NASA Astrophysics Data System (ADS)
Takemiya, Tetsushi
, and that (2) the AMF terminates optimization erroneously when the optimization problems have constraints. The first problem is due to inaccuracy in computing derivatives in the AMF, and the second problem is due to erroneous treatment of the trust region ratio, which sets the size of the domain for an optimization in the AMF. In order to solve the first problem of the AMF, automatic differentiation (AD) technique, which reads the codes of analysis models and automatically generates new derivative codes based on some mathematical rules, is applied. If derivatives are computed with the generated derivative code, they are analytical, and the required computational time is independent of the number of design variables, which is very advantageous for realistic aerospace engineering problems. However, if analysis models implement iterative computations such as computational fluid dynamics (CFD), which solves system partial differential equations iteratively, computing derivatives through the AD requires a massive memory size. The author solved this deficiency by modifying the AD approach and developing a more efficient implementation with CFD, and successfully applied the AD to general CFD software. In order to solve the second problem of the AMF, the governing equation of the trust region ratio, which is very strict against the violation of constraints, is modified so that it can accept the violation of constraints within some tolerance. By accepting violations of constraints during the optimization process, the AMF can continue optimization without terminating immaturely and eventually find the true optimum design point. With these modifications, the AMF is referred to as "Robust AMF," and it is applied to airfoil and wing aerodynamic design problems using Euler CFD software. The former problem has 21 design variables, and the latter 64. In both problems, derivatives computed with the proposed AD method are first compared with those computed with the finite
Experimental Investigation on Adaptive Robust Controller Designs Applied to Constrained Manipulators
Nogueira, Samuel L.; Pazelli, Tatiana F. P. A. T.; Siqueira, Adriano A. G.; Terra, Marco H.
2013-01-01
In this paper, two interlaced studies are presented. The first is directed to the design and construction of a dynamic 3D force/moment sensor. The device is applied to provide a feedback signal of forces and moments exerted by the robotic end-effector. This development has become an alternative solution to the existing multi-axis load cell based on static force and moment sensors. The second one shows an experimental investigation on the performance of four different adaptive nonlinear ℋ∞ control methods applied to a constrained manipulator subject to uncertainties in the model and external disturbances. Coordinated position and force control is evaluated. Adaptive procedures are based on neural networks and fuzzy systems applied in two different modeling strategies. The first modeling strategy requires a well-known nominal model for the robot, so that the intelligent systems are applied only to estimate the effects of uncertainties, unmodeled dynamics and external disturbances. The second strategy considers that the robot model is completely unknown and, therefore, intelligent systems are used to estimate these dynamics. A comparative study is conducted based on experimental implementations performed with an actual planar manipulator and with the dynamic force sensor developed for this purpose. PMID:23598503
A robust nonlinear skid-steering control design applied to the MULE (6x6) unmanned ground vehicle
NASA Astrophysics Data System (ADS)
Kaloust, Joseph
2006-05-01
The paper presents a robust nonlinear skid-steering control design concept. The control concept is based on the recursive/backstepping control design technique and is capable of compensating for uncertainties associated with sensor noise measurements and/or system dynamic state uncertainties. The objective of this control design is to demonstrate the performance of the nonlinear controller under uncertainty associate with road traction (rough off-road and on-road terrain). The MULE vehicle is used in the simulation modeling and results.
Robustness analysis applied to substructure controller synthesis
NASA Technical Reports Server (NTRS)
Gonzalez-Oberdoerffer, Marcelo F.; Craig, Roy R., Jr.
1993-01-01
The stability and robustness of the controlled system obtained via the substructure control synthesis (SCS) method of Su et al. (1990) were examined using a six-bay truss model, and employing an LQG control design method to obtain controllers for two separate structures. It is found that the assembled controller provides a stability in this instance. A qualitative assessment of the stability robustness of the system with controller designed with the SCS method is provided by obtaining a controller using the complete truss model and comparing the robustness of the corresponding closed-loop systems.
Robust design of dynamic observers
NASA Technical Reports Server (NTRS)
Bhattacharyya, S. P.
1974-01-01
The two (identity) observer realizations z = Mz + Ky and z = transpose of Az + transpose of K(y - transpose of Cz), respectively called the open loop and closed loop realizations, for the linear system x = Ax, y = Cx are analyzed with respect to the requirement of robustness; i.e., the requirement that the observer continue to regulate the error x - z satisfactorily despite small variations in the observer parameters from the projected design values. The results show that the open loop realization is never robust, that robustness requires a closed loop implementation, and that the closed loop realization is robust with respect to small perturbations in the gains transpose of K if and only if the observer can be built to contain an exact replica of the unstable and underdamped dynamics of the system being observed. These results clarify the stringent accuracy requirements on both models and hardware that must be met before an observer can be considered for use in a control system.
Applying robust multibit watermarks to digital images
NASA Astrophysics Data System (ADS)
Tsolis, Dimitrios; Nikolopoulos, Spiridon; Drossos, Lambros; Sioutas, Spyros; Papatheodorou, Theodore
2009-05-01
The current work is focusing on the implementation of a robust multibit watermarking algorithm for digital images, which is based on an innovative spread spectrum technique analysis. The paper presents the watermark embedding and detection algorithms, which use both wavelets and the Discrete Cosine Transform and analyzes the arising issues.
Robust multivariable controller design for flexible spacecraft
NASA Technical Reports Server (NTRS)
Joshi, Suresh M.; Armstrong, Ernest S.
1986-01-01
Large, flexible spacecraft are typically characterized by a large number of significant elastic modes with very small inherent damping, low, closely spaced natural frequencies, and the lack of accurate knowledge of the structural parameters. Summarized here is some recent research on the design of robust controllers for such spacecraft, which will maintain stability, and possible performance, despite these problems. Two types of controllers are considered, the first being the linear-quadratic-Gaussian-(LQG)-type. The second type utilizes output feedback using collocated sensors and actuators. The problem of designing robust LQG-type controllers using the frequency domain loop transfer recovery (LTR) method is considered, and the method is applied to a large antenna model. Analytical results regarding the regions of stability for LQG-type controllers in the presence of actuator nonlinearities are also presented. The results obtained for the large antenna indicate that the LQG/LTR method is a promising approach for control system design for flexible spacecraft. For the second type of controllers (collocated controllers), it is proved that the stability is maintained in the presence of certain commonly encountered nonlinearities and first-order actuator dynamics. These results indicate that collocated controllers are good candidates for robust control in situations where model errors are large.
Robust controller design for a skid to turn missile
NASA Astrophysics Data System (ADS)
Sreenatha, A. G.; Rajhans, Vivek; Bhardwaj, Neeraj
1999-11-01
The design and analysis of Robust Autopilot for skid-to-turn missile is presented. Two of the popular Robust Controller design approaches, The Loop Shaping Design Procedure (LSDP) and The Robust Eigenstructure Assignment are considered. The missile model considered in the present work is having lightly damped modes and non-minimum phase zeros, with stringent performance requirements. Numerical results are presented to evaluate the Robustness of stability and performance of the controller. Merits and demerits of the above said methodologies are brought out clearly as applied to this specific plant.
Evaluating efficiency and robustness in cilia design
NASA Astrophysics Data System (ADS)
Guo, Hanliang; Kanso, Eva
2016-03-01
Motile cilia are used by many eukaryotic cells to transport flow. Cilia-driven flows are important to many physiological functions, yet a deep understanding of the interplay between the mechanical structure of cilia and their physiological functions in healthy and diseased conditions remains elusive. To develop such an understanding, one needs a quantitative framework to assess cilia performance and robustness when subject to perturbations in the cilia apparatus. Here we link cilia design (beating patterns) to function (flow transport) in the context of experimentally and theoretically derived cilia models. We particularly examine the optimality and robustness of cilia design. Optimality refers to efficiency of flow transport, while robustness is defined as low sensitivity to variations in the design parameters. We find that suboptimal designs can be more robust than optimal ones. That is, designing for the most efficient cilium does not guarantee robustness. These findings have significant implications on the understanding of cilia design in artificial and biological systems.
Evaluating efficiency and robustness in cilia design.
Guo, Hanliang; Kanso, Eva
2016-03-01
Motile cilia are used by many eukaryotic cells to transport flow. Cilia-driven flows are important to many physiological functions, yet a deep understanding of the interplay between the mechanical structure of cilia and their physiological functions in healthy and diseased conditions remains elusive. To develop such an understanding, one needs a quantitative framework to assess cilia performance and robustness when subject to perturbations in the cilia apparatus. Here we link cilia design (beating patterns) to function (flow transport) in the context of experimentally and theoretically derived cilia models. We particularly examine the optimality and robustness of cilia design. Optimality refers to efficiency of flow transport, while robustness is defined as low sensitivity to variations in the design parameters. We find that suboptimal designs can be more robust than optimal ones. That is, designing for the most efficient cilium does not guarantee robustness. These findings have significant implications on the understanding of cilia design in artificial and biological systems. PMID:27078459
Design of flight control systems via robust decoupled servomechanism theory
NASA Technical Reports Server (NTRS)
Wang, S.-H.; Davison, E. J.
1979-01-01
Decoupling theory and robust servomechanism theory are applied to the design of linear multivariable systems with large parameter variations. In addition to being approximately decoupled in the transient period, the over-all system achieves tracking and disturbance rejection robustly in the steady state. An example in flight control system is given.
Robust Design Optimization via Failure Domain Bounding
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.
2007-01-01
This paper extends and applies the strategies recently developed by the authors for handling constraints under uncertainty to robust design optimization. For the scope of this paper, robust optimization is a methodology aimed at problems for which some parameters are uncertain and are only known to belong to some uncertainty set. This set can be described by either a deterministic or a probabilistic model. In the methodology developed herein, optimization-based strategies are used to bound the constraint violation region using hyper-spheres and hyper-rectangles. By comparing the resulting bounding sets with any given uncertainty model, it can be determined whether the constraints are satisfied for all members of the uncertainty model (i.e., constraints are feasible) or not (i.e., constraints are infeasible). If constraints are infeasible and a probabilistic uncertainty model is available, upper bounds to the probability of constraint violation can be efficiently calculated. The tools developed enable approximating not only the set of designs that make the constraints feasible but also, when required, the set of designs for which the probability of constraint violation is below a prescribed admissible value. When constraint feasibility is possible, several design criteria can be used to shape the uncertainty model of performance metrics of interest. Worst-case, least-second-moment, and reliability-based design criteria are considered herein. Since the problem formulation is generic and the tools derived only require standard optimization algorithms for their implementation, these strategies are easily applicable to a broad range of engineering problems.
Robust Decentralized Controller Design: Subsystem Approach
NASA Astrophysics Data System (ADS)
Rosinová, Danica; Thuan, Nguyen Quang; Veselý, Vojtech; Marko, L'ubomír
2012-01-01
The paper addresses the problem of the robust output feedback PI controller design for complex large-scale stable systems with a state decentralized control structure. A decentralized control design procedure is proposed for static output feedback control which is based on solving robust control design problems of subsystems' size. The presented approach is based
Robust holographic storage system design.
Watanabe, Takahiro; Watanabe, Minoru
2011-11-21
Demand is increasing daily for large data storage systems that are useful for applications in spacecraft, space satellites, and space robots, which are all exposed to radiation-rich space environment. As candidates for use in space embedded systems, holographic storage systems are promising because they can easily provided the demanded large-storage capability. Particularly, holographic storage systems, which have no rotation mechanism, are demanded because they are virtually maintenance-free. Although a holographic memory itself is an extremely robust device even in a space radiation environment, its associated lasers and drive circuit devices are vulnerable. Such vulnerabilities sometimes engendered severe problems that prevent reading of all contents of the holographic memory, which is a turn-off failure mode of a laser array. This paper therefore presents a proposal for a recovery method for the turn-off failure mode of a laser array on a holographic storage system, and describes results of an experimental demonstration. PMID:22109441
Towards designing robust coupled networks
Schneider, Christian M.; Yazdani, Nuri; Araújo, Nuno A. M.; Havlin, Shlomo; Herrmann, Hans J.
2013-01-01
Natural and technological interdependent systems have been shown to be highly vulnerable due to cascading failures and an abrupt collapse of global connectivity under initial failure. Mitigating the risk by partial disconnection endangers their functionality. Here we propose a systematic strategy of selecting a minimum number of autonomous nodes that guarantee a smooth transition in robustness. Our method which is based on betweenness is tested on various examples including the famous 2003 electrical blackout of Italy. We show that, with this strategy, the necessary number of autonomous nodes can be reduced by a factor of five compared to a random choice. We also find that the transition to abrupt collapse follows tricritical scaling characterized by a set of exponents which is independent on the protection strategy. PMID:23752705
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.
Robust Crossfeed Design for Hovering Rotorcraft
NASA Technical Reports Server (NTRS)
Catapang, David R.
1993-01-01
Control law design for rotorcraft fly-by-wire systems normally attempts to decouple angular responses using fixed-gain crossfeeds. This approach can lead to poor decoupling over the frequency range of pilot inputs and increase the load on the feedback loops. In order to improve the decoupling performance, dynamic crossfeeds may be adopted. Moreover, because of the large changes that occur in rotorcraft dynamics due to small changes about the nominal design condition, especially for near-hovering flight, the crossfeed design must be 'robust'. A new low-order matching method is presented here to design robust crossfeed compensators for multi-input, multi-output (MIMO) systems. The technique identifies degrees-of-freedom that can be decoupled using crossfeeds, given an anticipated set of parameter variations for the range of flight conditions of concern. Cross-coupling is then reduced for degrees-of-freedom that can use crossfeed compensation by minimizing off-axis response magnitude average and variance. Results are presented for the analysis of pitch, roll, yaw and heave coupling of the UH-60 Black Hawk helicopter in near-hovering flight. Robust crossfeeds are designed that show significant improvement in decoupling performance and robustness over nominal, single design point, compensators. The design method and results are presented in an easily used graphical format that lends significant physical insight to the design procedure. This plant pre-compensation technique is an appropriate preliminary step to the design of robust feedback control laws for rotorcraft.
Robust Tensioned Kevlar Suspension Design
NASA Technical Reports Server (NTRS)
Young, Joseph B.; Naylor, Bret J.; Holmes, Warren A.
2012-01-01
One common but challenging problem in cryogenic engineering is to produce a mount that has excellent thermal isolation but is also rigid. Such mounts can be achieved by suspending the load from a network of fibers or strings held in tension. Kevlar fibers are often used for this purpose owing to their high strength and low thermal conductivity. A suite of compact design elements has been developed to improve the reliability of suspension systems made of Kevlar.
Design optimization for cost and quality: The robust design approach
NASA Technical Reports Server (NTRS)
Unal, Resit
1990-01-01
Designing reliable, low cost, and operable space systems has become the key to future space operations. Designing high quality space systems at low cost is an economic and technological challenge to the designer. A systematic and efficient way to meet this challenge is a new method of design optimization for performance, quality, and cost, called Robust Design. Robust Design is an approach for design optimization. It consists of: making system performance insensitive to material and subsystem variation, thus allowing the use of less costly materials and components; making designs less sensitive to the variations in the operating environment, thus improving reliability and reducing operating costs; and using a new structured development process so that engineering time is used most productively. The objective in Robust Design is to select the best combination of controllable design parameters so that the system is most robust to uncontrollable noise factors. The robust design methodology uses a mathematical tool called an orthogonal array, from design of experiments theory, to study a large number of decision variables with a significantly small number of experiments. Robust design also uses a statistical measure of performance, called a signal-to-noise ratio, from electrical control theory, to evaluate the level of performance and the effect of noise factors. The purpose is to investigate the Robust Design methodology for improving quality and cost, demonstrate its application by the use of an example, and suggest its use as an integral part of space system design process.
Robust Control Design for Large Space Structures
NASA Technical Reports Server (NTRS)
Eastman, W. L.; Bossi, J. A.
1985-01-01
The control design problem for the class of future spacecraft referred to as large space structures (LSS) is by now well known. The issue is the reduced order control of a very high order, lightly damped system with uncertain system parameters, particularly in the high frequency modes. A design methodology which incorporates robustness considerations as part of the design process is presented. Combining pertinent results from multivariable systems theory and optimal control and estimation, LQG eigenstructure assignment and LQG frequency shaping, were used to improve singular value robustness measures in the presence of control and observation spillover.
Robust linear quadratic designs with respect to parameter uncertainty
NASA Technical Reports Server (NTRS)
Douglas, Joel; Athans, Michael
1992-01-01
The authors derive a linear quadratic regulator (LQR) which is robust to parametric uncertainty by using the overbounding method of I. R. Petersen and C. V. Hollot (1986). The resulting controller is determined from the solution of a single modified Riccati equation. It is shown that, when applied to a structural system, the controller gains add robustness by minimizing the potential energy of uncertain stiffness elements, and minimizing the rate of dissipation of energy through uncertain damping elements. A worst-case disturbance in the direction of the uncertainty is also considered. It is proved that performance robustness has been increased with the robust LQR when compared to a mismatched LQR design where the controller is designed on the nominal system, but applied to the actual uncertain system.
Extensibility of a linear rapid robust design methodology
NASA Astrophysics Data System (ADS)
Steinfeldt, Bradley A.; Braun, Robert D.
2016-05-01
The extensibility of a linear rapid robust design methodology is examined. This analysis is approached from a computational cost and accuracy perspective. The sensitivity of the solution's computational cost is examined by analysing effects such as the number of design variables, nonlinearity of the CAs, and nonlinearity of the response in addition to several potential complexity metrics. Relative to traditional robust design methods, the linear rapid robust design methodology scaled better with the size of the problem and had performance that exceeded the traditional techniques examined. The accuracy of applying a method with linear fundamentals to nonlinear problems was examined. It is observed that if the magnitude of nonlinearity is less than 1000 times that of the nominal linear response, the error associated with applying successive linearization will result in ? errors in the response less than 10% compared to the full nonlinear error.
Robust regression applied to fractal/multifractal analysis.
NASA Astrophysics Data System (ADS)
Portilla, F.; Valencia, J. L.; Tarquis, A. M.; Saa-Requejo, A.
2012-04-01
Fractal and multifractal are concepts that have grown increasingly popular in recent years in the soil analysis, along with the development of fractal models. One of the common steps is to calculate the slope of a linear fit commonly using least squares method. This shouldn't be a special problem, however, in many situations using experimental data the researcher has to select the range of scales at which is going to work neglecting the rest of points to achieve the best linearity that in this type of analysis is necessary. Robust regression is a form of regression analysis designed to circumvent some limitations of traditional parametric and non-parametric methods. In this method we don't have to assume that the outlier point is simply an extreme observation drawn from the tail of a normal distribution not compromising the validity of the regression results. In this work we have evaluated the capacity of robust regression to select the points in the experimental data used trying to avoid subjective choices. Based on this analysis we have developed a new work methodology that implies two basic steps: • Evaluation of the improvement of linear fitting when consecutive points are eliminated based on R p-value. In this way we consider the implications of reducing the number of points. • Evaluation of the significance of slope difference between fitting with the two extremes points and fitted with the available points. We compare the results applying this methodology and the common used least squares one. The data selected for these comparisons are coming from experimental soil roughness transect and simulated based on middle point displacement method adding tendencies and noise. The results are discussed indicating the advantages and disadvantages of each methodology. Acknowledgements Funding provided by CEIGRAM (Research Centre for the Management of Agricultural and Environmental Risks) and by Spanish Ministerio de Ciencia e Innovación (MICINN) through project no
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.
NASA Technical Reports Server (NTRS)
Bayard, David S.; Chiang, Richard Y.
1996-01-01
This paper demonstrates an approach to frequency domain identification for the explicit purpose of designing robust H(infinity) controllers. The approach transforms raw experimental data into a plant set estimate directly usable by modern robust control design software(e.g., Matlab Robust Control Toolboxes [11][2]). A key issue in control design from raw data is the question of whether the controller will work when applied to the true system. The main feature fo this approach is that the resulting controller in guaranteed to work as designed(when applied to the true system) to a prescribed statistical confidence. While the overall methodology addresses key theoretical issues, it has at the same time been specifically designed to support practical implementations. A simulation example is included to demonstrate the overall approach.
A method for designing robust multivariable feedback systems
NASA Technical Reports Server (NTRS)
Milich, David A.; Athans, Michael; Valavani, Lena; Stein, Gunter
1988-01-01
A new methodology is developed for the synthesis of linear, time-invariant (LTI) controllers for multivariable LTI systems. The aim is to achieve stability and performance robustness of the feedback system in the presence of multiple unstructured uncertainty blocks; i.e., to satisfy a frequency-domain inequality in terms of the structured singular value. The design technique is referred to as the causality recovery methodology (CRM). Starting with an initial (nominally) stabilizing compensator, the CRM produces a closed-loop system whose performance-robustness is at least as good as, and hopefully superior to, that of the original design. The robustness improvement is obtained by solving an infinite-dimensional, convex optimization program. A finite-dimensional implementation of the CRM was developed, and it was applied to a multivariate design example.
A method for designing robust multivariable feedback systems
NASA Technical Reports Server (NTRS)
Milich, David Albert; Athans, Michael; Valavani, Lena; Stein, Gunter
1988-01-01
A new methodology is developed for the synthesis of linear, time-invariant (LTI) controllers for multivariable LTI systems. The aim is to achieve stability and performance robustness of the feedback system in the presence of multiple unstructured uncertainty blocks; i.e., to satisfy a frequency-domain inequality in terms of the structured singular value. The design technique is referred to as the Causality Recovery Methodology (CRM). Starting with an initial (nominally) stabilizing compensator, the CRM produces a closed-loop system whose performance-robustness is at least as good as, and hopefully superior to, that of the original design. The robustness improvement is obtained by solving an infinite-dimensional, convex optimization program. A finite-dimensional implementation of the CRM was developed, and it was applied to a multivariate design example.
Matlab as a robust control design tool
NASA Technical Reports Server (NTRS)
Gregory, Irene M.
1994-01-01
This presentation introduces Matlab as a tool used in flight control research. The example used to illustrate some of the capabilities of this software is a robust controller designed for a single stage to orbit air breathing vehicles's ascent to orbit. The global requirements of the controller are to stabilize the vehicle and follow a trajectory in the presence of atmospheric disturbances and strong dynamic coupling between airframe and propulsion.
NASA Technical Reports Server (NTRS)
Ryan, R.
1993-01-01
Robustness is a buzz word common to all newly proposed space systems design as well as many new commercial products. The image that one conjures up when the word appears is a 'Paul Bunyon' (lumberjack design), strong and hearty; healthy with margins in all aspects of the design. In actuality, robustness is much broader in scope than margins, including such factors as simplicity, redundancy, desensitization to parameter variations, control of parameter variations (environments flucation), and operational approaches. These must be traded with concepts, materials, and fabrication approaches against the criteria of performance, cost, and reliability. This includes manufacturing, assembly, processing, checkout, and operations. The design engineer or project chief is faced with finding ways and means to inculcate robustness into an operational design. First, however, be sure he understands the definition and goals of robustness. This paper will deal with these issues as well as the need for the requirement for robustness.
A Robust Control Design Framework for Substructure Models
NASA Technical Reports Server (NTRS)
Lim, Kyong B.
1994-01-01
A framework for designing control systems directly from substructure models and uncertainties is proposed. The technique is based on combining a set of substructure robust control problems by an interface stiffness matrix which appears as a constant gain feedback. Variations of uncertainties in the interface stiffness are treated as a parametric uncertainty. It is shown that multivariable robust control can be applied to generate centralized or decentralized controllers that guarantee performance with respect to uncertainties in the interface stiffness, reduced component modes and external disturbances. The technique is particularly suited for large, complex, and weakly coupled flexible structures.
Robustness of speckle imaging techniques applied to horizontal imaging scenarios
NASA Astrophysics Data System (ADS)
Bos, Jeremy P.
Atmospheric turbulence near the ground severely limits the quality of imagery acquired over long horizontal paths. In defense, surveillance, and border security applications, there is interest in deploying man-portable, embedded systems incorporating image reconstruction to improve the quality of imagery available to operators. To be effective, these systems must operate over significant variations in turbulence conditions while also subject to other variations due to operation by novice users. Systems that meet these requirements and are otherwise designed to be immune to the factors that cause variation in performance are considered robust. In addition to robustness in design, the portable nature of these systems implies a preference for systems with a minimum level of computational complexity. Speckle imaging methods are one of a variety of methods recently been proposed for use in man-portable horizontal imagers. In this work, the robustness of speckle imaging methods is established by identifying a subset of design parameters that provide immunity to the expected variations in operating conditions while minimizing the computation time necessary for image recovery. This performance evaluation is made possible using a novel technique for simulating anisoplanatic image formation. I find that incorporate as few as 15 image frames and 4 estimates of the object phase per reconstructed frame provide an average reduction of 45% reduction in Mean Squared Error (MSE) and 68% reduction in deviation in MSE. In addition, the Knox-Thompson phase recovery method is demonstrated to produce images in half the time required by the bispectrum. Finally, it is shown that certain blind image quality metrics can be used in place of the MSE to evaluate reconstruction quality in field scenarios. Using blind metrics rather depending on user estimates allows for reconstruction quality that differs from the minimum MSE by as little as 1%, significantly reducing the deviation in
Design of robust failure detection filters
NASA Technical Reports Server (NTRS)
San Martin, A. M.; Vander Velde, W. E.
1986-01-01
An essential aspect of the design of control systems for large, flexible spacecraft is fault tolerance. Because it is anticipated that a large number of sensors and actuators will be required to realize good control over these assemblies, the detection and isolation of component failures cannot be based on direct comparisons among replicated components. Instead, the notion of 'analytic redundancy' must be employed for the FDI function. Unfortunately this makes the FDI function sensitive to modeling errors which are certain to exist in the large space structure problem due to model truncation and parameter uncertainty. This paper addresses the robustness to model error of one method of FDI residual generation - the failure detection filter. Initial designs were found to be extremely sensitive to modeling error. The sources of this sensitivity are analyzed and modifications to the design are suggested. The improved filter is shown to have much better visibility of the failure signatures relative to the background due to modeling error.
Design analysis, robust methods, and stress classification
Bees, W.J.
1993-01-01
This special edition publication volume is comprised of papers presented at the 1993 ASME Pressure Vessels and Piping Conference, July 25--29, 1993 in Denver, Colorado. The papers were prepared for presentations in technical sessions developed under the auspices of the PVPD Committees on Computer Technology, Design and Analysis, Operations Applications and Components. The topics included are: Analysis of Pressure Vessels and Components; Expansion Joints; Robust Methods; Stress Classification; and Non-Linear Analysis. Individual papers have been processed separately for inclusion in the appropriate data bases.
System identification for robust control design
Dohner, J.L.
1995-04-01
System identification for the purpose of robust control design involves estimating a nominal model of a physical system and the uncertainty bounds of that nominal model via the use of experimentally measured input/output data. Although many algorithms have been developed to identify nominal models, little effort has been directed towards identifying uncertainty bounds. Therefore, in this document, a discussion of both nominal model identification and bounded output multiplicative uncertainty identification will be presented. This document is divided into several sections. Background information relevant to system identification and control design will be presented. A derivation of eigensystem realization type algorithms will be presented. An algorithm will be developed for calculating the maximum singular value of output multiplicative uncertainty from measured data. An application will be given involving the identification of a complex system with aliased dynamics, feedback control, and exogenous noise disturbances. And, finally, a short discussion of results will be presented.
Computational methods of robust controller design for aerodynamic flutter suppression
NASA Technical Reports Server (NTRS)
Anderson, L. R.
1981-01-01
The development of Riccati iteration, a tool for the design and analysis of linear control systems is examined. First, Riccati iteration is applied to the problem of pole placement and order reduction in two-time scale control systems. Order reduction, yielding a good approximation to the original system, is demonstrated using a 16th order linear model of a turbofan engine. Next, a numerical method for solving the Riccati equation is presented and demonstrated for a set of eighth order random examples. A literature review of robust controller design methods follows which includes a number of methods for reducing the trajectory and performance index sensitivity in linear regulators. Lastly, robust controller design for large parameter variations is discussed.
Robust Bayesian decision theory applied to optimal dosage.
Abraham, Christophe; Daurès, Jean-Pierre
2004-04-15
We give a model for constructing an utility function u(theta,d) in a dose prescription problem. theta and d denote respectively the patient state of health and the dose. The construction of u is based on the conditional probabilities of several variables. These probabilities are described by logistic models. Obviously, u is only an approximation of the true utility function and that is why we investigate the sensitivity of the final decision with respect to the utility function. We construct a class of utility functions from u and approximate the set of all Bayes actions associated to that class. Then, we measure the sensitivity as the greatest difference between the expected utilities of two Bayes actions. Finally, we apply these results to weighing up a chemotherapy treatment of lung cancer. This application emphasizes the importance of measuring robustness through the utility of decisions rather than the decisions themselves. PMID:15057878
Robust control systems design by H-infinity optimization theory
NASA Technical Reports Server (NTRS)
Chang, B. C.; Li, X. P.; Banda, S. S.; Yeh, H. H.
1991-01-01
In this paper, step-by-step procedures of applying the H-infinity theory to robust control systems design are given. The objective of the paper is to eliminate the possible difficulties a control engineer may encounter in applying H-infinity control theory and to clear up some misconceptions about H-infinity theory like high-gain controller and numerical obstacles, etc. An efficient algorithm is used to compute the optimal H-infinity norm. The Glover and Doyle (1988) controller formulas are slightly modified and used to construct an optimal controller without any numerical difficulties.
Robust Path Planning and Feedback Design Under Stochastic Uncertainty
NASA Technical Reports Server (NTRS)
Blackmore, Lars
2008-01-01
Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.
Robust PID Parameter Design for Embedded Temperature Control System Using Taguchi Method
NASA Astrophysics Data System (ADS)
Suzuki, Arata; Sugimoto, Kenji
This paper proposes a robust PID parameter design scheme using Taguchi's robust design method. This scheme is applied to an embedded PID temperature control system which is affected by outside (room) temperature. The effectiveness of this scheme is verified experimentally with a cooking household appliance.
Robust design of polyrhythmic neural circuits
NASA Astrophysics Data System (ADS)
Schwabedal, Justus T. C.; Neiman, Alexander B.; Shilnikov, Andrey L.
2014-08-01
Neural circuit motifs producing coexistent rhythmic patterns are treated as building blocks of multifunctional neuronal networks. We study the robustness of such a motif of inhibitory model neurons to reliably sustain bursting polyrhythms under random perturbations. Without noise, the exponential stability of each of the coexisting rhythms increases with strengthened synaptic coupling, thus indicating an increased robustness. Conversely, after adding noise we find that noise-induced rhythm switching intensifies if the coupling strength is increased beyond a critical value, indicating a decreased robustness. We analyze this stochastic arrhythmia and develop a generic description of its dynamic mechanism. Based on our mechanistic insight, we show how physiological parameters of neuronal dynamics and network coupling can be balanced to enhance rhythm robustness against noise. Our findings are applicable to a broad class of relaxation-oscillator networks, including Fitzhugh-Nagumo and other Hodgkin-Huxley-type networks.
Applying Software Design Methodology to Instructional Design
NASA Astrophysics Data System (ADS)
East, J. Philip
2004-12-01
The premise of this paper is that computer science has much to offer the endeavor of instructional improvement. Software design processes employed in computer science for developing software can be used for planning instruction and should improve instruction in much the same manner that design processes appear to have improved software. Techniques for examining the software development process can be applied to an examination of the instructional process. Furthermore, the computer science discipline is particularly well suited to these tasks. Thus, computer science can develop instructional design expertise for export to other disciplines to improve education in all disciplines and, eventually, at all levels.
Robust Decision-making Applied to Model Selection
Hemez, Francois M.
2012-08-06
The scientific and engineering communities are relying more and more on numerical models to simulate ever-increasingly complex phenomena. Selecting a model, from among a family of models that meets the simulation requirements, presents a challenge to modern-day analysts. To address this concern, a framework is adopted anchored in info-gap decision theory. The framework proposes to select models by examining the trade-offs between prediction accuracy and sensitivity to epistemic uncertainty. The framework is demonstrated on two structural engineering applications by asking the following question: Which model, of several numerical models, approximates the behavior of a structure when parameters that define each of those models are unknown? One observation is that models that are nominally more accurate are not necessarily more robust, and their accuracy can deteriorate greatly depending upon the assumptions made. It is posited that, as reliance on numerical models increases, establishing robustness will become as important as demonstrating accuracy.
Robust Design of Motor PWM Control using Modeling and Simulation
NASA Astrophysics Data System (ADS)
Zhan, Wei
A robust design method is developed for Pulse Width Modulation (PWM) motor speed control. A first principle model for DC permanent magnetic motor is used to build a Simulink model for simulation and analysis. Based on the simulation result, the main factors that contributed to the average speed variation are identified using Design of Experiment (DOE). A robust solution is derived to reduce the aver age speed control variation using Response Surface Method (RSM). The robustness of the new design is verified using the simulation model.
Analytical redundancy and the design of robust failure detection systems
NASA Technical Reports Server (NTRS)
Chow, E. Y.; Willsky, A. S.
1984-01-01
The Failure Detection and Identification (FDI) process is viewed as consisting of two stages: residual generation and decision making. It is argued that a robust FDI system can be achieved by designing a robust residual generation process. Analytical redundancy, the basis for residual generation, is characterized in terms of a parity space. Using the concept of parity relations, residuals can be generated in a number of ways and the design of a robust residual generation process can be formulated as a minimax optimization problem. An example is included to illustrate this design methodology. Previously announcedd in STAR as N83-20653
NASA Astrophysics Data System (ADS)
Hwang, Kwang-Hyeon; Lee, Kwon-Hee; Park, Gyung-Jin; Lee, Byeong-Leul; Cho, Yong-Chul; Lee, Seok-Han
2003-01-01
Recently, there has been considerable interest in micro gyroscopes made of silicon chips. These can be applied to many microelectromechanical systems, such as devices for stabilization, general rate control, directional pointing, autopilot systems, and missile control. A decoupled vibratory gyroscope has been fabricated and tested. In this research, design improvement is obtained from numerical analyses as well as from a theoretical design point of view. The existing design is analyzed by using the axiomatic approach, which provides a general framework for design. For axiomatic design, the functional requirements (FRs) are twofold: firstly, the natural frequencies should have fixed values, and secondly the system should be robust to large tolerances. According to the independence axiom, the design parameters (DPs) are classified into the same number of groups as the FRs. Each group of DPs is separately determined according to the sequence indicated by axiomatic design. When a group of DPs should be determined to enhance robustness, the Taguchi concept is employed to maintain robust performance regardless of the tolerances. It is noted that the Taguchi method is used as a unit process in the sequence of the axiomatic design.
A robust industrial accelerator window design
NASA Astrophysics Data System (ADS)
Schuetz, Marlin N.; Vroom, David A.
1998-06-01
An improved design for the thin metal foil window associated with high power industrial accelarators has been developed and tested. This design, which employs specifically shaped flanges, greatly reduce the stresses normally present on accelerators windows and has lead to longer window lifetime and a better means of window cooling.
Design for robustness of unique, multi-component engineering systems
NASA Astrophysics Data System (ADS)
Shelton, Kenneth A.
2007-12-01
The purpose of this research is to advance the science of conceptual designing for robustness in unique, multi-component engineering systems. Robustness is herein defined as the ability of an engineering system to operate within a desired performance range even if the actual configuration has differences from specifications within specified tolerances. These differences are caused by three sources, namely manufacturing errors, system degradation (operational wear and tear), and parts availability. Unique, multi-component engineering systems are defined as systems produced in unique or very small production numbers. They typically have design and manufacturing costs on the order of billions of dollars, and have multiple, competing performance objectives. Design time for these systems must be minimized due to competition, high manpower costs, long manufacturing times, technology obsolescence, and limited available manpower expertise. Most importantly, design mistakes cannot be easily corrected after the systems are operational. For all these reasons, robustness of these systems is absolutely critical. This research examines the space satellite industry in particular. Although inherent robustness assurance is absolutely critical, it is difficult to achieve in practice. The current state of the art for robustness in the industry is to overdesign components and subsystems with redundancy and margin. The shortfall is that it is not known if the added margins were either necessary or sufficient given the risk management preferences of the designer or engineering system customer. To address this shortcoming, new assessment criteria to evaluate robustness in design concepts have been developed. The criteria are comprised of the "Value Distance", addressing manufacturing errors and system degradation, and "Component Distance", addressing parts availability. They are based on an evolutionary computation format that uses a string of alleles to describe the components in the
Designing Robust Hierarchically Textured Oleophobic Fabrics.
Kleingartner, Justin A; Srinivasan, Siddarth; Truong, Quoc T; Sieber, Michael; Cohen, Robert E; McKinley, Gareth H
2015-12-01
Commercially available woven fabrics (e.g., nylon- or PET-based fabrics) possess inherently re-entrant textures in the form of cylindrical yarns and fibers. We analyze the liquid repellency of woven and nanotextured oleophobic fabrics using a nested model with n levels of hierarchy that is constructed from modular units of cylindrical and spherical building blocks. At each level of hierarchy, the density of the topographical features is captured using a dimensionless textural parameter D(n)*. For a plain-woven mesh comprised of chemically treated fiber bundles (n = 2), the tight packing of individual fibers in each bundle (D2* ≈ 1) imposes a geometric constraint on the maximum oleophobicity that can be achieved solely by modifying the surface energy of the coating. For liquid droplets contacting such tightly bundled fabrics with modified surface energies, we show that this model predicts a lower bound on the equilibrium contact angle of θ(E) ≈ 57° below which the Cassie–Baxter to Wenzel wetting transition occurs spontaneously, and this is validated experimentally. We demonstrate how the introduction of an additional higher order micro-/nanotexture onto the fibers (n = 3) is necessary to overcome this limit and create more robustly nonwetting fabrics. Finally, we show a simple experimental realization of the enhanced oleophobicity of fabrics by depositing spherical microbeads of poly(methyl methacrylate)/fluorodecyl polyhedral oligomeric silsesquioxane (fluorodecyl POSS) onto the fibers of a commercial woven nylon fabric. PMID:26473386
Robust sliding mode control applied to double Inverted pendulum system
Mahjoub, Sonia; Derbel, Nabil; Mnif, Faical
2009-03-05
A three hierarchical sliding mode control is presented for a class of an underactuated system which can overcome the mismatched perturbations. The considered underactuated system is a double inverted pendulum (DIP), can be modeled by three subsystems. Such structure allows the construction of several designs of hierarchies for the controller. For all hierarchical designs, the asymptotic stability of every layer sliding mode surface and the sliding mode surface of subsystems are proved theoretically by Barbalat's lemma. Simulation results show the validity of these methods.
Robust Control Design for Systems With Probabilistic Uncertainty
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Kenny, Sean P.
2005-01-01
This paper presents a reliability- and robustness-based formulation for robust control synthesis for systems with probabilistic uncertainty. In a reliability-based formulation, the probability of violating design requirements prescribed by inequality constraints is minimized. In a robustness-based formulation, a metric which measures the tendency of a random variable/process to cluster close to a target scalar/function is minimized. A multi-objective optimization procedure, which combines stability and performance requirements in time and frequency domains, is used to search for robustly optimal compensators. Some of the fundamental differences between the proposed strategy and conventional robust control methods are: (i) unnecessary conservatism is eliminated since there is not need for convex supports, (ii) the most likely plants are favored during synthesis allowing for probabilistic robust optimality, (iii) the tradeoff between robust stability and robust performance can be explored numerically, (iv) the uncertainty set is closely related to parameters with clear physical meaning, and (v) compensators with improved robust characteristics for a given control structure can be synthesized.
Object oriented simulation implementation in support of robust system design
Not Available
1993-04-01
A very brief description of two ``classes`` developed for use in design optimization and sensitivity analyses are given. These classes are used in simulations of systems in early design phases as well as system response assessments. The instanciated classes were coupled to system models to demonstrate the practically and efficiency of using these objects in complex robust design processes.
Design of robust level control system of nuclear steam generator
NASA Astrophysics Data System (ADS)
Lee, Y. J.; Na, M. G.
2007-12-01
The nuclear steam generator feedwater control system is designed by the robust control methods. The design is divided into two steps. First, the feedwater controller in the feedwater station is designed by H ∞ and MWS methods. Then the controller located on the feedback loop is designed both by classical PID and by robust technique. It is found that the feedback controller of simple PID whose coefficients vary with the power is proper for the system performance. The simulations show that the hybrid system of H ∞ and PID has a good performance with proper stability margins.
Robust synthetic biology design: stochastic game theory approach
Chen, Bor-Sen; Chang, Chia-Hung; Lee, Hsiao-Ching
2009-01-01
Motivation: 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. Results: 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. Availability: http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf Contact: bschen@ee.nthu.edu.tw Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19435742
Apply Design Patterns to Refactor Software Design
NASA Technical Reports Server (NTRS)
Baggs, Rhoda; Shaykhian, Gholam Ali
2007-01-01
Refactoring software design is a method of changing software design while explicitly preserving its unique design functionalities. Presented approach is to utilize design patterns as the basis for refactoring software design. Comparison of a design solution will be made through C++ programming language examples to exploit this approach. Developing reusable component will be discussed, the paper presents that the construction of such components can diminish the added burden of both refactoring and the use of design patterns.
Robust control design verification using the modular modeling system
Edwards, R.M.; Ben-Abdennour, A.; Lee, K.Y.
1991-01-01
The Modular Modeling System (B W MMS) is being used as a design tool to verify robust controller designs for improving power plant performance while also providing fault-accommodating capabilities. These controllers are designed based on optimal control theory and are thus model based controllers which are targeted for implementation in a computer based digital control environment. The MMS is being successfully used to verify that the controllers are tolerant of uncertainties between the plant model employed in the controller and the actual plant; i.e., that they are robust. The two areas in which the MMS is being used for this purpose is in the design of (1) a reactor power controller with improved reactor temperature response, and (2) the design of a multiple input multiple output (MIMO) robust fault-accommodating controller for a deaerator level and pressure control problem.
Trading Robustness Requirements in Mars Entry Trajectory Design
NASA Technical Reports Server (NTRS)
Lafleur, Jarret M.
2009-01-01
One of the most important metrics characterizing an atmospheric entry trajectory in preliminary design is the size of its predicted landing ellipse. Often, requirements for this ellipse are set early in design and significantly influence both the expected scientific return from a particular mission and the cost of development. Requirements typically specify a certain probability level (6-level) for the prescribed ellipse, and frequently this latter requirement is taken at 36. However, searches for the justification of 36 as a robustness requirement suggest it is an empirical rule of thumb borrowed from non-aerospace fields. This paper presents an investigation into the sensitivity of trajectory performance to varying robustness (6-level) requirements. The treatment of robustness as a distinct objective is discussed, and an analysis framework is presented involving the manipulation of design variables to effect trades between performance and robustness objectives. The scenario for which this method is illustrated is the ballistic entry of an MSL-class Mars entry vehicle. Here, the design variable is entry flight path angle, and objectives are parachute deploy altitude performance and error ellipse robustness. Resulting plots show the sensitivities between these objectives and trends in the entry flight path angles required to design to these objectives. Relevance to the trajectory designer is discussed, as are potential steps for further development and use of this type of analysis.
Robust crossfeed design for hovering rotorcraft. M.S. Thesis
NASA Technical Reports Server (NTRS)
Catapang, David R.
1993-01-01
Control law design for rotorcraft fly-by-wire systems normally attempts to decouple angular responses using fixed-gain crossfeeds. This approach can lead to poor decoupling over the frequency range of pilot inputs and increase the load on the feedback loops. In order to improve the decoupling performance, dynamic crossfeeds may be adopted. Moreover, because of the large changes that occur in rotorcraft dynamics due to small changes about the nominal design condition, especially for near-hovering flight, the crossfeed design must be 'robust.' A new low-order matching method is presented here to design robost crossfeed compensators for multi-input, multi-output (MIMO) systems. The technique identifies degrees-of-freedom that can be decoupled using crossfeeds, given an anticipated set of parameter variations for the range of flight conditions of concern. Cross-coupling is then reduced for degrees-of-freedom that can use crossfeed compensation by minimizing off-axis response magnitude average and variance. Results are presented for the analysis of pitch, roll, yaw, and heave coupling of the UH-60 Black Hawk helicopter in near-hovering flight. Robust crossfeeds are designed that show significant improvement in decoupling performance and robustness over nominal, single design point, compensators. The design method and results are presented in an easily-used graphical format that lends significant physical insight to the design procedure. This plant pre-compensation technique is an appropriate preliminary step to the design of robust feedback control laws for rotorcraft.
Designing Flood Management Systems for Joint Economic and Ecological Robustness
NASA Astrophysics Data System (ADS)
Spence, C. M.; Grantham, T.; Brown, C. M.; Poff, N. L.
2015-12-01
Freshwater ecosystems across the United States are threatened by hydrologic change caused by water management operations and non-stationary climate trends. Nonstationary hydrology also threatens flood management systems' performance. Ecosystem managers and flood risk managers need tools to design systems that achieve flood risk reduction objectives while sustaining ecosystem functions and services in an uncertain hydrologic future. Robust optimization is used in water resources engineering to guide system design under climate change uncertainty. Using principles introduced by Eco-Engineering Decision Scaling (EEDS), we extend robust optimization techniques to design flood management systems that meet both economic and ecological goals simultaneously across a broad range of future climate conditions. We use three alternative robustness indices to identify flood risk management solutions that preserve critical ecosystem functions in a case study from the Iowa River, where recent severe flooding has tested the limits of the existing flood management system. We seek design modifications to the system that both reduce expected cost of flood damage while increasing ecologically beneficial inundation of riparian floodplains across a wide range of plausible climate futures. The first robustness index measures robustness as the fraction of potential climate scenarios in which both engineering and ecological performance goals are met, implicitly weighting each climate scenario equally. The second index builds on the first by using climate projections to weight each climate scenario, prioritizing acceptable performance in climate scenarios most consistent with climate projections. The last index measures robustness as mean performance across all climate scenarios, but penalizes scenarios with worse performance than average, rewarding consistency. Results stemming from alternate robustness indices reflect implicit assumptions about attitudes toward risk and reveal the
Enabling Rapid and Robust Structural Analysis During Conceptual Design
NASA Technical Reports Server (NTRS)
Eldred, Lloyd B.; Padula, Sharon L.; Li, Wu
2015-01-01
This paper describes a multi-year effort to add a structural analysis subprocess to a supersonic aircraft conceptual design process. The desired capabilities include parametric geometry, automatic finite element mesh generation, static and aeroelastic analysis, and structural sizing. The paper discusses implementation details of the new subprocess, captures lessons learned, and suggests future improvements. The subprocess quickly compares concepts and robustly handles large changes in wing or fuselage geometry. The subprocess can rank concepts with regard to their structural feasibility and can identify promising regions of the design space. The automated structural analysis subprocess is deemed robust and rapid enough to be included in multidisciplinary conceptual design and optimization studies.
Design for robustness of unique, multi-component engineering systems
NASA Astrophysics Data System (ADS)
Shelton, Kenneth A.
2007-12-01
The purpose of this research is to advance the science of conceptual designing for robustness in unique, multi-component engineering systems. Robustness is herein defined as the ability of an engineering system to operate within a desired performance range even if the actual configuration has differences from specifications within specified tolerances. These differences are caused by three sources, namely manufacturing errors, system degradation (operational wear and tear), and parts availability. Unique, multi-component engineering systems are defined as systems produced in unique or very small production numbers. They typically have design and manufacturing costs on the order of billions of dollars, and have multiple, competing performance objectives. Design time for these systems must be minimized due to competition, high manpower costs, long manufacturing times, technology obsolescence, and limited available manpower expertise. Most importantly, design mistakes cannot be easily corrected after the systems are operational. For all these reasons, robustness of these systems is absolutely critical. This research examines the space satellite industry in particular. Although inherent robustness assurance is absolutely critical, it is difficult to achieve in practice. The current state of the art for robustness in the industry is to overdesign components and subsystems with redundancy and margin. The shortfall is that it is not known if the added margins were either necessary or sufficient given the risk management preferences of the designer or engineering system customer. To address this shortcoming, new assessment criteria to evaluate robustness in design concepts have been developed. The criteria are comprised of the "Value Distance", addressing manufacturing errors and system degradation, and "Component Distance", addressing parts availability. They are based on an evolutionary computation format that uses a string of alleles to describe the components in the
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.
Existential Design Applied in Universal Design Settings.
Torkildsby, Anne Britt
2016-01-01
The critical design method aims to discuss ways of opening up the (design) brief when planning, designing, building, operating and maintaining the future of the built environment - public as well as private, indoor as well as outdoor. Focusing on "designials" (fundamental forms of design being), the methodology intends to illustrate the fact that objects; including buildings, parks, transportation systems, etc. may directly encroach upon certain "existentials" (fundamental forms of human being) - thus shed light on how a design process is normally conducted, and furthermore, how that affects people's existential well-being. PMID:27534284
GPS baseline configuration design based on robustness analysis
NASA Astrophysics Data System (ADS)
Yetkin, M.; Berber, M.
2012-11-01
The robustness analysis results obtained from a Global Positioning System (GPS) network are dramatically influenced by the configuration
Towards Robust Designs Via Multiple-Objective Optimization Methods
NASA Technical Reports Server (NTRS)
Man Mohan, Rai
2006-01-01
Fabricating and operating complex systems involves dealing with uncertainty in the relevant variables. In the case of aircraft, flow conditions are subject to change during operation. Efficiency and engine noise may be different from the expected values because of manufacturing tolerances and normal wear and tear. Engine components may have a shorter life than expected because of manufacturing tolerances. In spite of the important effect of operating- and manufacturing-uncertainty on the performance and expected life of the component or system, traditional aerodynamic shape optimization has focused on obtaining the best design given a set of deterministic flow conditions. Clearly it is important to both maintain near-optimal performance levels at off-design operating conditions, and, ensure that performance does not degrade appreciably when the component shape differs from the optimal shape due to manufacturing tolerances and normal wear and tear. These requirements naturally lead to the idea of robust optimal design wherein the concept of robustness to various perturbations is built into the design optimization procedure. The basic ideas involved in robust optimal design will be included in this lecture. The imposition of the additional requirement of robustness results in a multiple-objective optimization problem requiring appropriate solution procedures. Typically the costs associated with multiple-objective optimization are substantial. Therefore efficient multiple-objective optimization procedures are crucial to the rapid deployment of the principles of robust design in industry. Hence the companion set of lecture notes (Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks ) deals with methodology for solving multiple-objective Optimization problems efficiently, reliably and with little user intervention. Applications of the methodologies presented in the companion lecture to robust design will be included here. The
Applying Software Design Methodology to Instructional Design
ERIC Educational Resources Information Center
East, J. Philip
2004-01-01
The premise of this paper is that computer science has much to offer the endeavor of instructional improvement. Software design processes employed in computer science for developing software can be used for planning instruction and should improve instruction in much the same manner that design processes appear to have improved software. Techniques…
Design and tuning of robust PID controller for HVAC systems
Kasahara, Masato; Matsuba, Tadahiko; Kuzuu, Yoshiaki; Yamazaki, Takanori; Hashimoto, Yukihiro; Kamimura, Kazuyuki; Kurosu, Shigeru
1999-07-01
This paper concerns the development of a new design and tuning method for use with robust proportional-plus-integral-plus-derivative (PID) controllers that are commonly used in the heating, ventilating, and air-conditioning (HVAC) fields. The robust PID controller is designed for temperature control of a single-zone environmental space. Although the dynamics of environmental space are described by higher-order transfer functions, most HVAC plants are approximated by first-order lag plus deadtime systems. Its control performance is examined for this commonly approximated controlled plant. Since most HVAC plants are complex with nonlinearity, distributed parameters, and multivariables, a single set of PID gains does not necessarily yield a satisfactory control performance. For this reason, the PID controller must be designed as a robust control system considering model uncertainty caused by changes in characteristics of the plant. The PID gains obtained by solving a two-disk type of mixed sensitivity problem can be modified by contrast to those tuned by the traditional Ziegler-Nichols rule. The results, which are surprisingly simple, are given as linear functions of ratio of deadtime to time constant for robustness. The numerical simulation and the experiments on a commercial-size test plant for air conditioning suggest that the robust PID controller proposed in this paper is effective enough for practical applications.
Robust optimization for water distribution systems least cost design
NASA Astrophysics Data System (ADS)
Perelman, Lina; Housh, Mashor; Ostfeld, Avi
2013-10-01
The objective of the least cost design problem of a water distribution system is to find its minimum cost with discrete diameters as decision variables and hydraulic controls as constraints. The goal of a robust least cost design is to find solutions which guarantee its feasibility independent of the data (i.e., under model uncertainty). A robust counterpart approach for linear uncertain problems is adopted in this study, which represents the uncertain stochastic problem as its deterministic equivalent. Robustness is controlled by a single parameter providing a trade-off between the probability of constraint violation and the objective cost. Two principal models are developed: uncorrelated uncertainty model with implicit design reliability, and correlated uncertainty model with explicit design reliability. The models are tested on three example applications and compared for uncertainty in consumers' demands. The main contribution of this study is the inclusion of the ability to explicitly account for different correlations between water distribution system demand nodes. In particular, it is shown that including correlation information in the design phase has a substantial advantage in seeking more efficient robust solutions.
Robust process design and springback compensation of a decklid inner
NASA Astrophysics Data System (ADS)
Zhang, Xiaojing; Grimm, Peter; Carleer, Bart; Jin, Weimin; Liu, Gang; Cheng, Yingchao
2013-12-01
Springback compensation is one of the key topics in current die face engineering. The accuracy of the springback simulation, the robustness of method planning and springback are considered to be the main factors which influences the effectiveness of springback compensation. In the present paper, the basic principles of springback compensation are presented firstly. These principles consist of an accurate full cycle simulation with final validation setting and the robust process design and optimization are discussed in detail via an industrial example, a decklid inner. Moreover, an effective compensation strategy is put forward based on the analysis of springback and the simulation based springback compensation is introduced in the phase of process design. In the end, the final verification and comparison in tryout and production is given in this paper, which verified that the methodology of robust springback compensation is effective during the die development.
Towards robust optimal design of storm water systems
NASA Astrophysics Data System (ADS)
Marquez Calvo, Oscar; Solomatine, Dimitri
2015-04-01
In this study the focus is on the design of a storm water or a combined sewer system. Such a system should be capable to handle properly most of the storm to minimize the damages caused by flooding due to the lack of capacity of the system to cope with rain water at peak times. This problem is a multi-objective optimization problem: we have to take into account the minimization of the construction costs, the minimization of damage costs due to flooding, and possibly other criteria. One of the most important factors influencing the design of storm water systems is the expected amount of water to deal with. It is common that this infrastructure is developed with the capacity to cope with events that occur once in, say 10 or 20 years - so-called design rainfall events. However, rainfall is a random variable and such uncertainty typically is not taken explicitly into account in optimization. Rainfall design data is based on historical information of rainfalls, but many times this data is based on unreliable measures; or in not enough historical information; or as we know, the patterns of rainfall are changing regardless of historical information. There are also other sources of uncertainty influencing design, for example, leakages in the pipes and accumulation of sediments in pipes. In the context of storm water or combined sewer systems design or rehabilitation, robust optimization technique should be able to find the best design (or rehabilitation plan) within the available budget but taking into account uncertainty in those variables that were used to design the system. In this work we consider various approaches to robust optimization proposed by various authors (Gabrel, Murat, Thiele 2013; Beyer, Sendhoff 2007) and test a novel method ROPAR (Solomatine 2012) to analyze robustness. References Beyer, H.G., & Sendhoff, B. (2007). Robust optimization - A comprehensive survey. Comput. Methods Appl. Mech. Engrg., 3190-3218. Gabrel, V.; Murat, C., Thiele, A. (2014
Robust and versatile software system for optimal design of MEMS structures
NASA Astrophysics Data System (ADS)
Kwak, Byung M.; Lee, Sang H.; Huh, Jae S.
2000-04-01
A CAD-integrated total design system for MEMS is developed which can perform analysis and design for mechanical performance of a MEMS structure. The software works in a parametric CAD platform and makes users to do from CAD modeling and analysis to design optimization. Basic philosophy is to assure robustness, versatility and user friendliness. To satisfy these requirements; 1) Design variables are selectable directly form CAD model, 2) Commercial codes are utilized as many as available, and 3) Design sensitivity analysis must be simple and robust. Commercial finite element codes and some newly developed modules are integrated in the system for analysis. For design sensitivity analysis, two approaches were implemented: finite difference method and the Taguchi method. The approximate methods adopted seem to be simple and robust, which can be applied to design of complex practical structures. The design sensitivity analysis by finite difference method, with nonlinear programming and trade-off study, gives satisfactory results. The Taguchi method module is integrated for robust optimal design of MEMS structure. Although it is not meant to find the exact optimum point, it is applicable to practical problems where performance characteristics are hard to evaluate, since this does not require any derivative information. Two examples are taken to examine performance of the developed design tool and proposed methodology. It relieves much of the difficulties often met in conventional design works and has shown practicability for structural design of MEMS.
Robust, Decoupled, Flight Control Design with Rate Saturating Actuators
NASA Technical Reports Server (NTRS)
Snell, S. A.; Hess, R. A.
1997-01-01
Techniques for the design of control systems for manually controlled, high-performance aircraft must provide the following: (1) multi-input, multi-output (MIMO) solutions, (2) acceptable handling qualities including no tendencies for pilot-induced oscillations, (3) a tractable approach for compensator design, (4) performance and stability robustness in the presence of significant plant uncertainty, and (5) performance and stability robustness in the presence actuator saturation (particularly rate saturation). A design technique built upon Quantitative Feedback Theory is offered as a candidate methodology which can provide flight control systems meeting these requirements, and do so over a considerable part of the flight envelope. An example utilizing a simplified model of a supermaneuverable fighter aircraft demonstrates the proposed design methodology.
Simulation/optimization modeling for robust pumping strategy design.
Kalwij, Ineke M; Peralta, Richard C
2006-01-01
A new simulation/optimization modeling approach is presented for addressing uncertain knowledge of aquifer parameters. The Robustness Enhancing Optimizer (REO) couples genetic algorithm and tabu search as optimizers and incorporates aquifer parameter sensitivity analysis to guide multiple-realization optimization. The REO maximizes strategy robustness for a pumping strategy that is optimal for a primary objective function (OF), such as cost. The more robust a strategy, the more likely it is to achieve management goals in the field, even if the physical system differs from the model. The REO is applied to trinitrotoluene and Royal Demolition Explosive plumes at Umatilla Chemical Depot in Oregon to develop robust least cost strategies. The REO efficiently develops robust pumping strategies while maintaining the optimal value of the primary OF-differing from the common situation in which a primary OF value degrades as strategy reliability increases. The REO is especially valuable where data to develop realistic probability density functions (PDFs) or statistically derived realizations are unavailable. Because they require much less field data, REO-developed strategies might not achieve as high a mathematical reliability as strategies developed using many realizations based upon real aquifer parameter PDFs. REO-developed strategies might or might not yield a better OF value in the field. PMID:16857035
Robust Airfoil Optimization in High Resolution Design Space
NASA Technical Reports Server (NTRS)
Li, Wu; Padula, Sharon L.
2003-01-01
The robust airfoil shape optimization is a direct method for drag reduction over a given range of operating conditions and has three advantages: (1) it prevents severe degradation in the off-design performance by using a smart descent direction in each optimization iteration, (2) it uses a large number of B-spline control points as design variables yet the resulting airfoil shape is fairly smooth, and (3) it allows the user to make a trade-off between the level of optimization and the amount of computing time consumed. The robust optimization method is demonstrated by solving a lift-constrained drag minimization problem for a two-dimensional airfoil in viscous flow with a large number of geometric design variables. Our experience with robust optimization indicates that our strategy produces reasonable airfoil shapes that are similar to the original airfoils, but these new shapes provide drag reduction over the specified range of Mach numbers. We have tested this strategy on a number of advanced airfoil models produced by knowledgeable aerodynamic design team members and found that our strategy produces airfoils better or equal to any designs produced by traditional design methods.
Robustness-Based Design Optimization Under Data Uncertainty
NASA Technical Reports Server (NTRS)
Zaman, Kais; McDonald, Mark; Mahadevan, Sankaran; Green, Lawrence
2010-01-01
This paper proposes formulations and algorithms for design optimization under both aleatory (i.e., natural or physical variability) and epistemic uncertainty (i.e., imprecise probabilistic information), from the perspective of system robustness. The proposed formulations deal with epistemic uncertainty arising from both sparse and interval data without any assumption about the probability distributions of the random variables. A decoupled approach is proposed in this paper to un-nest the robustness-based design from the analysis of non-design epistemic variables to achieve computational efficiency. The proposed methods are illustrated for the upper stage design problem of a two-stage-to-orbit (TSTO) vehicle, where the information on the random design inputs are only available as sparse point and/or interval data. As collecting more data reduces uncertainty but increases cost, the effect of sample size on the optimality and robustness of the solution is also studied. A method is developed to determine the optimal sample size for sparse point data that leads to the solutions of the design problem that are least sensitive to variations in the input random variables.
Optimal Robust Motion Controller Design Using Multiobjective Genetic Algorithm
Svečko, Rajko
2014-01-01
This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution. PMID:24987749
Robust design of configurations and parameters of adaptable products
NASA Astrophysics Data System (ADS)
Zhang, Jian; Chen, Yongliang; Xue, Deyi; Gu, Peihua
2014-03-01
An adaptable product can satisfy different customer requirements by changing its configuration and parameter values during the operation stage. Design of adaptable products aims at reducing the environment impact through replacement of multiple different products with single adaptable ones. Due to the complex architecture, multiple functional requirements, and changes of product configurations and parameter values in operation, impact of uncertainties to the functional performance measures needs to be considered in design of adaptable products. In this paper, a robust design approach is introduced to identify the optimal design configuration and parameters of an adaptable product whose functional performance measures are the least sensitive to uncertainties. An adaptable product in this paper is modeled by both configurations and parameters. At the configuration level, methods to model different product configuration candidates in design and different product configuration states in operation to satisfy design requirements are introduced. At the parameter level, four types of product/operating parameters and relations among these parameters are discussed. A two-level optimization approach is developed to identify the optimal design configuration and its parameter values of the adaptable product. A case study is implemented to illustrate the effectiveness of the newly developed robust adaptable design method.
Robust power system controller design based on measured models
Fatehi, F.; Smith, J.R.; Pierre, D.A.
1996-05-01
This paper presents combined system identification and controller design methods to dampen low-frequency oscillations in multimachine power systems. An iterative closed-loop identification method is used to find a linear model for the power system. Linear quadratic Gaussian controller design with loop transfer recovery (LQG/LTR), based on a generalized technique for the nonminimum phase (NMP) power system model, is used to design controllers. Simulation results are presented to demonstrate the robustness of controllers based on closed-loop identified plant models and the amount of loop transfer recovery that is possible for NMP plant models.
Robust Control Design for Vibration Isolation of an Electron Beam Projection Lithography System
NASA Astrophysics Data System (ADS)
Wang, Fu-Cheng; Hong, Min-Feng; Yen, Jia-Yush
2010-06-01
This paper describes vibration control for an electron beam projection lithography (EPL) system. Two kinds of disturbances should be considered for an EPL: load disturbances from the machine and ground disturbances from the environment. However, the suspension settings for insulating these two disturbances conflict with each other. Therefore, we propose a double-layer optical table and apply disturbance response decomposing (DRD) techniques to independently control the disturbances. We use a passive control structure to isolate the ground disturbances, and an active control structure to suppress load disturbances. In addition, symmetric transformation is applied to decouple a full optical table into bounce/pitch and roll/warp half-table models, which can be further decoupled into quarter-table models to simplify controller design. Finally, we apply robust control techniques to design active controllers. From both simulation and experimental results, the designed H∞ robust controllers are proven effective in reducing EPL system vibrations.
Robust co-ordinated AVR-PSS design
Law, K.T.; Hill, D.J. . Dept. of Electrical Engineering and Computer Engineering); Godfrey, N.R. )
1994-08-01
This paper considers the design of auto-voltage regulator (AVR) and power system stabilizer (PSS) for the case of single machine connected to the infinite bus. Although it is not a true representation of the real power system, it is hoped that the insights into the single machine can help in the design of AVR-PSS for multi-machine power systems. The framework of Internal Model Control (IMC) is used to explore the properties and structures of an ideal AVR and an ideal PSS. Although these ideal controllers are not implementable in practice, they provide valuable insights and understanding of the design constraints of the problem which help to lead them to an implementable sub-optimal solution. This resulting AVR-PSS is not only robust but it also allows direct trade-off between voltage regulation and damping performance. The proposed PSS is a merely proportional gain, hence it gives considerable promise for ease of tuning especially in a multimachine system. This paper is a summary of a series of work done on robust co-ordinated AVR-PSS design. In particular, due to limited space, details of robust tuning and analysis techniques will not be presented here.
Robust circuit & architecture design in the nanoscale regime
NASA Astrophysics Data System (ADS)
Ashraf, Rehman
Silicon based integrated circuit (IC) technology is approaching its physical limits. For sub 10nm technology nodes, the carbon nanotube (CNT) based field effect transistor has emerged as a promising device because of its excellent electronic properties. One of the major challenges faced by the CNT technology is the unwanted growth of metallic tubes. At present, there is no known CNT fabrication technology which allows the fabrication of 100% semiconducting CNTs. The presence of metallic tubes creates a short between the drain and source terminals of the transistor and has a detrimental impact on the delay, static power and yield of CNT based gates. This thesis will address the challenge of designing robust carbon nanotube based circuits in the presence of metallic tubes. For a small percentage of metallic tubes, circuit level solutions are proposed to increase the functional yield of CNT based gates in the presence of metallic tubes. Accurate analytical models with less than a 3% inaccuracy rate are developed to estimate the yield of CNT based circuit for a different percentage of metallic tubes and different drive strengths of logic gates. Moreover, a design methodology is developed for yield-aware carbon nanotube based circuits in the presence of metallic tubes using different CNFET transistor configurations. Architecture based on regular logic bricks with underlying hybrid CNFET configurations are developed which gives better trade-offs in terms of performance, power, and functional yield. In the case when the percentage of metallic tubes is large, the proposed circuit level techniques are not sufficient. Extra processing techniques must be applied to remove the metallic tubes. The tube removal techniques have trade-offs, as the removal process is not perfect and removes semiconducting tubes in addition to removing unwanted metallic tubes. As a result, stochastic removal of tubes from the drive and fanout gate(s) results in large variation in the performance of
NASA Technical Reports Server (NTRS)
Murphy, Patrick C.; Davidson, John B.
1998-01-01
A multi-input, multi-output control law design methodology, named "CRAFT", is presented. CRAFT stands for the design objectives addressed, namely, Control power, Robustness, Agility, and Flying Qualities Tradeoffs. The methodology makes use of control law design metrics from each of the four design objective areas. It combines eigenspace assignment, which allows for direct specification of eigenvalues and eigenvectors, with a graphical approach for representing the metrics that captures numerous design goals in one composite illustration. Sensitivity of the metrics to eigenspace choice is clearly displayed, enabling the designer to assess the cost of design tradeoffs. This approach enhances the designer's ability to make informed design tradeoffs and to reach effective final designs. An example of the CRAFT methodology applied to an advanced experimental fighter and discussion of associated design issues are provided.
Frequency domain identification for robust large space structure control design
NASA Technical Reports Server (NTRS)
Yam, Y.; Bayard, D. S.; Scheid, R. E.
1991-01-01
A methodology is demonstrated for frequency domain identification of large space structures which systematically transforms experimental raw data into a form required for synthesizing H(infinity) controllers using modern robust control design software (e.g., Matlab Toolboxes). A unique feature of this approach is that the additive uncertainty is characterized to a specified statistic confidence rather than with hard bounds. In this study, the difference in robust performance is minimal between the two levels of confidence. In general cases, the present methodology provides a tool for performance/confidence level tradeoff studies. For simplicity, the additive uncertainty on a frequency grid is considered and the interpolation error in between grid points is neglected.
Optimal flexible sample size design with robust power.
Zhang, Lanju; Cui, Lu; Yang, Bo
2016-08-30
It is well recognized that sample size determination is challenging because of the uncertainty on the treatment effect size. Several remedies are available in the literature. Group sequential designs start with a sample size based on a conservative (smaller) effect size and allow early stop at interim looks. Sample size re-estimation designs start with a sample size based on an optimistic (larger) effect size and allow sample size increase if the observed effect size is smaller than planned. Different opinions favoring one type over the other exist. We propose an optimal approach using an appropriate optimality criterion to select the best design among all the candidate designs. Our results show that (1) for the same type of designs, for example, group sequential designs, there is room for significant improvement through our optimization approach; (2) optimal promising zone designs appear to have no advantages over optimal group sequential designs; and (3) optimal designs with sample size re-estimation deliver the best adaptive performance. We conclude that to deal with the challenge of sample size determination due to effect size uncertainty, an optimal approach can help to select the best design that provides most robust power across the effect size range of interest. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26999385
Analysis and design of robust decentralized controllers for nonlinear systems
Schoenwald, D.A.
1993-07-01
Decentralized control strategies for nonlinear systems are achieved via feedback linearization techniques. New results on optimization and parameter robustness of non-linear systems are also developed. In addition, parametric uncertainty in large-scale systems is handled by sensitivity analysis and optimal control methods in a completely decentralized framework. This idea is applied to alleviate uncertainty in friction parameters for the gimbal joints on Space Station Freedom. As an example of decentralized nonlinear control, singular perturbation methods and distributed vibration damping are merged into a control strategy for a two-link flexible manipulator.
Robust integrated autopilot/autothrottle design using constrained parameter optimization
NASA Technical Reports Server (NTRS)
Ly, Uy-Loi; Voth, Christopher; Sanjay, Swamy
1990-01-01
A multivariable control design method based on constrained parameter optimization was applied to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the following: (1) direct synthesis of a multivariable 'inner-loop' feedback control system based on total energy control principles; (2) synthesis of speed/altitude-hold designs as 'outer-loop' feedback/feedforward control systems around the above inner loop; and (3) direct synthesis of a combined 'inner-loop' and 'outer-loop' multivariable control system. The design procedure offers a direct and structured approach for the determination of a set of controller gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The presented approach may be applied to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by this method following careful problem formulation of the design objectives and constraints. Performance characteristics of the optimization design were improved over the current autopilot design on the B737-100 Transport Research Vehicle (TSRV) at the landing approach and cruise flight conditions; particularly in the areas of closed-loop damping, command responses, and control activity in the presence of turbulence.
Designing robust unitary gates: Application to concatenated composite pulses
Ichikawa, Tsubasa; Bando, Masamitsu; Kondo, Yasushi; Nakahara, Mikio
2011-12-15
We propose a simple formalism to design unitary gates robust against given systematic errors. This formalism generalizes our previous observation [Y. Kondo and M. Bando, J. Phys. Soc. Jpn. 80, 054002 (2011)] that vanishing dynamical phase in some composite gates is essential to suppress pulse-length errors. By employing our formalism, we derive a composite unitary gate which can be seen as a concatenation of two known composite unitary operations. The obtained unitary gate has high fidelity over a wider range of error strengths compared to existing composite gates.
Applying Expert System on the Development of a Robust Model for Groundwater Parameter Identification
NASA Astrophysics Data System (ADS)
Hsu, K.; Chang, L.; Jung, C.; Huang, C.; Chen, J.; Tsai, P. J.; Chen, Y.; Chang, P.
2011-12-01
Conventional groundwater parameter identification modeling based on optimization, such as UCODE, has difficulty converging to a global optimum in a high dimension situation. To avoid this convergence problem, this study integrates a rule-based expert system and a groundwater simulation model, MODFLOW 2000, to develop a robust methodology for groundwater parameter identification. Because the expert system requires calibration rules to identify parameters, users can flexibly add new rules or modify existing rules with this proposed methodology. Therefore, the proposed methodology can adapt for new parameter identification problems easily. We apply this proposed methodology to a real case study of Choshuihsi Alluvial Fan which is located at the central Taiwan. To test the robustness for high dimension problems, the proposed methodology is applied to calibrate the net recharge rates in a transient simulation in the study area. The result is compared with the calibration results obtained from UCODE. The results show that the initial guess dramatically effects the convergency of the optimization using UCODE, but our proposed methodology is very robust for achieving the convergence requirements of output error criteria for high dimensional problems. These results presented the robustness and the applicability of the proposed methodology for high dimensional groundwater parameter identification problems.
Quantum theory as plausible reasoning applied to data obtained by robust experiments.
De Raedt, H; Katsnelson, M I; Michielsen, K
2016-05-28
We review recent work that employs the framework of logical inference to establish a bridge between data gathered through experiments and their objective description in terms of human-made concepts. It is shown that logical inference applied to experiments for which the observed events are independent and for which the frequency distribution of these events is robust with respect to small changes of the conditions under which the experiments are carried out yields, without introducing any concept of quantum theory, the quantum theoretical description in terms of the Schrödinger or the Pauli equation, the Stern-Gerlach or Einstein-Podolsky-Rosen-Bohm experiments. The extraordinary descriptive power of quantum theory then follows from the fact that it is plausible reasoning, that is common sense, applied to reproducible and robust experimental data. PMID:27091169
Robust design and model validation of nonlinear compliant micromechanisms.
Howell, Larry L.; Baker, Michael Sean; Wittwer, Jonathan W.
2005-02-01
Although the use of compliance or elastic flexibility in microelectromechanical systems (MEMS) helps eliminate friction, wear, and backlash, compliant MEMS are known to be sensitive to variations in material properties and feature geometry, resulting in large uncertainties in performance. This paper proposes an approach for design stage uncertainty analysis, model validation, and robust optimization of nonlinear MEMS to account for critical process uncertainties including residual stress, layer thicknesses, edge bias, and material stiffness. A fully compliant bistable micromechanism (FCBM) is used as an example, demonstrating that the approach can be used to handle complex devices involving nonlinear finite element models. The general shape of the force-displacement curve is validated by comparing the uncertainty predictions to measurements obtained from in situ force gauges. A robust design is presented, where simulations show that the estimated force variation at the point of interest may be reduced from {+-}47 {micro}N to {+-}3 {micro}N. The reduced sensitivity to process variations is experimentally validated by measuring the second stable position at multiple locations on a wafer.
A robust adaptive autopilot design for decomposed bank to turn missiles
NASA Astrophysics Data System (ADS)
Song, Kwang Sub
2001-07-01
A decomposed robust adaptive controller design procedure is developed for 3-channel BTT missile systems. Three decomposed subsystems are constructed for highly nonlinear and coupled dynamic systems after parameter analysis is carried out. Appropriate adaptive optimal inner loop controllers are designed for accurate tracking performance to the reference command inputs of the respective subsystems. For robustness of systems, decomposed outer loop structures are introduced to minimize system coupling and to reduce nonlinear effects of BTT missile dynamic systems. The overall outer loop robust controller is designed to accommodate parameter variations and uncertainties with referenced model systems. The robust outer loop controller is designed by constructing decomposed stabilizing controllers in the form of the Youla parameterization. The results can be readily generalized to N-channel systems. The design procedure is built upon the J-spectral factorization approach to Hinfinity control. Instead of the centralized control, we employed decentralized controllers for reduced complexity in control implementations. In this research, a new concept for system modeling and decomposition, which uses the rate of system dynamics or the sensitivity of system parameter. After exhaustive classification and investigations of system characteristics, we can categorize several subsystems from overall system dynamic models. Subsystems are characterized by system dynamics with similar rates of changes. Once we get relatively small sized and homogeneous parameter groups, it is easier to design respective controllers. Otherwise, difficult trade offs must be made on control objectives for different kinds of dynamic characteristics of the whole system. The new idea is applied to a typical BTT missile system. Simulations results demonstrate that decomposed controller design is satisfactory for the BTT missile autopilot systems with good robustness and dynamic performances.
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.
Robust Feedback Linearization Applied to a Separation Column for {sup 13}C
Dulf, Eva-Henrietta; Pop, Cristina-Ioana; Festila, Clement; Dulf, Francisc
2009-03-05
In the present developing plan to apply the cryogenic technology for the production of the {sup 13}C, an efficient and safe operation is a strong reason to conceive and to apply a modern computer based control strategy. The authors are concerned with the problem of developing effective and readily implemental techniques for modelling and control of the isotope separation plant. These columns are characterized by complex nonlinearities, with large time-delays. Furthermore, are subject to external disturbances, which are difficult to model. The present paper presents two models of the plant: a nonlinear model and a linear system obtained by robust feedback linearization.
Lin, Yuqun
2014-01-01
The performance of the suspension system is one of the most important factors in the vehicle design. For the double wishbone suspension system, the conventional deterministic optimization does not consider any deviations of design parameters, so design sensitivity analysis and robust optimization design are proposed. In this study, the design parameters of the robust optimization are the positions of the key points, and the random factors are the uncertainties in manufacturing. A simplified model of the double wishbone suspension is established by software ADAMS. The sensitivity analysis is utilized to determine main design variables. Then, the simulation experiment is arranged and the Latin hypercube design is adopted to find the initial points. The Kriging model is employed for fitting the mean and variance of the quality characteristics according to the simulation results. Further, a particle swarm optimization method based on simple PSO is applied and the tradeoff between the mean and deviation of performance is made to solve the robust optimization problem of the double wishbone suspension system. PMID:24683334
Robust parameter design for automatically controlled systems and nanostructure synthesis
NASA Astrophysics Data System (ADS)
Dasgupta, Tirthankar
2007-12-01
This research focuses on developing comprehensive frameworks for developing robust parameter design methodology for dynamic systems with automatic control and for synthesis of nanostructures. In many automatically controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and vice versa and therefore an integrated approach is necessary. A parameter design methodology in the presence of feedback control is developed for processes of long duration under the assumption that experimental noise factors are uncorrelated over time. Systems that follow a pure-gain dynamic model are considered and the best proportional-integral and minimum mean squared error control strategies are developed by using robust parameter design. The proposed method is illustrated using a simulated example and a case study in a urea packing plant. This idea is also extended to cases with on-line noise factors. The possibility of integrating feedforward control with a minimum mean squared error feedback control scheme is explored. To meet the needs of large scale synthesis of nanostructures, it is critical to systematically find experimental conditions under which the desired nanostructures are synthesized reproducibly, at large quantity and with controlled morphology. The first part of the research in this area focuses on modeling and optimization of existing experimental data. Through a rigorous statistical analysis of experimental data, models linking the probabilities of obtaining specific morphologies to the process variables are developed. A new iterative algorithm for fitting a Multinomial GLM is proposed and used. The optimum process conditions, which maximize the above probabilities and make the synthesis process less sensitive to variations of process variables around set values, are derived from the fitted models using Monte-Carlo simulations. The second part of the research deals with development of an experimental design methodology, tailor
Advanced Vibration Analysis Tool Developed for Robust Engine Rotor Designs
NASA Technical Reports Server (NTRS)
Min, James B.
2005-01-01
The primary objective of this research program is to develop vibration analysis tools, design tools, and design strategies to significantly improve the safety and robustness of turbine engine rotors. Bladed disks in turbine engines always feature small, random blade-to-blade differences, or mistuning. Mistuning can lead to a dramatic increase in blade forced-response amplitudes and stresses. Ultimately, this results in high-cycle fatigue, which is a major safety and cost concern. In this research program, the necessary steps will be taken to transform a state-of-the-art vibration analysis tool, the Turbo- Reduce forced-response prediction code, into an effective design tool by enhancing and extending the underlying modeling and analysis methods. Furthermore, novel techniques will be developed to assess the safety of a given design. In particular, a procedure will be established for using natural-frequency curve veerings to identify ranges of operating conditions (rotational speeds and engine orders) in which there is a great risk that the rotor blades will suffer high stresses. This work also will aid statistical studies of the forced response by reducing the necessary number of simulations. Finally, new strategies for improving the design of rotors will be pursued.
A robust parameter design for multi-response problems
NASA Astrophysics Data System (ADS)
Zandieh, M.; Amiri, M.; Vahdani, B.; Soltani, R.
2009-08-01
Most real world search and optimization problems naturally involve multiple responses. In this paper we investigate a multiple response problem within desirability function framework and try to determine values of input variables that achieve a target value for each response through three meta-heuristic algorithms such as genetic algorithm (GA), simulated annealing (SA) and tabu search (TS). Each algorithm has some parameters that need to be accurately calibrated to ensure the best performance. For this purpose, a robust calibration is applied to the parameters by means of Taguchi method. The computational results of these three algorithms are compared against each others. The superior performance of SA over TS and TS over GA is inferred from the obtained results in various situations.
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.
Efficiency and robustness of different bus network designs
NASA Astrophysics Data System (ADS)
Pang, John Zhen Fu; Bin Othman, Nasri; Ng, Keng Meng; Monterola, Christopher
2015-07-01
We compare the efficiencies and robustness of four transport networks that can be possibly formed as a result of deliberate city planning. The networks are constructed based on their spatial resemblance to the cities of Manhattan (lattice), Sudan (random), Beijing (single-blob) and Greater Cairo (dual-blob). For a given type, a genetic algorithm is employed to obtain an optimized set of the bus routes. We then simulate how commuter travels using Yen's algorithms for k shortest paths on an adjacency matrix. The cost of traveling such as walking between stations is captured by varying the weighted sums of matrices. We also consider the number of transfers a posteriori by looking at the computed shortest paths. With consideration to distances via radius of gyration, redundancies of travel and number of bus transfers, our simulations indicate that random and dual-blob are more efficient than single-blob and lattice networks. Moreover, dual-blob type is least robust when node removals are targeted but is most resilient when node failures are random. The work hopes to guide and provide technical perspectives on how geospatial distribution of a city limits the optimality of transport designs.
Robustness in Nature as a Design Principle for Artificial Intelligence
NASA Astrophysics Data System (ADS)
Schuster, Alfons
Robustness is a feature in many systems, natural and artificial alike. This chapter investigates robustness from a variety of perspectives including its appearances in nature and its application in modern environments. A particular focus investigates the relevance and importance of robustness in a discipline where many techniques are inspired by problem-solving strategies found in nature—artificial intelligence. The challenging field of artificial intelligence provides an opportunity to engage in a wider discussion on the subject of robustness.
Robust Optimization Design Algorithm for High-Frequency TWTs
NASA Technical Reports Server (NTRS)
Wilson, Jeffrey D.; Chevalier, Christine T.
2010-01-01
Traveling-wave tubes (TWTs), such as the Ka-band (26-GHz) model recently developed for the Lunar Reconnaissance Orbiter, are essential as communication amplifiers in spacecraft for virtually all near- and deep-space missions. This innovation is a computational design algorithm that, for the first time, optimizes the efficiency and output power of a TWT while taking into account the effects of dimensional tolerance variations. Because they are primary power consumers and power generation is very expensive in space, much effort has been exerted over the last 30 years to increase the power efficiency of TWTs. However, at frequencies higher than about 60 GHz, efficiencies of TWTs are still quite low. A major reason is that at higher frequencies, dimensional tolerance variations from conventional micromachining techniques become relatively large with respect to the circuit dimensions. When this is the case, conventional design- optimization procedures, which ignore dimensional variations, provide inaccurate designs for which the actual amplifier performance substantially under-performs that of the design. Thus, this new, robust TWT optimization design algorithm was created to take account of and ameliorate the deleterious effects of dimensional variations and to increase efficiency, power, and yield of high-frequency TWTs. This design algorithm can help extend the use of TWTs into the terahertz frequency regime of 300-3000 GHz. Currently, these frequencies are under-utilized because of the lack of efficient amplifiers, thus this regime is known as the "terahertz gap." The development of an efficient terahertz TWT amplifier could enable breakthrough applications in space science molecular spectroscopy, remote sensing, nondestructive testing, high-resolution "through-the-wall" imaging, biomedical imaging, and detection of explosives and toxic biochemical agents.
Salinas, Cristian; Muzic, Raymond F. Jr.; Ernsberger, Paul; Saidel, Gerald M.
2007-01-15
Myocardial {beta} adrenergic receptor ({beta}-AR) concentration can substantially decrease in congestive heart failure and significantly increase in chronic volume overload, such as in severe aortic valve regurgitation. Positron emission tomography (PET) with an appropriate ligand-receptor model can be used for noninvasive estimation of myocardial {beta}-AR concentration in vivo. An optimal design of the experiment protocol, however, is needed for sufficiently precise estimates of {beta}-AR concentration in a heterogeneous population. Standard methods of optimal design do not account for a heterogeneous population with a wide range of {beta}-AR concentrations and other physiological parameters and consequently are inadequate. To address this, we have developed a methodology to design a robust two-injection protocol that provides reliable estimates of myocardial {beta}-AR concentration in normal and pathologic states. A two-injection protocol of the high affinity {beta}-AR antagonist [{sup 18}F]-(S)-fluorocarazolol was designed based on a computer-generated (or synthetic) population incorporating a wide range of {beta}-AR concentrations. Timing and dosage of the ligand injections were optimally designed with minimax criterion to provide the least bad {beta}-AR estimates for the worst case in the synthetic population. This robust experiment design for PET was applied to experiments with pigs before and after {beta}-AR upregulation by chemical sympathectomy. Estimates of {beta}-AR concentration were found by minimizing the difference between the model-predicted and experimental PET data. With this robust protocol, estimates of {beta}-AR concentration showed high precision in both normal and pathologic states. The increase in {beta}-AR concentration after sympathectomy predicted noninvasively with PET is consistent with the increase shown by in vitro assays in pig myocardium. A robust experiment protocol was designed for PET that yields reliable estimates of {beta
Intergration of system identification and robust controller designs for flexible structures in space
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Lew, Jiann-Shiun
1990-01-01
An approach is developed using experimental data to identify a reduced-order model and its model error for a robust controller design. There are three steps involved in the approach. First, an approximately balanced model is identified using the Eigensystem Realization Algorithm, which is an identification algorithm. Second, the model error is calculated and described in frequency domain in terms of the H(infinity) norm. Third, a pole placement technique in combination with a H(infinity) control method is applied to design a controller for the considered system. A set experimental data from an existing setup, namely the Mini-Mast system, is used to illustrate and verify the approach.
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.
Design of a robust SHM system for composite structures
NASA Astrophysics Data System (ADS)
Beard, Shawn; Liu, Ching-Chao; Chang, Fu-Kuo
2007-04-01
Composites are becoming increasingly popular materials used in a wide range of applications on large-scale structures such as windmill blades, rocket motor cases, and aircraft fuselage and wings. For these large structures, using composites greatly enhances the operation and performance of the application, but also introduces extraordinary inspection challenges that push the limits of traditional NDE in terms of time and cost. Recent advances in Structural Health Monitoring (SHM) technologies offer a promising solution to these inspection challenges. But efficient design methodologies and implementation procedures are needed to ensure the reliability and robustness of SHM technologies for use in real-world applications. This paper introduces the essential elements of the design and implementation process by way of example. State-of-the-art techniques to optimize sensor placement, perform self-diagnostics, compensate for environmental conditions, and generate probability of detection (POD) curves for any application are discussed. The techniques are presented in relation to Acellent's recently developed SmartComposite System that is used to monitor the integrity of large composite structures. The system builds on the active sensor network technology of Acellent that is analogous to a built-in acousto-ultrasonic NDE system. Key features of the system include new miniaturized lightweight hardware, self-diagnostics and adaptive algorithm to automatically compensate for damaged sensors, reliable damage detection under different environmental conditions, and generation of POD curves. This paper will provide an overview of the system and demonstrate its key features.
Designing for Damage: Robust Flight Control Design using Sliding Mode Techniques
NASA Technical Reports Server (NTRS)
Vetter, T. K.; Wells, S. R.; Hess, Ronald A.; Bacon, Barton (Technical Monitor); Davidson, John (Technical Monitor)
2002-01-01
A brief review of sliding model control is undertaken, with particular emphasis upon the effects of neglected parasitic dynamics. Sliding model control design is interpreted in the frequency domain. The inclusion of asymptotic observers and control 'hedging' is shown to reduce the effects of neglected parasitic dynamics. An investigation into the application of observer-based sliding mode control to the robust longitudinal control of a highly unstable is described. The sliding mode controller is shown to exhibit stability and performance robustness superior to that of a classical loop-shaped design when significant changes in vehicle and actuator dynamics are employed to model airframe damage.
A novel methodology for building robust design rules by using design based metrology (DBM)
NASA Astrophysics Data System (ADS)
Lee, Myeongdong; Choi, Seiryung; Choi, Jinwoo; Kim, Jeahyun; Sung, Hyunju; Yeo, Hyunyoung; Shim, Myoungseob; Jin, Gyoyoung; Chung, Eunseung; Roh, Yonghan
2013-03-01
This paper addresses a methodology for building robust design rules by using design based metrology (DBM). Conventional method for building design rules has been using a simulation tool and a simple pattern spider mask. At the early stage of the device, the estimation of simulation tool is poor. And the evaluation of the simple pattern spider mask is rather subjective because it depends on the experiential judgment of an engineer. In this work, we designed a huge number of pattern situations including various 1D and 2D design structures. In order to overcome the difficulties of inspecting many types of patterns, we introduced Design Based Metrology (DBM) of Nano Geometry Research, Inc. And those mass patterns could be inspected at a fast speed with DBM. We also carried out quantitative analysis on PWQ silicon data to estimate process variability. Our methodology demonstrates high speed and accuracy for building design rules. All of test patterns were inspected within a few hours. Mass silicon data were handled with not personal decision but statistical processing. From the results, robust design rules are successfully verified and extracted. Finally we found out that our methodology is appropriate for building robust design rules.
Robustness analysis and controller design for static var compensators in power systems
NASA Astrophysics Data System (ADS)
Yu, Xuechun I.
effect of the supplementary controller on improving system dynamic performance and stability limits is also examined. The technique is applied to two test systems which are the four-machine test system and the IEEE 50-generator test system. Both the analysis and synthesis results clearly demonstrate the efficacy of the mu-based technique in analyzing and designing controls to meet robust performance and stability requirement.
Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate
NASA Astrophysics Data System (ADS)
Samaras, C.; Cook, L.
2015-12-01
Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.
Robust two-parameter invariant CFAR detection utilizing order statistics applied to Weibull clutter
NASA Astrophysics Data System (ADS)
Nagle, Daniel T.; Saniie, Jafar
1992-08-01
Constant False Alarm Rate (CFAR) detectors are designed to perform when the clutter information is partially unknown and/or varying. This is accomplished using local threshold estimates from background observations in which the CFAR level is maintained. However, when local observations contain target or irrelevant information, censoring is warranted to improve detection performance. Order Statistics (OS) processors have been shown to perform robustly (referring to type II errors or CFAR loss) for heterogeneous background clutter observations, and their performance has been analyzed for exponential clutter with unknown power. In this paper, several order statistics are used to create an invariant test statistic for Weibull clutter with two varying parameters (i.e., power and skewness). The robustness of a two-parameter invariant CFAR detector is analyzed and compared with an uncensored Weibull-Two Parameter (WTP) CFAR detector and conventional Cell Averaging (CA)-CFAR detector (i.e., designed invariant to exponential clutter). The performance trade-offs of these detectors are gaged for different scenarios of volatile clutter environments.
Robust Stability Analysis of the Space Launch System Control Design: A Singular Value Approach
NASA Technical Reports Server (NTRS)
Pei, Jing; Newsome, Jerry R.
2015-01-01
Classical stability analysis consists of breaking the feedback loops one at a time and determining separately how much gain or phase variations would destabilize the stable nominal feedback system. For typical launch vehicle control design, classical control techniques are generally employed. In addition to stability margins, frequency domain Monte Carlo methods are used to evaluate the robustness of the design. However, such techniques were developed for Single-Input-Single-Output (SISO) systems and do not take into consideration the off-diagonal terms in the transfer function matrix of Multi-Input-Multi-Output (MIMO) systems. Robust stability analysis techniques such as H(sub infinity) and mu are applicable to MIMO systems but have not been adopted as standard practices within the launch vehicle controls community. This paper took advantage of a simple singular-value-based MIMO stability margin evaluation method based on work done by Mukhopadhyay and Newsom and applied it to the SLS high-fidelity dynamics model. The method computes a simultaneous multi-loop gain and phase margin that could be related back to classical margins. The results presented in this paper suggest that for the SLS system, traditional SISO stability margins are similar to the MIMO margins. This additional level of verification provides confidence in the robustness of the control design.
Applying vision feedback to crane controller design
NASA Astrophysics Data System (ADS)
Lee, Lun-Hui; Huang, Pei-Hsiang; Pan, Shing-Tai; Wijaya Lie, Handra; Chiang, Tung-Chien; Chang, Cheng-Yuan
2015-01-01
Encoders are generally used to track the motion of industrial mechanisms. However, the information obtained by encoders may have errors due to encoder aging or mechanism-design problem. Therefore, information by visual feedback is a better way to track the movement of industrial mechanisms. However, image information costs lots of computing effort so it is not easy to be used in real-time control applications. This manuscript derives a simple but effective visual feedback method to follow the target and the image information is obtained only by a general handy camcorder. Besides, the proposed method can track multi-locations in a meantime. Fast image pattern recognition and localisation of the colour histogram by using a moving tracking block is applied to increase the calculation speed. Finally, the obtained locations information by the proposed visual feedback method is applied in an industrial crane control system to verify the effectiveness.
Robust controller design of four wheel steering systems using mu synthesis techniques
Gao, X.; McVey, B.D.; Tokar, R.L.
1995-02-27
In this paper, a linearized four wheel steering (4WS) system model is deduced and then modified into a form which is appropriate for applying Matlab {mu} Toolbox to design robust controller. Several important topics are discussed in detail, such as (1) how to make system set-up match Matlab {mu} Toolbox requirement, (2) how to select weights based on plant`s uncertainty, (3) how to solve controller discretization problem, and (4) how to adjust the system so that the conditions necessary for using a state-space formula to solve H{infinity} optimal (sub-optimal) problem and performing the Matlab {mu} Toolbox D--K iteration procedure are satisfied. Finally simulation results of robust controller and a PID controller are compared.
Design of robust controllers for smart structural systems with structured uncertainties
NASA Astrophysics Data System (ADS)
Sana, Sridhar; Rao, Vittal S.
2000-06-01
Effective integration of sensors, actuators and controllers with the structures is key to the success of smart structures. This concept has been manifested in numerous applications of smart structures in the areas such as civil, aerospace and automotive engineering. Control systems to be integrated with the structure is of paramount importance for ensuring the performance requirements in the presence of modal parameter variations, modeling errors and control effort constraints. The primary uncertainty associated with smart structural systems use the natural frequency variations. Linear Matrix Inequalities (LMIs) can be utilized to incorporate the real parameter uncertainty due to parameter variations and control input limits in the controller design. One of the challenges in the design of such controllers is the conservatism due to over bounding effect from the multiple constraints. Additional conservatism can also come from the approximation of the real parametric uncertainty due to modal parameter variations as sector bounded nonlinear, time varying or complex valued uncertainty. Using the traditional robustness analysis methods such as small gain theorem in the controller design will result in conservative designs leading to poor performance. In this paper, we present a controller synthesis procedure based on Popov stability results for reducing the conservatism in the design. Robust controllers are designed for real- parametric uncertainty arising from natural frequency variations in the presence of control input limits. Maximum possible attenuation in the structural response due to finite energy disturbances is also achieved. Trade-off between the robustness versus the control input limit is discussed. The design procedure is applied on a smart structural test article and the results are presented.
Design and Evaluation of a Robust PID Controller for a Fully Implantable Artificial Pancreas
2015-01-01
Treatment of type 1 diabetes mellitus could be greatly improved by applying a closed-loop control strategy to insulin delivery, also known as an artificial pancreas (AP). In this work, we outline the design of a fully implantable AP using intraperitoneal (IP) insulin delivery and glucose sensing. The design process utilizes the rapid glucose sensing and insulin action offered by the IP space to tune a PID controller with insulin feedback to provide safe and effective insulin delivery. The controller was tuned to meet robust performance and stability specifications. An anti-reset windup strategy was introduced to prevent dangerous undershoot toward hypoglycemia after a large meal disturbance. The final controller design achieved 78% of time within the tight glycemic range of 80–140 mg/dL, with no time spent in hypoglycemia. The next step is to test this controller design in an animal model to evaluate the in vivo performance. PMID:26538805
A design methodology for robust failure detection and isolation
NASA Technical Reports Server (NTRS)
Pattipati, K. R.; Willsky, A. S.; Deckert, J. C.; Eterno, J. S.; Weiss, J. S.
1984-01-01
A decentralized failure detection and isolation (FDI) methodology, which is robust with respect to model uncertainties and noise, is presented Redundancy metrics are developed, and optimization problems are posed for the choices of robust parity relations. Closed-form solutions for some special failure cases are given. Connections are drawn with other disciplines, and the use of the metrics to evaluate alternative FDI schemes is discussed.
Design of a robust EMG sensing interface for pattern classification.
Huang, He; Zhang, Fan; Sun, Yan L; He, Haibo
2010-10-01
Electromyographic (EMG) pattern classification has been widely investigated for neural control of external devices in order to assist with movements of patients with motor deficits. Classification performance deteriorates due to inevitable disturbances to the sensor interface, which significantly challenges the clinical value of this technique. This study aimed to design a sensor fault detection (SFD) module in the sensor interface to provide reliable EMG pattern classification. This module monitored the recorded signals from individual EMG electrodes and performed a self-recovery strategy to recover the classification performance when one or more sensors were disturbed. To evaluate this design, we applied synthetic disturbances to EMG signals collected from leg muscles of able-bodied subjects and a subject with a transfemoral amputation and compared the accuracies for classifying transitions between different locomotion modes with and without the SFD module. The results showed that the SFD module maintained classification performance when one signal was distorted and recovered about 20% of classification accuracy when four signals were distorted simultaneously. The method was simple to implement. Additionally, these outcomes were observed for all subjects, including the leg amputee, which implies the promise of the designed sensor interface for providing a reliable neural-machine interface for artificial legs. PMID:20811091
Design of a robust EMG sensing interface for pattern classification
NASA Astrophysics Data System (ADS)
Huang, He; Zhang, Fan; Sun, Yan L.; He, Haibo
2010-10-01
Electromyographic (EMG) pattern classification has been widely investigated for neural control of external devices in order to assist with movements of patients with motor deficits. Classification performance deteriorates due to inevitable disturbances to the sensor interface, which significantly challenges the clinical value of this technique. This study aimed to design a sensor fault detection (SFD) module in the sensor interface to provide reliable EMG pattern classification. This module monitored the recorded signals from individual EMG electrodes and performed a self-recovery strategy to recover the classification performance when one or more sensors were disturbed. To evaluate this design, we applied synthetic disturbances to EMG signals collected from leg muscles of able-bodied subjects and a subject with a transfemoral amputation and compared the accuracies for classifying transitions between different locomotion modes with and without the SFD module. The results showed that the SFD module maintained classification performance when one signal was distorted and recovered about 20% of classification accuracy when four signals were distorted simultaneously. The method was simple to implement. Additionally, these outcomes were observed for all subjects, including the leg amputee, which implies the promise of the designed sensor interface for providing a reliable neural-machine interface for artificial legs.
Design of a robust EMG sensing interface for pattern classification
Huang, He; Zhang, Fan; Sun, Yan L.; He, Haibo
2010-01-01
Electromyographic (EMG) pattern classification has been widely investigated for neural control of external devices in order to assist with movements of patients with motor deficits. Classification performance deteriorates due to inevitable disturbances to the sensor interface, which significantly challenges the clinical value of this technique. This study aimed to design a sensor fault detection (SFD) module in the sensor interface to provide reliable EMG pattern classification. This module monitored the recorded signals from individual EMG electrodes and performed a self-recovery strategy to recover the classification performance when one or more sensors were disturbed. To evaluate this design, we applied synthetic disturbances to EMG signals collected from leg muscles of able-bodied subjects and a subject with a transfemoral amputation and compared the accuracies for classifying transitions between different locomotion modes with and without the SFD module. The results showed that the SFD module maintained classification performance when one signal was distorted and recovered about 20% of classification accuracy when four signals were distorted simultaneously. The method was simple to implement. Additionally, these outcomes were observed for all subjects, including the leg amputee, which implies the promise of the designed sensor interface for providing a reliable neural-machine interface for artificial legs. PMID:20811091
Reducing Design Risk Using Robust Design Methods: A Dual Response Surface Approach
NASA Technical Reports Server (NTRS)
Unal, Resit; Yeniay, Ozgur; Lepsch, Roger A. (Technical Monitor)
2003-01-01
Space transportation system conceptual design is a multidisciplinary process containing considerable element of risk. Risk here is defined as the variability in the estimated (output) performance characteristic of interest resulting from the uncertainties in the values of several disciplinary design and/or operational parameters. Uncertainties from one discipline (and/or subsystem) may propagate to another, through linking parameters and the final system output may have a significant accumulation of risk. This variability can result in significant deviations from the expected performance. Therefore, an estimate of variability (which is called design risk in this study) together with the expected performance characteristic value (e.g. mean empty weight) is necessary for multidisciplinary optimization for a robust design. Robust design in this study is defined as a solution that minimizes variability subject to a constraint on mean performance characteristics. Even though multidisciplinary design optimization has gained wide attention and applications, the treatment of uncertainties to quantify and analyze design risk has received little attention. This research effort explores the dual response surface approach to quantify variability (risk) in critical performance characteristics (such as weight) during conceptual design.
Student design projects in applied acoustics.
Bös, Joachim; Moritz, Karsten; Skowronek, Adam; Thyes, Christian; Tschesche, Johannes; Hanselka, Holger
2012-03-01
This paper describes a series of student projects which are intended to complement theoretical education in acoustics and engineering noise control with practical experience. The projects are also intended to enhance the students' ability to work in a team, to manage a project, and to present their results. The projects are carried out in close cooperation with industrial partners so that the students can get a taste of the professional life of noise control engineers. The organization of such a project, its execution, and some of the results from the most recent student project are presented as a demonstrative example. This latest project involved the creation of noise maps of a production hall, the acoustic analysis of a packaging machine, and the acoustic analysis of a spiral vibratory conveyor. Upon completion of the analysis, students then designed, applied, and verified some simple preliminary noise reduction measures to demonstrate the potential of these techniques. PMID:22423803
Ignition target design and robustness studies for the National Ignition Facility
Krauser, W.J.; Hoffman, N.M.; Wilson, D.C.
1995-12-01
Recent results are presented from two-dimensional LASNEX calculations of the indirectly driven hohlraum and ignition capsules proposed for the National Ignition Facility (NIF). The calculations concentrate on two capsule designs, the baseline design which has a bromine-doped plastic ablator, and the beryllium design which has a copper-doped beryllium ablator. Both capsules have a cryogenic fuel layer. Primary emphasis in these calculations is placed upon robustness studies detailing various sensitivities. These studies fall naturally into two categories, those performed with integrated modeling where the capsule, hohlraum, and laser rays all are modeled simultaneously with the laser power levels as the only energy input, and those performed in a capsule-only mode where an externally imposed drive is applied to the exterior of the ignition capsule and only the capsule performance is modeled. Integrated modeling calculations address sensitivities to, e.g., the laser pointing; among other things, capsule-only calculations address yield degradation due to the growth of hydrodynamic instabilities seeded by initial surface roughnesses on the capsules. Limitations of the calculational models and directions for future research are discussed. The results of the robustness studies performed to date enhance the authors` confidence that the NIF can achieve ignition and produce 10--15 MJ of capsule yield with one or more capsule designs.
Simulation Assisted Risk Assessment Applied to Launch Vehicle Conceptual Design
NASA Technical Reports Server (NTRS)
Mathias, Donovan L.; Go, Susie; Gee, Ken; Lawrence, Scott
2008-01-01
A simulation-based risk assessment approach is presented and is applied to the analysis of abort during the ascent phase of a space exploration mission. The approach utilizes groupings of launch vehicle failures, referred to as failure bins, which are mapped to corresponding failure environments. Physical models are used to characterize the failure environments in terms of the risk due to blast overpressure, resulting debris field, and the thermal radiation due to a fireball. The resulting risk to the crew is dynamically modeled by combining the likelihood of each failure, the severity of the failure environments as a function of initiator and time of the failure, the robustness of the crew module, and the warning time available due to early detection. The approach is shown to support the launch vehicle design process by characterizing the risk drivers and identifying regions where failure detection would significantly reduce the risk to the crew.
NASA Astrophysics Data System (ADS)
Martowicz, Adam; Uhl, Tadeusz
2012-10-01
The paper discusses the applicability of a reliability- and performance-based multi-criteria robust design optimization technique for micro-electromechanical systems, considering their technological uncertainties. Nowadays, micro-devices are commonly applied systems, especially in the automotive industry, taking advantage of utilizing both the mechanical structure and electronic control circuit on one board. Their frequent use motivates the elaboration of virtual prototyping tools that can be applied in design optimization with the introduction of technological uncertainties and reliability. The authors present a procedure for the optimization of micro-devices, which is based on the theory of reliability-based robust design optimization. This takes into consideration the performance of a micro-device and its reliability assessed by means of uncertainty analysis. The procedure assumes that, for each checked design configuration, the assessment of uncertainty propagation is performed with the meta-modeling technique. The described procedure is illustrated with an example of the optimization carried out for a finite element model of a micro-mirror. The multi-physics approach allowed the introduction of several physical phenomena to correctly model the electrostatic actuation and the squeezing effect present between electrodes. The optimization was preceded by sensitivity analysis to establish the design and uncertain domains. The genetic algorithms fulfilled the defined optimization task effectively. The best discovered individuals are characterized by a minimized value of the multi-criteria objective function, simultaneously satisfying the constraint on material strength. The restriction of the maximum equivalent stresses was introduced with the conditionally formulated objective function with a penalty component. The yielded results were successfully verified with a global uniform search through the input design domain.
Reliability-based robust design optimization of vehicle components, Part II: Case studies
NASA Astrophysics Data System (ADS)
Zhang, Yimin
2015-06-01
The reliability-based optimization, the reliability- based sensitivity analysis and robust design method are employed to propose an effective approach for reliability-based robust design optimization of vehicle components in Part I. Applications of the method are further discussed for reliability-based robust optimization of vehicle components in this paper. Examples of axles, torsion bar, coil and composite springs are illustrated for numerical investigations. Results have shown the proposed method is an efficient method for reliability-based robust design optimization of vehicle components.
A robust rotorcraft flight control system design methodology utilizing quantitative feedback theory
NASA Technical Reports Server (NTRS)
Gorder, Peter James
1993-01-01
Rotorcraft flight control systems present design challenges which often exceed those associated with fixed-wing aircraft. First, large variations in the response characteristics of the rotorcraft result from the wide range of airspeeds of typical operation (hover to over 100 kts). Second, the assumption of vehicle rigidity often employed in the design of fixed-wing flight control systems is rarely justified in rotorcraft where rotor degrees of freedom can have a significant impact on the system performance and stability. This research was intended to develop a methodology for the design of robust rotorcraft flight control systems. Quantitative Feedback Theory (QFT) was chosen as the basis for the investigation. Quantitative Feedback Theory is a technique which accounts for variability in the dynamic response of the controlled element in the design robust control systems. It was developed to address a Multiple-Input Single-Output (MISO) design problem, and utilizes two degrees of freedom to satisfy the design criteria. Two techniques were examined for extending the QFT MISO technique to the design of a Multiple-Input-Multiple-Output (MIMO) flight control system (FCS) for a UH-60 Black Hawk Helicopter. In the first, a set of MISO systems, mathematically equivalent to the MIMO system, was determined. QFT was applied to each member of the set simultaneously. In the second, the same set of equivalent MISO systems were analyzed sequentially, with closed loop response information from each loop utilized in subsequent MISO designs. The results of each technique were compared, and the advantages of the second, termed Sequential Loop Closure, were clearly evident.
Decentralized adaptive control of robot manipulators with robust stabilization design
NASA Technical Reports Server (NTRS)
Yuan, Bau-San; Book, Wayne J.
1988-01-01
Due to geometric nonlinearities and complex dynamics, a decentralized technique for adaptive control for multilink robot arms is attractive. Lyapunov-function theory for stability analysis provides an approach to robust stabilization. Each joint of the arm is treated as a component subsystem. The adaptive controller is made locally stable with servo signals including proportional and integral gains. This results in the bound on the dynamical interactions with other subsystems. A nonlinear controller which stabilizes the system with uniform boundedness is used to improve the robustness properties of the overall system. As a result, the robot tracks the reference trajectories with convergence. This strategy makes computation simple and therefore facilitates real-time implementation.
Robust control design techniques for active flutter suppression
NASA Technical Reports Server (NTRS)
Ozbay, Hitay; Bachmann, Glen R.
1994-01-01
In this paper, an active flutter suppression problem is studied for a thin airfoil in unsteady aerodynamics. The mathematical model of this system is infinite dimensional because of Theodorsen's function which is irrational. Several second order approximations of Theodorsen's function are compared. A finite dimensional model is obtained from such an approximation. We use H infinity control techniques to find a robustly stabilizing controller for active flutter suppression.
Integration of system identification and robust controller designs for flexible structures in space
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Lew, Jiann-Shiun
1990-01-01
A novel approach is developed using experimental data from the structural testing of a physical system to identify a reduced-order model and its error for a robust controller design. There are three steps involved in the approach. First, an approximately balanced model is identified using the eigensystem realization algorithm, which is an identification algorithm. Second, the model error is calculated and described in frequency domain in terms of the H(infinity) norm. Third, a pole-placement technique in combination with an H(infinity) control method is applied to design a controller for the system. A set of experimental data from an existing setup, namely the Mini-Mast system, is used to illustrate and verify the approach development in this paper.
Optimal and Robust Design Method for Two-Chip Out-of-Plane Microaccelerometers
Lee, Sangmin; Ko, Hyoungho; Choi, Byoungdoo; Cho, Dong-il Dan
2010-01-01
In this paper, an optimal and robust design method to implement a two-chip out-of-plane microaccelerometer system is presented. The two-chip microsystem consists of a MEMS chip for sensing the external acceleration and a CMOS chip for signal processing. An optimized design method to determine the device thickness, the sacrificial gap, and the vertical gap length of the M EMS sensing element is applied to minimize the fundamental noise level and also to achieve the robustness to the fabrication variations. In order to cancel out the offset and gain variations due to parasitic capacitances and process variations, a digitally trimmable architecture consisting of an 11 bit capacitor array is adopted in the analog front-end of the CMOS capacitive readout circuit. The out-of-plane microaccelerometer has the scale factor of 372 mV/g∼389 mV/g, the output nonlinearity of 0.43% FSO∼0.60% FSO, the input range of ±2 g and a bias instability of 122 μg∼229 μg. The signal-to-noise ratio and the noise equivalent resolution are measured to be 74.00 dB∼75.23 dB and 180 μg/rtHz∼190 μg/rtHz, respectively. The in-plane cross-axis sensitivities are measured to be 1.1%∼1.9% and 0.3%∼0.7% of the out-of-plane sensitivity, respectively. The results show that the optimal and robust design method for the MEMS sensing element and the highly trimmable capacity of the CMOS capacitive readout circuit are suitable to enhance the die-to-die uniformity of the packaged microsystem, without compromising the performance characteristics. PMID:22163484
NASA Technical Reports Server (NTRS)
Collins, Emmanuel G., Jr.; Richter, Stephen
1990-01-01
One well known deficiency of LQG compensators is that they do not guarantee any measure of robustness. This deficiency is especially highlighted when considering control design for complex systems such as flexible structures. There has thus been a need to generalize LQG theory to incorporate robustness constraints. Here we describe the maximum entropy approach to robust control design for flexible structures, a generalization of LQG theory, pioneered by Hyland, which has proved useful in practice. The design equations consist of a set of coupled Riccati and Lyapunov equations. A homotopy algorithm that is used to solve these design equations is presented.
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.
NASA Astrophysics Data System (ADS)
Shin, Sangmun; Cho, Byung Rae
2008-11-01
Many practitioners and researchers have implemented robust design and tolerance design as quality improvement and process optimization tools for more than two decades. Robust design is an enhanced process/product design methodology for determining the best settings of control factors while minimizing process bias and variability. Tolerance design is aimed at determining the best tolerance limits for minimizing the total cost incurred by both the customer and manufacturer by balancing quality loss due to variations in product performance and the cost of controlling these variations. Although robust design and tolerance design have received much attention from researchers and practitioners, there is ample room for improvement. First, most researchers consider robust design and tolerance design as separate research fields. Second, most research work is based on a single quality characteristic. The primary goal of this paper is to integrate a sequential robust design-tolerance design optimization procedure within a bi-objective paradigm, which, the authors believe, is the first attempt in the robust design and tolerance design literature. Models are proposed and numerical examples along with sensitivity analysis are performed for verification purposes.
Design and Validation of Optimized Feedforward with Robust Feedback Control of a Nuclear Reactor
Shaffer, Roman; He Weidong; Edwards, Robert M.
2004-08-15
Design applications for robust feedback and optimized feedforward control, with confirming results from experiments conducted on the Pennsylvania State University TRIGA reactor, are presented. The combination of feedforward and feedback control techniques complement each other in that robust control offers guaranteed closed-loop stability in the presence of uncertainties, and optimized feedforward offers an approach to achieving performance that is sometimes limited by overly conservative robust feedback control. The design approach taken in this work combines these techniques by first designing robust feedback control. Alternative methods for specifying a low-order linear model and uncertainty specifications, while seeking as much performance as possible, are discussed and evaluated. To achieve desired performance characteristics, the optimized feedforward control is then computed by using the nominal nonlinear plant model that incorporates the robust feedback control.
NASA Technical Reports Server (NTRS)
Newsom, J. R.; Mukhopadhyay, V.
1983-01-01
A method for designing robust feedback controllers for multiloop systems is presented. Robustness is characterized in terms of the minimum singular value of the system return difference matrix at the plant input. Analytical gradients of the singular values with respect to design variables in the controller are derived. A cumulative measure of the singular values and their gradients with respect to the design variables is used with a numerical optimization technique to increase the system's robustness. Both unconstrained and constrained optimization techniques are evaluated. Numerical results are presented for a two output drone flight control system.
Robustness of fuzzy logic power system stabilizers applied to multimachine power system
Hiyama, Takashi . Dept. of Electrical Engineering and Computer Science)
1994-09-01
This paper investigates the robustness of fuzzy logic stabilizers using the information of speed and acceleration states of a study unit. The input signals are the real power output and/or the speed of the study unit. Non-linear simulations show the robustness of the fuzzy logic power system stabilizers. Experiments are also performed by using a micro-machine system. The results show the feasibility of proposed fuzzy logic stabilizer.
Robustness of controllers designed using Galerkin type approximations
NASA Technical Reports Server (NTRS)
Morris, K. A.
1990-01-01
One of the difficulties in designing controllers for infinite-dimensional systems arises from attempting to calculate a state for the system. It is shown that Galerkin type approximations can be used to design controllers which will perform as designed when implemented on the original infinite-dimensional system. No assumptions, other than those typically employed in numerical analysis, are made on the approximating scheme.
A Robust Design Methodology for Optimal Microscale Secondary Flow Control in Compact Inlet Diffusers
NASA Technical Reports Server (NTRS)
Anderson, Bernhard H.; Keller, Dennis J.
2001-01-01
It is the purpose of this study to develop an economical Robust design methodology for microscale secondary flow control in compact inlet diffusers. To illustrate the potential of economical Robust Design methodology, two different mission strategies were considered for the subject inlet, namely Maximum Performance and Maximum HCF Life Expectancy. The Maximum Performance mission maximized total pressure recovery while the Maximum HCF Life Expectancy mission minimized the mean of the first five Fourier harmonic amplitudes, i.e., 'collectively' reduced all the harmonic 1/2 amplitudes of engine face distortion. Each of the mission strategies was subject to a low engine face distortion constraint, i.e., DC60<0.10, which is a level acceptable for commercial engines. For each of these missions strategies, an 'Optimal Robust' (open loop control) and an 'Optimal Adaptive' (closed loop control) installation was designed over a twenty degree angle-of-incidence range. The Optimal Robust installation used economical Robust Design methodology to arrive at a single design which operated over the entire angle-of-incident range (open loop control). The Optimal Adaptive installation optimized all the design parameters at each angle-of-incidence. Thus, the Optimal Adaptive installation would require a closed loop control system to sense a proper signal for each effector and modify that effector device, whether mechanical or fluidic, for optimal inlet performance. In general, the performance differences between the Optimal Adaptive and Optimal Robust installation designs were found to be marginal. This suggests, however, that Optimal Robust open loop installation designs can be very competitive with Optimal Adaptive close loop designs. Secondary flow control in inlets is inherently robust, provided it is optimally designed. Therefore, the new methodology presented in this paper, combined array 'Lower Order' approach to Robust DOE, offers the aerodynamicist a very viable and
Applying Knowledge of Quantitative Design and Analysis
ERIC Educational Resources Information Center
Baskas, Richard S.
2011-01-01
This study compared and contrasted two quantitative scholarly articles in relation to their research designs. Their designs were analyzed by the comparison of research references and research specific vocabulary to describe how various research methods were used. When researching and analyzing quantitative scholarly articles, it is imperative to…
Optimization methods applied to hybrid vehicle design
NASA Technical Reports Server (NTRS)
Donoghue, J. F.; Burghart, J. H.
1983-01-01
The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.
Robust Kalman filter design for active flutter suppression systems
NASA Technical Reports Server (NTRS)
Garrard, W. L.; Mahesh, J. K.; Stone, C. R.; Dunn, H. J.
1982-01-01
Additional insight is provided into the use of the Doyle-Stein (1979, 1981) technique in aeroelastic control problems by examining the application of the method to a flutter control problem. The system to be controlled consists of a full-size wind tunnel model of a wing, plus an aileron, an actuator, and an accelerometer used to sense the motion of the wing. A full-state feedback controller was designed using linear optimal control theory, and a Kalman filter was used in the feedback loop for state estimation. The filter design procedure is explained along with that to improve closed-loop properties of the system. The locus of the poles of the filter is examined as a scalar design parameter is varied. The Doyle-Stein design procedure is shown to substantially improve the stability properties of an active flutter controller designed using the linear quadratic Gaussian control theory.
Two Reconfigurable Flight-Control Design Methods: Robust Servomechanism and Control Allocation
NASA Technical Reports Server (NTRS)
Burken, John J.; Lu, Ping; Wu, Zheng-Lu; Bahm, Cathy
2001-01-01
Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the fight body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.
Using open robust design models to estimate temporary emigration from capture-recapture data
Kendall, W.L.; Bjorkland, R.
2001-01-01
Capture-recapture studies are crucial in many circumstances for estimating demographic parameters for wildlife and fish populations. Pollock's robust design, involving multiple sampling occasions per period of interest, provides several advantages over classical approaches. This includes the ability to estimate the probability of being present and available for detection, which in some situations is equivalent to breeding probability. We present a model for estimating availability for detection that relaxes two assumptions required in previous approaches. The first is that the sampled population is closed to additions and deletions across samples within a period of interest. The second is that each member of the population has the same probability of being available for detection in a given period. We apply our model to estimate survival and breeding probability in a study of hawksbill sea turtles (Eretmochelys imbricata), where previous approaches are not appropriate.
Yiamsawas, Doungporn; Boonpavanitchakul, Kanittha; Kangwansupamonkon, Wiyong
2011-05-15
Research highlights: {yields} Taguchi robust design can be applied to study ZnO nanocrystal growth. {yields} Spherical-like and rod-like shaped of ZnO nanocrystals can be obtained from solvothermal method. {yields} [NaOH]/[Zn{sup 2+}] ratio plays the most important factor on the aspect ratio of prepared ZnO. -- Abstract: Zinc oxide (ZnO) nanoparticles and nanorods were successfully synthesized by a solvothermal process. Taguchi robust design was applied to study the factors which result in stronger ZnO nanocrystal growth. The factors which have been studied are molar concentration ratio of sodium hydroxide and zinc acetate, amount of polymer templates and molecular weight of polymer templates. Transmission electron microscopy and X-ray diffraction technique were used to analyze the experiment results. The results show that the concentration ratio of sodium hydroxide and zinc acetate ratio has the greatest effect on ZnO nanocrystal growth.
Jumbo squid beaks: inspiration for design of robust organic composites.
Miserez, Ali; Li, Youli; Waite, J Herbert; Zok, Frank
2007-01-01
The hard tissues found in some invertebrate marine organisms represent intriguing paradigms for robust, lightweight materials. The present study focuses on one such tissue: that comprising the beak of the jumbo squid (Dosidicus gigas). Its main constituents are chitin fibers (15-20wt.%) and histidine- and glycine-rich proteins (40-45%). Notably absent are mineral phases, metals and halogens. Despite being fully organic, beak hardness and stiffness are at least twice those of the most competitive synthetic organic materials (notably engineering polymers) and comparable to those of Glycera and Nereis jaws. Furthermore, the combination of hardness and stiffness makes the beaks more resistant to plastic deformation when in contact with blunt abrasives than virtually all metals and polymers. The 3,4-dihydroxy-l-phenylalanine and abundant histidine content in the beak proteins as well as the pigmented hydrolysis-resistant residue are suggestive of aromatic cross-linking. A high cross-linking density between the proteins and chitin may be the single most important determinant of hardness and stiffness in the beak. Beak microstructure is characterized by a lamellar arrangement of the constituents, with a weak interface that promotes crack deflection and endows the structure with high fracture toughness. The susceptibility of this microstructure to cracking along these interfaces from contact stresses at the external surface is mitigated by the presence of a protective coating. PMID:17113369
Systems design analysis applied to launch vehicle configuration
NASA Technical Reports Server (NTRS)
Ryan, R.; Verderaime, V.
1993-01-01
As emphasis shifts from optimum-performance aerospace systems to least lift-cycle costs, systems designs must seek, adapt, and innovate cost improvement techniques in design through operations. The systems design process of concept, definition, and design was assessed for the types and flow of total quality management techniques that may be applicable in a launch vehicle systems design analysis. Techniques discussed are task ordering, quality leverage, concurrent engineering, Pareto's principle, robustness, quality function deployment, criteria, and others. These cost oriented techniques are as applicable to aerospace systems design analysis as to any large commercial system.
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.
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.
Robust Coordinated AVR-PSS Design Using H∞ Static Output Feedback Control
NASA Astrophysics Data System (ADS)
Bevrani, Hassan; Hiyama, Takashi
This paper addresses a new robust control methodology to enhance the power system stability and voltage regulation as an integrated design approach. The automatic voltage regulation (AVR) and power system stabilizer (PSS) design problems are reduced to solve a single H∞ based static output feedback control problem. To determine the optimal gains, an iterative linear matrix inequalities (LMI) algorithm is used. A four-machine infinite-bus system example is given to demonstrate the efficiency of developed approach. The proposed robust technique is shown to maintain the robust performance and minimize the effects of disturbances, properly.
Optimisation in the Design of Environmental Sensor Networks with Robustness Consideration
Budi, Setia; de Souza, Paulo; Timms, Greg; Malhotra, Vishv; Turner, Paul
2015-01-01
This work proposes the design of Environmental Sensor Networks (ESN) through balancing robustness and redundancy. An Evolutionary Algorithm (EA) is employed to find the optimal placement of sensor nodes in the Region of Interest (RoI). Data quality issues are introduced to simulate their impact on the performance of the ESN. Spatial Regression Test (SRT) is also utilised to promote robustness in data quality of the designed ESN. The proposed method provides high network representativeness (fit for purpose) with minimum sensor redundancy (cost), and ensures robustness by enabling the network to continue to achieve its objectives when some sensors fail. PMID:26633392
Robust Multivariable Optimization and Performance Simulation for ASIC Design
NASA Technical Reports Server (NTRS)
DuMonthier, Jeffrey; Suarez, George
2013-01-01
Application-specific-integrated-circuit (ASIC) design for space applications involves multiple challenges of maximizing performance, minimizing power, and ensuring reliable operation in extreme environments. This is a complex multidimensional optimization problem, which must be solved early in the development cycle of a system due to the time required for testing and qualification severely limiting opportunities to modify and iterate. Manual design techniques, which generally involve simulation at one or a small number of corners with a very limited set of simultaneously variable parameters in order to make the problem tractable, are inefficient and not guaranteed to achieve the best possible results within the performance envelope defined by the process and environmental requirements. What is required is a means to automate design parameter variation, allow the designer to specify operational constraints and performance goals, and to analyze the results in a way that facilitates identifying the tradeoffs defining the performance envelope over the full set of process and environmental corner cases. The system developed by the Mixed Signal ASIC Group (MSAG) at the Goddard Space Flight Center is implemented as a framework of software modules, templates, and function libraries. It integrates CAD tools and a mathematical computing environment, and can be customized for new circuit designs with only a modest amount of effort as most common tasks are already encapsulated. Customization is required for simulation test benches to determine performance metrics and for cost function computation.
Applying colour science in colour design
NASA Astrophysics Data System (ADS)
Luo, Ming Ronnier
2006-06-01
Although colour science has been widely used in a variety of industries over the years, it has not been fully explored in the field of product design. This paper will initially introduce the three main application fields of colour science: colour specification, colour-difference evaluation and colour appearance modelling. By integrating these advanced colour technologies together with modern colour imaging devices such as display, camera, scanner and printer, some computer systems have been recently developed to assist designers for designing colour palettes through colour selection by means of a number of widely used colour order systems, for creating harmonised colour schemes via a categorical colour system, for generating emotion colours using various colour emotional scales and for facilitating colour naming via a colour-name library. All systems are also capable of providing accurate colour representation on displays and output to different imaging devices such as printers.
Designing Robust and Reliable Timestamps for Remote Patient Monitoring.
Clarke, Malcolm; Schluter, Paul; Reinhold, Barry; Reinhold, Brian
2015-09-01
Having timestamps that are robust and reliable is essential for remote patient monitoring in order for patient data to have context and to be correlated with other data. However, unlike hospital systems for which guidelines on timestamps are currently provided by HL7 and IHE, remote patient monitoring platforms are: operated in environments where it can be difficult to synchronize with reliable time sources; include devices with simple or no clock; and may store data spanning significant periods before able to upload. Existing guidelines prove inadequate. This paper analyzes the requirements and the operating scenarios of remote patient monitoring platforms and defines a framework to convey information on the conditions under which observations were made by the device and forwarded by the gateway in order for data to be managed appropriately and to include both reference to local time and an underlying continuous reference timeline. We define the timestamp formats of HL7 to denote the different conditions of operation and describe extensions to the existing definition of the HL7 timestamp to differentiate between time local to GMT (+0000) and universal coordinated time or network time protocol time where no geographic time zone is implied (-0000). We further describe how timestamps from devices having only simple or no clocks might be managed reliably by a gateway to provide timestamps that are referenced to local time and an underlying continuous reference timeline. We extend the HL7 message to include information to permit a subsequent receiver of the data to understand the quality of the timestamp and how it has been translated. We present evaluation from deploying a platform for 12 months. PMID:25095271
NASA Astrophysics Data System (ADS)
Gharibnezhad, Fahit; Mujica, Luis E.; Rodellar, José
2015-01-01
Using Principal Component Analysis (PCA) for Structural Health Monitoring (SHM) has received considerable attention over the past few years. PCA has been used not only as a direct method to identify, classify and localize damages but also as a significant primary step for other methods. Despite several positive specifications that PCA conveys, it is very sensitive to outliers. Outliers are anomalous observations that can affect the variance and the covariance as vital parts of PCA method. Therefore, the results based on PCA in the presence of outliers are not fully satisfactory. As a main contribution, this work suggests the use of robust variant of PCA not sensitive to outliers, as an effective way to deal with this problem in SHM field. In addition, the robust PCA is compared with the classical PCA in the sense of detecting probable damages. The comparison between the results shows that robust PCA can distinguish the damages much better than using classical one, and even in many cases allows the detection where classic PCA is not able to discern between damaged and non-damaged structures. Moreover, different types of robust PCA are compared with each other as well as with classical counterpart in the term of damage detection. All the results are obtained through experiments with an aircraft turbine blade using piezoelectric transducers as sensors and actuators and adding simulated damages.
Applied virtual reality in aerospace design
NASA Technical Reports Server (NTRS)
Hale, Joseph P.
1995-01-01
A virtual reality (VR) applications program has been under development at the Marshall Space Flight Center (MSFC) since 1989. The objectives of the MSFC VR Applications Program are to develop, assess, validate, and utilize VR in hardware development, operations development and support, mission operations training and science training. Before VR can be used with confidence in a particular application, VR must be validated for that class of applications. For that reason, specific validation studies for selected classes of applications have been proposed and are currently underway. These include macro-ergonomic 'control room class' design analysis, Spacelab stowage reconfiguration training, a full-body microgravity functional reach simulator, a gross anatomy teaching simulator, and micro-ergonomic design analysis. This paper describes the MSFC VR Applications Program and the validation studies.
NASA Technical Reports Server (NTRS)
Olds, John Robert; Walberg, Gerald D.
1993-01-01
Multidisciplinary design optimization (MDO) is an emerging discipline within aerospace engineering. Its goal is to bring structure and efficiency to the complex design process associated with advanced aerospace launch vehicles. Aerospace vehicles generally require input from a variety of traditional aerospace disciplines - aerodynamics, structures, performance, etc. As such, traditional optimization methods cannot always be applied. Several multidisciplinary techniques and methods were proposed as potentially applicable to this class of design problem. Among the candidate options are calculus-based (or gradient-based) optimization schemes and parametric schemes based on design of experiments theory. A brief overview of several applicable multidisciplinary design optimization methods is included. Methods from the calculus-based class and the parametric class are reviewed, but the research application reported focuses on methods from the parametric class. A vehicle of current interest was chosen as a test application for this research. The rocket-based combined-cycle (RBCC) single-stage-to-orbit (SSTO) launch vehicle combines elements of rocket and airbreathing propulsion in an attempt to produce an attractive option for launching medium sized payloads into low earth orbit. The RBCC SSTO presents a particularly difficult problem for traditional one-variable-at-a-time optimization methods because of the lack of an adequate experience base and the highly coupled nature of the design variables. MDO, however, with it's structured approach to design, is well suited to this problem. The result of the application of Taguchi methods, central composite designs, and response surface methods to the design optimization of the RBCC SSTO are presented. Attention is given to the aspect of Taguchi methods that attempts to locate a 'robust' design - that is, a design that is least sensitive to uncontrollable influences on the design. Near-optimum minimum dry weight solutions are
A robust inverse inviscid method for airfoil design
NASA Astrophysics Data System (ADS)
Chaviaropoulos, P.; Dedoussis, V.; Papailiou, K. D.
An irrotational inviscid compressible inverse design method for two-dimensional airfoil profiles is described. The method is based on the potential streamfunction formulation, where the physical space on which the boundaries of the airfoil are sought, is mapped onto the (phi, psi) space via a body-fitted coordinate transformation. A novel procedure based on differential geometry arguments is employed to derive the governing equations for the inverse problem, by requiring the curvature of the flat 2-D Euclidean space to be zero. An auxiliary coordinate transformation permits the definition of C-type computational grids on the (phi, psi) plane resulting to a more accurate description of the leading edge region. Geometry is determined by integrating Frenet equations along the grid lines. To validate the method inverse calculation results are compared to direct, `reproduction', calculation results. The design procedure of a new airfoil shape is also presented.
Robust Control for Microgravity Vibration Isolation using Fixed Order, Mixed H2/Mu Design
NASA Technical Reports Server (NTRS)
Whorton, Mark
2003-01-01
Many space-science experiments need an active isolation system to provide a sufficiently quiescent microgravity environment. Modern control methods provide the potential for both high-performance and robust stability in the presence of parametric uncertainties that are characteristic of microgravity vibration isolation systems. While H2 and H(infinity) methods are well established, neither provides the levels of attenuation performance and robust stability in a compensator with low order. Mixed H2/H(infinity), controllers provide a means for maximizing robust stability for a given level of mean-square nominal performance while directly optimizing for controller order constraints. This paper demonstrates the benefit of mixed norm design from the perspective of robustness to parametric uncertainties and controller order for microgravity vibration isolation. A nominal performance metric analogous to the mu measure, for robust stability assessment is also introduced in order to define an acceptable trade space from which different control methodologies can be compared.
Robust model matching design methodology for a stochastic synthetic gene network.
Chen, Bor-Sen; Chang, Chia-Hung; Wang, Yu-Chao; Wu, Chih-Hung; Lee, Hsiao-Ching
2011-03-01
Synthetic biology has shown its potential and promising applications in the last decade. However, many synthetic gene networks cannot work properly and maintain their desired behaviors due to intrinsic parameter variations and extrinsic disturbances. In this study, the intrinsic parameter uncertainties and external disturbances are modeled in a non-linear stochastic gene network to mimic the real environment in the host cell. Then a non-linear stochastic robust matching design methodology is introduced to withstand the intrinsic parameter fluctuations and to attenuate the extrinsic disturbances in order to achieve a desired reference matching purpose. To avoid solving the Hamilton-Jacobi inequality (HJI) in the non-linear stochastic robust matching design, global linearization technique is used to simplify the design procedure by solving a set of linear matrix inequalities (LMIs). As a result, the proposed matching design methodology of the robust synthetic gene network can be efficiently designed with the help of LMI toolbox in Matlab. Finally, two in silico design examples of the robust synthetic gene network are given to illustrate the design procedure and to confirm the robust model matching performance to achieve the desired behavior in spite of stochastic parameter fluctuations and environmental disturbances in the host cell. PMID:21215760
Reliability Assessment of a Robust Design Under Uncertainty for a 3-D Flexible Wing
NASA Technical Reports Server (NTRS)
Gumbert, Clyde R.; Hou, Gene J. -W.; Newman, Perry A.
2003-01-01
The paper presents reliability assessment results for the robust designs under uncertainty of a 3-D flexible wing previously reported by the authors. Reliability assessments (additional optimization problems) of the active constraints at the various probabilistic robust design points are obtained and compared with the constraint values or target constraint probabilities specified in the robust design. In addition, reliability-based sensitivity derivatives with respect to design variable mean values are also obtained and shown to agree with finite difference values. These derivatives allow one to perform reliability based design without having to obtain second-order sensitivity derivatives. However, an inner-loop optimization problem must be solved for each active constraint to find the most probable point on that constraint failure surface.
A Statistical Approach Reveals Designs for the Most Robust Stochastic Gene Oscillators
2016-01-01
The engineering of transcriptional networks presents many challenges due to the inherent uncertainty in the system structure, changing cellular context, and stochasticity in the governing dynamics. One approach to address these problems is to design and build systems that can function across a range of conditions; that is they are robust to uncertainty in their constituent components. Here we examine the parametric robustness landscape of transcriptional oscillators, which underlie many important processes such as circadian rhythms and the cell cycle, plus also serve as a model for the engineering of complex and emergent phenomena. The central questions that we address are: Can we build genetic oscillators that are more robust than those already constructed? Can we make genetic oscillators arbitrarily robust? These questions are technically challenging due to the large model and parameter spaces that must be efficiently explored. Here we use a measure of robustness that coincides with the Bayesian model evidence, combined with an efficient Monte Carlo method to traverse model space and concentrate on regions of high robustness, which enables the accurate evaluation of the relative robustness of gene network models governed by stochastic dynamics. We report the most robust two and three gene oscillator systems, plus examine how the number of interactions, the presence of autoregulation, and degradation of mRNA and protein affects the frequency, amplitude, and robustness of transcriptional oscillators. We also find that there is a limit to parametric robustness, beyond which there is nothing to be gained by adding additional feedback. Importantly, we provide predictions on new oscillator systems that can be constructed to verify the theory and advance design and modeling approaches to systems and synthetic biology. PMID:26835539
A Statistical Approach Reveals Designs for the Most Robust Stochastic Gene Oscillators.
Woods, Mae L; Leon, Miriam; Perez-Carrasco, Ruben; Barnes, Chris P
2016-06-17
The engineering of transcriptional networks presents many challenges due to the inherent uncertainty in the system structure, changing cellular context, and stochasticity in the governing dynamics. One approach to address these problems is to design and build systems that can function across a range of conditions; that is they are robust to uncertainty in their constituent components. Here we examine the parametric robustness landscape of transcriptional oscillators, which underlie many important processes such as circadian rhythms and the cell cycle, plus also serve as a model for the engineering of complex and emergent phenomena. The central questions that we address are: Can we build genetic oscillators that are more robust than those already constructed? Can we make genetic oscillators arbitrarily robust? These questions are technically challenging due to the large model and parameter spaces that must be efficiently explored. Here we use a measure of robustness that coincides with the Bayesian model evidence, combined with an efficient Monte Carlo method to traverse model space and concentrate on regions of high robustness, which enables the accurate evaluation of the relative robustness of gene network models governed by stochastic dynamics. We report the most robust two and three gene oscillator systems, plus examine how the number of interactions, the presence of autoregulation, and degradation of mRNA and protein affects the frequency, amplitude, and robustness of transcriptional oscillators. We also find that there is a limit to parametric robustness, beyond which there is nothing to be gained by adding additional feedback. Importantly, we provide predictions on new oscillator systems that can be constructed to verify the theory and advance design and modeling approaches to systems and synthetic biology. PMID:26835539
Applying the miniaturization technologies for biosensor design.
Derkus, Burak
2016-05-15
Microengineering technologies give us some opportunities in developing high-tech sensing systems that operate with low volumes of samples, integrates one or more laboratory functions on a single substrate, and enables automation. These millimetric sized devices can be produced for only a few dollars, which makes them promising candidates for mass-production. Besides electron beam lithography, stencil lithography, nano-imprint lithography or dip pen lithography, basic photolithography is the technique which is extensively used for the design of microengineered sensing systems. This technique has some advantages such as easy-to-manufacture, do not require expensive instrumentation, and allow creation of lower micron-sized patterns. In this review, it has been focused on three different type of microengineered sensing devices which are developed using micro/nano-patterning techniques, microfluidic technology, and microelectromechanics system based technology. PMID:26800206
A robust Feasible Directions algorithm for design synthesis
NASA Technical Reports Server (NTRS)
Vanderplaats, G. N.
1983-01-01
A nonlinear optimization algorithm is developed which combines the best features of the Method of Feasible Directions and the Generalized Reduced Gradient Method. This algorithm utilizes the direction-finding sub-problem from the Method of Feasible Directions to find a search direction which is equivalent to that of the Generalized Reduced Gradient Method, but does not require the addition of a large number of slack variables associated with inequality constraints. This method provides a core-efficient algorithm for the solution of optimization problems with a large number of inequality constraints. Further optimization efficiency is derived by introducing the concept of infrequent gradient calculations. In addition, it is found that the sensitivity of the optimum design to changes in the problem parameters can be obtained using this method without the need for second derivatives or Lagrange multipliers. A numerical example is given in order to demonstrate the efficiency of the algorithm and the sensitivity analysis.
Robust H infinity control design for the space station with structured parameter uncertainty
NASA Technical Reports Server (NTRS)
Byun, Kuk-Whan; Wie, Bong; Geller, David; Sunkel, John
1992-01-01
A robust H-infinity control design methodology and its application to a Space Station attitude and momentum control problem are presented. This new approach incorporates nonlinear multi-parameter variations in the state-space formulation of H-infinity control theory. An application of this robust H-infinity control synthesis technique to the Space Station control problem yields a remarkable result in stability robustness with respect to the moments-of-inertia variation of about 73% in one of the structured uncertainty directions. The performance and stability of this new robust H-infinity controller for the Space Station are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.
Robust H(infinity) control design for the Space Station with structured parameter uncertainty
NASA Technical Reports Server (NTRS)
Byun, Kuk-Whan; Wie, Bong; Geller, David; Sunkel, John
1990-01-01
A robust H(infinity) control design methodology and its application to a Space Station attitude and momentum control problem are presented. This new approach incorporates nonlinear multiparameter variations in the state-space formulation of H(infinity) control theory. An application of this robust control synthesis technique tothe Space Station control problem yields a remarkable result in stability robustness with respect to the moments-of-inertia variation of about 73 percent in one of the structured uncertainty directions. The performance and stability of this new robust H(infinity) controller for the Space Station are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.
Robust Design of Reliability Test Plans Using Degradation Measures.
Lane, Jonathan Wesley; Lane, Jonathan Wesley; Crowder, Stephen V.; Crowder, Stephen V.
2014-10-01
With short production development times, there is an increased need to demonstrate product reliability relatively quickly with minimal testing. In such cases there may be few if any observed failures. Thus, it may be difficult to assess reliability using the traditional reliability test plans that measure only time (or cycles) to failure. For many components, degradation measures will contain important information about performance and reliability. These measures can be used to design a minimal test plan, in terms of number of units placed on test and duration of the test, necessary to demonstrate a reliability goal. Generally, the assumption is made that the error associated with a degradation measure follows a known distribution, usually normal, although in practice cases may arise where that assumption is not valid. In this paper, we examine such degradation measures, both simulated and real, and present non-parametric methods to demonstrate reliability and to develop reliability test plans for the future production of components with this form of degradation.
Sahni, Narinder S.; Piepel, Gregory F.; Naes, Tormod
2009-04-01
The quality of an industrial product depends on the raw material proportions and the process variable levels, both of which need to be taken into account in designing a product. This article presents a case study from the food industry in which both kinds of variables were studied by combining a constrained mixture experiment design and a central composite process variable design. Based on the natural structure of the situation, a split-plot experiment was designed and models involving the raw material proportions and process variable levels (separately and combined) were fitted. Combined models were used to study: (i) the robustness of the process to variations in raw material proportions, and (ii) the robustness of the raw material recipes with respect to fluctuations in the process variable levels. Further, the expected variability in the robust settings was studied using the bootstrap.
Stochastic Satbility and Performance Robustness of Linear Multivariable Systems
NASA Technical Reports Server (NTRS)
Ryan, Laurie E.; Stengel, Robert F.
1990-01-01
Stochastic robustness, a simple technique used to estimate the robustness of linear, time invariant systems, is applied to a single-link robot arm control system. Concepts behind stochastic stability robustness are extended to systems with estimators and to stochastic performance robustness. Stochastic performance robustness measures based on classical design specifications are introduced, and the relationship between stochastic robustness measures and control system design parameters are discussed. The application of stochastic performance robustness, and the relationship between performance objectives and design parameters are demonstrated by means of example. The results prove stochastic robustness to be a good overall robustness analysis method that can relate robustness characteristics to control system design parameters.
NASA Astrophysics Data System (ADS)
Beuchat, X.; Schaefli, B.; Soutter, M.; Mermoud, A.
2012-02-01
Rainfall is poorly modeled by general circulation models (GCMs) and requires appropriate downscaling for local-scale hydrological impact studies. Such downscaling methods should be robust and accurate (to handle, e.g., extreme events and uncertainties), but the noncontinuous and highly nonlinear nature of rainfall makes this task particularly challenging. This paper brings together and extends state-of-the-art methods into an integrated and robust probabilistic methodology to downscale local daily rainfall series from an ensemble of climate simulations. The downscaling is based on generalized linear models (GLMs) that relate monthly GCM-scale atmospheric variables to local-scale daily rainfall series. A cross-validation step ensures that the fitted models are correctly conditioned by the climate variables, and a statistical procedure is proposed to test whether the statistical relationships identified for the reference period also hold in a future perturbed climate (i.e., to test the stationarity assumption). Additionally, we propose a strategy to downweigh poorly performing GCM-GLM couples. The methodology is assessed at 27 locations covering Switzerland and is shown to perform well in reproducing historical rainfall statistics including extremes and interannual variability. Furthermore, the projections are consistent with the simulations of physically based dynamical models. Using an original visualization method based on heat maps, we show that although the downscaling models were fitted at each of the 27 sites independently, their projections follow a spatially coherent pattern and that regions exhibiting different climate change impacts can be identified.
NASA Astrophysics Data System (ADS)
Ju, Yaping; Zhang, Chuhua
2016-03-01
Blade fouling has been proved to be a great threat to compressor performance in operating stage. The current researches on fouling-induced performance degradations of centrifugal compressors are based mainly on simplified roughness models without taking into account the realistic factors such as spatial non-uniformity and randomness of the fouling-induced surface roughness. Moreover, little attention has been paid to the robust design optimization of centrifugal compressor impellers with considerations of blade fouling. In this paper, a multi-objective robust design optimization method is developed for centrifugal impellers under surface roughness uncertainties due to blade fouling. A three-dimensional surface roughness map is proposed to describe the nonuniformity and randomness of realistic fouling accumulations on blades. To lower computational cost in robust design optimization, the support vector regression (SVR) metamodel is combined with the Monte Carlo simulation (MCS) method to conduct the uncertainty analysis of fouled impeller performance. The analyzed results show that the critical fouled region associated with impeller performance degradations lies at the leading edge of blade tip. The SVR metamodel has been proved to be an efficient and accurate means in the detection of impeller performance variations caused by roughness uncertainties. After design optimization, the robust optimal design is found to be more efficient and less sensitive to fouling uncertainties while maintaining good impeller performance in the clean condition. This research proposes a systematic design optimization method for centrifugal compressors with considerations of blade fouling, providing a practical guidance to the design of advanced centrifugal compressors.
Control design for robust stability in linear regulators: Application to aerospace flight control
NASA Technical Reports Server (NTRS)
Yedavalli, R. K.
1986-01-01
Time domain stability robustness analysis and design for linear multivariable uncertain systems with bounded uncertainties is the central theme of the research. After reviewing the recently developed upper bounds on the linear elemental (structured), time varying perturbation of an asymptotically stable linear time invariant regulator, it is shown that it is possible to further improve these bounds by employing state transformations. Then introducing a quantitative measure called the stability robustness index, a state feedback conrol design algorithm is presented for a general linear regulator problem and then specialized to the case of modal systems as well as matched systems. The extension of the algorithm to stochastic systems with Kalman filter as the state estimator is presented. Finally an algorithm for robust dynamic compensator design is presented using Parameter Optimization (PO) procedure. Applications in a aircraft control and flexible structure control are presented along with a comparison with other existing methods.
Synthesis of structural/control systems robust with respect to design variable tolerances
NASA Technical Reports Server (NTRS)
Thomas, H. L.; Schmit, L. A.
1991-01-01
A methodology is presented for the synthesis of control augmented structures which can be modeled as an assemblage of beam, truss, and nonstructural mass elements augmented by a robust noncollocated direct output feedback control system. The control system is robust in the sense that it can tolerate manufacturing and realization errors. The robust control system is synthesized using a constraint buffering technique in conjunction with the approximation concepts approach to system synthesis. All of the design constraints on the system, including the dynamic stability, are buffered by a nonlinear quantity that is a function of acceptable tolerances on the design variables and the sensitivity of the constraints to changes in these design variables. Numerical results which illustrate the effectiveness of the method presented are given.
Design Method of ILQ Robust Current Control System for Synchronous Reluctance Electrical Motors
NASA Astrophysics Data System (ADS)
Amano, Yoko; Takami, Hiroshi; Fujii, Takao
In this paper, a robust current control system for a synchronous reluctance electrical motor by an ILQ (Inverse Linear Quadratic) design method is proposed newly. First, for performing simultaneously decouple and large region linearization of an d-q axes system in the synchronous reluctance electrical motor using nonlinear state feedback, it is derived that a linear current-voltage state equation linearized model by the d-q axes decouple of the synchronous reluctance electrical motor. Next, according to the ILQ design method, an optimum solution and an optimal condition that achieve the robust current control system for the synchronous reluctance electrical motor are analytically derived, then the robust current control system can be designed. Finally, in practical experiments, we compare the proposed method with the PI (Proportional Integral) control method, the creativity and the usefulness of the proposed method are confirmed by experimental results.
LMI-Based 2-Degrees-of-Freedom Controller Design for Robust Vibration Suppression Positioning
NASA Astrophysics Data System (ADS)
Kato, Takanori; Maeda, Yoshihiro; Iwasaki, Makoto; Hirai, Hiromu
This paper presents a novel 2-degrees-of-freedom (2-DOF) controller design for the robust vibration suppression positioning of mechatronic systems against the frequency perturbation in mechanical vibration modes. The authors have already proposed an linear matrix inequality (LMI)-based feedforward (FF) compensator design method to provide the robust properties in positioning against the perturbation, while the feedback (FB) controller has been independently designed to ensure the robust stability on the basis of the 2-DOF controller design concept. However, a problem still remains in the conventional design that the FB characteristic causes the deterioration of the FF control performance because the undesired response in the FB system due to the perturbation affects the ideal response by the FF compensation. The proposed controller design in this paper, therefore, includes the FB control system with the perturbation in the FF design model to solve the problem in the conventional design. In addition, the FB controller is optimally designed to improve the positioning performance as a cooperated design between FB and FF controllers. The effectiveness of the proposed approach has been verified by numerical simulations and experiments using a prototype.
NASA Technical Reports Server (NTRS)
Troudet, T.; Garg, S.; Merrill, W.
1992-01-01
The design of a dynamic neurocontroller with good robustness properties is presented for a multivariable aircraft control problem. The internal dynamics of the neurocontroller are synthesized by a state estimator feedback loop. The neurocontrol is generated by a multilayer feedforward neural network which is trained through backpropagation to minimize an objective function that is a weighted sum of tracking errors, and control input commands and rates. The neurocontroller exhibits good robustness through stability margins in phase and vehicle output gains. By maintaining performance and stability in the presence of sensor failures in the error loops, the structure of the neurocontroller is also consistent with the classical approach of flight control design.
Multi-point objective-oriented sequential sampling strategy for constrained robust design
NASA Astrophysics Data System (ADS)
Zhu, Ping; Zhang, Siliang; Chen, Wei
2015-03-01
Metamodelling techniques are widely used to approximate system responses of expensive simulation models. In association with the use of metamodels, objective-oriented sequential sampling methods have been demonstrated to be effective in balancing the need for searching an optimal solution versus reducing the metamodelling uncertainty. However, existing infilling criteria are developed for deterministic problems and restricted to one sampling point in one iteration. To exploit the use of multiple samples and identify the true robust solution in fewer iterations, a multi-point objective-oriented sequential sampling strategy is proposed for constrained robust design problems. In this article, earlier development of objective-oriented sequential sampling strategy for unconstrained robust design is first extended to constrained problems. Next, a double-loop multi-point sequential sampling strategy is developed. The proposed methods are validated using two mathematical examples followed by a highly nonlinear automotive crashworthiness design example. The results show that the proposed method can mitigate the effect of both metamodelling uncertainty and design uncertainty, and identify the robust design solution more efficiently than the single-point sequential sampling approach.
Kendall, W.L.; Hines, J.E.
1999-01-01
Several papers have demonstrated the advantages of collecting capture-recapture data using subsamples (i.e. Pollock's robust design). Compared with a standard design (i.e. one sample per period), this approach (1) permits the estimation of more demographic parameters and (2) in many cases produces more efficient estimators. Program SURVIV is a powerful tool for computing parameter estimates under the robust design. However, multinomial models developed for the robust design require cells for each possible capture history that occurs across the subsamples within a period. This makes the process of entering cell probabilities in SURVIV very tedious and subject to errors. Program RDSURVIV combines SURVIV with a front end that converts capture histories taken under the robust design to the proper input format for estimating parameters under a general model, and builds that model. This model permits Markovian temporary emigration, trap response in capture probabilities and time variation in all parameters. Program RDSURVIV also automatically computes estimates under a series of submodels, but also permits the user to specify other submodels.
Kendall, W.L.; Hines, J.E.
1999-01-01
Several papers have demonstrated the advantages of collecting capture-recapture data using subsamples (i.e., Pollock?s robust design). Compared to a standard design (i.e., one sample per period), this approach (1) permits the estimation of more demographic parameters and (2) in many cases produces more efficient estimators. Program SURVIV is a powerful tool for computing parameter estimates under the robust design. However, multinomial models developed for the robust design require cells for each possible capture history that occurs across the subsamples within a period. This makes the process of entering cell probabilities in SURVIV very tedious and subject to errors. Program RDSURVIV combines SURVIV with a front end that converts capture histories taken under the robust design to the proper input format for estimating parameters under a general model, and builds that model. This model permits Markovian temporary emigration, trap response in capture probabilities, and time variation in all parameters. Program RDSURVIV also automatically computes estimates under a series of submodels, but also permits the user to specify other submodels.
Steps toward an Empirical Evaluation of Robust Regression Applied to Reaction-Time Data.
ERIC Educational Resources Information Center
Sternberg, Saul; And Others
Because analyses of reaction-time data are sensitive to aberrant observations and violations of statistical assumptions, a new approach is suggested. In this empirical approach, one applies the same criteria to the problem of selecting a statistical method as one uses to select among alternative experimental procedures. Six criteria are presented…
Universal Design for Online Courses: Applying Principles to Pedagogy
ERIC Educational Resources Information Center
Rao, Kavita; Edelen-Smith, Patricia; Wailehua, Cat-Uyen
2015-01-01
Universal design (UD) educational frameworks provide useful guidelines for designing accessible learning environments with the intention of supporting students with and without disabilities. This article describes how one university instructor defined and applied the principles of Universal Instructional Design (UID) to pedagogy, while designing…
Applying Learning Design to Work-Based Learning
ERIC Educational Resources Information Center
Miao, Yongwu; Hoppe, Heinz Ulrich
2011-01-01
Learning design is currently slanted to reflect a course-based approach to learning. This article explores whether the concept of learning design could be applied to support the informal aspects of work-based learning (WBL). It also discusses the characteristics of WBL and presents a WBL-specific learning design that highlights the key features…
Quality by Design Approaches to Formulation Robustness-An Antibody Case Study.
Wurth, Christine; Demeule, Barthelemy; Mahler, Hanns-Christian; Adler, Michael
2016-05-01
The International Conference on Harmonization Q8 (R2) includes a requirement that "Critical formulation attributes and process parameters are generally identified through an assessment of the extent to which their variation can impact the quality of the drug product," that is, the need to assess the robustness of a formulation. In this article, a quality-by-design-based definition of a "robust formulation" for a biopharmaceutical product is proposed and illustrated with a case study. A multivariate formulation robustness study was performed for a selected formulation of a monoclonal antibody to demonstrate acceptable quality at the target composition as well as at the edges of the allowable composition ranges and fulfillment of the end-of-shelf-life stability requirements of 36 months at the intended storage temperature (2°C-8°C). Extrapolation of 24 months' formulation robustness data to end of shelf life showed that the MAb formulation was robust within the claimed formulation composition ranges. Based on this case study, we propose that a formulation can be claimed as "robust" if all drug substance and drug product critical quality attributes remain within their respective end-of-shelf-life critical quality attribute-acceptance criteria throughout the entire claimed formulation composition range. PMID:27001536
NASA Technical Reports Server (NTRS)
Singh, M.
1999-01-01
Ceramic matrix composite (CMC) components are being designed, fabricated, and tested for a number of high temperature, high performance applications in aerospace and ground based systems. The critical need for and the role of reliable and robust databases for the design and manufacturing of ceramic matrix composites are presented. A number of issues related to engineering design, manufacturing technologies, joining, and attachment technologies, are also discussed. Examples of various ongoing activities in the area of composite databases. designing to codes and standards, and design for manufacturing are given.
A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities
McClintock, B.T.; White, Gary C.; Burnham, K.P.
2006-01-01
This article introduces the beta-binomial estimator (BBE), a closed-population abundance mark-resight model combining the favorable qualities of maximum likelihood theory and the allowance of individual heterogeneity in sighting probability (p). The model may be parameterized for a robust sampling design consisting of multiple primary sampling occasions where closure need not be met between primary occasions. We applied the model to brown bear data from three study areas in Alaska and compared its performance to the joint hypergeometric estimator (JHE) and Bowden's estimator (BOWE). BBE estimates suggest heterogeneity levels were non-negligible and discourage the use of JHE for these data. Compared to JHE and BOWE, confidence intervals were considerably shorter for the AICc model-averaged BBE. To evaluate the properties of BBE relative to JHE and BOWE when sample sizes are small, simulations were performed with data from three primary occasions generated under both individual heterogeneity and temporal variation in p. All models remained consistent regardless of levels of variation in p. In terms of precision, the AICc model-averaged BBE showed advantages over JHE and BOWE when heterogeneity was present and mean sighting probabilities were similar between primary occasions. Based on the conditions examined, BBE is a reliable alternative to JHE or BOWE and provides a framework for further advances in mark-resight abundance estimation. ?? 2006 American Statistical Association and the International Biometric Society.
Enhancing Functional Robustness of Gene Regulatory Networks Based on Fitness Landscape Design
NASA Astrophysics Data System (ADS)
Kim, Kyung
We aim to develop design principles for enhancing functional robustness of engineered cells using gene-network topology. We observed the effect of genetic regulation types (inhibition and activation) on robustness. Inhibition was much more stable than activation in E. coli. In the case of activation, if the upstream activator expression is shutdown by mutation, then its downstream expression is shut down as well. Without activation, the activator shutdown due to mutation will make its downstream expression ``remains`` turned off. Thus, the change in the metabolic load is higher in the activation case. Therefore, the stronger activation, the less robust the circuits are. In the inhibition case, we found that the story becomes opposite. When an inhibitor expression is shut down by mutation, the downstream expression turns on because the inhibitor is not expressed. This compensates changes in the metabolic load that might have been decreased without the inhibition. This result presents potential significant roles of network topology on the robustness of engineered cellular networks. This also emphasizes that the concept of fitness landscape, where the local slope corresponds to the fitness difference between different genotypes, can be useful to design robust gene circuits. We acknowledge the support of the NSF (MCB Award # 1515280).
Applying macro design tools to the design of MEMS accelerometers
Davies, B.R.; Rodgers, M.S.; Montague, S.
1998-02-01
This paper describes the design of two different surface micromachined (MEMS) accelerometers and the use of design and analysis tools intended for macro sized devices. This work leverages a process for integrating both the micromechanical structures and microelectronics circuitry of a MEMS accelerometer on the same chip. In this process, the mechanical components of the sensor are first fabricated at the bottom of a trench etched into the wafer substrate. The trench is then filled with oxide and sealed to protect the mechanical components during subsequent microelectronics processing. The wafer surface is then planarized in preparation for CMOS processing. Next, the CMOS electronics are fabricated and the mechanical structures are released. The mechanical structure of each sensor consists of two polysilicon plate masses suspended by multiple springs (cantilevered beam structures) over corresponding polysilicon plates fixed to the substrate to form two parallel plate capacitors. One polysilicon plate mass is suspended using compliant springs forming a variable capacitor. The other polysilicon plate mass is suspended using very stiff springs acting as a fixed capacitor. Acceleration is measured by comparing the variable capacitance with the fixed capacitance during acceleration.
Estimating survival and breeding probability for pond-breeding amphibians: a modified robust design
Bailey, L.L.; Kendall, W.L.; Church, D.R.; Wilbur, H.M.
2004-01-01
Many studies of pond-breeding amphibians involve sampling individuals during migration to and from breeding habitats. Interpreting population processes and dynamics from these studies is difficult because (1) only a proportion of the population is observable each season, while an unknown proportion remains unobservable (e.g., non-breeding adults) and (2) not all observable animals are captured. Imperfect capture probability can be easily accommodated in capture?recapture models, but temporary transitions between observable and unobservable states, often referred to as temporary emigration, is known to cause problems in both open- and closed-population models. We develop a multistate mark?recapture (MSMR) model, using an open-robust design that permits one entry and one exit from the study area per season. Our method extends previous temporary emigration models (MSMR with an unobservable state) in two ways. First, we relax the assumption of demographic closure (no mortality) between consecutive (secondary) samples, allowing estimation of within-pond survival. Also, we add the flexibility to express survival probability of unobservable individuals (e.g., ?non-breeders?) as a function of the survival probability of observable animals while in the same, terrestrial habitat. This allows for potentially different annual survival probabilities for observable and unobservable animals. We apply our model to a relictual population of eastern tiger salamanders (Ambystoma tigrinum tigrinum). Despite small sample sizes, demographic parameters were estimated with reasonable precision. We tested several a priori biological hypotheses and found evidence for seasonal differences in pond survival. Our methods could be applied to a variety of pond-breeding species and other taxa where individuals are captured entering or exiting a common area (e.g., spawning or roosting area, hibernacula).
HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN
While heuristic optimization is applied in environmental applications, ad-hoc algorithm configuration is typical. We use a multi-layer sorptive barrier design problem as a benchmark for an algorithm-tuning procedure, as applied to three heuristics (genetic algorithms, simulated ...
Applying axiomatic design to a medication distribution system
NASA Astrophysics Data System (ADS)
Raguini, Pepito B.
As the need to minimize medication errors drives many medical facilities to come up with robust solutions to the most common error that affects patient's safety, these hospitals would be wise to put a concerted effort into finding methodologies that can facilitate an optimized medical distribution system. If the hospitals' upper management is looking for an optimization method that is an ideal fit, it is just as important that the right tool be selected for the application at hand. In the present work, we propose the application of Axiomatic Design (AD), which is a process that focuses on the generation and selection of functional requirements to meet the customer needs for product and/or process design. The appeal of the axiomatic approach is to provide both a formal design process and a set of technical coefficients for meeting the customer's needs. Thus, AD offers a strategy for the effective integration of people, design methods, design tools and design data. Therefore, we propose the AD methodology to medical applications with the main objective of allowing nurses the opportunity to provide cost effective delivery of medications to inpatients, thereby improving quality patient care. The AD methodology will be implemented through the use of focused stores, where medications can be readily stored and can be conveniently located near patients, as well as a mobile apparatus that can also store medications and is commonly used by hospitals, the medication cart. Moreover, a robust methodology called the focused store methodology will be introduced and developed for both the uncapacitated and capacitated case studies, which will set up an appropriate AD framework and design problem for a medication distribution case study.
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.
Applying a fuzzy-set-based method for robust estimation of coupling loss factors
NASA Astrophysics Data System (ADS)
Nunes, R. F.; Ahmida, K. M.; Arruda, J. R. F.
2007-10-01
Finite element models have been used by many authors to provide accurate estimations of coupling loss factors. Although much progress has been achieved in this area, little attention has been paid to the influence of uncertain parameters in the finite element model used to estimate these factors. It is well known that, in the mid-frequency range, uncertainty is a major issue. In this context, a spectral element method combined with a special implementation of a fuzzy-set-based method, which is called the transformation method, is proposed as an alternative to compute coupling loss factors. The proposed technique is applied to a frame-type junction, which can consist of two beams connected at an arbitrary angle. In this context, two problems are investigated. In the first one, the influence of the confidence intervals of the coupling loss factors on the estimated energy envelopes assuming a unit power input is considered. In the other problem the influence of the envelope of the input power obtained considering the confidence intervals of the coupling loss factors is also taken into account. The estimates of the intervals are obtained by using the spectral element method combined with a fuzzy-set-based method. Results using a Monte Carlo analysis for the estimation of the coupling loss factors under the influence of uncertain parameters are shown for comparison and verification of the fuzzy method.
Dynamic reliability-based robust design optimization with time-variant probabilistic constraints
NASA Astrophysics Data System (ADS)
Wang, Pingfeng; Wang, Zequn; Almaktoom, Abdulaziz T.
2014-06-01
With the increasing complexity of engineering systems, ensuring high system reliability and system performance robustness throughout a product life cycle is of vital importance in practical engineering design. Dynamic reliability analysis, which is generally encountered due to time-variant system random inputs, becomes a primary challenge in reliability-based robust design optimization (RBRDO). This article presents a new approach to efficiently carry out dynamic reliability analysis for RBRDO. The key idea of the proposed approach is to convert time-variant probabilistic constraints to time-invariant ones by efficiently constructing a nested extreme response surface (NERS) and then carry out dynamic reliability analysis using NERS in an iterative RBRDO process. The NERS employs an efficient global optimization technique to identify the extreme time responses that correspond to the worst case scenario of system time-variant limit state functions. With these extreme time samples, a kriging-based time prediction model is built and used to estimate extreme responses for any given arbitrary design in the design space. An adaptive response prediction and model maturation mechanism is developed to guarantee the accuracy and efficiency of the proposed NERS approach. The NERS is integrated with RBRDO with time-variant probabilistic constraints to achieve optimum designs of engineered systems with desired reliability and performance robustness. Two case studies are used to demonstrate the efficacy of the proposed approach.
NASA Astrophysics Data System (ADS)
Sarjaš, Andrej; Chowdhury, Amor; Svečko, Rajko
2016-09-01
This paper presents the synthesis of an optimal robust controller design using the polynomial pole placement technique and multi-criteria optimisation procedure via an evolutionary computation algorithm - differential evolution. The main idea of the design is to provide a reliable fixed-order robust controller structure and an efficient closed-loop performance with a preselected nominally characteristic polynomial. The multi-criteria objective functions have quasi-convex properties that significantly improve convergence and the regularity of the optimal/sub-optimal solution. The fundamental aim of the proposed design is to optimise those quasi-convex functions with fixed closed-loop characteristic polynomials, the properties of which are unrelated and hard to present within formal algebraic frameworks. The objective functions are derived from different closed-loop criteria, such as robustness with metric ?∞, time performance indexes, controller structures, stability properties, etc. Finally, the design results from the example verify the efficiency of the controller design and also indicate broader possibilities for different optimisation criteria and control structures.
Robust controller designs for second-order dynamic systems - A virtual passive approach
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Phan, Minh
1991-01-01
A robust controller design is presented for second-order dynamic systems. The controller is model-independent and itself is a virtual second-order dynamic system. Conditions on actuator and sensor placements are identified for controller designs that guarantee overall closed-loop stability. The dynamic controller can be viewed as a virtual passive damping system that serves to stabilize the actual dynamic system. The control gians are interpreted as virtual mass, spring, and dashpot elements that play the same roles as actual physical elements in stability analysis. Position, velocity, and acceleration feedback are considered. Simple examples are provided to illustrate the physical meaning of this controller design.
Robust controller designs for second-order dynamic system: A virtual passive approach
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Phan, Minh
1990-01-01
A robust controller design is presented for second-order dynamic systems. The controller is model-independent and itself is a virtual second-order dynamic system. Conditions on actuator and sensor placements are identified for controller designs that guarantee overall closed-loop stability. The dynamic controller can be viewed as a virtual passive damping system that serves to stabilize the actual dynamic system. The control gains are interpreted as virtual mass, spring, and dashpot elements that play the same roles as actual physical elements in stability analysis. Position, velocity, and acceleration feedback are considered. Simple examples are provided to illustrate the physical meaning of this controller design.
Design of a nonlinear robust controller for a complete unmanned aerial vehicle mission
NASA Astrophysics Data System (ADS)
Sadraey, Mohammad Hashem
Unmanned Aerial Vehicle (UAV) flight control systems must be capable of delivering the required performance while handling nonlinearities and uncertainties in the vehicle model, the atmosphere, and ambient wind. These factors necessitate the development of nonlinear flight control system design methods that can handle large nonlinearities and uncertainties. Variable approaches to the linear control of UAVs have been discussed in the recent literature. However, the development of a nonlinear robust autopilot has not been addressed to any significant degree. The development of a nonlinear autopilot based on robust control methods will be discussed in this dissertation. In this design technique, the nonlinear UAV model is not linearized. The control law is designed using the Hinfinity technique. This dissertation presents the results of an exploratory study to examine robust autopilot nonlinear design methods for the UAV and compare this new approach with existing PID, LQR, and linear Hinfinity techniques. Since the method must then be verified, its flight simulation will be done using MATLAB/SIMULINK. Verification, validation and robustness tests are documented at the end of this dissertation. The airplane examined is called the Hawkeye. It was designed and built by KU students in the fall of 2004. It is a small, 14 foot wingspan, remotely controlled airplane made from composite materials with a maximum takeoff weight of 90 lbs. It will be used in the future as a small UAV for research programs at KU. The mission includes take-off, climb, cruise, a one and a half circle accomplished in a level turn, and a return back to its original airfield accomplished by cruising back, descending, and completing an approach and landing. After take-off, the airplane is required to climb to 1,000 ft altitude, and then it travels 5,000 ft over the ground into the target area. It will then take some photos of that target using its camera. The complete mission for the UAV lasts about
Design of inner coupling matrix for robustly self-synchronizing networks
NASA Astrophysics Data System (ADS)
Gequn, Liu; Zhiguo, Zhan; Knowles, Gareth
2015-12-01
A self-synchronizing network may undergo change of scale and topology during its functioning, thus adjustment of parameters is necessary to enable the synchronization. The adjustment cost and runtime-break demand a method to maintain continuous operation of the network. To address these issues, this paper presents an analytical method for the design of the inner coupling matrix. The proposed method renders the synchronization robust to change of network scale and topology. It is usual in network models that scale and topology are represented by outer coupling matrix. In this paper we only consider diffusively coupled networks. For these networks, the eigenvalues of the outer coupling matrix are all non-positive. By utilizing this property, the designed inner coupling matrix can cover the entire left half of complex plane within the synchronized region to underlie robustness of synchronization. After elaborating the applicability of several types of synchronization state for a robustly self-synchronizing network, the analytical design method is given for the stable equilibrium point case. Sometimes the Jacobian matrix of the node dynamical equation may lead to an unrealizable complex inner coupling matrix in the method. We then introduce a lemma of matrix transformation to prevent this possibility. Additionally, we investigated the choice of inner coupling matrix to get a desirable self-synchronization speed. The corresponding condition in the design procedure is given to drive the network synchronization faster than convergence of each node. Finally, the article includes examples that show effectiveness and soundness of the method.
Converse, S.J.; Kendall, W.L.; Doherty, P.F., Jr.; Naughton, M.B.; Hines, J.E.
2009-01-01
For many animal populations, one or more life stages are not accessible to sampling, and therefore an unobservable state is created. For colonially-breeding populations, this unobservable state could represent the subset of adult breeders that have foregone breeding in a given year. This situation applies to many seabird populations, notably albatrosses, where skipped breeders are either absent from the colony, or are present but difficult to capture or correctly assign to breeding state. Kendall et al. have proposed design strategies for investigations of seabird demography where such temporary emigration occurs, suggesting the use of the robust design to permit the estimation of time-dependent parameters and to increase the precision of estimates from multi-state models. A traditional robust design, where animals are subject to capture multiple times in a sampling season, is feasible in many cases. However, due to concerns that multiple captures per season could cause undue disturbance to animals, Kendall et al. developed a less-invasive robust design (LIRD), where initial captures are followed by an assessment of the ratio of marked-to-unmarked birds in the population or sampled plot. This approach has recently been applied in the Northwestern Hawaiian Islands to populations of Laysan (Phoebastria immutabilis) and black-footed (P. nigripes) albatrosses. In this paper, we outline the LIRD and its application to seabird population studies. We then describe an approach to determining optimal allocation of sampling effort in which we consider a non-robust design option (nRD), and variations of both the traditional robust design (RD), and the LIRD. Variations we considered included the number of secondary sampling occasions for the RD and the amount of total effort allocated to the marked-to-unmarked ratio assessment for the LIRD. We used simulations, informed by early data from the Hawaiian study, to address optimal study design for our example cases. We found that
NASA Astrophysics Data System (ADS)
Ho, D.; Salmonson, J.; Haan, S.; Clark, D.; Lindl, J.; Meezan, N.; Thomas, C.
2015-11-01
We present six ignition designs using W-doped HDC ablators with, respectively, 2, 3, and 4-step increases in Tr. Fuel adiabat α ranges between 1.5 and 4. The 4-step design has the lowest α of 1.5 but has the highest ablation front Rayleigh-Taylor (RT) growth. Consequently, the overall robustness of the 4-step design is inferior to the intermediate- α 3-step design, assuming typical currently measured surface roughness spectrum. As the foot level is increased further and the shocks merge inside the fuel, the fuel adiabat is raised to 4. The RT growth and mix are reduced but the 1D margin is decreased making it overall more susceptible to surface roughness. The 2-step α = 2.5 design turns out to be the most robust against surface roughness and still can deliver very high 1D yield of 14.5 MJ. Systematic evaluation of the robustness of these capsules with respect to low-mode radiation asymmetries, will also be discussed. Different paths to achieve low-convergence-ratio implosions (i.e. high velocity and high α as one option versus low velocity and low α as another option), while still giving respectable neutron yield will be presented. Finally, we discuss how the performance of these doped capsules changes; if the Au wall of the hohlraum is replaced by U. Work performed under auspices of U.S. DOE by LLNL under DE-AC52-07NA27344.
Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems
NASA Technical Reports Server (NTRS)
Koch, Patrick N.
1997-01-01
Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for
NASA Astrophysics Data System (ADS)
Nambu, Yohsuke; Takashima, Toshihide; Inagaki, Akiya
2015-12-01
This paper examines the effects of connecting multiplexing shunt circuits composed of inductors and resistors to piezoelectric transducers so as to improve the robustness of a piezoelectric vibration absorber (PVA). PVAs are well known to be effective at suppressing the vibration of an adaptive structure; their weakness is low robustness to changes in the dynamic parameters of the system, including the main structure and the absorber. In the application to space structures, the temperature-dependency of capacitance of piezoelectric ceramics is the factor that causes performance reduction. To improve robustness to the temperature-dependency of the capacitance, this paper proposes a multiple-PVA system that is composed of distributed piezoelectric transducers and several shunt circuits. The optimization problems that determine both the frequencies and the damping ratios of the PVAs are multi-objective problems, which are solved using a real-coded genetic algorithm in this paper. A clamped aluminum beam with four groups of piezoelectric ceramics attached was considered in simulations and experiments. Numerical simulations revealed that the PVA systems designed using the proposed method had tolerance to changes in the capacitances. Furthermore, experiments using a thermostatic bath were conducted to reveal the effectiveness and robustness of the PVA systems. The maximum peaks of the transfer functions of the beam with the open circuit, the single-PVA system, the double-PVA system, and the quadruple-PVA system at 20 °C were 14.3 dB, -6.91 dB, -7.47 dB, and -8.51 dB, respectively. The experimental results also showed that the multiple-PVA system is more robust than a single PVA in a variable temperature environment from -10 °C to 50 °C. In conclusion, the use of multiple PVAs results in an effective, robust vibration control method for adaptive structures.
Robust attitude control design for spacecraft under assigned velocity and control constraints.
Hu, Qinglei; Li, Bo; Zhang, Youmin
2013-07-01
A novel robust nonlinear control design under the constraints of assigned velocity and actuator torque is investigated for attitude stabilization of a rigid spacecraft. More specifically, a nonlinear feedback control is firstly developed by explicitly taking into account the constraints on individual angular velocity components as well as external disturbances. Considering further the actuator misalignments and magnitude deviation, a modified robust least-squares based control allocator is employed to deal with the problem of distributing the previously designed three-axis moments over the available actuators, in which the focus of this control allocation is to find the optimal control vector of actuators by minimizing the worst-case residual error using programming algorithms. The attitude control performance using the controller structure is evaluated through a numerical example. PMID:23618744
Evaluation of power costs in applying TMR to FPGA designs.
Rollins, Nathaniel; Wirthlin, M. J.; Graham, P. S.
2004-01-01
Triple modular redundancy (TMR) is a technique commonly used to mitigate against design failures caused by single event upsets (SEUs). The SEU immunity that TMR provides comes at the cost of increased design area and decreased speed. Additionally, the cost of increased power due to TMR must be considered. This paper evaluates the power costs of TMR and validates the evaluations with actual measurements. Sensitivity to design placement is another important part of this study. Power consumption costs due to TMR are also evaluated in different FPGA architectures. This study shows that power consumption rises in the range of 3x to 7x when TMR is applied to a design.
Sequential approximate optimization-based robust design of SiC-Si3N4 nanocomposite microstructures
NASA Astrophysics Data System (ADS)
Mejía-Rodríguez, Gilberto; Renaud, John E.; Kim, Han Sung; Tomar, Vikas
2013-03-01
A simulation-based robust design optimization methodology to predict the most suitable microstructures of SiC-Si 3N 4 nanocomposites for desired high-temperature toughness is presented. The focus is on finding robust nanocomposite microstructures with maximum toughness at two temperatures: 1500°C and 1600°C. Within this context a sequential approximate optimization algorithm under uncertainty is applied to six different test problems addressing different aspects of robust microstructure generation. During optimization, statistical uncertainties inherent to the computational microstructural generation are quantified and introduced in the optimization framework. The results show that the SiC volume fraction, the number of Si 3N 4 grains, the grain size distribution of the Si 3N 4 grains, and the grain size of the SiC particles have varied effects on the microstructure toughness at different temperatures. At 1500°C, the preferred microstructure is the one with higher Si 3N 4 volume fraction, whereas at 1600°C, the preferred microstructure is the one with higher SiC volume fraction.
Robust controller design for flexible structures using normalized coprime factor plant descriptions
NASA Technical Reports Server (NTRS)
Armstrong, Ernest S.
1993-01-01
Stabilization is a fundamental requirement in the design of feedback compensators for flexible structures. The search for the largest neighborhood around a given design plant for which a single controller produces closed-loop stability can be formulated as an H(sub infinity) control problem. The use of normalized coprime factor plant descriptions, in which the plant perturbations are defined as additive modifications to the coprime factors, leads to a closed-form expression for the maximum neighborhood boundary allowing optimal and suboptimal H(sub infinity) compensators to be computed directly without the usual gamma iteration. A summary of the theory on robust stabilization using normalized coprime factor plant descriptions is presented, and the application of the theory to the computation of robustly stable compensators for the phase version of the Control-Structures Interaction (CSI) Evolutionary Model is described. Results from the application indicate that the suboptimal version of the theory has the potential of providing the bases for the computation of low-authority compensators that are robustly stable to expected variations in design model parameters and additive unmodeled dynamics.
Robust design of spot welds in automotive structures: A decision-making methodology
NASA Astrophysics Data System (ADS)
Ouisse, M.; Cogan, S.
2010-05-01
Automotive structures include thousands of spot welds whose design must allow the assembled vehicle to satisfy a wide variety of performance constraints including static, dynamic and crash criteria. The objective of a standard optimization strategy is to reduce the number of spot welds as much as possible while satisfying all the design objectives. However, a classical optimization of the spot weld distribution using an exhaustive search approach is simply not feasible due to the very high order of the design space and the subsequently prohibitive calculation costs. Moreover, even if this calculation could be done, the result would not necessarily be very informative with respect to the design robustness to manufacturing uncertainties (location of welds and defective welds) and to the degradation of spot welds due to fatigue effects over the lifetime of the vehicle. In this paper, a decision-making methodology is presented which allows some aspects of the robustness issues to be integrated into the spot weld design process. The starting point is a given distribution of spot welds on the structure, which is based on both engineering know-how and preliminary critical numerical results, in particular criteria such as crash behavior. An over-populated spot weld distribution is then built in order to satisfy the remaining design criteria, such as static torsion angle and modal behavior. Then, an efficient optimization procedure based on energy considerations is used to eliminate redundant spot welds while preserving as far as possible the nominal structural behavior. The resulting sub-optimal solution is then used to provide a decision indicator for defining effective quality control procedures (e.g. visual post-assembly inspection of a small number of critical spot welds) as well as designing redundancy into critical zones. The final part of the paper is related to comparing the robustness of competing designs. Some decision-making indicators are presented to help the
Variable-complexity optimization applied to airfoil design
NASA Astrophysics Data System (ADS)
Thokala, Praveen; Martins, Joaquim R. R. A.
2007-04-01
Variable-complexity methods are applied to aerodynamic shape design problems with the objective of reducing the total computational cost of the optimization process. Two main strategies are employed: the use of different levels of fidelity in the analysis models (variable fidelity) and the use of different sets of design variables (variable parameterization). Variable-fidelity methods with three different types of corrections are implemented and applied to a set of two-dimensional airfoil optimization problems that use computational fluid dynamics for the analysis. Variable parameterization is also used to solve the same problems. Both strategies are shown to reduce the computational cost of the optimization.
A methodology for robust structural design with application to active aeroelastic wings
NASA Astrophysics Data System (ADS)
Zink, Paul Scott
A new design process for Active Aeroelastic Wing (AAW) technology was developed, in which control surface gear ratios and structural design variables were treated together in the same optimization problem, acting towards the same objective of weight minimization. This is in contrast to traditional AAW design processes that treat design of the gear ratios and design of the structure as separate optimization problems, each with their own different objectives and constraints, executed in an iterative fashion. The demonstration of the new AAW design process, implemented in an efficient modal-based structural analysis and optimization code, on a lightweight fighter resulted in a 15% reduction in wing box skin weight over a more traditional AAW design process. In addition, the new process was far more streamlined than the traditional approach in that it was performed in one continuous run and did not require the exchange of data between modules. The new AAW design process was then used in the development of a methodology for the design of AAW structures that are robust to uncertainty in maneuver loads which arise from the use of linear aerodynamics. Maneuver load uncertainty was modeled probabilistically and based on typical differences between rigid loads as predicted by nonlinear and linear aerodynamic theory. These models were used to augment the linear aerodynamic loads that had been used in the AAW design process. Characteristics of the robust design methodology included: use of a criticality criterion based on a strain energy formulation to determine what loads were most critical to the structure, Latin Hypercube Sampling for the propagation of uncertainty to the criterion function, and redesign of the structure, using the new AAW design process, to the most critical loads identified. The demonstration of the methodology resulted in a wing box skin structure that was 11% heavier than an AAW structure designed only with linear aerodynamics. However, it was
Pfister, A.; Goossen, C.; Coogler, K.; Gorgemans, J.
2012-07-01
Both the International Atomic Energy Agency (IAEA) and the U.S. Nuclear Regulatory Commission (NRC) require existing and new nuclear power plants to conduct plant assessments to demonstrate the unit's ability to withstand external hazards. The events that occurred at the Fukushima-Dai-ichi nuclear power station demonstrated the importance of designing a nuclear power plant with the ability to protect the plant against extreme external hazards. The innovative design of the AP1000{sup R} nuclear power plant provides unparalleled protection against catastrophic external events which can lead to extensive infrastructure damage and place the plant in an extended abnormal situation. The AP1000 plant is an 1100-MWe pressurized water reactor with passive safety features and extensive plant simplifications that enhance construction, operation, maintenance and safety. The plant's compact safety related footprint and protection provided by its robust nuclear island structures prevent significant damage to systems, structures, and components required to safely shutdown the plant and maintain core and spent fuel pool cooling and containment integrity following extreme external events. The AP1000 nuclear power plant has been extensively analyzed and reviewed to demonstrate that it's nuclear island design and plant layout provide protection against both design basis and extreme beyond design basis external hazards such as extreme seismic events, external flooding that exceeds the maximum probable flood limit, and malicious aircraft impact. The AP1000 nuclear power plant uses fail safe passive features to mitigate design basis accidents. The passive safety systems are designed to function without safety-grade support systems (such as AC power, component cooling water, service water, compressed air or HVAC). The plant has been designed to protect systems, structures, and components critical to placing the reactor in a safe shutdown condition within the steel containment vessel
Reliability Engineering and Robust Design: New Methods for Thermal/Fluid Engineering
NASA Astrophysics Data System (ADS)
Cullimore, Brent A.; Tsuyuki, Glenn T.
2002-07-01
Recent years have witnessed more improvement to the SINDA/FLUINT thermohydraulic analyzer than at any other time in its long history. These improvements have included not only expansions in analytic power, but also the additions of high-level modules that offer revolutions in thermal/fluid engineering itself. One such high-level module, "Reliability Engineering," is described in this paper. Reliability Engineering means considering tolerances in design parameters, uncertainties in environments, uncertainties in application (e.g. usage scenarios), and variations in manufacturing as the stochastic phenomena that they are. Using this approach, the probability that a design will achieve its required performance (i.e., the reliability) is calculated, providing an assessment of risk or confidence in the design, and quantifying the amount of over- or under-design present. The design to be evaluated for reliability will likely have been produced using traditional methods. Possibly, the design was generated using the Solver optimizer, another high-level module available in SINDA/FLUINT. Using design optimization, the user quantifies the goals that make one design better than another (mass, efficiency, etc.), and specifies the thresholds or requirements which render a given design viable or useless (exceeding a performance limit, etc.). SINDA/FLUINT then automatically searches for an optimal design. Robust Design means factoring reliability into the development of the design itself: designing for a target reliability and thereby avoiding either costly over-design or dangerous under-design in the first place. Such an approach eliminates a deterministic stack-up of tolerances, worst-case scenarios, safety factors, and margins that have been the traditional approaches for treating uncertainties. In any real system or product, heat transfer and fluid flow play a limited role: there are many other aspects to a successful design than the realm of thermal/fluids that is encompassed
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.
Bionic Concept Applied to Flow Slab Design of PEMFC
NASA Astrophysics Data System (ADS)
Wang, C. T.; Chang, C. P.
A character of fuel cell with high potency and low pollution was known well and considered as a new generation of power technology. In this study a novel design of flow slab addressed and originated from bionic concept will be applied to improve the performance of PEMFC. Simulation results executed at Re = 100 show that the bionic flow type will possess a better uniformity of velocity and lower pressure drop. Besides, the integral performance concerned at SDR and PDR will also show the bionic flow type to be an outstanding design. Hence, this novel flow design addressed will be useful to promotion of PEMFC.
NASA Technical Reports Server (NTRS)
Turso, James A.; Litt, Jonathan S.
2004-01-01
A method for accommodating engine deterioration via a scheduled Linear Parameter Varying Quadratic Lyapunov Function (LPVQLF)-Based controller is presented. The LPVQLF design methodology provides a means for developing unconditionally stable, robust control of Linear Parameter Varying (LPV) systems. The controller is scheduled on the Engine Deterioration Index, a function of estimated parameters that relate to engine health, and is computed using a multilayer feedforward neural network. Acceptable thrust response and tight control of exhaust gas temperature (EGT) is accomplished by adjusting the performance weights on these parameters for different levels of engine degradation. Nonlinear simulations demonstrate that the controller achieves specified performance objectives while being robust to engine deterioration as well as engine-to-engine variations.
Design of Robust PI Controllers and their Application to a Nonlinear Electronic System
NASA Astrophysics Data System (ADS)
Matušů, Radek; Vaneková, Katarína; Prokop, Roman; Bakošová, Monika
2010-01-01
The principal aim of the paper is to present a possible approach to the design of simple Proportional-Integral (PI) robust controllers and subsequently to demonstrate their applicability during control of a laboratory model with uncertain parameters through the Programmable Logic Controller (PLC) SIMATIC S7-300 by Siemens Company. The proposed and utilized synthesis consists of two steps. The former one is determination of controller parameters area, which ensures the robustly stable control loop and is based on computing/plotting the stability boundary locus while the latter one lies in the final choice of the controller itself relying on algebraic techniques. The basic theoretical parts are followed by laboratory experiments in which the 3rd order nonlinear electronic model has been successfully controlled in various working points.
Applying riding-posture optimization on bicycle frame design.
Hsiao, Shih-Wen; Chen, Rong-Qi; Leng, Wan-Lee
2015-11-01
Customization design is a trend for developing a bicycle in recent years. Thus, the comfort of riding a bike is an important factor that should be paid much attention to while developing a bicycle. From the viewpoint of ergonomics, the concept of "fitting object to the human body" is designed into the bicycle frame in this study. Firstly, the important feature points of riding posture were automatically detected by the image processing method. In the measurement process, the best riding posture was identified experimentally, thus the positions of feature points and joint angles of human body were obtained. Afterwards, according to the measurement data, three key points: the handlebar, the saddle and the crank center, were identified and applied to the frame design of various bicycle types. Lastly, this study further proposed a frame size table for common bicycle types, which is helpful for the designer to design a bicycle. PMID:26154206
Probabilistic Methods for Uncertainty Propagation Applied to Aircraft Design
NASA Technical Reports Server (NTRS)
Green, Lawrence L.; Lin, Hong-Zong; Khalessi, Mohammad R.
2002-01-01
Three methods of probabilistic uncertainty propagation and quantification (the method of moments, Monte Carlo simulation, and a nongradient simulation search method) are applied to an aircraft analysis and conceptual design program to demonstrate design under uncertainty. The chosen example problems appear to have discontinuous design spaces and thus these examples pose difficulties for many popular methods of uncertainty propagation and quantification. However, specific implementation features of the first and third methods chosen for use in this study enable successful propagation of small uncertainties through the program. Input uncertainties in two configuration design variables are considered. Uncertainties in aircraft weight are computed. The effects of specifying required levels of constraint satisfaction with specified levels of input uncertainty are also demonstrated. The results show, as expected, that the designs under uncertainty are typically heavier and more conservative than those in which no input uncertainties exist.
Robust Optimal Design of Experiments for Model Discrimination Using an Interactive Software Tool
Stegmaier, Johannes; Skanda, Dominik; Lebiedz, Dirk
2013-01-01
Mathematical modeling of biochemical processes significantly contributes to a better understanding of biological functionality and underlying dynamic mechanisms. To support time consuming and costly lab experiments, kinetic reaction equations can be formulated as a set of ordinary differential equations, which in turn allows to simulate and compare hypothetical models in silico. To identify new experimental designs that are able to discriminate between investigated models, the approach used in this work solves a semi-infinite constrained nonlinear optimization problem using derivative based numerical algorithms. The method takes into account parameter variabilities such that new experimental designs are robust against parameter changes while maintaining the optimal potential to discriminate between hypothetical models. In this contribution we present a newly developed software tool that offers a convenient graphical user interface for model discrimination. We demonstrate the beneficial operation of the discrimination approach and the usefulness of the software tool by analyzing a realistic benchmark experiment from literature. New robust optimal designs that allow to discriminate between the investigated model hypotheses of the benchmark experiment are successfully calculated and yield promising results. The involved robustification approach provides maximally discriminating experiments for the worst parameter configurations, which can be used to estimate the meaningfulness of upcoming experiments. A major benefit of the graphical user interface is the ability to interactively investigate the model behavior and the clear arrangement of numerous variables. In addition to a brief theoretical overview of the discrimination method and the functionality of the software tool, the importance of robustness of experimental designs against parameter variability is demonstrated on a biochemical benchmark problem. The software is licensed under the GNU General Public License
Robust optimal design of experiments for model discrimination using an interactive software tool.
Stegmaier, Johannes; Skanda, Dominik; Lebiedz, Dirk
2013-01-01
Mathematical modeling of biochemical processes significantly contributes to a better understanding of biological functionality and underlying dynamic mechanisms. To support time consuming and costly lab experiments, kinetic reaction equations can be formulated as a set of ordinary differential equations, which in turn allows to simulate and compare hypothetical models in silico. To identify new experimental designs that are able to discriminate between investigated models, the approach used in this work solves a semi-infinite constrained nonlinear optimization problem using derivative based numerical algorithms. The method takes into account parameter variabilities such that new experimental designs are robust against parameter changes while maintaining the optimal potential to discriminate between hypothetical models. In this contribution we present a newly developed software tool that offers a convenient graphical user interface for model discrimination. We demonstrate the beneficial operation of the discrimination approach and the usefulness of the software tool by analyzing a realistic benchmark experiment from literature. New robust optimal designs that allow to discriminate between the investigated model hypotheses of the benchmark experiment are successfully calculated and yield promising results. The involved robustification approach provides maximally discriminating experiments for the worst parameter configurations, which can be used to estimate the meaningfulness of upcoming experiments. A major benefit of the graphical user interface is the ability to interactively investigate the model behavior and the clear arrangement of numerous variables. In addition to a brief theoretical overview of the discrimination method and the functionality of the software tool, the importance of robustness of experimental designs against parameter variability is demonstrated on a biochemical benchmark problem. The software is licensed under the GNU General Public License
A robust approach to human-computer interface design using the Taguchi method
Reed, B.M.
1991-01-01
The application of Dr. Genichi Taguchi's approach for design optimization, called Robust Design, to the design of human-computer interface software is investigated. The taguchi method is used to select a near optimum set of interface design alternatives to improve user acceptance of the resulting interface software product with minimum sensitivity to uncontrollable noise caused by human behavioral characteristics. Design alternatives for interaction with personal micro-computers are identified. Several important and representative alternatives are chosen as design parameters for the Taguchi matrix experiment. A noise field with three human behavioral characteristics as noise factors were chosen as a representative noise array. Task accomplishment scenarios were developed for demonstration of the design parameters on an interactive human-computer interface. Experimentation was conducted using selected human subjects to study the effect of the various settings of the design parameters on user acceptance of the interface. Using the results of the matrix experiment, a near optimum set of design parameter values was selected.
Robust optimal design of diffusion-weighted magnetic resonance experiments for skin microcirculation
NASA Astrophysics Data System (ADS)
Choi, J.; Raguin, L. G.
2010-10-01
Skin microcirculation plays an important role in several diseases including chronic venous insufficiency and diabetes. Magnetic resonance (MR) has the potential to provide quantitative information and a better penetration depth compared with other non-invasive methods such as laser Doppler flowmetry or optical coherence tomography. The continuous progress in hardware resulting in higher sensitivity must be coupled with advances in data acquisition schemes. In this article, we first introduce a physical model for quantifying skin microcirculation using diffusion-weighted MR (DWMR) based on an effective dispersion model for skin leading to a q-space model of the DWMR complex signal, and then design the corresponding robust optimal experiments. The resulting robust optimal DWMR protocols improve the worst-case quality of parameter estimates using nonlinear least squares optimization by exploiting available a priori knowledge of model parameters. Hence, our approach optimizes the gradient strengths and directions used in DWMR experiments to robustly minimize the size of the parameter estimation error with respect to model parameter uncertainty. Numerical evaluations are presented to demonstrate the effectiveness of our approach as compared to conventional DWMR protocols.
Designing Agent Utilities for Coordinated, Scalable and Robust Multi-Agent Systems
NASA Technical Reports Server (NTRS)
Tumer, Kagan
2005-01-01
Coordinating the behavior of a large number of agents to achieve a system level goal poses unique design challenges. In particular, problems of scaling (number of agents in the thousands to tens of thousands), observability (agents have limited sensing capabilities), and robustness (the agents are unreliable) make it impossible to simply apply methods developed for small multi-agent systems composed of reliable agents. To address these problems, we present an approach based on deriving agent goals that are aligned with the overall system goal, and can be computed using information readily available to the agents. Then, each agent uses a simple reinforcement learning algorithm to pursue its own goals. Because of the way in which those goals are derived, there is no need to use difficult to scale external mechanisms to force collaboration or coordination among the agents, or to ensure that agents actively attempt to appropriate the tasks of agents that suffered failures. To present these results in a concrete setting, we focus on the problem of finding the sub-set of a set of imperfect devices that results in the best aggregate device. This is a large distributed agent coordination problem where each agent (e.g., device) needs to determine whether to be part of the aggregate device. Our results show that the approach proposed in this work provides improvements of over an order of magnitude over both traditional search methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents failed midway through the simulation) the system's performance degrades gracefully and still outperforms a failure-free and centralized search algorithm. The results also show that the gains increase as the size of the system (e.g., number of agents) increases. This latter result is particularly encouraging and suggests that this method is ideally suited for domains where the number of agents is currently in the
Free-Energy-Based Design Policy for Robust Network Control against Environmental Fluctuation
Iwai, Takuya; Kominami, Daichi; Murata, Masayuki; Yomo, Tetsuya
2015-01-01
Bioinspired network control is a promising approach for realizing robust network controls. It relies on a probabilistic mechanism composed of positive and negative feedback that allows the system to eventually stabilize on the best solution. When the best solution fails due to environmental fluctuation, the system cannot keep its function until the system finds another solution again. To prevent the temporal loss of the function, the system should prepare some solution candidates and stochastically select available one from them. However, most bioinspired network controls are not designed with this issue in mind. In this paper, we propose a thermodynamics-based design policy that allows systems to retain an appropriate degree of randomness depending on the degree of environmental fluctuation, which prepares the system for the occurrence of environmental fluctuation. Furthermore, we verify the design policy by using an attractor selection model-based multipath routing to run simulation experiments. PMID:26167525
NASA Astrophysics Data System (ADS)
Badri, Pouya; Amini, Amir; Sojoodi, Mahdi
2016-12-01
This paper deals with designing a robust fixed-order non-fragile dynamic output feedback controller for active suspension system of a quarter-car, by means of convex optimization and linear matrix inequalities (LMIs). Our purpose is to design a low-order controller that keeps the desired design specifications besides the simplicity of the implementation. The proposed controller is capable of asymptotically stabilizing the closed-loop system and developing H∞ control, despite model uncertainties and nonlinear dynamics of the quarter-car as well as the norm bounded perturbations of controller parameters. Furthermore, controller parameters are prevented from taking very large and undesirable amounts through appropriate LMI constraints. Finally, a numerical example is presented to show the effectiveness of the proposed method by comparing it with similar works.
A robust variable sampling time BLDC motor control design based upon μ-synthesis.
Hung, Chung-Wen; Yen, Jia-Yush
2013-01-01
The variable sampling rate system is encountered in many applications. When the speed information is derived from the position marks along the trajectory, one would have a speed dependent sampling rate system. The conventional fixed or multisampling rate system theory may not work in these cases because the system dynamics include the uncertainties which resulted from the variable sampling rate. This paper derived a convenient expression for the speed dependent sampling rate system. The varying sampling rate effect is then translated into multiplicative uncertainties to the system. The design then uses the popular μ-synthesis process to achieve a robust performance controller design. The implementation on a BLDC motor demonstrates the effectiveness of the design approach. PMID:24327804
A Robust Variable Sampling Time BLDC Motor Control Design Based upon μ-Synthesis
Yen, Jia-Yush
2013-01-01
The variable sampling rate system is encountered in many applications. When the speed information is derived from the position marks along the trajectory, one would have a speed dependent sampling rate system. The conventional fixed or multisampling rate system theory may not work in these cases because the system dynamics include the uncertainties which resulted from the variable sampling rate. This paper derived a convenient expression for the speed dependent sampling rate system. The varying sampling rate effect is then translated into multiplicative uncertainties to the system. The design then uses the popular μ-synthesis process to achieve a robust performance controller design. The implementation on a BLDC motor demonstrates the effectiveness of the design approach. PMID:24327804
Multivariable output feedback robust adaptive tracking control design for a class of delayed systems
NASA Astrophysics Data System (ADS)
Mirkin, Boris; Gutman, Per-Olof
2015-02-01
In this paper, we develop a model reference adaptive control scheme for a class of multi-input multi-output nonlinearly perturbed dynamic systems with unknown time-varying state delays which is also robust with respect to an external disturbance with unknown bounds. The output feedback adaptive control scheme uses feedback actions only, and thus does not require a direct measurement of the command or disturbance signals. A suitable Lyapunov-Krasovskii type functional is introduced to design the adaptation algorithms and to prove stability.
Faircloth, Brant C.; Glenn, Travis C.
2012-01-01
Ligating adapters with unique synthetic oligonucleotide sequences (sequence tags) onto individual DNA samples before massively parallel sequencing is a popular and efficient way to obtain sequence data from many individual samples. Tag sequences should be numerous and sufficiently different to ensure sequencing, replication, and oligonucleotide synthesis errors do not cause tags to be unrecoverable or confused. However, many design approaches only protect against substitution errors during sequencing and extant tag sets contain too few tag sequences. We developed an open-source software package to validate sequence tags for conformance to two distance metrics and design sequence tags robust to indel and substitution errors. We use this software package to evaluate several commercial and non-commercial sequence tag sets, design several large sets (maxcount = 7,198) of edit metric sequence tags having different lengths and degrees of error correction, and integrate a subset of these edit metric tags to polymerase chain reaction (PCR) primers and sequencing adapters. We validate a subset of these edit metric tagged PCR primers and sequencing adapters by sequencing on several platforms and subsequent comparison to commercially available alternatives. We find that several commonly used sets of sequence tags or design methodologies used to produce sequence tags do not meet the minimum expectations of their underlying distance metric, and we find that PCR primers and sequencing adapters incorporating edit metric sequence tags designed by our software package perform as well as their commercial counterparts. We suggest that researchers evaluate sequence tags prior to use or evaluate tags that they have been using. The sequence tag sets we design improve on extant sets because they are large, valid across the set, and robust to the suite of substitution, insertion, and deletion errors affecting massively parallel sequencing workflows on all currently used platforms
A robust helium-cooled shield/blanket design for ITER
NASA Astrophysics Data System (ADS)
Wong, C. P. C.; Bourque, R. F.; Baxi, C. B.; Colleraine, A. P.; Grunloh, H. J.; Letchenberg, T.; Leuer, J. A.; Reis, E. E.; Redler, K.; Will, R.
1993-11-01
General Atomics Fusion and Reactor Groups have completed a helium-cooled, conceptual shield/blanket design for ITER. The configuration selected is a pressurized tubes design embedded in radially oriented plates. This plate can be made from ferritic steel or from V-alloy. Helium leakage to the plasma chamber is eliminated by conservative, redundant design and proper quality control and inspection programs. High helium pressure at 18 MPa is used to reduce pressure drop and enhance heat transfer. This high gas pressure is believed practical when confined in small diameter tubes. Ample industrial experience exists for safe high gas pressure operations. Inboard shield design is highlighted in this study since the allowable void fraction is more limited. Lithium is used as the thermal contacting medium and for tritium breeding; its safety concerns are minimized by a modular, low inventory design that requires no circulation of the liquid metal for the purpose of heat removal. This design is robust, conservative, reliable, and meets all design goals and requirements. It can also be built with present-day technology.
Probabilistic Design and Analysis for Robust Design of Advanced Thermoelectric Conversion Systems
Hendricks, Terry J.; Karri, Naveen K.
2007-04-01
ABSTRACT Research work has investigated the impacts and effects of single- and multi-variable stochasticity on optimum thermoelectric (TE) system design for automotive and industrial energy recovery applications because many critical design and environmental parameters input to the design optimization process can be randomly variable. Analysis tools and techniques have been developed to investigate a variety of stochastic behaviors in critical input parameters, including Gaussian, Log-Normal, Weibull, Gamma, or any type of user-defined probability distribution. Recent accomplishments discussed in this work show that Gaussian input probability distributions can create non-Gaussian outcome distributions for optimum TE areas, required cold-side mass flow rates, and expected power generation; optimum deterministically-derived designs (TE areas and cold-side mass flow rates) should be significantly modified in response to stochastically variable inputs; and outcome parameter standard deviations can be quite significant and magnified relative to input parameter standard deviations. Multiple variable stochastic inputs tend to significantly increase the output design parameter variability (i.e., standard deviations). Coupled, interactive effects/impacts of multiple stochastic input parameters in this research have demonstrated that reductions of optimum TE areas by 9-10% relative to deterministic optimum values was warranted in key stochastic analyses cases studied. Reductions in required cold-side mass flow rates may also be justified. Optimum system power output also was characterized by relatively high standard deviations and variability as a result of stochastic input parameter effects on the TE design optimization process, this would be an important consideration when integrating the overall power system design with power management electronics and energy storage subsystems.
Sontag, Eduardo; Davidsohn, Noah; Subramanian, Sairam; Purnick, Priscilla E. M.; Lauffenburger, Douglas; Weiss, Ron
2012-01-01
Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of β-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation) are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for ‘synthetic cellular heterogeneity’ that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism), demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a ‘phenotypic sensitivity analysis’ method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in isolation
Porel, A.; Sanyal, Y.; Kundu, A.
2014-01-01
The aim of the present study was the development and validation of a simple, precise and specific reversed phase HPLC method for the simultaneous determination of 22 components present in different essential oils namely cinnamon bark oil, caraway oil and cardamom fruit oil. The chromatographic separation of all the components was achieved on Wakosil–II C18 column with mixture of 30 mM ammonium acetate buffer (pH 4.7), methanol and acetonitrile in different ratio as mobile phase in a ternary linear gradient mode. The calibration graphs plotted with five different concentrations of each component were linear with a regression coefficient R2 >0.999. The limit of detection and limit of quantitation were estimated for all the components. Effect on analytical responses by small and deliberate variation of critical factors was examined by robustness testing with Design of Experiment employing Central Composite Design and established that this method was robust. The method was then validated for linearity, precision, accuracy, specificity and demonstrated to be applicable to the determination of the ingredients in commercial sample of essential oil. PMID:24799735
A robust approach to the design of an electromagnetic shield based on pyrolitic carbon
NASA Astrophysics Data System (ADS)
Lamberti, Patrizia; Kuzhir, Polina; Tucci, Vincenzo
2016-07-01
A robust approach to the design of an electromagnetic shield based on ultra-thin pyrolytic carbon (PyC, 5 ÷ 110 nm) films is proposed. Finite Element Method (FEM) simulations and Monte Carlo based tolerance analysis are used to show that even a deviation of 15 ÷ 20% from the nominal values of the most important design parameters of the PyC film, i.e. its thickness and sheet resistance, does not significantly affect the wanted level of electromagnetic interference shielding efficiency (EMI SE). The ranges of the SE show that EMI shield based on PyC film is characterized by a robust behavior with respect to the variation of such parameters due to the production processes. Therefore, since the PyC can be produced on a scalable basis, is chemically inert, significantly transparent in the visible range and can be deposited onto both metal and dielectric substrates, including flexible polymers, it may be appropriate for the highly demanding technological needs associated to the graphene revolution and can be developed from laboratory to mass production applications.
Assessing target design robustness for Shock Ignition using 3D laser raytracing
NASA Astrophysics Data System (ADS)
Schiavi, Angelo; Atzeni, Stefano; Marocchino, Alberto
2014-10-01
Shock ignition (SI) is a laser direct-drive Inertial Confinement Fusion scheme in which fuel compression and hot spot formation are separated. Shock ignition shows potential for high gain at laser energy below 1 MJ (see review Ref.), and could be tested on present large scale facilities. We produced an analytical model for SI which allows rescaling of target and laser drive parameters starting from a given point design. The goal is to redefine a laser-target configuration increasing the robustness while preserving its performance. We developed a metric for ignition margins specific to SI. We report on simulations of rescaled targets using 2D hydrodynamic fluid model with 3D laser raytracing. The robustness with respect to target fabrication parameters and laser facility fluctuations will be assessed for an original reference design as well as for a rescaled target, testing the accuracy of the ignition margin predictor just developed. Work supported by the Italian MIUR Project PRIN2012AY5LEL.
Porel, A; Sanyal, Y; Kundu, A
2014-01-01
The aim of the present study was the development and validation of a simple, precise and specific reversed phase HPLC method for the simultaneous determination of 22 components present in different essential oils namely cinnamon bark oil, caraway oil and cardamom fruit oil. The chromatographic separation of all the components was achieved on Wakosil-II C18 column with mixture of 30 mM ammonium acetate buffer (pH 4.7), methanol and acetonitrile in different ratio as mobile phase in a ternary linear gradient mode. The calibration graphs plotted with five different concentrations of each component were linear with a regression coefficient R(2) >0.999. The limit of detection and limit of quantitation were estimated for all the components. Effect on analytical responses by small and deliberate variation of critical factors was examined by robustness testing with Design of Experiment employing Central Composite Design and established that this method was robust. The method was then validated for linearity, precision, accuracy, specificity and demonstrated to be applicable to the determination of the ingredients in commercial sample of essential oil. PMID:24799735
A TCAD approach to robust ESD design in oxide-confined VCSELs
NASA Astrophysics Data System (ADS)
Meier, Hektor; Santschi, Rafael; Odermatt, Stefan; Witzigmann, Bernd; Eitel, Sven; Nallet, Franck; Letay, Gergö
2007-02-01
Electrostatic Discharge (ESD) events can cause irreversible damage during production, packaging and application of Vertical-Cavity Surface Emitting Lasers (VCSELs). Experimental investigation of those damage patterns inside a real device is a complex and expensive task. Simulation tools can provide insight into the physics during an actual discharge event. This paper aims to analyze ESD events in VCSELs with a microscopic simulation. With the help of a state-of-the art Technology Computer Aided Design (TCAD) virtual ESD tests are performed on oxide-confined VCSELs. The 2-D simulation model takes into account high-field effects and self-heating in a hydrodynamic framework that allows time-dependent spatially resolved monitoring of critical quantities (such as electric field across the oxide, temperature profile, current densities) during the ESD events. Human Body Model (HBM), Machine Model (MM) and Charged Device Model (CDM) show typical local heating and current crowding effects which may lead to irreversible damaging of the device. For slow ESD events the temperature peak is found near the center of the device. Faster pulses show maximum temperature at the interface between oxide and aperture. Physics-based explanations in terms of local electric field, heat generation and heat transport are given. Oxide aperture, thickness and its position relative to the intrinsic region strongly influence self-heating, electric fields, current density profiles and the dielectric breakdown conditions. The impact of those factors on ESD robustness are analyzed and guidelines for robust ESD design in VCSELs are presented.
Flight control design using a blend of modern nonlinear adaptive and robust techniques
NASA Astrophysics Data System (ADS)
Yang, Xiaolong
In this dissertation, the modern control techniques of feedback linearization, mu synthesis, and neural network based adaptation are used to design novel control laws for two specific applications: F/A-18 flight control and reusable launch vehicle (an X-33 derivative) entry guidance. For both applications, the performance of the controllers is assessed. As a part of a NASA Dryden program to develop and flight test experimental controllers for an F/A-18 aircraft, a novel method of combining mu synthesis and feedback linearization is developed to design longitudinal and lateral-directional controllers. First of all, the open-loop and closed-loop dynamics of F/A-18 are investigated. The production F/A-18 controller as well as the control distribution mechanism are studied. The open-loop and closed-loop handling qualities of the F/A-18 are evaluated using low order transfer functions. Based on this information, a blend of robust mu synthesis and feedback linearization is used to design controllers for a low dynamic pressure envelope of flight conditions. For both the longitudinal and the lateral-directional axes, a robust linear controller is designed for a trim point in the center of the envelope. Then by including terms to cancel kinematic nonlinearities and variations in the aerodynamic forces and moments over the flight envelope, a complete nonlinear controller is developed. In addition, to compensate for the model uncertainty, linearization error and variations between operating points, neural network based adaptation is added to the designed longitudinal controller. The nonlinear simulations, robustness and handling qualities analysis indicate that the performance is similar to or better than that for the production F/A-18 controllers. When the dynamic pressure is very low, the performance of both the experimental and the production flight controllers is degraded, but Level I handling qualities are still achieved. A new generation of Reusable Launch Vehicles
A new smooth robust control design for uncertain nonlinear systems with non-vanishing disturbances
NASA Astrophysics Data System (ADS)
Xian, Bin; Zhang, Yao
2016-06-01
In this paper, we consider the control problem for a general class of nonlinear system subjected to uncertain dynamics and non-varnishing disturbances. A smooth nonlinear control algorithm is presented to tackle these uncertainties and disturbances. The proposed control design employs the integral of a nonlinear sigmoid function to compensate the uncertain dynamics, and achieve a uniformly semi-global practical asymptotic stable tracking control of the system outputs. A novel Lyapunov-based stability analysis is employed to prove the convergence of the tracking errors and the stability of the closed-loop system. Numerical simulation results on a two-link robot manipulator are presented to illustrate the performance of the proposed control algorithm comparing with the layer-boundary sliding mode controller and the robust of integration of sign of error control design. Furthermore, real-time experiment results for the attitude control of a quadrotor helicopter are also included to confirm the effectiveness of the proposed algorithm.
Optimal and robust design of brain-state-in-a-box neural associative memories.
Park, Yonmook
2010-03-01
This paper presents a new optimization approach to the design of associative memories via the brain-state-in-a-box (BSB) neural network. The optimization approach proposed in this paper provides the large and uniform domains of attraction of the prototype patterns, the large robustness margin for the weight matrix of the perturbed BSB neural network, the asymptotic stability of the prototype patterns, and the global stability of the BSB neural network. Based on some known qualitative properties of the BSB neural network and theoretical results presented in this paper, a synthesis method of the BSB-based associative memory is established. The synthesis method presented in this paper is given in the form of a linear matrix inequality-based optimization problem, which can be efficiently solved by a readily available software. Design examples are given to demonstrate the applicability of the proposed method and to compare with the existing synthesis methods. PMID:19914797
NASA Astrophysics Data System (ADS)
Mindrup, Frank M.; Friend, Mark A.; Bauer, Kenneth W.
2011-06-01
There are numerous anomaly detection algorithms proposed for hyperspectral imagery. Robust parameter design (RPD) techniques have been applied to some of these algorithms in an attempt to choose robust settings capable of operating consistently across a large variety of image scenes. Typically, training and test sets of hyperspectral images are chosen randomly. Previous research developed a frameworkfor optimizing anomaly detection in HSI by considering specific image characteristics as noise variables within the context of RPD; these characteristics include the Fisher's score, ratio of target pixels and number of clusters. This paper describes a method for selecting hyperspectral image training and test subsets yielding consistent RPD results based on these noise features. These subsets are not necessarily orthogonal, but still provide improvements over random training and test subset assignments by maximizing the volume and average distance between image noise characteristics. Several different mathematical models representing the value of a training and test set based on such measures as the D-optimal score and various distance norms are tested in a simulation experiment.
Min, H. Jason; Beyeler, Walter E.; Glass, Laura M.
2008-01-01
Background The US government proposes pandemic influenza mitigation guidance that includes isolation and antiviral treatment of ill persons, voluntary household member quarantine and antiviral prophylaxis, social distancing of individuals, school closure, reduction of contacts at work, and prioritized vaccination. Is this the best strategy combination? Is choice of this strategy robust to pandemic uncertainties? What are critical enablers of community resilience? Methods and Findings We systematically simulate a broad range of pandemic scenarios and mitigation strategies using a networked, agent-based model of a community of explicit, multiply-overlapping social contact networks. We evaluate illness and societal burden for alterations in social networks, illness parameters, or intervention implementation. For a 1918-like pandemic, the best strategy minimizes illness to <1% of the population and combines network-based (e.g. school closure, social distancing of all with adults' contacts at work reduced), and case-based measures (e.g. antiviral treatment of the ill and prophylaxis of household members). We find choice of this best strategy robust to removal of enhanced transmission by the young, additional complexity in contact networks, and altered influenza natural history including extended viral shedding. Administration of age-group or randomly targeted 50% effective pre-pandemic vaccine with 7% population coverage (current US H5N1 vaccine stockpile) had minimal effect on outcomes. In order, mitigation success depends on rapid strategy implementation, high compliance, regional mitigation, and rigorous rescinding criteria; these are the critical enablers for community resilience. Conclusions Systematic evaluation of feasible, recommended pandemic influenza interventions generally confirms the US community mitigation guidance yields best strategy choices for pandemic planning that are robust to a wide range of uncertainty. The best strategy combines network- and
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Bushnell, Dennis M. (Technical Monitor)
2002-01-01
This paper presents a study on the optimization of systems with structured uncertainties, whose inputs and outputs can be exhaustively described in the probabilistic sense. By propagating the uncertainty from the input to the output in the space of the probability density functions and the moments, optimization problems that pursue performance, robustness and reliability based designs are studied. Be specifying the desired outputs in terms of desired probability density functions and then in terms of meaningful probabilistic indices, we settle a computationally viable framework for solving practical optimization problems. Applications to static optimization and stability control are used to illustrate the relevance of incorporating uncertainty in the early stages of the design. Several examples that admit a full probabilistic description of the output in terms of the design variables and the uncertain inputs are used to elucidate the main features of the generic problem and its solution. Extensions to problems that do not admit closed form solutions are also evaluated. Concrete evidence of the importance of using a consistent probabilistic formulation of the optimization problem and a meaningful probabilistic description of its solution is provided in the examples. In the stability control problem the analysis shows that standard deterministic approaches lead to designs with high probability of running into instability. The implementation of such designs can indeed have catastrophic consequences.
Design of SPARC V8 superscalar pipeline applied Tomasulo's algorithm
NASA Astrophysics Data System (ADS)
Yang, Xue; Yu, Lixin; Feng, Yunkai
2014-04-01
A superscalar pipeline applied Tomasulo's algorithm is presented in this paper. The design begins with a dual-issue superscalar processor based on LEON2. Tomasulo's algorithm is adopted to implement out-of-order execution. Instructions are separated into three different parts and executed by three different function units so as to reduce area and promote execution speed. Results wrote back into registers are still in program order, for the aim of ensure the function veracity. Mechanisms of the reservation station, common data bus, and reorder buffer are presented in detail. The structure can sends and executes three instructions at most at a time. Branch prediction can also be realized by reorder buffer. Performance of the scalar pipeline applied Tomasulo's algorithm is promoted by 41.31% compared to singleissue pipeline..
Combining band recovery data and Pollock's robust design to model temporary and permanent emigration
Lindberg, M.S.; Kendall, W.L.; Hines, J.E.; Anderson, M.G.
2001-01-01
Capture-recapture models are widely used to estimate demographic parameters of marked populations. Recently, this statistical theory has been extended to modeling dispersal of open populations. Multistate models can be used to estimate movement probabilities among subdivided populations if multiple sites are sampled. Frequently, however, sampling is limited to a single site. Models described by Burnham (1993, in Marked Individuals in the Study of Bird Populations, 199-213), which combined open population capture-recapture and band-recovery models, can be used to estimate permanent emigration when sampling is limited to a single population. Similarly, Kendall, Nichols, and Hines (1997, Ecology 51, 563-578) developed models to estimate temporary emigration under Pollock's (1982, Journal of Wildlife Management 46, 757-760) robust design. We describe a likelihood-based approach to simultaneously estimate temporary and permanent emigration when sampling is limited to a single population. We use a sampling design that combines the robust design and recoveries of individuals obtained immediately following each sampling period. We present a general form for our model where temporary emigration is a first-order Markov process, and we discuss more restrictive models. We illustrate these models with analysis of data on marked Canvasback ducks. Our analysis indicates that probability of permanent emigration for adult female Canvasbacks was 0.193 (SE = 0.082) and that birds that were present at the study area in year i - 1 had a higher probability of presence in year i than birds that were not present in year i - 1.
Flight control system design factors for applying automated testing techniques
NASA Technical Reports Server (NTRS)
Sitz, Joel R.; Vernon, Todd H.
1990-01-01
Automated validation of flight-critical embedded systems is being done at ARC Dryden Flight Research Facility. The automated testing techniques are being used to perform closed-loop validation of man-rated flight control systems. The principal design features and operational experiences of the X-29 forward-swept-wing aircraft and F-18 High Alpha Research Vehicle (HARV) automated test systems are discussed. Operationally applying automated testing techniques has accentuated flight control system features that either help or hinder the application of these techniques. The paper also discusses flight control system features which foster the use of automated testing techniques.
NASA Astrophysics Data System (ADS)
Dores, Delfim Zambujo Das
2005-11-01
Engineering research over the last few years has successfully demonstrated the potential of thrust vector control using counterflow at conditions up to Mach 2. Flow configurations that include the pitch vectoring of rectangular jets and multi-axis vector control in diamond and axisymmetric nozzle geometries have been studied. Although bistable (on-off) fluid-based control has been around for some time, the present counterflow thrust vector control is unique because proportional and continuous jet response can be achieved in the absence of moving parts, while avoiding jet attachment, which renders most fluidic approaches unacceptable for aircraft and missile control applications. However, before this study, research had been limited to open-loop studies of counterflow thrust vectoring. For practical implementation it was vital that the counterflow scheme be used in conjunction with feedback control. Hence, the focus of this research was to develop and experimentally demonstrate a feedback control design methodology for counterflow thrust vectoring. This research focused on 2-D (pitch) thrust vectoring and addresses four key modeling issues. The first issue is to determine the measured variable to be commanded since the thrust vector angle is not measurable in real time. The second related issue is to determine the static mapping from the thrust vector angle to this measured variable. The third issue is to determine the dynamic relationship between the measured variable and the thrust vector angle. The fourth issue is to develop dynamic models with uncertainty characterizations. The final and main goal was the design and implementation of robust controllers that yield closed-loop systems with fast response times, and avoid overshoot in order to aid in the avoidance of attachment. These controllers should be simple and easy to implement in real applications. Hence, PID design has been chosen. Robust control design is accomplished by using ℓ1 control theory in
Design of Robust Adaptive Unbalance Response Controllers for Rotors with Magnetic Bearings
NASA Technical Reports Server (NTRS)
Knospe, Carl R.; Tamer, Samir M.; Fedigan, Stephen J.
1996-01-01
Experimental results have recently demonstrated that an adaptive open loop control strategy can be highly effective in the suppression of unbalance induced vibration on rotors supported in active magnetic bearings. This algorithm, however, relies upon a predetermined gain matrix. Typically, this matrix is determined by an optimal control formulation resulting in the choice of the pseudo-inverse of the nominal influence coefficient matrix as the gain matrix. This solution may result in problems with stability and performance robustness since the estimated influence coefficient matrix is not equal to the actual influence coefficient matrix. Recently, analysis tools have been developed to examine the robustness of this control algorithm with respect to structured uncertainty. Herein, these tools are extended to produce a design procedure for determining the adaptive law's gain matrix. The resulting control algorithm has a guaranteed convergence rate and steady state performance in spite of the uncertainty in the rotor system. Several examples are presented which demonstrate the effectiveness of this approach and its advantages over the standard optimal control formulation.
Robust fault-tolerant tracking control design for spacecraft under control input saturation.
Bustan, Danyal; Pariz, Naser; Sani, Seyyed Kamal Hosseini
2014-07-01
In this paper, a continuous globally stable tracking control algorithm is proposed for a spacecraft in the presence of unknown actuator failure, control input saturation, uncertainty in inertial matrix and external disturbances. The design method is based on variable structure control and has the following properties: (1) fast and accurate response in the presence of bounded disturbances; (2) robust to the partial loss of actuator effectiveness; (3) explicit consideration of control input saturation; and (4) robust to uncertainty in inertial matrix. In contrast to traditional fault-tolerant control methods, the proposed controller does not require knowledge of the actuator faults and is implemented without explicit fault detection and isolation processes. In the proposed controller a single parameter is adjusted dynamically in such a way that it is possible to prove that both attitude and angular velocity errors will tend to zero asymptotically. The stability proof is based on a Lyapunov analysis and the properties of the singularity free quaternion representation of spacecraft dynamics. Results of numerical simulations state that the proposed controller is successful in achieving high attitude performance in the presence of external disturbances, actuator failures, and control input saturation. PMID:24751476
Silva, Marta M.; Rodrigues, Ana F.; Correia, Cláudia; Sousa, Marcos F.Q.; Brito, Catarina; Coroadinha, Ana S.
2015-01-01
Human embryonic stem cells (hESCs) have an enormous potential as a source for cell replacement therapies, tissue engineering, and in vitro toxicology applications. The lack of standardized and robust bioprocesses for hESC expansion has hindered the application of hESCs and their derivatives in clinical settings. We developed a robust and well-characterized bioprocess for hESC expansion under fully defined conditions and explored the potential of transcriptomic and metabolomic tools for a more comprehensive assessment of culture system impact on cell proliferation, metabolism, and phenotype. Two different hESC lines (feeder-dependent and feeder-free lines) were efficiently expanded on xeno-free microcarriers in stirred culture systems. Both hESC lines maintained the expression of stemness markers such as Oct-4, Nanog, SSEA-4, and TRA1-60 and the ability to spontaneously differentiate into the three germ layers. Whole-genome transcriptome profiling revealed a phenotypic convergence between both hESC lines along the expansion process in stirred-tank bioreactor cultures, providing strong evidence of the robustness of the cultivation process to homogenize cellular phenotype. Under low-oxygen tension, results showed metabolic rearrangement with upregulation of the glycolytic machinery favoring an anaerobic glycolysis Warburg-effect-like phenotype, with no evidence of hypoxic stress response, in contrast to two-dimensional culture. Overall, we report a standardized expansion bioprocess that can guarantee maximal product quality. Furthermore, the “omics” tools used provided relevant findings on the physiological and metabolic changes during hESC expansion in environmentally controlled stirred-tank bioreactors, which can contribute to improved scale-up production systems. Significance The clinical application of human pluripotent stem cells (hPSCs) has been hindered by the lack of robust protocols able to sustain production of high cell numbers, as required for
Designing the Electronic Classroom: Applying Learning Theory and Ergonomic Design Principles.
ERIC Educational Resources Information Center
Emmons, Mark; Wilkinson, Frances C.
2001-01-01
Applies learning theory and ergonomic principles to the design of effective learning environments for library instruction. Discusses features of electronic classroom ergonomics, including the ergonomics of physical space, environmental factors, and workstations; and includes classroom layouts. (Author/LRW)
Data-Division-Specific Robustness and Power of Randomization Tests for ABAB Designs
ERIC Educational Resources Information Center
Manolov, Rumen; Solanas, Antonio; Bulte, Isis; Onghena, Patrick
2010-01-01
This study deals with the statistical properties of a randomization test applied to an ABAB design in cases where the desirable random assignment of the points of change in phase is not possible. To obtain information about each possible data division, the authors carried out a conditional Monte Carlo simulation with 100,000 samples for each…