as good as that of any initial design. The algorithm is approximated by a finite dimensional process for the purposes of implementation. Two numerical examples confirm the potential viability of the CRM concept; however, the robustness improvement comes at the expense of increased computational burden and compensator complexity.

Simple robust control laws for robot manipulators. Part 2: Adaptive case

NASA Technical Reports Server (NTRS)

Bayard, D. S.; Wen, J. T.

1987-01-01

A new class of asymptotically stable adaptive control laws is introduced for application to the robotic manipulator. Unlike most applications of adaptive control theory to robotic manipulators, this analysis addresses the nonlinear dynamics directly without approximation, linearization, or ad hoc assumptions, and utilizes a parameterization based on physical (time-invariant) quantities. This approach is made possible by using energy-like Lyapunov functions which retain the nonlinear character and structure of the dynamics, rather than simple quadratic forms which are ubiquitous to the adaptive control literature, and which have bound the theory tightly to linear systems with unknown parameters. It is a unique feature of these results that the adaptive forms arise by straightforward certainty equivalence adaptation of their nonadaptive counterparts found in the companion to this paper (i.e., by replacing unknown quantities by their estimates) and that this simple approach leads to asymptotically stable closed-loop adaptive systems. Furthermore, it is emphasized that this approach does not require convergence of the parameter estimates (i.e., via persistent excitation), invertibility of the mass matrix estimate, or measurement of the joint accelerations.

Control of Multilayer Networks

PubMed Central

Menichetti, Giulia; Dall’Asta, Luca; Bianconi, Ginestra

2016-01-01

The controllability of a network is a theoretical problem of relevance in a variety of contexts ranging from financial markets to the brain. Until now, network controllability has been characterized only on isolated networks, while the vast majority of complex systems are formed by multilayer networks. Here we build a theoretical framework for the linear controllability of multilayer networks by mapping the problem into a combinatorial matching problem. We found that correlating the external signals in the different layers can significantly reduce the multiplex network robustness to node removal, as it can be seen in conjunction with a hybrid phase transition occurring in interacting Poisson networks. Moreover we observe that multilayer networks can stabilize the fully controllable multiplex network configuration that can be stable also when the full controllability of the single network is not stable. PMID:26869210

Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays.

PubMed

Mejias, Jorge F; Payeur, Alexandre; Selin, Erik; Maler, Leonard; Longtin, André

2014-01-01

The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry-also known as "open-loop feedback"-, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves) via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain.

Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays

PubMed Central

Mejias, Jorge F.; Payeur, Alexandre; Selin, Erik; Maler, Leonard; Longtin, André

2014-01-01

The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry—also known as “open-loop feedback”—, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves) via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain. PMID:24616694

Uncertainty Modeling for Robustness Analysis of Control Upset Prevention and Recovery Systems

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.; Khong, Thuan H.; Shin, Jong-Yeob; Kwatny, Harry; Chang, Bor-Chin; Balas, Gary J.

2005-01-01

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. Such systems (developed for failure detection, identification, and reconfiguration, as well as upset recovery) need to be evaluated over broad regions of the flight envelope and under extreme flight conditions, and should include various sources of uncertainty. However, formulation of linear fractional transformation (LFT) models for representing system uncertainty can be very difficult for complex parameter-dependent systems. This paper describes a preliminary LFT modeling software tool which uses a matrix-based computational approach that can be directly applied to parametric uncertainty problems involving multivariate matrix polynomial dependencies. Several examples are presented (including an F-16 at an extreme flight condition, a missile model, and a generic example with numerous crossproduct terms), and comparisons are given with other LFT modeling tools that are currently available. The LFT modeling method and preliminary software tool presented in this paper are shown to compare favorably with these methods.

Outcome based state budget allocation for diabetes prevention programs using multi-criteria optimization with robust weights.

PubMed

Mehrotra, Sanjay; Kim, Kibaek

2011-12-01

We consider the problem of outcomes based budget allocations to chronic disease prevention programs across the United States (US) to achieve greater geographical healthcare equity. We use Diabetes Prevention and Control Programs (DPCP) by the Center for Disease Control and Prevention (CDC) as an example. We present a multi-criteria robust weighted sum model for such multi-criteria decision making in a group decision setting. The principal component analysis and an inverse linear programming techniques are presented and used to study the actual 2009 budget allocation by CDC. Our results show that the CDC budget allocation process for the DPCPs is not likely model based. In our empirical study, the relative weights for different prevalence and comorbidity factors and the corresponding budgets obtained under different weight regions are discussed. Parametric analysis suggests that money should be allocated to states to promote diabetes education and to increase patient-healthcare provider interactions to reduce disparity across the US.

Analysis and design of gain scheduled control systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Shamma, Jeff S.

1988-01-01

Gain scheduling, as an idea, is to construct a global feedback control system for a time varying and/or nonlinear plant from a collection of local time invariant designs. However in the absence of a sound analysis, these designs come with no guarantees on the robustness, performance, or even nominal stability of the overall gain schedule design. Such an analysis is presented for three types of gain scheduling situations: (1) a linear parameter varying plant scheduling on its exogenous parameters, (2) a nonlinear plant scheduling on a prescribed reference trajectory, and (3) a nonlinear plant scheduling on the current plant output. Conditions are given which guarantee that the stability, robustness, and performance properties of the fixed operating point designs carry over to the global gain scheduled designs, such as the scheduling variable should vary slowly and capture the plants nonlinearities. Finally, an alternate design framework is proposed which removes the slowing varying restriction or gain scheduled systems. This framework addresses some fundamental feedback issues previously ignored in standard gain.

Robust adaptive controller design for a class of uncertain nonlinear systems using online T-S fuzzy-neural modeling approach.

PubMed

Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian

2011-04-01

This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.

H Infinity Control of Magnetic Bearings to Ensure Both System and External Periodic Disturbance Robustness

NASA Technical Reports Server (NTRS)

Jiang, Yuhong; Zmood, R. B.

1996-01-01

Both self-excited and forced disturbances often lead to severe rotor vibrations in a magnetic bearing systems with long slender shafts. This problem has been studied using the H-infinity method, and stability with good robustness can be achieved for the linearized model of a magnetic bearing when small transient disturbances are applied. In this paper, the H-infinity control method for self-excited and forced disturbances is first reviewed. It is then applied to the control of a magnetic bearing rotor system. In modelling the system, the shaft is first discretized into 18 finite elements and then three levels of condensation are applied. This leads to a system with three masses and three compliant elements which can be described by six state variable coordinates. Simulation of the resultant system design has been performed at speeds up to 10,000 rpm. Disturbances in terms of different initial displacements, initial impulses, and external periodic inputs have been imposed. The simulation results show that good stability can be achieved under these different transient disturbances using the proposed controller while at the same time reducing the sensitivity to external periodic disturbances.

Effect of smoothing on robust chaos.

PubMed

Deshpande, Amogh; Chen, Qingfei; Wang, Yan; Lai, Ying-Cheng; Do, Younghae

2010-08-01

In piecewise-smooth dynamical systems, situations can arise where the asymptotic attractors of the system in an open parameter interval are all chaotic (e.g., no periodic windows). This is the phenomenon of robust chaos. Previous works have established that robust chaos can occur through the mechanism of border-collision bifurcation, where border is the phase-space region where discontinuities in the derivatives of the dynamical equations occur. We investigate the effect of smoothing on robust chaos and find that periodic windows can arise when a small amount of smoothness is present. We introduce a parameter of smoothing and find that the measure of the periodic windows in the parameter space scales linearly with the parameter, regardless of the details of the smoothing function. Numerical support and a heuristic theory are provided to establish the scaling relation. Experimental evidence of periodic windows in a supposedly piecewise linear dynamical system, which has been implemented as an electronic circuit, is also provided.

Robust Linear Models for Cis-eQTL Analysis.

PubMed

Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C

2015-01-01

Expression Quantitative Trait Loci (eQTL) analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives), and to some extent also type I errors (false positives). Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.

Development of Control Models and a Robust Multivariable Controller for Surface Shape Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winters, Scott Eric

2003-06-18

Surface shape control techniques are applied to many diverse disciplines, such as adaptive optics, noise control, aircraft flutter control and satellites, with an objective to achieve a desirable shape for an elastic body by the application of distributed control forces. Achieving the desirable shape is influenced by many factors, such as, actuator locations, sensor locations, surface precision and controller performance. Building prototypes to complete design optimizations or controller development can be costly or impractical. This shortfall, puts significant value in developing accurate modeling and control simulation approaches. This thesis focuses on the field of adaptive optics, although these developments havemore » the potential for application in many other fields. A static finite element model is developed and validated using a large aperture interferometer system. This model is then integrated into a control model using a linear least squares algorithm and Shack-Hartmann sensor. The model is successfully exercised showing functionality for various wavefront aberrations. Utilizing a verified model shows significant value in simulating static surface shape control problems with quantifiable uncertainties. A new dynamic model for a seven actuator deformable mirror is presented and its accuracy is proven through experiment. Bond graph techniques are used to generate the state space model of the multi-actuator deformable mirror including piezo-electric actuator dynamics. Using this verified model, a robust multi-input multi-output (MIMO) H ∞ controller is designed and implemented. This controller proved superior performance as compared to a standard proportional-integral controller (PI) design.« less

Closed-loop stability of linear quadratic optimal systems in the presence of modeling errors

NASA Technical Reports Server (NTRS)

Toda, M.; Patel, R.; Sridhar, B.

1976-01-01

The well-known stabilizing property of linear quadratic state feedback design is utilized to evaluate the robustness of a linear quadratic feedback design in the presence of modeling errors. Two general conditions are obtained for allowable modeling errors such that the resulting closed-loop system remains stable. One of these conditions is applied to obtain two more particular conditions which are readily applicable to practical situations where a designer has information on the bounds of modeling errors. Relations are established between the allowable parameter uncertainty and the weighting matrices of the quadratic performance index, thereby enabling the designer to select appropriate weighting matrices to attain a robust feedback design.

A new design of robust H∞ sliding mode control for uncertain stochastic T-S fuzzy time-delay systems.

PubMed

Gao, Qing; Feng, Gang; Xi, Zhiyu; Wang, Yong; Qiu, Jianbin

2014-09-01

In this paper, a novel dynamic sliding mode control scheme is proposed for a class of uncertain stochastic nonlinear time-delay systems represented by Takagi-Sugeno fuzzy models. The key advantage of the proposed scheme is that two very restrictive assumptions in most existing sliding mode control approaches for stochastic fuzzy systems have been removed. It is shown that the closed-loop control system trajectories can be driven onto the sliding surface in finite time almost certainly. It is also shown that the stochastic stability of the resulting sliding motion can be guaranteed in terms of linear matrix inequalities; moreover, the sliding-mode controller can be obtained simultaneously. Simulation results illustrating the advantages and effectiveness of the proposed approaches are also provided.

Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2012-01-01

This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

Model Checking Techniques for Assessing Functional Form Specifications in Censored Linear Regression Models.

PubMed

León, Larry F; Cai, Tianxi

2012-04-01

In this paper we develop model checking techniques for assessing functional form specifications of covariates in censored linear regression models. These procedures are based on a censored data analog to taking cumulative sums of "robust" residuals over the space of the covariate under investigation. These cumulative sums are formed by integrating certain Kaplan-Meier estimators and may be viewed as "robust" censored data analogs to the processes considered by Lin, Wei & Ying (2002). The null distributions of these stochastic processes can be approximated by the distributions of certain zero-mean Gaussian processes whose realizations can be generated by computer simulation. Each observed process can then be graphically compared with a few realizations from the Gaussian process. We also develop formal test statistics for numerical comparison. Such comparisons enable one to assess objectively whether an apparent trend seen in a residual plot reects model misspecification or natural variation. We illustrate the methods with a well known dataset. In addition, we examine the finite sample performance of the proposed test statistics in simulation experiments. In our simulation experiments, the proposed test statistics have good power of detecting misspecification while at the same time controlling the size of the test.

Artificial Neural Identification and LMI Transformation for Model Reduction-Based Control of the Buck Switch-Mode Regulator

NASA Astrophysics Data System (ADS)

Al-Rabadi, Anas N.

2009-10-01

This research introduces a new method of intelligent control for the control of the Buck converter using newly developed small signal model of the pulse width modulation (PWM) switch. The new method uses supervised neural network to estimate certain parameters of the transformed system matrix [Ã]. Then, a numerical algorithm used in robust control called linear matrix inequality (LMI) optimization technique is used to determine the permutation matrix [P] so that a complete system transformation {[B˜], [C˜], [Ẽ]} is possible. The transformed model is then reduced using the method of singular perturbation, and state feedback control is applied to enhance system performance. The experimental results show that the new control methodology simplifies the model in the Buck converter and thus uses a simpler controller that produces the desired system response for performance enhancement.

In-Flight Suppression of an Unstable F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen S.; Gilligan, Eric T.; Wall, John H.; Miller, Christopher J.; Hanson, Curtis E.; Orr, Jeb S.

2015-01-01

NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off-nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using post-flight frequency-domain reconstruction, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

A novel integrated approach for path following and directional stability control of road vehicles after a tire blow-out

NASA Astrophysics Data System (ADS)

Wang, Fei; Chen, Hong; Guo, Konghui; Cao, Dongpu

2017-09-01

The path following and directional stability are two crucial problems when a road vehicle experiences a tire blow-out or sudden tire failure. Considering the requirement of rapid road vehicle motion control during a tire blow-out, this article proposes a novel linearized decoupling control procedure with three design steps for a class of second order multi-input-multi-output non-affine system. The evaluating indicators for controller performance are presented and a performance related control parameter distribution map is obtained based on the stochastic algorithm which is an innovation for non-blind parameter adjustment in engineering implementation. The analysis on the robustness of the proposed integrated controller is also performed. The simulation studies for a range of driving conditions are conducted, to demonstrate the effectiveness of the proposed controller.

Robust biological parametric mapping: an improved technique for multimodal brain image analysis

NASA Astrophysics Data System (ADS)

Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

2011-03-01

Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

Vehicle active steering control research based on two-DOF robust internal model control

NASA Astrophysics Data System (ADS)

Wu, Jian; Liu, Yahui; Wang, Fengbo; Bao, Chunjiang; Sun, Qun; Zhao, Youqun

2016-07-01

Because of vehicle's external disturbances and model uncertainties, robust control algorithms have obtained popularity in vehicle stability control. The robust control usually gives up performance in order to guarantee the robustness of the control algorithm, therefore an improved robust internal model control(IMC) algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness. The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties. In order to separate the design process of model tracking from the robustness design process, the improved 2 degree of freedom(DOF) robust internal model controller structure is given from the standard Youla parameterization. Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm, on the basis of a nonlinear vehicle simulation model with a magic tyre model. Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance, which can enhance the vehicle stability and handling, regardless of variations of the vehicle model parameters and the external crosswind interferences. Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.

Development and validation of a method for mercury determination in seawater for the process control of a candidate certified reference material.

PubMed

Sánchez, Raquel; Snell, James; Held, Andrea; Emons, Hendrik

2015-08-01

A simple, robust and reliable method for mercury determination in seawater matrices based on the combination of cold vapour generation and inductively coupled plasma mass spectrometry (CV-ICP-MS) and its complete in-house validation are described. The method validation covers parameters such as linearity, limit of detection (LOD), limit of quantification (LOQ), trueness, repeatability, intermediate precision and robustness. A calibration curve covering the whole working range was achieved with coefficients of determination typically higher than 0.9992. The repeatability of the method (RSDrep) was 0.5 %, and the intermediate precision was 2.3 % at the target mass fraction of 20 ng/kg. Moreover, the method was robust with respect to the salinity of the seawater. The limit of quantification was 2.7 ng/kg, which corresponds to 13.5 % of the target mass fraction in the future certified reference material (20 ng/kg). An uncertainty budget for the measurement of mercury in seawater has been established. The relative expanded (k = 2) combined uncertainty is 6 %. The performance of the validated method was demonstrated by generating results for process control and a homogeneity study for the production of a candidate certified reference material.

Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

PubMed

Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

2010-09-01

This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.

A Higher Harmonic Optimal Controller to Optimise Rotorcraft Aeromechanical Behaviour

NASA Technical Reports Server (NTRS)

Leyland, Jane Anne

1996-01-01

Three methods to optimize rotorcraft aeromechanical behavior for those cases where the rotorcraft plant can be adequately represented by a linear model system matrix were identified and implemented in a stand-alone code. These methods determine the optimal control vector which minimizes the vibration metric subject to constraints at discrete time points, and differ from the commonly used non-optimal constraint penalty methods such as those employed by conventional controllers in that the constraints are handled as actual constraints to an optimization problem rather than as just additional terms in the performance index. The first method is to use a Non-linear Programming algorithm to solve the problem directly. The second method is to solve the full set of non-linear equations which define the necessary conditions for optimality. The third method is to solve each of the possible reduced sets of equations defining the necessary conditions for optimality when the constraints are pre-selected to be either active or inactive, and then to simply select the best solution. The effects of maneuvers and aeroelasticity on the systems matrix are modelled by using a pseudo-random pseudo-row-dependency scheme to define the systems matrix. Cases run to date indicate that the first method of solution is reliable, robust, and easiest to use, and that it was superior to the conventional controllers which were considered.

A new decentralised controller design method for a class of strongly interconnected systems

NASA Astrophysics Data System (ADS)

Duan, Zhisheng; Jiang, Zhong-Ping; Huang, Lin

2017-02-01

In this paper, two interconnected structures are first discussed, under which some closed-loop subsystems must be unstable to make the whole interconnected system stable, which can be viewed as a kind of strongly interconnected systems. Then, comparisons with small gain theorem are discussed and large gain interconnected characteristics are shown. A new approach for the design of decentralised controllers is presented by determining the Lyapunov function structure previously, which allows the existence of unstable subsystems. By fully utilising the orthogonal space information of input matrix, some new understandings are presented for the construction of Lyapunov matrix. This new method can deal with decentralised state feedback, static output feedback and dynamic output feedback controllers in a unified framework. Furthermore, in order to reduce the design conservativeness and deal with robustness, a new robust decentralised controller design method is given by combining with the parameter-dependent Lyapunov function method. Some basic rules are provided for the choice of initial variables in Lyapunov matrix or new introduced slack matrices. As byproducts, some linear matrix inequality based sufficient conditions are established for centralised static output feedback stabilisation. Effects of unstable subsystems in nonlinear Lur'e systems are further discussed. The corresponding decentralised controller design method is presented for absolute stability. The examples illustrate that the new method is significantly effective.

[Regulation of hypnosis in Propofol anesthesia administration based on non-linear control strategy].

PubMed

Ilyas, Muhammad; Khaqan, Ali; Iqbal, Jamshed; Riaz, Raja Ali

Continuous adjustment of Propofol in manual delivery of anesthesia for conducting a surgical procedure overburdens the workload of an anesthetist who is working in a multi-tasking scenario. Going beyond manual administration and Target Controlled Infusion, closed-loop control of Propofol infusion has the potential to offer several benefits in terms of handling perturbations and reducing the effect of inter-patient variability. This paper proposes a closed-loop automated drug administration approach to control Depth Of Hypnosis in anesthesia. In contrast with most of the existing research on anesthesia control which makes use of linear control strategies or their improved variants, the novelty of the present research lies in applying robust control strategy i.e. Sliding Mode Control to accurately control drug infusion. Based on the derived patient's model, the designed controller uses measurements from EEG to regulate DOH on Bispectral Index by controlling infusion rate of Propofol. The performance of the controller is investigated and characterized with real dataset of 8 patients undergoing surgery. Results of this in silico study indicate that for all the patients, with 0% overshoot observed, the steady state error lies in between ±5. Clinically, this implies that in all the cases, without any overdose, the controller maintains the desired DOH level for smooth conduction of surgical procedures. Copyright © 2016 Sociedade Brasileira de Anestesiologia. Publicado por Elsevier Editora Ltda. All rights reserved.

Regulation of hypnosis in Propofol anesthesia administration based on non-linear control strategy.

PubMed

Ilyas, Muhammad; Khaqan, Ali; Iqbal, Jamshed; Riaz, Raja Ali

Continuous adjustment of Propofol in manual delivery of anesthesia for conducting a surgical procedure overburdens the workload of an anesthetist who is working in a multi-tasking scenario. Going beyond manual administration and Target Controlled Infusion, closed-loop control of Propofol infusion has the potential to offer several benefits in terms of handling perturbations and reducing the effect of inter-patient variability. This paper proposes a closed-loop automated drug administration approach to control Depth Of Hypnosis in anesthesia. In contrast with most of the existing research on anesthesia control which makes use of linear control strategies or their improved variants, the novelty of the present research lies in applying robust control strategy i.e. Sliding Mode Control to accurately control drug infusion. Based on the derived patient's model, the designed controller uses measurements from EEG to regulate DOH on Bispectral Index by controlling infusion rate of Propofol. The performance of the controller is investigated and characterized with real dataset of 8 patients undergoing surgery. Results of this in silico study indicate that for all the patients, with 0% overshoot observed, the steady state error lies in between ±5. Clinically, this implies that in all the cases, without any overdose, the controller maintains the desired DOH level for smooth conduction of surgical procedures. Copyright © 2016 Sociedade Brasileira de Anestesiologia. Published by Elsevier Editora Ltda. All rights reserved.

Robust sensor fault detection and isolation of gas turbine engines subjected to time-varying parameter uncertainties

NASA Astrophysics Data System (ADS)

Pourbabaee, Bahareh; Meskin, Nader; Khorasani, Khashayar

2016-08-01

In this paper, a novel robust sensor fault detection and isolation (FDI) strategy using the multiple model-based (MM) approach is proposed that remains robust with respect to both time-varying parameter uncertainties and process and measurement noise in all the channels. The scheme is composed of robust Kalman filters (RKF) that are constructed for multiple piecewise linear (PWL) models that are constructed at various operating points of an uncertain nonlinear system. The parameter uncertainty is modeled by using a time-varying norm bounded admissible structure that affects all the PWL state space matrices. The robust Kalman filter gain matrices are designed by solving two algebraic Riccati equations (AREs) that are expressed as two linear matrix inequality (LMI) feasibility conditions. The proposed multiple RKF-based FDI scheme is simulated for a single spool gas turbine engine to diagnose various sensor faults despite the presence of parameter uncertainties, process and measurement noise. Our comparative studies confirm the superiority of our proposed FDI method when compared to the methods that are available in the literature.

Control of variable speed variable pitch wind turbine based on a disturbance observer

NASA Astrophysics Data System (ADS)

Ren, Haijun; Lei, Xin

2017-11-01

In this paper, a novel sliding mode controller based on disturbance observer (DOB) to optimize the efficiency of variable speed variable pitch (VSVP) wind turbine is developed and analyzed. Due to the highly nonlinearity of the VSVP system, the model is linearly processed to obtain the state space model of the system. Then, a conventional sliding mode controller is designed and a DOB is added to estimate wind speed. The proposed control strategy can successfully deal with the random nature of wind speed, the nonlinearity of VSVP system, the uncertainty of parameters and external disturbance. Via adding the observer to the sliding mode controller, it can greatly reduce the chattering produced by the sliding mode switching gain. The simulation results show that the proposed control system has the effectiveness and robustness.

Robust, Practical Adaptive Control for Launch Vehicles

NASA Technical Reports Server (NTRS)

Orr, Jeb. S.; VanZwieten, Tannen S.

2012-01-01

A modern mechanization of a classical adaptive control concept is presented with an application to launch vehicle attitude control systems. Due to a rigorous flight certification environment, many adaptive control concepts are infeasible when applied to high-risk aerospace systems; methods of stability analysis are either intractable for high complexity models or cannot be reconciled in light of classical requirements. Furthermore, many adaptive techniques appearing in the literature are not suitable for application to conditionally stable systems with complex flexible-body dynamics, as is often the case with launch vehicles. The present technique is a multiplicative forward loop gain adaptive law similar to that used for the NASA X-15 flight research vehicle. In digital implementation with several novel features, it is well-suited to application on aerodynamically unstable launch vehicles with thrust vector control via augmentation of the baseline attitude/attitude-rate feedback control scheme. The approach is compatible with standard design features of autopilots for launch vehicles, including phase stabilization of lateral bending and slosh via linear filters. In addition, the method of assessing flight control stability via classical gain and phase margins is not affected under reasonable assumptions. The algorithm s ability to recover from certain unstable operating regimes can in fact be understood in terms of frequency-domain criteria. Finally, simulation results are presented that confirm the ability of the algorithm to improve performance and robustness in realistic failure scenarios.

Using Length of Stay to Control for Unobserved Heterogeneity When Estimating Treatment Effect on Hospital Costs with Observational Data: Issues of Reliability, Robustness, and Usefulness.

PubMed

May, Peter; Garrido, Melissa M; Cassel, J Brian; Morrison, R Sean; Normand, Charles

2016-10-01

To evaluate the sensitivity of treatment effect estimates when length of stay (LOS) is used to control for unobserved heterogeneity when estimating treatment effect on cost of hospital admission with observational data. We used data from a prospective cohort study on the impact of palliative care consultation teams (PCCTs) on direct cost of hospital care. Adult patients with an advanced cancer diagnosis admitted to five large medical and cancer centers in the United States between 2007 and 2011 were eligible for this study. Costs were modeled using generalized linear models with a gamma distribution and a log link. We compared variability in estimates of PCCT impact on hospitalization costs when LOS was used as a covariate, as a sample parameter, and as an outcome denominator. We used propensity scores to account for patient characteristics associated with both PCCT use and total direct hospitalization costs. We analyzed data from hospital cost databases, medical records, and questionnaires. Our propensity score weighted sample included 969 patients who were discharged alive. In analyses of hospitalization costs, treatment effect estimates are highly sensitive to methods that control for LOS, complicating interpretation. Both the magnitude and significance of results varied widely with the method of controlling for LOS. When we incorporated intervention timing into our analyses, results were robust to LOS-controls. Treatment effect estimates using LOS-controls are not only suboptimal in terms of reliability (given concerns over endogeneity and bias) and usefulness (given the need to validate the cost-effectiveness of an intervention using overall resource use for a sample defined at baseline) but also in terms of robustness (results depend on the approach taken, and there is little evidence to guide this choice). To derive results that minimize endogeneity concerns and maximize external validity, investigators should match and analyze treatment and comparison arms on baseline factors only. Incorporating intervention timing may deliver results that are more reliable, more robust, and more useful than those derived using LOS-controls. © Health Research and Educational Trust.

Passivity-based control of linear time-invariant systems modelled by bond graph

NASA Astrophysics Data System (ADS)

Galindo, R.; Ngwompo, R. F.

2018-02-01

Closed-loop control systems are designed for linear time-invariant (LTI) controllable and observable systems modelled by bond graph (BG). Cascade and feedback interconnections of BG models are realised through active bonds with no loading effect. The use of active bonds may lead to non-conservation of energy and the overall system is modelled by proposed pseudo-junction structures. These structures are build by adding parasitic elements to the BG models and the overall system may become singularly perturbed. The structures for these interconnections can be seen as consisting of inner structures that satisfy energy conservation properties and outer structures including multiport-coupled dissipative fields. These fields highlight energy properties like passivity that are useful for control design. In both interconnections, junction structures and dissipative fields for the controllers are proposed, and passivity is guaranteed for the closed-loop systems assuring robust stability. The cascade interconnection is applied to the structural representation of closed-loop transfer functions, when a stabilising controller is applied to a given nominal plant. Applications are given when the plant and the controller are described by state-space realisations. The feedback interconnection is used getting necessary and sufficient stability conditions based on the closed-loop characteristic polynomial, solving a pole-placement problem and achieving zero-stationary state error.

NL(q) Theory: A Neural Control Framework with Global Asymptotic Stability Criteria.

PubMed

Vandewalle, Joos; De Moor, Bart L.R.; Suykens, Johan A.K.

1997-06-01

In this paper a framework for model-based neural control design is presented, consisting of nonlinear state space models and controllers, parametrized by multilayer feedforward neural networks. The models and closed-loop systems are transformed into so-called NL(q) system form. NL(q) systems represent a large class of nonlinear dynamical systems consisting of q layers with alternating linear and static nonlinear operators that satisfy a sector condition. For such NL(q)s sufficient conditions for global asymptotic stability, input/output stability (dissipativity with finite L(2)-gain) and robust stability and performance are presented. The stability criteria are expressed as linear matrix inequalities. In the analysis problem it is shown how stability of a given controller can be checked. In the synthesis problem two methods for neural control design are discussed. In the first method Narendra's dynamic backpropagation for tracking on a set of specific reference inputs is modified with an NL(q) stability constraint in order to ensure, e.g., closed-loop stability. In a second method control design is done without tracking on specific reference inputs, but based on the input/output stability criteria itself, within a standard plant framework as this is done, for example, in H( infinity ) control theory and &mgr; theory. Copyright 1997 Elsevier Science Ltd.

Synthesis of nonlinear frequency responses with experimentally extracted nonlinear modes

NASA Astrophysics Data System (ADS)

Peter, Simon; Scheel, Maren; Krack, Malte; Leine, Remco I.

2018-02-01

Determining frequency response curves is a common task in the vibration analysis of nonlinear systems. Measuring nonlinear frequency responses is often challenging and time consuming due to, e.g., coexisting stable or unstable vibration responses and structure-exciter-interaction. The aim of the current paper is to develop a method for the synthesis of nonlinear frequency responses near an isolated resonance, based on data that can be easily and automatically obtained experimentally. The proposed purely experimental approach relies on (a) a standard linear modal analysis carried out at low vibration levels and (b) a phase-controlled tracking of the backbone curve of the considered forced resonance. From (b), the natural frequency and vibrational deflection shape are directly obtained as a function of the vibration level. Moreover, a damping measure can be extracted by power considerations or from the linear modal analysis. In accordance with the single nonlinear mode assumption, the near-resonant frequency response can then be synthesized using this data. The method is applied to a benchmark structure consisting of a cantilevered beam attached to a leaf spring undergoing large deflections. The results are compared with direct measurements of the frequency response. The proposed approach is fast, robust and provides a good estimate for the frequency response. It is also found that direct frequency response measurement is less robust due to bifurcations and using a sine sweep excitation with a conventional force controller leads to underestimation of maximum vibration response.

The Effects of School Gardens on Children's Science Knowledge: A randomized controlled trial of low-income elementary schools

NASA Astrophysics Data System (ADS)

Wells, Nancy M.; Myers, Beth M.; Todd, Lauren E.; Barale, Karen; Gaolach, Brad; Ferenz, Gretchen; Aitken, Martha; Henderson, Charles R., , Jr.; Tse, Caroline; Pattison, Karen Ostlie; Taylor, Cayla; Connerly, Laura; Carson, Janet B.; Gensemer, Alexandra Z.; Franz, Nancy K.; Falk, Elizabeth

2015-11-01

This randomized controlled trial or 'true experiment' examines the effects of a school garden intervention on the science knowledge of elementary school children. Schools were randomly assigned to a group that received the garden intervention (n = 25) or to a waitlist control group that received the garden intervention at the end of the study (n = 24). The garden intervention consisted of both raised-bed garden kits and a series of 19 lessons. Schools, located in the US states of Arkansas, Iowa, Washington, and New York, were all low-income as defined by having 50% or more children qualifying for the federal school lunch program. Participants were students in second, fourth, and fifth grade (ages 6-12) at baseline (n = 3,061). Science knowledge was measured using a 7-item questionnaire focused on nutritional science and plant science. The survey was administered at baseline (Fall 2011) and at three time points during the intervention (Spring 2012, Fall 2012, and Spring 2013). Garden intervention fidelity (GIF) captured the robustness or fidelity of the intervention delivered in each classroom based on both lessons delivered and garden activities. Analyses were conducted using general linear mixed models. Survey data indicated that among children in the garden intervention, science knowledge increased from baseline to follow-up more than among control group children. However, science knowledge scores were uniformly poor and gains were very modest. GIF, which takes into account the robustness of the intervention, revealed a dose-response relation with science knowledge: more robust or substantial intervention implementations corresponded to stronger treatment effects.

Improving Multi-Objective Management of Water Quality Tipping Points: Revisiting the Classical Shallow Lake Problem

NASA Astrophysics Data System (ADS)

Quinn, J. D.; Reed, P. M.; Keller, K.

2015-12-01

Recent multi-objective extensions of the classical shallow lake problem are useful for exploring the conceptual and computational challenges that emerge when managing irreversible water quality tipping points. Building on this work, we explore a four objective version of the lake problem where a hypothetical town derives economic benefits from polluting a nearby lake, but at the risk of irreversibly tipping the lake into a permanently polluted state. The trophic state of the lake exhibits non-linear threshold dynamics; below some critical phosphorus (P) threshold it is healthy and oligotrophic, but above this threshold it is irreversibly eutrophic. The town must decide how much P to discharge each year, a decision complicated by uncertainty in the natural P inflow to the lake. The shallow lake problem provides a conceptually rich set of dynamics, low computational demands, and a high level of mathematical difficulty. These properties maximize its value for benchmarking the relative merits and limitations of emerging decision support frameworks, such as Direct Policy Search (DPS). Here, we explore the use of DPS as a formal means of developing robust environmental pollution control rules that effectively account for deeply uncertain system states and conflicting objectives. The DPS reformulation of the shallow lake problem shows promise in formalizing pollution control triggers and signposts, while dramatically reducing the computational complexity of the multi-objective pollution control problem. More broadly, the insights from the DPS variant of the shallow lake problem formulated in this study bridge emerging work related to socio-ecological systems management, tipping points, robust decision making, and robust control.

Applied Joint-Space Torque and Stiffness Control of Tendon-Driven Fingers

NASA Technical Reports Server (NTRS)

Abdallah, Muhammad E.; Platt, Robert, Jr.; Wampler, Charles W.; Hargrave, Brian

2010-01-01

Existing tendon-driven fingers have applied force control through independent tension controllers on each tendon, i.e. in the tendon-space. The coupled kinematics of the tendons, however, cause such controllers to exhibit a transient coupling in their response. This problem can be resolved by alternatively framing the controllers in the joint-space of the manipulator. This work presents a joint-space torque control law that demonstrates both a decoupled and significantly faster response than an equivalent tendon-space formulation. The law also demonstrates greater speed and robustness than comparable PI controllers. In addition, a tension distribution algorithm is presented here to allocate forces from the joints to the tendons. It allocates the tensions so that they satisfy both an upper and lower bound, and it does so without requiring linear programming or open-ended iterations. The control law and tension distribution algorithm are implemented on the robotic hand of Robonaut-2.

A High-Authority/Low-Authority Control Strategy for Coupled Aircraft-Style Bays

NASA Technical Reports Server (NTRS)

Schiller, N. H.; Fuller, C. R.; Cabell, R. H.

2006-01-01

This paper presents a numerical investigation of an active structural acoustic control strategy for coupled aircraft-style bays. While structural coupling can destabilize or limit the performance of some model-based decentralized control systems, fullycoupled centralized control strategies are impractical for typical aircraft containing several hundred bays. An alternative is to use classical rate feedback with matched, collocated transducer pairs to achieve active damping. Unfortunately, due to the conservative nature of this strategy, stability is guaranteed at the expense of achievable noise reduction. Therefore, this paper describes the development of a combined control strategy using robust active damping in addition to a high-authority controller based on linear quadratic Gaussian (LQG) theory. The combined control system is evaluated on a tensioned, two-bay model using piezoceramic actuators and ideal point velocity sensors. Transducer placement on the two-bay structure is discussed, and the advantages of a combined control strategy are presented.

L(sub 1) Adaptive Flight Control System: Flight Evaluation and Technology Transition

NASA Technical Reports Server (NTRS)

Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Isaac; Gregory, Irene M.; Cao, Chengyu

2010-01-01

Certification of adaptive control technologies for both manned and unmanned aircraft represent a major challenge for current Verification and Validation techniques. A (missing) key step towards flight certification of adaptive flight control systems is the definition and development of analysis tools and methods to support Verification and Validation for nonlinear systems, similar to the procedures currently used for linear systems. In this paper, we describe and demonstrate the advantages of L(sub l) adaptive control architectures for closing some of the gaps in certification of adaptive flight control systems, which may facilitate the transition of adaptive control into military and commercial aerospace applications. As illustrative examples, we present the results of a piloted simulation evaluation on the NASA AirSTAR flight test vehicle, and results of an extensive flight test program conducted by the Naval Postgraduate School to demonstrate the advantages of L(sub l) adaptive control as a verifiable robust adaptive flight control system.

Autonomous spacecraft attitude control using magnetic torquing only

NASA Technical Reports Server (NTRS)

Musser, Keith L.; Ebert, Ward L.

1989-01-01

Magnetic torquing of spacecraft has been an important mechanism for attitude control since the earliest satellites were launched. Typically a magnetic control system has been used for precession/nutation damping for gravity-gradient stabilized satellites, momentum dumping for systems equipped with reaction wheels, or momentum-axis pointing for spinning and momentum-biased spacecraft. Although within the small satellite community there has always been interest in expensive, light-weight, and low-power attitude control systems, completely magnetic control systems have not been used for autonomous three-axis stabilized spacecraft due to the large computational requirements involved. As increasingly more powerful microprocessors have become available, this has become less of an impediment. These facts have motivated consideration of the all-magnetic attitude control system presented here. The problem of controlling spacecraft attitude using only magnetic torquing is cast into the form of the Linear Quadratic Regulator (LQR), resulting in a linear feedback control law. Since the geomagnetic field along a satellite trajectory is not constant, the system equations are time varying. As a result, the optimal feedback gains are time-varying. Orbit geometry is exploited to treat feedback gains as a function of position rather than time, making feasible the onboard solution of the optimal control problem. In simulations performed to date, the control laws have shown themselves to be fairly robust and a good candidate for an onboard attitude control system.

Manipulation of ultracold Rb atoms using a single linearly chirped laser pulse.

PubMed

Collins, T A; Malinovskaya, S A

2012-06-15

At ultracold temperatures, atoms are free from thermal motion, which makes them ideal objects of investigations aiming to advance high-precision spectroscopy, metrology, quantum computation, producing Bose condensates, etc. The quantum state of ultracold atoms may be created and manipulated by making use of quantum control methods employing low-intensity pulses. We theoretically investigate population dynamics of ultracold Rb vapor induced by nanosecond linearly chirped pulses having kW/cm2 beam intensity and show a possibility of controllable population transfer between hyperfine (HpF) levels of 5(2)/S(1/2) state through Raman transitions. Satisfying the one-photon resonance condition with the lowest of the HpF states of 5(2)/P(1/2) or 5(2)/P(3/2) state allows us to enter the adiabatic region of population transfer at very low field intensities, such that corresponding Rabi frequencies are less than or equal to the HpF splitting. This methodology provides a robust way to create a specifically designed superposition state in Rb in the basis of HpF levels and perform state manipulation controllable on the picosecond-to-nanosecond time scale.

Robust detection, isolation and accommodation for sensor failures

NASA Technical Reports Server (NTRS)

Emami-Naeini, A.; Akhter, M. M.; Rock, S. M.

1986-01-01

The objective is to extend the recent advances in robust control system design of multivariable systems to sensor failure detection, isolation, and accommodation (DIA), and estimator design. This effort provides analysis tools to quantify the trade-off between performance robustness and DIA sensitivity, which are to be used to achieve higher levels of performance robustness for given levels of DIA sensitivity. An innovations-based DIA scheme is used. Estimators, which depend upon a model of the process and process inputs and outputs, are used to generate these innovations. Thresholds used to determine failure detection are computed based on bounds on modeling errors, noise properties, and the class of failures. The applicability of the newly developed tools are demonstrated on a multivariable aircraft turbojet engine example. A new concept call the threshold selector was developed. It represents a significant and innovative tool for the analysis and synthesis of DiA algorithms. The estimators were made robust by introduction of an internal model and by frequency shaping. The internal mode provides asymptotically unbiased filter estimates.The incorporation of frequency shaping of the Linear Quadratic Gaussian cost functional modifies the estimator design to make it suitable for sensor failure DIA. The results are compared with previous studies which used thresholds that were selcted empirically. Comparison of these two techniques on a nonlinear dynamic engine simulation shows improved performance of the new method compared to previous techniques

Development of a Design Methodology for Reconfigurable Flight Control Systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.; McLean, C.

2000-01-01

A methodology is presented for the design of flight control systems that exhibit stability and performance-robustness in the presence of actuator failures. The design is based upon two elements. The first element consists of a control law that will ensure at least stability in the presence of a class of actuator failures. This law is created by inner-loop, reduced-order, linear dynamic inversion, and outer-loop compensation based upon Quantitative Feedback Theory. The second element consists of adaptive compensators obtained from simple and approximate time-domain identification of the dynamics of the 'effective vehicle' with failed actuator(s). An example involving the lateral-directional control of a fighter aircraft is employed both to introduce the proposed methodology and to demonstrate its effectiveness and limitations.

Reduced conservatism in stability robustness bounds by state transformation

NASA Technical Reports Server (NTRS)

Yedavalli, R. K.; Liang, Z.

1986-01-01

This note addresses the issue of 'conservatism' in the time domain stability robustness bounds obtained by the Liapunov approach. A state transformation is employed to improve the upper bounds on the linear time-varying perturbation of an asymptotically stable linear time-invariant system for robust stability. This improvement is due to the variance of the conservatism of the Liapunov approach with respect to the basis of the vector space in which the Liapunov function is constructed. Improved bounds are obtained, using a transformation, on elemental and vector norms of perturbations (i.e., structured perturbations) as well as on a matrix norm of perturbations (i.e., unstructured perturbations). For the case of a diagonal transformation, an algorithm is proposed to find the 'optimal' transformation. Several examples are presented to illustrate the proposed analysis.

Mathematical model of unmanned aerial vehicle used for endurance autonomous monitoring

NASA Astrophysics Data System (ADS)

Chelaru, Teodor-Viorel; Chelaru, Adrian

2014-12-01

The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used to local observations, surveillance and monitoring interest area. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using nonlinear model, as well as a linear one for obtaining guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and autonomous control system. This theoretical development allows us to build stability matrix, command matrix and control matrix and finally to analyse the stability of autonomous UAV flight. A robust guidance system, based on uncoupled state will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analysed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chelaru, Teodor-Viorel, E-mail: teodor.chelaru@upb.ro; Chelaru, Adrian, E-mail: achelaru@incas.ro

The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used to local observations, surveillance and monitoring interest area. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using nonlinear model, as well as a linear one for obtaining guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and autonomous control system. This theoretical development allows us to build stability matrix, command matrix and control matrix and finally to analyse the stability of autonomous UAV flight. A robust guidance system,more » based on uncoupled state will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analysed.« less

High-precision control of LSRM based X-Y table for industrial applications.

PubMed

Pan, J F; Cheung, Norbert C; Zou, Yu

2013-01-01

The design of an X-Y table applying direct-drive linear switched reluctance motor (LSRM) principle is proposed in this paper. The proposed X-Y table has the characteristics of low cost, simple and stable mechanical structure. After the design procedure is introduced, an adaptive position control method based on online parameter identification and pole-placement regulation scheme is developed for the X-Y table. Experimental results prove the feasibility and its priority over a traditional PID controller with better dynamic response, static performance and robustness to disturbances. It is expected that the novel two-dimensional direct-drive system find its applications in high-precision manufacture area. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Large-scale linear programs in planning and prediction.

DOT National Transportation Integrated Search

2017-06-01

Large-scale linear programs are at the core of many traffic-related optimization problems in both planning and prediction. Moreover, many of these involve significant uncertainty, and hence are modeled using either chance constraints, or robust optim...

Robustness analysis of an air heating plant and control law by using polynomial chaos

DOE Office of Scientific and Technical Information (OSTI.GOV)

Colón, Diego; Ferreira, Murillo A. S.; Bueno, Átila M.

2014-12-10

This paper presents a robustness analysis of an air heating plant with a multivariable closed-loop control law by using the polynomial chaos methodology (MPC). The plant consists of a PVC tube with a fan in the air input (that forces the air through the tube) and a mass flux sensor in the output. A heating resistance warms the air as it flows inside the tube, and a thermo-couple sensor measures the air temperature. The plant has thus two inputs (the fan's rotation intensity and heat generated by the resistance, both measured in percent of the maximum value) and two outputsmore » (air temperature and air mass flux, also in percent of the maximal value). The mathematical model is obtained by System Identification techniques. The mass flux sensor, which is nonlinear, is linearized and the delays in the transfer functions are properly approximated by non-minimum phase transfer functions. The resulting model is transformed to a state-space model, which is used for control design purposes. The multivariable robust control design techniques used is the LQG/LTR, and the controllers are validated in simulation software and in the real plant. Finally, the MPC is applied by considering some of the system's parameters as random variables (one at a time, and the system's stochastic differential equations are solved by expanding the solution (a stochastic process) in an orthogonal basis of polynomial functions of the basic random variables. This method transforms the stochastic equations in a set of deterministic differential equations, which can be solved by traditional numerical methods (That is the MPC). Statistical data for the system (like expected values and variances) are then calculated. The effects of randomness in the parameters are evaluated in the open-loop and closed-loop pole's positions.« less

Chaos and Robustness in a Single Family of Genetic Oscillatory Networks

PubMed Central

Fu, Daniel; Tan, Patrick; Kuznetsov, Alexey; Molkov, Yaroslav I.

2014-01-01

Genetic oscillatory networks can be mathematically modeled with delay differential equations (DDEs). Interpreting genetic networks with DDEs gives a more intuitive understanding from a biological standpoint. However, it presents a problem mathematically, for DDEs are by construction infinitely-dimensional and thus cannot be analyzed using methods common for systems of ordinary differential equations (ODEs). In our study, we address this problem by developing a method for reducing infinitely-dimensional DDEs to two- and three-dimensional systems of ODEs. We find that the three-dimensional reductions provide qualitative improvements over the two-dimensional reductions. We find that the reducibility of a DDE corresponds to its robustness. For non-robust DDEs that exhibit high-dimensional dynamics, we calculate analytic dimension lines to predict the dependence of the DDEs’ correlation dimension on parameters. From these lines, we deduce that the correlation dimension of non-robust DDEs grows linearly with the delay. On the other hand, for robust DDEs, we find that the period of oscillation grows linearly with delay. We find that DDEs with exclusively negative feedback are robust, whereas DDEs with feedback that changes its sign are not robust. We find that non-saturable degradation damps oscillations and narrows the range of parameter values for which oscillations exist. Finally, we deduce that natural genetic oscillators with highly-regular periods likely have solely negative feedback. PMID:24667178

Exploiting structure: Introduction and motivation

NASA Technical Reports Server (NTRS)

Xu, Zhong Ling

1993-01-01

Research activities performed during the period of 29 June 1993 through 31 Aug. 1993 are summarized. The Robust Stability of Systems where transfer function or characteristic polynomial are multilinear affine functions of parameters of interest in two directions, Algorithmic and Theoretical, was developed. In the algorithmic direction, a new approach that reduces the computational burden of checking the robust stability of the system with multilinear uncertainty is found. This technique is called 'Stability by linear process.' In fact, the 'Stability by linear process' described gives an algorithm. In analysis, we obtained a robustness criterion for the family of polynomials with coefficients of multilinear affine function in the coefficient space and obtained the result for the robust stability of diamond families of polynomials with complex coefficients also. We obtained the limited results for SPR design and we provide a framework for solving ACS. Finally, copies of the outline of our results are provided in the appendix. Also, there is an administration issue in the appendix.

Controle d'attitude d'un lanceur en phase atmospherique approche par applications gardiennes

NASA Astrophysics Data System (ADS)

Dubanchet, Vincent

In a first phase, the modelling process underlines the presence of highly time varying parameters during the ascent, due to a fast mass variation along with propellant consumption. Linearizing the dynamical equations at six main flight instants yields linear time invariant models to be considered during control design. Each of them is to be stabilized by one control law, while respecting given specifications. The synthesis becomes even more complex when the bending modes are taken into account. Moreover, scheduling appears necessary to deal with the time variations. Indeed it is shown that no single gain setting is able to respect all the specifications along the trajectory. Furthermore, increasing complexity when modelling a whole launch vehicle pushes one to consider the model's errors and uncertainties. They represent a major issue in this study since it is asked to ensure the nominal performances in a robust fashion. Owing to their properties, guardian maps appear to be the most suitable tool to deal with such a problem of scheduling with robust performances. In light of this, the development of synthesis methods based on guardian maps is the main contribution of the project. It appears that actual state of the art in this field is focused on theoretical issues, whereas practical ones could be improved. Two approches are presented in the memoire. The first one is based on a graphical approach consisting in drawing the vanishing locus of guardian maps. A program using image analysis techniques is devised to check automatically which gain settings satisfy the constraints. The second one is based on an optimisation procedure involving guardian maps. Starting with the open loop system, the iterative process proposed ends up with a satisfactory gain setting for the closed-loop. These methods are tried and tested for the launch vehicle, with specifications from ASTRIUM-ST. Their practical application is motivated by the system complexity, the different kinds of constraints and the essential need for robustness. Many restrictions that finally bring about the interest and the efficiency of guardian maps for such a problem.

Robust Correlation Analyses: False Positive and Power Validation Using a New Open Source Matlab Toolbox

PubMed Central

Pernet, Cyril R.; Wilcox, Rand; Rousselet, Guillaume A.

2012-01-01

Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab(R) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand. PMID:23335907

Robust correlation analyses: false positive and power validation using a new open source matlab toolbox.

PubMed

Pernet, Cyril R; Wilcox, Rand; Rousselet, Guillaume A

2012-01-01

Pearson's correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab((R)) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand.

Network-Cognizant Voltage Droop Control for Distribution Grids

DOE PAGES

Baker, Kyri; Bernstein, Andrey; Dall'Anese, Emiliano; ...

2017-08-07

Our paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximation of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on themore » effect of DER power adjustments on the overall voltage profile. We pursued a robust approach to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.« less

In-Flight Suppression of a Destabilized F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

NASA Technical Reports Server (NTRS)

Wall, John H.; VanZwieten, Tannen S.; Gilligan, Eric T.; Miller, Christopher J.; Hanson, Curtis E.; Orr, Jeb S.

2015-01-01

NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using frequency-domain reconstruction of flight data, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

On the Stability of Collocated Controllers in the Presence or Uncertain Nonlinearities and Other Perils

NASA Technical Reports Server (NTRS)

Joshi, S. M.

1985-01-01

Robustness properties are investigated for two types of controllers for large flexible space structures, which use collocated sensors and actuators. The first type is an attitude controller which uses negative definite feedback of measured attitude and rate, while the second type is a damping enhancement controller which uses only velocity (rate) feedback. It is proved that collocated attitude controllers preserve closed loop global asymptotic stability when linear actuator/sensor dynamics satisfying certain phase conditions are present, or monotonic increasing nonlinearities are present. For velocity feedback controllers, the global asymptotic stability is proved under much weaker conditions. In particular, they have 90 phase margin and can tolerate nonlinearities belonging to the (0,infinity) sector in the actuator/sensor characteristics. The results significantly enhance the viability of both types of collocated controllers, especially when the available information about the large space structure (LSS) parameters is inadequate or inaccurate.

Network-Cognizant Voltage Droop Control for Distribution Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, Kyri; Bernstein, Andrey; Dall'Anese, Emiliano

Our paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximation of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on themore » effect of DER power adjustments on the overall voltage profile. We pursued a robust approach to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.« less

The generalised isodamping approach for robust fractional PID controllers design

NASA Astrophysics Data System (ADS)

Beschi, M.; Padula, F.; Visioli, A.

2017-06-01

In this paper, we present a novel methodology to design fractional-order proportional-integral-derivative controllers. Based on the description of the controlled system by means of a family of linear models parameterised with respect to a free variable that describes the real process operating point, we design the controller by solving a constrained min-max optimisation problem where the maximum sensitivity has to be minimised. Among the imposed constraints, the most important one is the new generalised isodamping condition, that defines the invariancy of the phase margin with respect to the free parameter variations. It is also shown that the well-known classical isodamping condition is a special case of the new technique proposed in this paper. Simulation results show the effectiveness of the proposed technique and the superiority of the fractional-order controller compared to its integer counterpart.

Robust high-precision attitude control for flexible spacecraft with improved mixed H2/H∞ control strategy under poles assignment constraint

NASA Astrophysics Data System (ADS)

Liu, Chuang; Ye, Dong; Shi, Keke; Sun, Zhaowei

2017-07-01

A novel improved mixed H2/H∞ control technique combined with poles assignment theory is presented to achieve attitude stabilization and vibration suppression simultaneously for flexible spacecraft in this paper. The flexible spacecraft dynamics system is described and transformed into corresponding state space form. Based on linear matrix inequalities (LMIs) scheme and poles assignment theory, the improved mixed H2/H∞ controller does not restrict the equivalence of the two Lyapunov variables involved in H2 and H∞ performance, which can reduce conservatives compared with traditional mixed H2/H∞ controller. Moreover, it can eliminate the coupling of Lyapunov matrix variables and system matrices by introducing slack variable that provides additional degree of freedom. Several simulations are performed to demonstrate the effectiveness and feasibility of the proposed method in this paper.

Novel AC Servo Rotating and Linear Composite Driving Device for Plastic Forming Equipment

NASA Astrophysics Data System (ADS)

Liang, Jin-Tao; Zhao, Sheng-Dun; Li, Yong-Yi; Zhu, Mu-Zhi

2017-07-01

The existing plastic forming equipment are mostly driven by traditional AC motors with long transmission chains, low efficiency, large size, low precision and poor dynamic response are the common disadvantages. In order to realize high performance forming processes, the driving device should be improved, especially for complicated processing motions. Based on electric servo direct drive technology, a novel AC servo rotating and linear composite driving device is proposed, which features implementing both spindle rotation and feed motion without transmission, so that compact structure and precise control can be achieved. Flux switching topology is employed in the rotating drive component for strong robustness, and fractional slot is employed in the linear direct drive component for large force capability. Then the mechanical structure for compositing rotation and linear motion is designed. A device prototype is manufactured, machining of each component and the whole assembly are presented respectively. Commercial servo amplifiers are utilized to construct the control system of the proposed device. To validate the effectiveness of the proposed composite driving device, experimental study on the dynamic test benches are conducted. The results indicate that the output torque can attain to 420 N·m and the dynamic tracking errors are less than about 0.3 rad in the rotating drive. the dynamic tracking errors are less than about 1.6 mm in the linear feed. The proposed research provides a method to construct high efficiency and accuracy direct driving device in plastic forming equipment.

A nonlinear control method based on ANFIS and multiple models for a class of SISO nonlinear systems and its application.

PubMed

Zhang, Yajun; Chai, Tianyou; Wang, Hong

2011-11-01

This paper presents a novel nonlinear control strategy for a class of uncertain single-input and single-output discrete-time nonlinear systems with unstable zero-dynamics. The proposed method combines adaptive-network-based fuzzy inference system (ANFIS) with multiple models, where a linear robust controller, an ANFIS-based nonlinear controller and a switching mechanism are integrated using multiple models technique. It has been shown that the linear controller can ensure the boundedness of the input and output signals and the nonlinear controller can improve the dynamic performance of the closed loop system. Moreover, it has also been shown that the use of the switching mechanism can simultaneously guarantee the closed loop stability and improve its performance. As a result, the controller has the following three outstanding features compared with existing control strategies. First, this method relaxes the assumption of commonly-used uniform boundedness on the unmodeled dynamics and thus enhances its applicability. Second, since ANFIS is used to estimate and compensate the effect caused by the unmodeled dynamics, the convergence rate of neural network learning has been increased. Third, a "one-to-one mapping" technique is adapted to guarantee the universal approximation property of ANFIS. The proposed controller is applied to a numerical example and a pulverizing process of an alumina sintering system, respectively, where its effectiveness has been justified.

Understanding uncertainty in precipitation changes in a balanced perturbed-physics ensemble under multiple climate forcings

NASA Astrophysics Data System (ADS)

Millar, R.; Ingram, W.; Allen, M. R.; Lowe, J.

2013-12-01

Temperature and precipitation patterns are the climate variables with the greatest impacts on both natural and human systems. Due to the small spatial scales and the many interactions involved in the global hydrological cycle, in general circulation models (GCMs) representations of precipitation changes are subject to considerable uncertainty. Quantifying and understanding the causes of uncertainty (and identifying robust features of predictions) in both global and local precipitation change is an essential challenge of climate science. We have used the huge distributed computing capacity of the climateprediction.net citizen science project to examine parametric uncertainty in an ensemble of 20,000 perturbed-physics versions of the HadCM3 general circulation model. The ensemble has been selected to have a control climate in top-of-atmosphere energy balance [Yamazaki et al. 2013, J.G.R.]. We force this ensemble with several idealised climate-forcing scenarios including carbon dioxide step and transient profiles, solar radiation management geoengineering experiments with stratospheric aerosols, and short-lived climate forcing agents. We will present the results from several of these forcing scenarios under GCM parametric uncertainty. We examine the global mean precipitation energy budget to understand the robustness of a simple non-linear global precipitation model [Good et al. 2012, Clim. Dyn.] as a better explanation of precipitation changes in transient climate projections under GCM parametric uncertainty than a simple linear tropospheric energy balance model. We will also present work investigating robust conclusions about precipitation changes in a balanced ensemble of idealised solar radiation management scenarios [Kravitz et al. 2011, Atmos. Sci. Let.].

Designing robust control laws using genetic algorithms

NASA Technical Reports Server (NTRS)

Marrison, Chris

1994-01-01

The purpose of this research is to create a method of finding practical, robust control laws. The robustness of a controller is judged by Stochastic Robustness metrics and the level of robustness is optimized by searching for design parameters that minimize a robustness cost function.

Generalized shrunken type-GM estimator and its application

NASA Astrophysics Data System (ADS)

Ma, C. Z.; Du, Y. L.

2014-03-01

The parameter estimation problem in linear model is considered when multicollinearity and outliers exist simultaneously. A class of new robust biased estimator, Generalized Shrunken Type-GM Estimation, with their calculated methods are established by combination of GM estimator and biased estimator include Ridge estimate, Principal components estimate and Liu estimate and so on. A numerical example shows that the most attractive advantage of these new estimators is that they can not only overcome the multicollinearity of coefficient matrix and outliers but also have the ability to control the influence of leverage points.

A distributed model predictive control scheme for leader-follower multi-agent systems

NASA Astrophysics Data System (ADS)

Franzè, Giuseppe; Lucia, Walter; Tedesco, Francesco

2018-02-01

In this paper, we present a novel receding horizon control scheme for solving the formation problem of leader-follower configurations. The algorithm is based on set-theoretic ideas and is tuned for agents described by linear time-invariant (LTI) systems subject to input and state constraints. The novelty of the proposed framework relies on the capability to jointly use sequences of one-step controllable sets and polyhedral piecewise state-space partitions in order to online apply the 'better' control action in a distributed receding horizon fashion. Moreover, we prove that the design of both robust positively invariant sets and one-step-ahead controllable regions is achieved in a distributed sense. Simulations and numerical comparisons with respect to centralised and local-based strategies are finally performed on a group of mobile robots to demonstrate the effectiveness of the proposed control strategy.

Lieb polariton topological insulators

NASA Astrophysics Data System (ADS)

Li, Chunyan; Ye, Fangwei; Chen, Xianfeng; Kartashov, Yaroslav V.; Ferrando, Albert; Torner, Lluis; Skryabin, Dmitry V.

2018-02-01

We predict that the interplay between the spin-orbit coupling, stemming from the transverse electric-transverse magnetic energy splitting, and the Zeeman effect in semiconductor microcavities supporting exciton-polariton quasiparticles, results in the appearance of unidirectional linear topological edge states when the top microcavity mirror is patterned to form a truncated dislocated Lieb lattice of cylindrical pillars. Periodic nonlinear edge states are found to emerge from the linear ones. They are strongly localized across the interface and they are remarkably robust in comparison to their counterparts in honeycomb lattices. Such robustness makes possible the existence of nested unidirectional dark solitons that move steadily along the lattice edge.

Linear regression based on Minimum Covariance Determinant (MCD) and TELBS methods on the productivity of phytoplankton

NASA Astrophysics Data System (ADS)

Gusriani, N.; Firdaniza

2018-03-01

The existence of outliers on multiple linear regression analysis causes the Gaussian assumption to be unfulfilled. If the Least Square method is forcedly used on these data, it will produce a model that cannot represent most data. For that, we need a robust regression method against outliers. This paper will compare the Minimum Covariance Determinant (MCD) method and the TELBS method on secondary data on the productivity of phytoplankton, which contains outliers. Based on the robust determinant coefficient value, MCD method produces a better model compared to TELBS method.

Robust Fault Detection and Isolation for Stochastic Systems

NASA Technical Reports Server (NTRS)

George, Jemin; Gregory, Irene M.

2010-01-01

This paper outlines the formulation of a robust fault detection and isolation scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves precise reconstruction of sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the robust fault detection and isolation system.

Sparse distributed memory: understanding the speed and robustness of expert memory

PubMed Central

Brogliato, Marcelo S.; Chada, Daniel M.; Linhares, Alexandre

2014-01-01

How can experts, sometimes in exacting detail, almost immediately and very precisely recall memory items from a vast repertoire? The problem in which we will be interested concerns models of theoretical neuroscience that could explain the speed and robustness of an expert's recollection. The approach is based on Sparse Distributed Memory, which has been shown to be plausible, both in a neuroscientific and in a psychological manner, in a number of ways. A crucial characteristic concerns the limits of human recollection, the “tip-of-tongue” memory event—which is found at a non-linearity in the model. We expand the theoretical framework, deriving an optimization formula to solve this non-linearity. Numerical results demonstrate how the higher frequency of rehearsal, through work or study, immediately increases the robustness and speed associated with expert memory. PMID:24808842

The dynamics and control of large flexible space structures, part 11

NASA Technical Reports Server (NTRS)

Bainum, Peter M.; Reddy, A. S. S. R; Diarra, Cheick M.; Li, Feiyue

1988-01-01

A mathematical model is developed to predict the dynamics of the proposed Spacecraft Control Laboratory Experiment during the stationkeeping phase. The Shuttle and reflector are assumed to be rigid, while the mass connecting the Shuttle to the reflector is assumed to be flexible with elastic deformations small as compared with its length. It is seen that in the presence of gravity-gradient torques, the system assumes a new equilibrium position primarily due to the offset in the mass attachment point to the reflector from the reflector's mass center. Control is assumed to be provided through the Shuttle's three torquers and throught six actuators located by painrs at two points on the mass and at the reflector mass center. Numerical results confirm the robustness of an LQR derived control strategy during stationkeeping with maximum control efforts significantly below saturation levels. The linear regulator theory is also used to derive control laws for the linearized model of the rigidized SCOLE configuration where the mast flexibility is not included. It is seen that this same type of control strategy can be applied for the rapid single axis slewing of the SCOLE through amplitudes as large as 20 degrees. These results provide a definite trade-off between the slightly larger slewing times with the considerable reduction in over-all control effort as compared with the results of the two point boundary value problem application of Pontryagin's Maximum Principle.

Molecular Precision at Micrometer Length Scales: Hierarchical Assembly of DNA-Protein Nanostructures.

PubMed

Schiffels, Daniel; Szalai, Veronika A; Liddle, J Alexander

2017-07-25

Robust self-assembly across length scales is a ubiquitous feature of biological systems but remains challenging for synthetic structures. Taking a cue from biology-where disparate molecules work together to produce large, functional assemblies-we demonstrate how to engineer microscale structures with nanoscale features: Our self-assembly approach begins by using DNA polymerase to controllably create double-stranded DNA (dsDNA) sections on a single-stranded template. The single-stranded DNA (ssDNA) sections are then folded into a mechanically flexible skeleton by the origami method. This process simultaneously shapes the structure at the nanoscale and directs the large-scale geometry. The DNA skeleton guides the assembly of RecA protein filaments, which provides rigidity at the micrometer scale. We use our modular design strategy to assemble tetrahedral, rectangular, and linear shapes of defined dimensions. This method enables the robust construction of complex assemblies, greatly extending the range of DNA-based self-assembly methods.

Exploiting structure: Introduction and motivation

NASA Technical Reports Server (NTRS)

Xu, Zhong Ling

1994-01-01

This annual report summarizes the research activities that were performed from 26 Jun. 1993 to 28 Feb. 1994. We continued to investigate the Robust Stability of Systems where transfer functions or characteristic polynomials are affine multilinear functions of parameters. An approach that differs from 'Stability by Linear Process' and that reduces the computational burden of checking the robust stability of the system with multilinear uncertainty was found for low order, 2-order, and 3-order cases. We proved a crucial theorem, the so-called Face Theorem. Previously, we have proven Kharitonov's Vertex Theorem and the Edge Theorem by Bartlett. The detail of this proof is contained in the Appendix. This Theorem provides a tool to describe the boundary of the image of the affine multilinear function. For SPR design, we have developed some new results. The third objective for this period is to design a controller for IHM by the H-infinity optimization technique. The details are presented in the Appendix.

Robust inference in the negative binomial regression model with an application to falls data.

PubMed

Aeberhard, William H; Cantoni, Eva; Heritier, Stephane

2014-12-01

A popular way to model overdispersed count data, such as the number of falls reported during intervention studies, is by means of the negative binomial (NB) distribution. Classical estimating methods are well-known to be sensitive to model misspecifications, taking the form of patients falling much more than expected in such intervention studies where the NB regression model is used. We extend in this article two approaches for building robust M-estimators of the regression parameters in the class of generalized linear models to the NB distribution. The first approach achieves robustness in the response by applying a bounded function on the Pearson residuals arising in the maximum likelihood estimating equations, while the second approach achieves robustness by bounding the unscaled deviance components. For both approaches, we explore different choices for the bounding functions. Through a unified notation, we show how close these approaches may actually be as long as the bounding functions are chosen and tuned appropriately, and provide the asymptotic distributions of the resulting estimators. Moreover, we introduce a robust weighted maximum likelihood estimator for the overdispersion parameter, specific to the NB distribution. Simulations under various settings show that redescending bounding functions yield estimates with smaller biases under contamination while keeping high efficiency at the assumed model, and this for both approaches. We present an application to a recent randomized controlled trial measuring the effectiveness of an exercise program at reducing the number of falls among people suffering from Parkinsons disease to illustrate the diagnostic use of such robust procedures and their need for reliable inference. © 2014, The International Biometric Society.

Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

PubMed

Li, Zhijun; Su, Chun-Yi

2013-09-01

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

PI controller design of a wind turbine: evaluation of the pole-placement method and tuning using constrained optimization

NASA Astrophysics Data System (ADS)

Mirzaei, Mahmood; Tibaldi, Carlo; Hansen, Morten H.

2016-09-01

PI/PID controllers are the most common wind turbine controllers. Normally a first tuning is obtained using methods such as pole-placement or Ziegler-Nichols and then extensive aeroelastic simulations are used to obtain the best tuning in terms of regulation of the outputs and reduction of the loads. In the traditional tuning approaches, the properties of different open loop and closed loop transfer functions of the system are not normally considered. In this paper, an assessment of the pole-placement tuning method is presented based on robustness measures. Then a constrained optimization setup is suggested to automatically tune the wind turbine controller subject to robustness constraints. The properties of the system such as the maximum sensitivity and complementary sensitivity functions (Ms and Mt ), along with some of the responses of the system, are used to investigate the controller performance and formulate the optimization problem. The cost function is the integral absolute error (IAE) of the rotational speed from a disturbance modeled as a step in wind speed. Linearized model of the DTU 10-MW reference wind turbine is obtained using HAWCStab2. Thereafter, the model is reduced with model order reduction. The trade-off curves are given to assess the tunings of the poles- placement method and a constrained optimization problem is solved to find the best tuning.

The comparison between several robust ridge regression estimators in the presence of multicollinearity and multiple outliers

NASA Astrophysics Data System (ADS)

Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said

2014-09-01

In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.

A robust hybrid fuzzy-simulated annealing-intelligent water drops approach for tuning a distribution static compensator nonlinear controller in a distribution system

NASA Astrophysics Data System (ADS)

Bagheri Tolabi, Hajar; Hosseini, Rahil; Shakarami, Mahmoud Reza

2016-06-01

This article presents a novel hybrid optimization approach for a nonlinear controller of a distribution static compensator (DSTATCOM). The DSTATCOM is connected to a distribution system with the distributed generation units. The nonlinear control is based on partial feedback linearization. Two proportional-integral-derivative (PID) controllers regulate the voltage and track the output in this control system. In the conventional scheme, the trial-and-error method is used to determine the PID controller coefficients. This article uses a combination of a fuzzy system, simulated annealing (SA) and intelligent water drops (IWD) algorithms to optimize the parameters of the controllers. The obtained results reveal that the response of the optimized controlled system is effectively improved by finding a high-quality solution. The results confirm that using the tuning method based on the fuzzy-SA-IWD can significantly decrease the settling and rising times, the maximum overshoot and the steady-state error of the voltage step response of the DSTATCOM. The proposed hybrid tuning method for the partial feedback linearizing (PFL) controller achieved better regulation of the direct current voltage for the capacitor within the DSTATCOM. Furthermore, in the event of a fault the proposed controller tuned by the fuzzy-SA-IWD method showed better performance than the conventional controller or the PFL controller without optimization by the fuzzy-SA-IWD method with regard to both fault duration and clearing times.

Single axis control of ball position in magnetic levitation system using fuzzy logic control

NASA Astrophysics Data System (ADS)

Sahoo, Narayan; Tripathy, Ashis; Sharma, Priyaranjan

2018-03-01

This paper presents the design and real time implementation of Fuzzy logic control(FLC) for the control of the position of a ferromagnetic ball by manipulating the current flowing in an electromagnet that changes the magnetic field acting on the ball. This system is highly nonlinear and open loop unstable. Many un-measurable disturbances are also acting on the system, making the control of it highly complex but interesting for any researcher in control system domain. First the system is modelled using the fundamental laws, which gives a nonlinear equation. The nonlinear model is then linearized at an operating point. Fuzzy logic controller is designed after studying the system in closed loop under PID control action. The controller is then implemented in real time using Simulink real time environment. The controller is tuned manually to get a stable and robust performance. The set point tracking performance of FLC and PID controllers were compared and analyzed.

Global optimization for quantum dynamics of few-fermion systems

NASA Astrophysics Data System (ADS)

Li, Xikun; Pecak, Daniel; Sowiński, Tomasz; Sherson, Jacob; Nielsen, Anne E. B.

2018-03-01

Quantum state preparation is vital to quantum computation and quantum information processing tasks. In adiabatic state preparation, the target state is theoretically obtained with nearly perfect fidelity if the control parameter is tuned slowly enough. As this, however, leads to slow dynamics, it is often desirable to be able to carry out processes more rapidly. In this work, we employ two global optimization methods to estimate the quantum speed limit for few-fermion systems confined in a one-dimensional harmonic trap. Such systems can be produced experimentally in a well-controlled manner. We determine the optimized control fields and achieve a reduction in the ramping time of more than a factor of four compared to linear ramping. We also investigate how robust the fidelity is to small variations of the control fields away from the optimized shapes.

Variable speed wind turbine control by discrete-time sliding mode approach.

PubMed

Torchani, Borhen; Sellami, Anis; Garcia, Germain

2016-05-01

The aim of this paper is to propose a new design variable speed wind turbine control by discrete-time sliding mode approach. This methodology is designed for linear saturated system. The saturation constraint is reported on inputs vector. To this end, the back stepping design procedure is followed to construct a suitable sliding manifold that guarantees the attainment of a stabilization control objective. It is well known that the mechanisms are investigated in term of the most proposed assumptions to deal with the damping, shaft stiffness and inertia effect of the gear. The objectives are to synthesize robust controllers that maximize the energy extracted from wind, while reducing mechanical loads and rotor speed tracking combined with an electromagnetic torque. Simulation results of the proposed scheme are presented. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Human motion planning based on recursive dynamics and optimal control techniques

NASA Technical Reports Server (NTRS)

Lo, Janzen; Huang, Gang; Metaxas, Dimitris

2002-01-01

This paper presents an efficient optimal control and recursive dynamics-based computer animation system for simulating and controlling the motion of articulated figures. A quasi-Newton nonlinear programming technique (super-linear convergence) is implemented to solve minimum torque-based human motion-planning problems. The explicit analytical gradients needed in the dynamics are derived using a matrix exponential formulation and Lie algebra. Cubic spline functions are used to make the search space for an optimal solution finite. Based on our formulations, our method is well conditioned and robust, in addition to being computationally efficient. To better illustrate the efficiency of our method, we present results of natural looking and physically correct human motions for a variety of human motion tasks involving open and closed loop kinematic chains.

Control concepts for active magnetic bearings

NASA Technical Reports Server (NTRS)

Siegwart, Roland; Vischer, D.; Larsonneur, R.; Herzog, R.; Traxler, Alfons; Bleuler, H.; Schweitzer, G.

1992-01-01

Active Magnetic Bearings (AMB) are becoming increasingly significant for various industrial applications. Examples are turbo-compressors, centrifuges, high speed milling and grinding spindles, vibration isolation, linear guides, magnetically levitated trains, vacuum and space applications. Thanks to the rapid progress and drastic cost reduction in power- and micro-electronics, the number of AMB applications is growing very rapidly. Industrial uses of AMBs leads to new requirements for AMB-actuators, sensor systems, and rotor dynamics. Especially desirable are new and better control concepts to meet demand such as low cost AMB, high stiffness, high performance, high robustness, high damping up to several kHz, vibration isolation, force-free rotation, and unbalance cancellation. This paper surveys various control concepts for AMBs and discusses their advantages and disadvantages. Theoretical and experimental results are presented.

Robust and efficient pharmacokinetic parameter non-linear least squares estimation for dynamic contrast enhanced MRI of the prostate.

PubMed

Kargar, Soudabeh; Borisch, Eric A; Froemming, Adam T; Kawashima, Akira; Mynderse, Lance A; Stinson, Eric G; Trzasko, Joshua D; Riederer, Stephen J

2018-05-01

To describe an efficient numerical optimization technique using non-linear least squares to estimate perfusion parameters for the Tofts and extended Tofts models from dynamic contrast enhanced (DCE) MRI data and apply the technique to prostate cancer. Parameters were estimated by fitting the two Tofts-based perfusion models to the acquired data via non-linear least squares. We apply Variable Projection (VP) to convert the fitting problem from a multi-dimensional to a one-dimensional line search to improve computational efficiency and robustness. Using simulation and DCE-MRI studies in twenty patients with suspected prostate cancer, the VP-based solver was compared against the traditional Levenberg-Marquardt (LM) strategy for accuracy, noise amplification, robustness to converge, and computation time. The simulation demonstrated that VP and LM were both accurate in that the medians closely matched assumed values across typical signal to noise ratio (SNR) levels for both Tofts models. VP and LM showed similar noise sensitivity. Studies using the patient data showed that the VP method reliably converged and matched results from LM with approximate 3× and 2× reductions in computation time for the standard (two-parameter) and extended (three-parameter) Tofts models. While LM failed to converge in 14% of the patient data, VP converged in the ideal 100%. The VP-based method for non-linear least squares estimation of perfusion parameters for prostate MRI is equivalent in accuracy and robustness to noise, while being more reliably (100%) convergent and computationally about 3× (TM) and 2× (ETM) faster than the LM-based method. Copyright © 2017 Elsevier Inc. All rights reserved.

Improved Convergence and Robustness of USM3D Solutions on Mixed Element Grids (Invited)

NASA Technical Reports Server (NTRS)

Pandya, Mohagna J.; Diskin, Boris; Thomas, James L.; Frink, Neal T.

2015-01-01

Several improvements to the mixed-element USM3D discretization and defect-correction schemes have been made. A new methodology for nonlinear iterations, called the Hierarchical Adaptive Nonlinear Iteration Scheme (HANIS), has been developed and implemented. It provides two additional hierarchies around a simple and approximate preconditioner of USM3D. The hierarchies are a matrix-free linear solver for the exact linearization of Reynolds-averaged Navier Stokes (RANS) equations and a nonlinear control of the solution update. Two variants of the new methodology are assessed on four benchmark cases, namely, a zero-pressure gradient flat plate, a bump-in-channel configuration, the NACA 0012 airfoil, and a NASA Common Research Model configuration. The new methodology provides a convergence acceleration factor of 1.4 to 13 over the baseline solver technology.

Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2016-06-01

Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.