Huang, Yi-Shao; Liu, Wel-Ping; Wu, Min; Wang, Zheng-Wu
2014-09-01
This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations. Copyright © 2014. Published by Elsevier Ltd.
NASA Astrophysics Data System (ADS)
Azizi, S.; Torres, L. A. B.; Palhares, R. M.
2018-01-01
The regional robust stabilisation by means of linear time-invariant state feedback control for a class of uncertain MIMO nonlinear systems with parametric uncertainties and control input saturation is investigated. The nonlinear systems are described in a differential algebraic representation and the regional stability is handled considering the largest ellipsoidal domain-of-attraction (DOA) inside a given polytopic region in the state space. A novel set of sufficient Linear Matrix Inequality (LMI) conditions with new auxiliary decision variables are developed aiming to design less conservative linear state feedback controllers with corresponding larger DOAs, by considering the polytopic description of the saturated inputs. A few examples are presented showing favourable comparisons with recently published similar control design methodologies.
Command Filtering-Based Fuzzy Control for Nonlinear Systems With Saturation Input.
Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Lin, Chong
2017-09-01
In this paper, command filtering-based fuzzy control is designed for uncertain multi-input multioutput (MIMO) nonlinear systems with saturation nonlinearity input. First, the command filtering method is employed to deal with the explosion of complexity caused by the derivative of virtual controllers. Then, fuzzy logic systems are utilized to approximate the nonlinear functions of MIMO systems. Furthermore, error compensation mechanism is introduced to overcome the drawback of the dynamics surface approach. The developed method will guarantee all signals of the systems are bounded. The effectiveness and advantages of the theoretic result are obtained by a simulation example.
Ao, Wei; Song, Yongdong; Wen, Changyun
2017-05-01
In this paper, we investigate the adaptive control problem for a class of nonlinear uncertain MIMO systems with actuator faults and quantization effects. Under some mild conditions, an adaptive robust fault-tolerant control is developed to compensate the affects of uncertainties, actuator failures and errors caused by quantization, and a range of the parameters for these quantizers is established. Furthermore, a Lyapunov-like approach is adopted to demonstrate that the ultimately uniformly bounded output tracking error is guaranteed by the controller, and the signals of the closed-loop system are ensured to be bounded, even in the presence of at most m-q actuators stuck or outage. Finally, numerical simulations are provided to verify and illustrate the effectiveness of the proposed adaptive schemes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Finite time control for MIMO nonlinear system based on higher-order sliding mode.
Liu, Xiangjie; Han, Yaozhen
2014-11-01
Considering a class of MIMO uncertain nonlinear system, a novel finite time stable control algorithm is proposed based on higher-order sliding mode concept. The higher-order sliding mode control problem of MIMO nonlinear system is firstly transformed into finite time stability problem of multivariable system. Then continuous control law, which can guarantee finite time stabilization of nominal integral chain system, is employed. The second-order sliding mode is used to overcome the system uncertainties. High frequency chattering phenomenon of sliding mode is greatly weakened, and the arbitrarily fast convergence is reached. The finite time stability is proved based on the quadratic form Lyapunov function. Examples concerning the triple integral chain system with uncertainty and the hovercraft trajectory tracking are simulated respectively to verify the effectiveness and the robustness of the proposed algorithm. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Chen, Zhenfeng; Ge, Shuzhi Sam; Zhang, Yun; Li, Yanan
2014-11-01
This paper presents adaptive neural tracking control for a class of uncertain multiinput-multioutput (MIMO) nonlinear systems in block-triangular form. All subsystems within these MIMO nonlinear systems are of completely nonaffine pure-feedback form and allowed to have different orders. To deal with the nonaffine appearance of the control variables, the mean value theorem is employed to transform the systems into a block-triangular strict-feedback form with control coefficients being couplings among various inputs and outputs. A systematic procedure is proposed for the design of a new singularity-free adaptive neural tracking control strategy. Such a design procedure can remove the couplings among subsystems and hence avoids the possible circular control construction problem. As a consequence, all the signals in the closed-loop system are guaranteed to be semiglobally uniformly ultimately bounded. Moreover, the outputs of the systems are ensured to converge to a small neighborhood of the desired trajectories. Simulation studies verify the theoretical findings revealed in this paper.
Shi, Wuxi; Luo, Rui; Li, Baoquan
2017-01-01
In this study, an adaptive fuzzy prescribed performance control approach is developed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with unknown control direction and unknown dead-zone inputs. The properties of symmetric matrix are exploited to design adaptive fuzzy prescribed performance controller, and a Nussbaum-type function is incorporated in the controller to estimate the unknown control direction. This method has two prominent advantages: it does not require the priori knowledge of control direction and only three parameters need to be updated on-line for this MIMO systems. It is proved that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. The effectiveness of the proposed approach is validated by simulation results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Long, Lijun; Zhao, Jun
2017-07-01
In this paper, the problem of adaptive neural output-feedback control is addressed for a class of multi-input multioutput (MIMO) switched uncertain nonlinear systems with unknown control gains. Neural networks (NNs) are used to approximate unknown nonlinear functions. In order to avoid the conservativeness caused by adoption of a common observer for all subsystems, an MIMO NN switched observer is designed to estimate unmeasurable states. A new switched observer-based adaptive neural control technique for the problem studied is then provided by exploiting the classical average dwell time (ADT) method and the backstepping method and the Nussbaum gain technique. It effectively handles the obstacle about the coexistence of multiple Nussbaum-type function terms, and improves the classical ADT method, since the exponential decline property of Lyapunov functions for individual subsystems is no longer satisfied. It is shown that the technique proposed is able to guarantee semiglobal uniformly ultimately boundedness of all the signals in the closed-loop system under a class of switching signals with ADT, and the tracking errors converge to a small neighborhood of the origin. The effectiveness of the approach proposed is illustrated by its application to a two inverted pendulum system.
Adaptive sensor-fault tolerant control for a class of multivariable uncertain nonlinear systems.
Khebbache, Hicham; Tadjine, Mohamed; Labiod, Salim; Boulkroune, Abdesselem
2015-03-01
This paper deals with the active fault tolerant control (AFTC) problem for a class of multiple-input multiple-output (MIMO) uncertain nonlinear systems subject to sensor faults and external disturbances. The proposed AFTC method can tolerate three additive (bias, drift and loss of accuracy) and one multiplicative (loss of effectiveness) sensor faults. By employing backstepping technique, a novel adaptive backstepping-based AFTC scheme is developed using the fact that sensor faults and system uncertainties (including external disturbances and unexpected nonlinear functions caused by sensor faults) can be on-line estimated and compensated via robust adaptive schemes. The stability analysis of the closed-loop system is rigorously proven using a Lyapunov approach. The effectiveness of the proposed controller is illustrated by two simulation examples. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan
2017-11-01
A neural network (NN) adaptive control design problem is addressed for a class of uncertain multi-input-multi-output (MIMO) nonlinear systems in block-triangular form. The considered systems contain uncertainty dynamics and their states are enforced to subject to bounded constraints as well as the couplings among various inputs and outputs are inserted in each subsystem. To stabilize this class of systems, a novel adaptive control strategy is constructively framed by using the backstepping design technique and NNs. The novel integral barrier Lyapunov functionals (BLFs) are employed to overcome the violation of the full state constraints. The proposed strategy can not only guarantee the boundedness of the closed-loop system and the outputs are driven to follow the reference signals, but also can ensure all the states to remain in the predefined compact sets. Moreover, the transformed constraints on the errors are used in the previous BLF, and accordingly it is required to determine clearly the bounds of the virtual controllers. Thus, it can relax the conservative limitations in the traditional BLF-based controls for the full state constraints. This conservatism can be solved in this paper and it is for the first time to control this class of MIMO systems with the full state constraints. The performance of the proposed control strategy can be verified through a simulation example.
Analog nonlinear MIMO receiver for optical mode division multiplexing transmission.
Spalvieri, Arnaldo; Boffi, Pierpaolo; Pecorino, Simone; Barletta, Luca; Magarini, Maurizio; Gatto, Alberto; Martelli, Paolo; Martinelli, Mario
2013-10-21
The complexity and the power consumption of digital signal processing are crucial issues in optical transmission systems based on mode division multiplexing and coherent multiple-input multiple-output (MIMO) processing at the receiver. In this paper the inherent characteristic of spatial separation between fiber modes is exploited, getting a MIMO system where joint demultiplexing and detection is based on spatially separated photodetectors. After photodetection, one has a MIMO system with nonlinear crosstalk between modes. The paper shows that the nonlinear crosstalk can be dealt with by a low-complexity and non-adaptive detection scheme, at least in the cases presented in the paper.
Adaptive Neural Control of Uncertain MIMO Nonlinear Systems With State and Input Constraints.
Chen, Ziting; Li, Zhijun; Chen, C L Philip
2017-06-01
An adaptive neural control strategy for multiple input multiple output nonlinear systems with various constraints is presented in this paper. To deal with the nonsymmetric input nonlinearity and the constrained states, the proposed adaptive neural control is combined with the backstepping method, radial basis function neural network, barrier Lyapunov function (BLF), and disturbance observer. By ensuring the boundedness of the BLF of the closed-loop system, it is demonstrated that the output tracking is achieved with all states remaining in the constraint sets and the general assumption on nonsingularity of unknown control coefficient matrices has been eliminated. The constructed adaptive neural control has been rigorously proved that it can guarantee the semiglobally uniformly ultimate boundedness of all signals in the closed-loop system. Finally, the simulation studies on a 2-DOF robotic manipulator system indicate that the designed adaptive control is effective.
Neural network L1 adaptive control of MIMO systems with nonlinear uncertainty.
Zhen, Hong-tao; Qi, Xiao-hui; Li, Jie; Tian, Qing-min
2014-01-01
An indirect adaptive controller is developed for a class of multiple-input multiple-output (MIMO) nonlinear systems with unknown uncertainties. This control system is comprised of an L 1 adaptive controller and an auxiliary neural network (NN) compensation controller. The L 1 adaptive controller has guaranteed transient response in addition to stable tracking. In this architecture, a low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signals. The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. NN weights are tuned on-line with no prior training and the project operator ensures the weights bounded. The global stability of the closed-system is derived based on the Lyapunov function. Numerical simulations of an MIMO system coupled with nonlinear uncertainties are used to illustrate the practical potential of our theoretical results.
The relative degree enhancement problem for MIMO nonlinear systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schoenwald, D.A.; Oezguener, Ue.
1995-07-01
The authors present a result for linearizing a nonlinear MIMO system by employing partial feedback - feedback at all but one input-output channel such that the SISO feedback linearization problem is solvable at the remaining input-output channel. The partial feedback effectively enhances the relative degree at the open input-output channel provided the feedback functions are chosen to satisfy relative degree requirements. The method is useful for nonlinear systems that are not feedback linearizable in a MIMO sense. Several examples are presented to show how these feedback functions can be computed. This strategy can be combined with decentralized observers for amore » completely decentralized feedback linearization result for at least one input-output channel.« less
Adaptive Fuzzy Tracking Control for a Class of MIMO Nonlinear Systems in Nonstrict-Feedback Form.
Chen, Bing; Lin, Chong; Liu, Xiaoping; Liu, Kefu
2015-12-01
This paper focuses on the problem of fuzzy adaptive control for a class of multiinput and multioutput (MIMO) nonlinear systems in nonstrict-feedback form, which contains the strict-feedback form as a special case. By the condition of variable partition, a new fuzzy adaptive backstepping is proposed for such a class of nonlinear MIMO systems. The suggested fuzzy adaptive controller guarantees that the proposed control scheme can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking errors eventually converge to a small neighborhood around the origin. The main advantage of this paper is that a control approach is systematically derived for nonlinear systems with strong interconnected terms which are the functions of all states of the whole system. Simulation results further illustrate the effectiveness of the suggested approach.
Tracking and disturbance rejection of MIMO nonlinear systems with PI controller
NASA Technical Reports Server (NTRS)
Desoer, C. A.; Lin, C. A.
1985-01-01
The tracking and disturbance rejection of a class of MIMO nonlinear systems with a linear proportional plus integral (PI) compensator is studied. Roughly speaking, it is shown that if the given nonlinear plant is exponentially stable and has a strictly increasing dc steady-state I/O map, then a simple PI compensator can be used to yield a stable unity-feedback closed-loop system which asymptotically tracks reference inputs that tend to constant vectors and asymptotically rejects disturbances that tend to constant vectors.
Tracking and disturbance rejection of MIMO nonlinear systems with PI controller
NASA Technical Reports Server (NTRS)
Desoer, C. A.; Lin, C.-A.
1985-01-01
The tracking and disturbance rejection of a class of MIMO nonlinear systems with linear proportional plus integral (PI) compensator is studied. Roughly speaking, it is shown that if the given nonlinear plant is exponentially stable and has a strictly increasing dc steady-state I/O map, then a simple PI compensator can be used to yield a stable unity-feedback closed-loop system which asymptotically tracks reference inputs that tend to constant vectors and asymptotically rejects disturbances that tend to constant vectors.
Niu, Ben; Li, Lu
2018-06-01
This brief proposes a new neural-network (NN)-based adaptive output tracking control scheme for a class of disturbed multiple-input multiple-output uncertain nonlinear switched systems with input delays. By combining the universal approximation ability of radial basis function NNs and adaptive backstepping recursive design with an improved multiple Lyapunov function (MLF) scheme, a novel adaptive neural output tracking controller design method is presented for the switched system. The feature of the developed design is that different coordinate transformations are adopted to overcome the conservativeness caused by adopting a common coordinate transformation for all subsystems. It is shown that all the variables of the resulting closed-loop system are semiglobally uniformly ultimately bounded under a class of switching signals in the presence of MLF and that the system output can follow the desired reference signal. To demonstrate the practicability of the obtained result, an adaptive neural output tracking controller is designed for a mass-spring-damper system.
Linear precoding based on polynomial expansion: reducing complexity in massive MIMO.
Mueller, Axel; Kammoun, Abla; Björnson, Emil; Debbah, Mérouane
Massive multiple-input multiple-output (MIMO) techniques have the potential to bring tremendous improvements in spectral efficiency to future communication systems. Counterintuitively, the practical issues of having uncertain channel knowledge, high propagation losses, and implementing optimal non-linear precoding are solved more or less automatically by enlarging system dimensions. However, the computational precoding complexity grows with the system dimensions. For example, the close-to-optimal and relatively "antenna-efficient" regularized zero-forcing (RZF) precoding is very complicated to implement in practice, since it requires fast inversions of large matrices in every coherence period. Motivated by the high performance of RZF, we propose to replace the matrix inversion and multiplication by a truncated polynomial expansion (TPE), thereby obtaining the new TPE precoding scheme which is more suitable for real-time hardware implementation and significantly reduces the delay to the first transmitted symbol. The degree of the matrix polynomial can be adapted to the available hardware resources and enables smooth transition between simple maximum ratio transmission and more advanced RZF. By deriving new random matrix results, we obtain a deterministic expression for the asymptotic signal-to-interference-and-noise ratio (SINR) achieved by TPE precoding in massive MIMO systems. Furthermore, we provide a closed-form expression for the polynomial coefficients that maximizes this SINR. To maintain a fixed per-user rate loss as compared to RZF, the polynomial degree does not need to scale with the system, but it should be increased with the quality of the channel knowledge and the signal-to-noise ratio.
NASA Astrophysics Data System (ADS)
Gregorio, Fernando; Cousseau, Juan; Werner, Stefan; Riihonen, Taneli; Wichman, Risto
2011-12-01
The design of predistortion techniques for broadband multiple input multiple output-OFDM (MIMO-OFDM) systems raises several implementation challenges. First, the large bandwidth of the OFDM signal requires the introduction of memory effects in the PD model. In addition, it is usual to consider an imbalanced in-phase and quadrature (IQ) modulator to translate the predistorted baseband signal to RF. Furthermore, the coupling effects, which occur when the MIMO paths are implemented in the same reduced size chipset, cannot be avoided in MIMO transceivers structures. This study proposes a MIMO-PD system that linearizes the power amplifier response and compensates nonlinear crosstalk and IQ imbalance effects for each branch of the multiantenna system. Efficient recursive algorithms are presented to estimate the complete MIMO-PD coefficients. The algorithms avoid the high computational complexity in previous solutions based on least squares estimation. The performance of the proposed MIMO-PD structure is validated by simulations using a two-transmitter antenna MIMO system. Error vector magnitude and adjacent channel power ratio are evaluated showing significant improvement compared with conventional MIMO-PD systems.
Hampson, Robert E.; Song, Dong; Chan, Rosa H.M.; Sweatt, Andrew J.; Riley, Mitchell R.; Gerhardt, Gregory A.; Shin, Dae C.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Samuel A.
2012-01-01
Collaborative investigations have characterized how multineuron hippocampal ensembles encode memory necessary for subsequent successful performance by rodents in a delayed nonmatch to sample (DNMS) task and utilized that information to provide the basis for a memory prosthesis to enhance performance. By employing a unique nonlinear dynamic multi-input/multi-output (MIMO) model, developed and adapted to hippocampal neural ensemble firing patterns derived from simultaneous recorded CA1 and CA3 activity, it was possible to extract information encoded in the sample phase necessary for successful performance in the nonmatch phase of the task. The extension of this MIMO model to online delivery of electrical stimulation delivered to the same recording loci that mimicked successful CA1 firing patterns, provided the means to increase levels of performance on a trial-by-trial basis. Inclusion of several control procedures provides evidence for the specificity of effective MIMO model generated patterns of electrical stimulation. Increased utility of the MIMO model as a prosthesis device was exhibited by the demonstration of cumulative increases in DNMS task performance with repeated MIMO stimulation over many sessions on both stimulation and nonstimulation trials, suggesting overall system modification with continued exposure. Results reported here are compatible with and extend prior demonstrations and further support the candidacy of the MIMO model as an effective cortical prosthesis. PMID:22438334
Pandey, Vinay Kumar; Kar, Indrani; Mahanta, Chitralekha
2017-07-01
In this paper, an adaptive control method using multiple models with second level adaptation is proposed for a class of nonlinear multi-input multi-output (MIMO) coupled systems. Multiple estimation models are used to tune the unknown parameters at the first level. The second level adaptation provides a single parameter vector for the controller. A feedback linearization technique is used to design a state feedback control. The efficacy of the designed controller is validated by conducting real time experiment on a laboratory setup of twin rotor MIMO system (TRMS). The TRMS setup is discussed in detail and the experiments were performed for regulation and tracking problem for pitch and yaw control using different reference signals. An Extended Kalman Filter (EKF) has been used to observe the unavailable states of the TRMS. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Lin, Chun-Ting; Ho, Chun-Hung; Huang, Hou-Tzu; Cheng, Yu-Hsuan
2014-03-15
This article proposes and experimentally demonstrates a radio-over-fiber system employing single-sideband single-carrier (SSB-SC) modulation at 60 GHz. SSB-SC modulation has a lower peak-to-average-power ratio than orthogonal frequency division multiplex (OFDM) modulation; therefore, the SSB-SC signals provide superior nonlinear tolerance, compared to OFDM signals. Moreover, multiple-input multiple-output (MIMO) technology was used extensively to enhance spectral efficiency. A least-mean-square-based equalizer was implemented, including MIMO channel estimation, frequency response equalization, and I/Q imbalance compensation to recover the MIMO signals. Thus, using 2×2 MIMO technology and 64-QAM SSB-SC signals, we achieved the highest data rate of 84 Gbps with 12 bit/s/Hz spectral efficiency using the 7-GHz license-free band at 60 GHz.
Lin, Chi-Hsiang; Lin, Chun-Ting; Huang, Hou-Tzu; Zeng, Wei-Siang; Chiang, Shou-Chih; Chang, Hsi-Yu
2015-05-04
This paper proposes a 2x2 MIMO OFDM Radio-over-Fiber scheme based on optical subcarrier multiplexing and 60-GHz MIMO wireless transmission. We also schematically investigated the principle of optical subcarrier multiplexing, which is based on a dual-parallel Mach-Zehnder modulator (DP-MZM). In our simulation result, combining two MIMO OFDM signals to drive DP-MZM gives rise to the PAPR augmentation of less than 0.4 dB, which mitigates nonlinear distortion. Moreover, we applied a Levin-Campello bit-loading algorithm to compensate for the uneven frequency responses in the V-band. The resulting system achieves OFDM signal rates of 61.5-Gbits/s with BER of 10(-3) over 25-km SMF transmission followed by 3-m wireless transmission.
Neural dynamic programming and its application to control systems
NASA Astrophysics Data System (ADS)
Seong, Chang-Yun
There are few general practical feedback control methods for nonlinear MIMO (multi-input-multi-output) systems, although such methods exist for their linear counterparts. Neural Dynamic Programming (NDP) is proposed as a practical design method of optimal feedback controllers for nonlinear MIMO systems. NDP is an offspring of both neural networks and optimal control theory. In optimal control theory, the optimal solution to any nonlinear MIMO control problem may be obtained from the Hamilton-Jacobi-Bellman equation (HJB) or the Euler-Lagrange equations (EL). The two sets of equations provide the same solution in different forms: EL leads to a sequence of optimal control vectors, called Feedforward Optimal Control (FOC); HJB yields a nonlinear optimal feedback controller, called Dynamic Programming (DP). DP produces an optimal solution that can reject disturbances and uncertainties as a result of feedback. Unfortunately, computation and storage requirements associated with DP solutions can be problematic, especially for high-order nonlinear systems. This dissertation presents an approximate technique for solving the DP problem based on neural network techniques that provides many of the performance benefits (e.g., optimality and feedback) of DP and benefits from the numerical properties of neural networks. We formulate neural networks to approximate optimal feedback solutions whose existence DP justifies. We show the conditions under which NDP closely approximates the optimal solution. Finally, we introduce the learning operator characterizing the learning process of the neural network in searching the optimal solution. The analysis of the learning operator provides not only a fundamental understanding of the learning process in neural networks but also useful guidelines for selecting the number of weights of the neural network. As a result, NDP finds---with a reasonable amount of computation and storage---the optimal feedback solutions to nonlinear MIMO control problems that would be very difficult to solve with DP. NDP was demonstrated on several applications such as the lateral autopilot logic for a Boeing 747, the minimum fuel control of a double-integrator plant with bounded control, the backward steering of a two-trailer truck, and the set-point control of a two-link robot arm.
Robust Decentralized Nonlinear Control for a Twin Rotor MIMO System
Belmonte, Lidia María; Morales, Rafael; Fernández-Caballero, Antonio; Somolinos, José Andrés
2016-01-01
This article presents the design of a novel decentralized nonlinear multivariate control scheme for an underactuated, nonlinear and multivariate laboratory helicopter denominated the twin rotor MIMO system (TRMS). The TRMS is characterized by a coupling effect between rotor dynamics and the body of the model, which is due to the action-reaction principle originated in the acceleration and deceleration of the motor-propeller groups. The proposed controller is composed of two nested loops that are utilized to achieve stabilization and precise trajectory tracking tasks for the controlled position of the generalized coordinates of the TRMS. The nonlinear internal loop is used to control the electrical dynamics of the platform, and the nonlinear external loop allows the platform to be perfectly stabilized and positioned in space. Finally, we illustrate the theoretical control developments with a set of experiments in order to verify the effectiveness of the proposed nonlinear decentralized feedback controller, in which a comparative study with other controllers is performed, illustrating the excellent performance of the proposed robust decentralized control scheme in both stabilization and trajectory tracking tasks. PMID:27472338
Robust Decentralized Nonlinear Control for a Twin Rotor MIMO System.
Belmonte, Lidia María; Morales, Rafael; Fernández-Caballero, Antonio; Somolinos, José Andrés
2016-07-27
This article presents the design of a novel decentralized nonlinear multivariate control scheme for an underactuated, nonlinear and multivariate laboratory helicopter denominated the twin rotor MIMO system (TRMS). The TRMS is characterized by a coupling effect between rotor dynamics and the body of the model, which is due to the action-reaction principle originated in the acceleration and deceleration of the motor-propeller groups. The proposed controller is composed of two nested loops that are utilized to achieve stabilization and precise trajectory tracking tasks for the controlled position of the generalized coordinates of the TRMS. The nonlinear internal loop is used to control the electrical dynamics of the platform, and the nonlinear external loop allows the platform to be perfectly stabilized and positioned in space. Finally, we illustrate the theoretical control developments with a set of experiments in order to verify the effectiveness of the proposed nonlinear decentralized feedback controller, in which a comparative study with other controllers is performed, illustrating the excellent performance of the proposed robust decentralized control scheme in both stabilization and trajectory tracking tasks.
MIMO nonlinear ultrasonic tomography by propagation and backpropagation method.
Dong, Chengdong; Jin, Yuanwei
2013-03-01
This paper develops a fast ultrasonic tomographic imaging method in a multiple-input multiple-output (MIMO) configuration using the propagation and backpropagation (PBP) method. By this method, ultrasonic excitation signals from multiple sources are transmitted simultaneously to probe the objects immersed in the medium. The scattering signals are recorded by multiple receivers. Utilizing the nonlinear ultrasonic wave propagation equation and the received time domain scattered signals, the objects are to be reconstructed iteratively in three steps. First, the propagation step calculates the predicted acoustic potential data at the receivers using an initial guess. Second, the difference signal between the predicted value and the measured data is calculated. Third, the backpropagation step computes updated acoustical potential data by backpropagating the difference signal to the same medium computationally. Unlike the conventional PBP method for tomographic imaging where each source takes turns to excite the acoustical field until all the sources are used, the developed MIMO-PBP method achieves faster image reconstruction by utilizing multiple source simultaneous excitation. Furthermore, we develop an orthogonal waveform signaling method using a waveform delay scheme to reduce the impact of speckle patterns in the reconstructed images. By numerical experiments we demonstrate that the proposed MIMO-PBP tomographic imaging method results in faster convergence and achieves superior imaging quality.
NASA Astrophysics Data System (ADS)
Luy, N. T.
2018-04-01
The design of distributed cooperative H∞ optimal controllers for multi-agent systems is a major challenge when the agents' models are uncertain multi-input and multi-output nonlinear systems in strict-feedback form in the presence of external disturbances. In this paper, first, the distributed cooperative H∞ optimal tracking problem is transformed into controlling the cooperative tracking error dynamics in affine form. Second, control schemes and online algorithms are proposed via adaptive dynamic programming (ADP) and the theory of zero-sum differential graphical games. The schemes use only one neural network (NN) for each agent instead of three from ADP to reduce computational complexity as well as avoid choosing initial NN weights for stabilising controllers. It is shown that despite not using knowledge of cooperative internal dynamics, the proposed algorithms not only approximate values to Nash equilibrium but also guarantee all signals, such as the NN weight approximation errors and the cooperative tracking errors in the closed-loop system, to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is shown by simulation results of an application to wheeled mobile multi-robot systems.
Statistical linearization for multi-input/multi-output nonlinearities
NASA Technical Reports Server (NTRS)
Lin, Ching-An; Cheng, Victor H. L.
1991-01-01
Formulas are derived for the computation of the random input-describing functions for MIMO nonlinearities; these straightforward and rigorous derivations are based on the optimal mean square linear approximation. The computations involve evaluations of multiple integrals. It is shown that, for certain classes of nonlinearities, multiple-integral evaluations are obviated and the computations are significantly simplified.
Hampson, Robert E.; Song, Dong; Chan, Rosa H.M.; Sweatt, Andrew J.; Riley, Mitchell R.; Goonawardena, Anushka V.; Marmarelis, Vasilis Z.; Gerhardt, Greg A.; Berger, Theodore W.; Deadwyler, Sam A.
2012-01-01
A major factor involved in providing closed loop feedback for control of neural function is to understand how neural ensembles encode online information critical to the final behavioral endpoint. This issue was directly assessed in rats performing a short-term delay memory task in which successful encoding of task information is dependent upon specific spatiotemporal firing patterns recorded from ensembles of CA3 and CA1 hippocampal neurons. Such patterns, extracted by a specially designed nonlinear multi-input multi-output (MIMO) nonlinear mathematical model, were used to predict successful performance online via a closed loop paradigm which regulated trial difficulty (time of retention) as a function of the “strength” of stimulus encoding. The significance of the MIMO model as a neural prosthesis has been demonstrated by substituting trains of electrical stimulation pulses to mimic these same ensemble firing patterns. This feature was used repeatedly to vary “normal” encoding as a means of understanding how neural ensembles can be “tuned” to mimic the inherent process of selecting codes of different strength and functional specificity. The capacity to enhance and tune hippocampal encoding via MIMO model detection and insertion of critical ensemble firing patterns shown here provides the basis for possible extension to other disrupted brain circuitry. PMID:22498704
Experimental comparison of conventional and nonlinear model-based control of a mixing tank
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haeggblom, K.E.
1993-11-01
In this case study concerning control of a laboratory-scale mixing tank, conventional multiloop single-input single-output (SISO) control is compared with model-based'' control where the nonlinearity and multivariable characteristics of the process are explicitly taken into account. It is shown, especially if the operating range of the process is large, that the two outputs (level and temperature) cannot be adequately controlled by multiloop SISO control even if gain scheduling is used. By nonlinear multiple-input multiple-output (MIMO) control, on the other hand, very good control performance is obtained. The basic approach to nonlinear control used in this study is first to transformmore » the process into a globally linear and decoupled system, and then to design controllers for this system. Because of the properties of the resulting MIMO system, the controller design is very easy. Two nonlinear control system designs based on a steady-state and a dynamic model, respectively, are considered. In the dynamic case, both setpoint tracking and disturbance rejection can be addressed separately.« less
Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam
2014-07-01
This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Berger, Theodore W.; Song, Dong; Chan, Rosa H. M.; Marmarelis, Vasilis Z.; LaCoss, Jeff; Wills, Jack; Hampson, Robert E.; Deadwyler, Sam A.; Granacki, John J.
2012-01-01
This paper describes the development of a cognitive prosthesis designed to restore the ability to form new long-term memories typically lost after damage to the hippocampus. The animal model used is delayed nonmatch-to-sample (DNMS) behavior in the rat, and the “core” of the prosthesis is a biomimetic multi-input/multi-output (MIMO) nonlinear model that provides the capability for predicting spatio-temporal spike train output of hippocampus (CA1) based on spatio-temporal spike train inputs recorded presynaptically to CA1 (e.g., CA3). We demonstrate the capability of the MIMO model for highly accurate predictions of CA1 coded memories that can be made on a single-trial basis and in real-time. When hippocampal CA1 function is blocked and long-term memory formation is lost, successful DNMS behavior also is abolished. However, when MIMO model predictions are used to reinstate CA1 memory-related activity by driving spatio-temporal electrical stimulation of hippocampal output to mimic the patterns of activity observed in control conditions, successful DNMS behavior is restored. We also outline the design in very-large-scale integration for a hardware implementation of a 16-input, 16-output MIMO model, along with spike sorting, amplification, and other functions necessary for a total system, when coupled together with electrode arrays to record extracellularly from populations of hippocampal neurons, that can serve as a cognitive prosthesis in behaving animals. PMID:22438335
Adaptive NN controller design for a class of nonlinear MIMO discrete-time systems.
Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip
2015-05-01
An adaptive neural network tracking control is studied for a class of multiple-input multiple-output (MIMO) nonlinear systems. The studied systems are in discrete-time form and the discretized dead-zone inputs are considered. In addition, the studied MIMO systems are composed of N subsystems, and each subsystem contains unknown functions and external disturbance. Due to the complicated framework of the discrete-time systems, the existence of the dead zone and the noncausal problem in discrete-time, it brings about difficulties for controlling such a class of systems. To overcome the noncausal problem, by defining the coordinate transformations, the studied systems are transformed into a special form, which is suitable for the backstepping design. The radial basis functions NNs are utilized to approximate the unknown functions of the systems. The adaptation laws and the controllers are designed based on the transformed systems. By using the Lyapunov method, it is proved that the closed-loop system is stable in the sense that the semiglobally uniformly ultimately bounded of all the signals and the tracking errors converge to a bounded compact set. The simulation examples and the comparisons with previous approaches are provided to illustrate the effectiveness of the proposed control algorithm.
Multivariable control of vapor compression systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
He, X.D.; Liu, S.; Asada, H.H.
1999-07-01
This paper presents the results of a study of multi-input multi-output (MIMO) control of vapor compression cycles that have multiple actuators and sensors for regulating multiple outputs, e.g., superheat and evaporating temperature. The conventional single-input single-output (SISO) control was shown to have very limited performance. A low order lumped-parameter model was developed to describe the significant dynamics of vapor compression cycles. Dynamic modes were analyzed based on the low order model to provide physical insight of system dynamic behavior. To synthesize a MIMO control system, the Linear-Quadratic Gaussian (LQG) technique was applied to coordinate compressor speed and expansion valve openingmore » with guaranteed stability robustness in the design. Furthermore, to control a vapor compression cycle over a wide range of operating conditions where system nonlinearities become evident, a gain scheduling scheme was used so that the MIMO controller could adapt to changing operating conditions. Both analytical studies and experimental tests showed that the MIMO control could significantly improve the transient behavior of vapor compression cycles compared to the conventional SISO control scheme. The MIMO control proposed in this paper could be extended to the control of vapor compression cycles in a variety of HVAC and refrigeration applications to improve system performance and energy efficiency.« less
Bounemeur, Abdelhamid; Chemachema, Mohamed; Essounbouli, Najib
2018-05-10
In this paper, an active fuzzy fault tolerant tracking control (AFFTTC) scheme is developed for a class of multi-input multi-output (MIMO) unknown nonlinear systems in the presence of unknown actuator faults, sensor failures and external disturbance. The developed control scheme deals with four kinds of faults for both sensors and actuators. The bias, drift, and loss of accuracy additive faults are considered along with the loss of effectiveness multiplicative fault. A fuzzy adaptive controller based on back-stepping design is developed to deal with actuator failures and unknown system dynamics. However, an additional robust control term is added to deal with sensor faults, approximation errors, and external disturbances. Lyapunov theory is used to prove the stability of the closed loop system. Numerical simulations on a quadrotor are presented to show the effectiveness of the proposed approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Feedback linearizing control of a MIMO power system
NASA Astrophysics Data System (ADS)
Ilyes, Laszlo
Prior research has demonstrated that either the mechanical or electrical subsystem of a synchronous electric generator may be controlled using single-input single-output (SISO) nonlinear feedback linearization. This research suggests a new approach which applies nonlinear feedback linearization to a multi-input multi-output (MIMO) model of the synchronous electric generator connected to an infinite bus load model. In this way, the electrical and mechanical subsystems may be linearized and simultaneously decoupled through the introduction of a pair of auxiliary inputs. This allows well known, linear, SISO control methods to be effectively applied to the resulting systems. The derivation of the feedback linearizing control law is presented in detail, including a discussion on the use of symbolic math processing as a development tool. The linearizing and decoupling properties of the control law are validated through simulation. And finally, the robustness of the control law is demonstrated.
Application of fuzzy adaptive control to a MIMO nonlinear time-delay pump-valve system.
Lai, Zhounian; Wu, Peng; Wu, Dazhuan
2015-07-01
In this paper, a control strategy to balance the reliability against efficiency is introduced to overcome the common off-design operation problem in pump-valve systems. The pump-valve system is a nonlinear multi-input-multi-output (MIMO) system with time delays which cannot be accurately measured but can be approximately modeled using Bernoulli Principle. A fuzzy adaptive controller is applied to approximate system parameters and achieve the control of delay-free model since the system model is inaccurate and the direct feedback linearization method cannot be applied. An extended Smith predictor is introduced to compensate time delays of the system using the inaccurate system model. The experiment is carried out to verify the effectiveness of the control strategy whose results show that the control performance is well achieved. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Gouta, Houssemeddine; Hadj Saïd, Salim; Barhoumi, Nabil; M'Sahli, Faouzi
2017-03-01
This paper deals with the problem of the observer based control design for a coupled four-tank liquid level system. For this MIMO system's dynamics, motivated by a desire to provide precise and sensorless liquid level control, a nonlinear predictive controller based on a continuous-discrete observer is presented. First, an analytical solution from the model predictive control (MPC) technique is developed for a particular class of nonlinear MIMO systems and its corresponding exponential stability is proven. Then, a high gain observer that runs in continuous-time with an output error correction time that is updated in a mixed continuous-discrete fashion is designed in order to estimate the liquid levels in the two upper tanks. The effectiveness of the designed control schemes are validated by two tests; The first one is maintaining a constant level in the first bottom tank while making the level in the second bottom tank to follow a sinusoidal reference signal. The second test is more difficult and it is made using two trapezoidal reference signals in order to see the decoupling performance of the system's outputs. Simulation and experimental results validate the objective of the paper. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Shieh, W; Yi, X; Ma, Y; Tang, Y
2007-08-06
In this paper, we conduct theoretical and experimental study on the PMD-supported transmission with coherent optical orthogonal frequency-division multiplexing (CO-OFDM). We first present the model for the optical fiber communication channel in the presence of the polarization effects. It shows that the optical fiber channel model can be treated as a special kind of multiple-input multiple-output (MIMO) model, namely, a two-input two-output (TITO) model which is intrinsically represented by a two-element Jones vector familiar to the optical communications community. The detailed discussions on various coherent optical MIMO-OFDM (CO-MIMO-OFDM) models are presented. Furthermore, we show the first experiment of polarization-diversity detection in CO-OFDM systems. In particular, a CO-OFDM signal at 10.7 Gb/s is successfully recovered after 900 ps differential-group-delay (DGD) and 1000-km transmission through SSMF fiber without optical dispersion compensation. The transmission experiment with higher-order PMD further confirms the immunity of the CO-OFDM signal to PMD in the transmission fiber. The nonlinearity performance of PMD-supported transmission is also reported. For the first time, nonlinear phase noise mitigation based on receiver digital signal processing is experimentally demonstrated for CO-OFDM transmission.
A support vector machine based control application to the experimental three-tank system.
Iplikci, Serdar
2010-07-01
This paper presents a support vector machine (SVM) approach to generalized predictive control (GPC) of multiple-input multiple-output (MIMO) nonlinear systems. The possession of higher generalization potential and at the same time avoidance of getting stuck into the local minima have motivated us to employ SVM algorithms for modeling MIMO systems. Based on the SVM model, detailed and compact formulations for calculating predictions and gradient information, which are used in the computation of the optimal control action, are given in the paper. The proposed MIMO SVM-based GPC method has been verified on an experimental three-tank liquid level control system. Experimental results have shown that the proposed method can handle the control task successfully for different reference trajectories. Moreover, a detailed discussion on data gathering, model selection and effects of the control parameters have been given in this paper. 2010 ISA. Published by Elsevier Ltd. All rights reserved.
Design And Implementation Of PID Controller Using Relay Feedback On TRMS (Twin Rotor MIMO System)
NASA Astrophysics Data System (ADS)
Shah, Dipesh H.
2011-12-01
Today, many process control problems can be adequately and routinely solved by conventional PID control strategies. The overriding reason that the PID controller is so widely accepted is its simple structure which has proved to be very robust with regard to many commonly met process control problems as for instance disturbances and nonlinearities. Relay feedback methods have been widely used in tuning proportional-integral-derivative controllers due to its closed loop nature. In this work, Relay based PID controller is designed and successfully implemented on TRMS (Twin Rotor MIMO System) in SISO and MIMO configurations. The performance of a Relay based PID controller for control of TRMS is investigated and performed satisfactorily. The system shares some features with a helicopter, such as important interactions between the vertical and horizontal motions. The RTWT toolbox in the MATLAB environment is used to perform real-time experiments.
Salgado, Iván; Mera-Hernández, Manuel; Chairez, Isaac
2017-11-01
This study addresses the problem of designing an output-based controller to stabilize multi-input multi-output (MIMO) systems in the presence of parametric disturbances as well as uncertainties in the state model and output noise measurements. The controller design includes a linear state transformation which separates uncertainties matched to the control input and the unmatched ones. A differential neural network (DNN) observer produces a nonlinear approximation of the matched perturbation and the unknown states simultaneously in the transformed coordinates. This study proposes the use of the Attractive Ellipsoid Method (AEM) to optimize the gains of the controller and the gain observer in the DNN structure. As a consequence, the obtained control input minimizes the convergence zone for the estimation error. Moreover, the control design uses the estimated disturbance provided by the DNN to obtain a better performance in the stabilization task in comparison with a quasi-minimal output feedback controller based on a Luenberger observer and a sliding mode controller. Numerical results pointed out the advantages obtained by the nonlinear control based on the DNN observer. The first example deals with the stabilization of an academic linear MIMO perturbed system and the second example stabilizes the trajectories of a DC-motor into a predefined operation point. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Development of model reference adaptive control theory for electric power plant control applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mabius, L.E.
1982-09-15
The scope of this effort includes the theoretical development of a multi-input, multi-output (MIMO) Model Reference Control (MRC) algorithm, (i.e., model following control law), Model Reference Adaptive Control (MRAC) algorithm and the formulation of a nonlinear model of a typical electric power plant. Previous single-input, single-output MRAC algorithm designs have been generalized to MIMO MRAC designs using the MIMO MRC algorithm. This MRC algorithm, which has been developed using Command Generator Tracker methodologies, represents the steady state behavior (in the adaptive sense) of the MRAC algorithm. The MRC algorithm is a fundamental component in the MRAC design and stability analysis.more » An enhanced MRC algorithm, which has been developed for systems with more controls than regulated outputs, alleviates the MRC stability constraint of stable plant transmission zeroes. The nonlinear power plant model is based on the Cromby model with the addition of a governor valve management algorithm, turbine dynamics and turbine interactions with extraction flows. An application of the MRC algorithm to a linearization of this model demonstrates its applicability to power plant systems. In particular, the generated power changes at 7% per minute while throttle pressure and temperature, reheat temperature and drum level are held constant with a reasonable level of control. The enhanced algorithm reduces significantly control fluctuations without modifying the output response.« less
Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan
2015-01-01
Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.
Coelho, Antonio Augusto Rodrigues
2016-01-01
This paper introduces the Fuzzy Logic Hypercube Interpolator (FLHI) and demonstrates applications in control of multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) processes with Hammerstein nonlinearities. FLHI consists of a Takagi-Sugeno fuzzy inference system where membership functions act as kernel functions of an interpolator. Conjunction of membership functions in an unitary hypercube space enables multivariable interpolation of N-dimensions. Membership functions act as interpolation kernels, such that choice of membership functions determines interpolation characteristics, allowing FLHI to behave as a nearest-neighbor, linear, cubic, spline or Lanczos interpolator, to name a few. The proposed interpolator is presented as a solution to the modeling problem of static nonlinearities since it is capable of modeling both a function and its inverse function. Three study cases from literature are presented, a single-input single-output (SISO) system, a MISO and a MIMO system. Good results are obtained regarding performance metrics such as set-point tracking, control variation and robustness. Results demonstrate applicability of the proposed method in modeling Hammerstein nonlinearities and their inverse functions for implementation of an output compensator with Model Based Predictive Control (MBPC), in particular Dynamic Matrix Control (DMC). PMID:27657723
NASA Astrophysics Data System (ADS)
Wang, Hongyan
2017-04-01
This paper addresses the waveform optimization problem for improving the detection performance of multi-input multioutput (MIMO) orthogonal frequency division multiplexing (OFDM) radar-based space-time adaptive processing (STAP) in the complex environment. By maximizing the output signal-to-interference-and-noise-ratio (SINR) criterion, the waveform optimization problem for improving the detection performance of STAP, which is subjected to the constant modulus constraint, is derived. To tackle the resultant nonlinear and complicated optimization issue, a diagonal loading-based method is proposed to reformulate the issue as a semidefinite programming one; thereby, this problem can be solved very efficiently. In what follows, the optimized waveform can be obtained to maximize the output SINR of MIMO-OFDM such that the detection performance of STAP can be improved. The simulation results show that the proposed method can improve the output SINR detection performance considerably as compared with that of uncorrelated waveforms and the existing MIMO-based STAP method.
Zhang, Shu; Taft, Cyrus W; Bentsman, Joseph; Hussey, Aaron; Petrus, Bryan
2012-09-01
Tuning a complex multi-loop PID based control system requires considerable experience. In today's power industry the number of available qualified tuners is dwindling and there is a great need for better tuning tools to maintain and improve the performance of complex multivariable processes. Multi-loop PID tuning is the procedure for the online tuning of a cluster of PID controllers operating in a closed loop with a multivariable process. This paper presents the first application of the simultaneous tuning technique to the multi-input-multi-output (MIMO) PID based nonlinear controller in the power plant control context, with the closed-loop system consisting of a MIMO nonlinear boiler/turbine model and a nonlinear cluster of six PID-type controllers. Although simplified, the dynamics and cross-coupling of the process and the PID cluster are similar to those used in a real power plant. The particular technique selected, iterative feedback tuning (IFT), utilizes the linearized version of the PID cluster for signal conditioning, but the data collection and tuning is carried out on the full nonlinear closed-loop system. Based on the figure of merit for the control system performance, the IFT is shown to deliver performance favorably comparable to that attained through the empirical tuning carried out by an experienced control engineer. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.
2013-04-22
Following for Unmanned Aerial Vehicles Using L1 Adaptive Augmentation of Commercial Autopilots, Journal of Guidance, Control, and Dynamics, (3 2010): 0...Naira Hovakimyan. L1 Adaptive Controller for MIMO system with Unmatched Uncertainties using Modi?ed Piecewise Constant Adaptation Law, IEEE 51st...adaptive input nominal input with Nominal input L1 ‐based control generator This L1 adaptive control architecture uses data from the reference model
Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian
2011-04-01
This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.
A novel optimization algorithm for MIMO Hammerstein model identification under heavy-tailed noise.
Jin, Qibing; Wang, Hehe; Su, Qixin; Jiang, Beiyan; Liu, Qie
2018-01-01
In this paper, we study the system identification of multi-input multi-output (MIMO) Hammerstein processes under the typical heavy-tailed noise. To the best of our knowledge, there is no general analytical method to solve this identification problem. Motivated by this, we propose a general identification method to solve this problem based on a Gaussian-Mixture Distribution intelligent optimization algorithm (GMDA). The nonlinear part of Hammerstein process is modeled by a Radial Basis Function (RBF) neural network, and the identification problem is converted to an optimization problem. To overcome the drawbacks of analytical identification method in the presence of heavy-tailed noise, a meta-heuristic optimization algorithm, Cuckoo search (CS) algorithm is used. To improve its performance for this identification problem, the Gaussian-mixture Distribution (GMD) and the GMD sequences are introduced to improve the performance of the standard CS algorithm. Numerical simulations for different MIMO Hammerstein models are carried out, and the simulation results verify the effectiveness of the proposed GMDA. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain.
Barba, Lida; Rodríguez, Nibaldo
2017-01-01
Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT.
A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain
Rodríguez, Nibaldo
2017-01-01
Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT. PMID:28261267
Bagherpoor, H M; Salmasi, Farzad R
2015-07-01
In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Nemirsky, Kristofer Kevin
In this thesis, the history and evolution of rotor aircraft with simulated annealing-based PID application were reviewed and quadcopter dynamics are presented. The dynamics of a quadcopter were then modeled, analyzed, and linearized. A cascaded loop architecture with PID controllers was used to stabilize the plant dynamics, which was improved upon through the application of simulated annealing (SA). A Simulink model was developed to test the controllers and verify the functionality of the proposed control system design. In addition, the data that the Simulink model provided were compared with flight data to present the validity of derived dynamics as a proper mathematical model representing the true dynamics of the quadcopter system. Then, the SA-based global optimization procedure was applied to obtain optimized PID parameters. It was observed that the tuned gains through the SA algorithm produced a better performing PID controller than the original manually tuned one. Next, we investigated the uncertain dynamics of the quadcopter setup. After adding uncertainty to the gyroscopic effects associated with pitch-and-roll rate dynamics, the controllers were shown to be robust against the added uncertainty. A discussion follows to summarize SA-based algorithm PID controller design and performance outcomes. Lastly, future work on SA application on multi-input-multi-output (MIMO) systems is briefly discussed.
A cortical neural prosthesis for restoring and enhancing memory
NASA Astrophysics Data System (ADS)
Berger, Theodore W.; Hampson, Robert E.; Song, Dong; Goonawardena, Anushka; Marmarelis, Vasilis Z.; Deadwyler, Sam A.
2011-08-01
A primary objective in developing a neural prosthesis is to replace neural circuitry in the brain that no longer functions appropriately. Such a goal requires artificial reconstruction of neuron-to-neuron connections in a way that can be recognized by the remaining normal circuitry, and that promotes appropriate interaction. In this study, the application of a specially designed neural prosthesis using a multi-input/multi-output (MIMO) nonlinear model is demonstrated by using trains of electrical stimulation pulses to substitute for MIMO model derived ensemble firing patterns. Ensembles of CA3 and CA1 hippocampal neurons, recorded from rats performing a delayed-nonmatch-to-sample (DNMS) memory task, exhibited successful encoding of trial-specific sample lever information in the form of different spatiotemporal firing patterns. MIMO patterns, identified online and in real-time, were employed within a closed-loop behavioral paradigm. Results showed that the model was able to predict successful performance on the same trial. Also, MIMO model-derived patterns, delivered as electrical stimulation to the same electrodes, improved performance under normal testing conditions and, more importantly, were capable of recovering performance when delivered to animals with ensemble hippocampal activity compromised by pharmacologic blockade of synaptic transmission. These integrated experimental-modeling studies show for the first time that, with sufficient information about the neural coding of memories, a neural prosthesis capable of real-time diagnosis and manipulation of the encoding process can restore and even enhance cognitive, mnemonic processes.
Terminal sliding mode tracking control for a class of SISO uncertain nonlinear systems.
Chen, Mou; Wu, Qing-Xian; Cui, Rong-Xin
2013-03-01
In this paper, the terminal sliding mode tracking control is proposed for the uncertain single-input and single-output (SISO) nonlinear system with unknown external disturbance. For the unmeasured disturbance of nonlinear systems, terminal sliding mode disturbance observer is presented. The developed disturbance observer can guarantee the disturbance approximation error to converge to zero in the finite time. Based on the output of designed disturbance observer, the terminal sliding mode tracking control is presented for uncertain SISO nonlinear systems. Subsequently, terminal sliding mode tracking control is developed using disturbance observer technique for the uncertain SISO nonlinear system with control singularity and unknown non-symmetric input saturation. The effects of the control singularity and unknown input saturation are combined with the external disturbance which is approximated using the disturbance observer. Under the proposed terminal sliding mode tracking control techniques, the finite time convergence of all closed-loop signals are guaranteed via Lyapunov analysis. Numerical simulation results are given to illustrate the effectiveness of the proposed terminal sliding mode tracking control. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.
Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.
Chen, Mou; Tao, Gang
2016-08-01
In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luh, G.C.
1994-01-01
This thesis presents the application of advanced modeling techniques to construct nonlinear forward and inverse models of internal combustion engines for the detection and isolation of incipient faults. The NARMAX (Nonlinear Auto-Regressive Moving Average modeling with eXogenous inputs) technique of system identification proposed by Leontaritis and Billings was used to derive the nonlinear model of a internal combustion engine, over operating conditions corresponding to the I/M240 cycle. The I/M240 cycle is a standard proposed by the United States Environmental Protection Agency to measure tailpipe emissions in inspection and maintenance programs and consists of a driving schedule developed for the purposemore » of testing compliance with federal vehicle emission standards for carbon monoxide, unburned hydrocarbons, and nitrogen oxides. The experimental work for model identification and validation was performed on a 3.0 liter V6 engine installed in an engine test cell at the Center for Automotive Research at The Ohio State University. In this thesis, different types of model structures were proposed to obtain multi-input multi-output (MIMO) nonlinear NARX models. A modification of the algorithm proposed by He and Asada was used to estimate the robust orders of the derived MIMO nonlinear models. A methodology for the analysis of inverse NARX model was developed. Two methods were proposed to derive the inverse NARX model: (1) inversion from the forward NARX model; and (2) direct identification of inverse model from the output-input data set. In this thesis, invertibility, minimum-phase characteristic of zero dynamics, and stability analysis of NARX forward model are also discussed. Stability in the sense of Lyapunov is also investigated to check the stability of the identified forward and inverse models. This application of inverse problem leads to the estimation of unknown inputs and to actuator fault diagnosis.« less
Yuan, Chengzhi; Licht, Stephen; He, Haibo
2017-09-26
In this paper, a new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics. A novel two-layer distributed formation learning control scheme is proposed, which consists of an upper-layer distributed adaptive observer and a lower-layer decentralized deterministic learning controller. This new formation learning control scheme advances existing techniques in three important ways: 1) the multi-AUV system under consideration has heterogeneous nonlinear uncertain dynamics; 2) the formation learning control protocol can be designed and implemented by each local AUV agent in a fully distributed fashion without using any global information; and 3) in addition to the formation control performance, the distributed control protocol is also capable of accurately identifying the AUVs' heterogeneous nonlinear uncertain dynamics and utilizing experiences to improve formation control performance. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed results.
Digital transceiver design for two-way AF-MIMO relay systems with imperfect CSI
NASA Astrophysics Data System (ADS)
Hu, Chia-Chang; Chou, Yu-Fei; Chen, Kui-He
2013-09-01
In the paper, combined optimization of the terminal precoders/equalizers and single-relay precoder is proposed for an amplify-and-forward (AF) multiple-input multiple-output (MIMO) two-way single-relay system with correlated channel uncertainties. Both terminal transceivers and relay precoding matrix are designed based on the minimum mean square error (MMSE) criterion when terminals are unable to erase completely self-interference due to imperfect correlated channel state information (CSI). This robust joint optimization problem of beamforming and precoding matrices under power constraints belongs to neither concave nor convex so that a nonlinear matrix-form conjugate gradient (MCG) algorithm is applied to explore local optimal solutions. Simulation results show that the robust transceiver design is able to overcome effectively the loss of bit-error-rate (BER) due to inclusion of correlated channel uncertainties and residual self-interference.
Nonlinear engine model for idle speed control
DOE Office of Scientific and Technical Information (OSTI.GOV)
Livshiz, M.; Sanvido, D.J.; Stiles, S.D.
1994-12-31
This paper describes a nonlinear model of an engine used for the design of idle speed control and prediction in a broad range of idle speeds and operational conditions. Idle speed control systems make use of both spark advance and the idle air actuator to control engine speed for improved response relative to variations in the target idle speed due to load disturbances. The control system at idle can be presented by a multiple input multiple output (MIMO) nonlinear model. Information of nonlinearities helps to improve performance of the system over the whole range of engine speeds. A proposed simplemore » nonlinear model of the engine at idle was applied for design of optimal controllers and predictors for improved steady state, load rejection and transition from and to idle. This paper describes vehicle results of engine speed prediction based on the described model.« less
Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza
2015-09-01
To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Koo, Min-Sung; Choi, Ho-Lim
2018-01-01
In this paper, we consider a control problem for a class of uncertain nonlinear systems in which there exists an unknown time-varying delay in the input and lower triangular nonlinearities. Usually, in the existing results, input delays have been coupled with feedforward (or upper triangular) nonlinearities; in other words, the combination of lower triangular nonlinearities and input delay has been rare. Motivated by the existing controller for input-delayed chain of integrators with nonlinearity, we show that the control of input-delayed nonlinear systems with two particular types of lower triangular nonlinearities can be done. As a control solution, we propose a newly designed feedback controller whose main features are its dynamic gain and non-predictor approach. Three examples are given for illustration.
Chang, Yeong-Chan
2005-12-01
This paper addresses the problem of designing adaptive fuzzy-based (or neural network-based) robust controls for a large class of uncertain nonlinear time-varying systems. This class of systems can be perturbed by plant uncertainties, unmodeled perturbations, and external disturbances. Nonlinear H(infinity) control technique incorporated with adaptive control technique and VSC technique is employed to construct the intelligent robust stabilization controller such that an H(infinity) control is achieved. The problem of the robust tracking control design for uncertain robotic systems is employed to demonstrate the effectiveness of the developed robust stabilization control scheme. Therefore, an intelligent robust tracking controller for uncertain robotic systems in the presence of high-degree uncertainties can easily be implemented. Its solution requires only to solve a linear algebraic matrix inequality and a satisfactorily transient and asymptotical tracking performance is guaranteed. A simulation example is made to confirm the performance of the developed control algorithms.
Adaptive identifier for uncertain complex nonlinear systems based on continuous neural networks.
Alfaro-Ponce, Mariel; Cruz, Amadeo Argüelles; Chairez, Isaac
2014-03-01
This paper presents the design of a complex-valued differential neural network identifier for uncertain nonlinear systems defined in the complex domain. This design includes the construction of an adaptive algorithm to adjust the parameters included in the identifier. The algorithm is obtained based on a special class of controlled Lyapunov functions. The quality of the identification process is characterized using the practical stability framework. Indeed, the region where the identification error converges is derived by the same Lyapunov method. This zone is defined by the power of uncertainties and perturbations affecting the complex-valued uncertain dynamics. Moreover, this convergence zone is reduced to its lowest possible value using ideas related to the so-called ellipsoid methodology. Two simple but informative numerical examples are developed to show how the identifier proposed in this paper can be used to approximate uncertain nonlinear systems valued in the complex domain.
Hashim, H A; Abido, M A
2015-01-01
This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm optimization (PSO), artificial bee colony (ABC), and differential evolution (DE). In this study, the gains of four fuzzy proportional derivative (PD) controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed.
Hashim, H. A.; Abido, M. A.
2015-01-01
This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm optimization (PSO), artificial bee colony (ABC), and differential evolution (DE). In this study, the gains of four fuzzy proportional derivative (PD) controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed. PMID:25960738
Wireless Computing Architecture III
2013-09-01
MIMO Multiple-Input and Multiple-Output MIMO /CON MIMO with concurrent hannel access and estimation MU- MIMO Multiuser MIMO OFDM Orthogonal...compressive sensing \\; a design for concurrent channel estimation in scalable multiuser MIMO networking; and novel networking protocols based on machine...Network, Antenna Arrays, UAV networking, Angle of Arrival, Localization MIMO , Access Point, Channel State Information, Compressive Sensing 16
A comparative study of linear and nonlinear MIMO feedback configurations
NASA Technical Reports Server (NTRS)
Desoer, C. A.; Lin, C. A.
1984-01-01
In this paper, a comparison is conducted of several feedback configurations which have appeared in the literature (e.g. unity-feedback, model-reference, etc.). The linear time-invariant multi-input multi-output case is considered. For each configuration, the stability conditions are specified, the relation between achievable I/O maps and the achievable disturbance-to-output maps is examined, and the effect of various subsystem perturbations on the system performance is studied. In terms of these considerations, it is demonstrated that one of the configurations considered is better than all the others. The results are then extended to the nonlinear multi-input multi-output case.
MIMO to LS-MIMO: A road to realization of 5G
NASA Astrophysics Data System (ADS)
Koppati, Naveena; Pavani, K.; Sharma, Dinesh; Sharma, Purnima K.
2017-07-01
MIMO means multiple inputs multiple outputs. As it refers MIMO is a RF technology used in many new technologies these days to increase link capacity and spectral efficiency. MIMO is used in Wi-Fi, LTE, 4G, 5G and other wireless technologies. This paper describes the earlier history of MIMO-OFDM and the antenna beam forming development in MIMO and types of MIMO. Also this treatise describes several decoding algorithms. The MIMO combined with OFDM increases the channel capacity. But the main problem is in estimating the transmitted signal from the received signal. So the channel knowledge is to be known in estimating the channel capacity. The advancement in MIMO-OFDM is Massive MIMO which is beneficial in providing additional data capacity in the increased traffic environment is described. In this memoir various application scenarios of LS-MIMO which increases the capacity are discussed.
Mobayen, Saleh
2018-06-01
This paper proposes a combination of composite nonlinear feedback and integral sliding mode techniques for fast and accurate chaos synchronization of uncertain chaotic systems with Lipschitz nonlinear functions, time-varying delays and disturbances. The composite nonlinear feedback method allows accurate following of the master chaotic system and the integral sliding mode control provides invariance property which rejects the perturbations and preserves the stability of the closed-loop system. Based on the Lyapunov- Krasovskii stability theory and linear matrix inequalities, a novel sufficient condition is offered for the chaos synchronization of uncertain chaotic systems. This method not only guarantees the robustness against perturbations and time-delays, but also eliminates reaching phase and avoids chattering problem. Simulation results demonstrate that the suggested procedure leads to a great control performance. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Hovakimyan, N; Nardi, F; Calise, A; Kim, Nakwan
2002-01-01
We consider adaptive output feedback control of uncertain nonlinear systems, in which both the dynamics and the dimension of the regulated system may be unknown. However, the relative degree of the regulated output is assumed to be known. Given a smooth reference trajectory, the problem is to design a controller that forces the system measurement to track it with bounded errors. The classical approach requires a state observer. Finding a good observer for an uncertain nonlinear system is not an obvious task. We argue that it is sufficient to build an observer for the output tracking error. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. The theoretical results are illustrated in the design of a controller for a fourth-order nonlinear system of relative degree two and a high-bandwidth attitude command system for a model R-50 helicopter.
Synthesis Methods for Robust Passification and Control
NASA Technical Reports Server (NTRS)
Kelkar, Atul G.; Joshi, Suresh M. (Technical Monitor)
2000-01-01
The research effort under this cooperative agreement has been essentially the continuation of the work from previous grants. The ongoing work has primarily focused on developing passivity-based control techniques for Linear Time-Invariant (LTI) systems. During this period, there has been a significant progress made in the area of passivity-based control of LTI systems and some preliminary results have also been obtained for nonlinear systems, as well. The prior work has addressed optimal control design for inherently passive as well as non- passive linear systems. For exploiting the robustness characteristics of passivity-based controllers the passification methodology was developed for LTI systems that are not inherently passive. Various methods of passification were first proposed in and further developed. The robustness of passification was addressed for multi-input multi-output (MIMO) systems for certain classes of uncertainties using frequency-domain methods. For MIMO systems, a state-space approach using Linear Matrix Inequality (LMI)-based formulation was presented, for passification of non-passive LTI systems. An LMI-based robust passification technique was presented for systems with redundant actuators and sensors. The redundancy in actuators and sensors was used effectively for robust passification using the LMI formulation. The passification was designed to be robust to an interval-type uncertainties in system parameters. The passification techniques were used to design a robust controller for Benchmark Active Control Technology wing under parametric uncertainties. The results on passive nonlinear systems, however, are very limited to date. Our recent work in this area was presented, wherein some stability results were obtained for passive nonlinear systems that are affine in control.
Liu, Derong; Yang, Xiong; Wang, Ding; Wei, Qinglai
2015-07-01
The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. The constrained-input coupled with the inability to identify accurately the uncertainties motivates the design of stabilizing controller based on reinforcement-learning (RL) methods. In this paper, a novel RL-based robust adaptive control algorithm is developed for a class of continuous-time uncertain nonlinear systems subject to input constraints. The robust control problem is converted to the constrained optimal control problem with appropriately selecting value functions for the nominal system. Distinct from typical action-critic dual networks employed in RL, only one critic neural network (NN) is constructed to derive the approximate optimal control. Meanwhile, unlike initial stabilizing control often indispensable in RL, there is no special requirement imposed on the initial control. By utilizing Lyapunov's direct method, the closed-loop optimal control system and the estimated weights of the critic NN are proved to be uniformly ultimately bounded. In addition, the derived approximate optimal control is verified to guarantee the uncertain nonlinear system to be stable in the sense of uniform ultimate boundedness. Two simulation examples are provided to illustrate the effectiveness and applicability of the present approach.
NASA Astrophysics Data System (ADS)
Li, Chengcheng; Li, Yuefeng; Wang, Guanglin
2017-07-01
The work presented in this paper seeks to address the tracking problem for uncertain continuous nonlinear systems with external disturbances. The objective is to obtain a model that uses a reference-based output feedback tracking control law. The control scheme is based on neural networks and a linear difference inclusion (LDI) model, and a PDC structure and H∞ performance criterion are used to attenuate external disturbances. The stability of the whole closed-loop model is investigated using the well-known quadratic Lyapunov function. The key principles of the proposed approach are as follows: neural networks are first used to approximate nonlinearities, to enable a nonlinear system to then be represented as a linearised LDI model. An LMI (linear matrix inequality) formula is obtained for uncertain and disturbed linear systems. This formula enables a solution to be obtained through an interior point optimisation method for some nonlinear output tracking control problems. Finally, simulations and comparisons are provided on two practical examples to illustrate the validity and effectiveness of the proposed method.
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.
NASA Astrophysics Data System (ADS)
Hampson, Robert E.; Song, Dong; Opris, Ioan; Santos, Lucas M.; Shin, Dae C.; Gerhardt, Greg A.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.
2013-12-01
Objective. Memory accuracy is a major problem in human disease and is the primary factor that defines Alzheimer’s, ageing and dementia resulting from impaired hippocampal function in the medial temporal lobe. Development of a hippocampal memory neuroprosthesis that facilitates normal memory encoding in nonhuman primates (NHPs) could provide the basis for improving memory in human disease states. Approach. NHPs trained to perform a short-term delayed match-to-sample (DMS) memory task were examined with multi-neuron recordings from synaptically connected hippocampal cell fields, CA1 and CA3. Recordings were analyzed utilizing a previously developed nonlinear multi-input multi-output (MIMO) neuroprosthetic model, capable of extracting CA3-to-CA1 spatiotemporal firing patterns during DMS performance. Main results. The MIMO model verified that specific CA3-to-CA1 firing patterns were critical for the successful encoding of sample phase information on more difficult DMS trials. This was validated by the delivery of successful MIMO-derived encoding patterns via electrical stimulation to the same CA1 recording locations during the sample phase which facilitated task performance in the subsequent, delayed match phase, on difficult trials that required more precise encoding of sample information. Significance. These findings provide the first successful application of a neuroprosthesis designed to enhance and/or repair memory encoding in primate brain.
Hampson, Robert E.; Song, Dong; Opris, Ioan; Santos, Lucas M.; Shin, Dae C.; Gerhardt, Greg A.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.
2014-01-01
Objective Memory accuracy is a major problem in human disease and is the primary factor that defines Alzheimer’s’, aging and dementia resulting from impaired hippocampal function in medial temporal lobe. Development of a hippocampal memory neuroprosthesis that facilitates normal memory encoding in nonhuman primates (NHPs) could provide the basis for improving memory in human disease states. Approach NHPs trained to perform a short-term delayed match to sample (DMS) memory task were examined with multi-neuron recordings from synaptically connected hippocampal cell fields, CA1 and CA3. Recordings were analyzed utilizing a previously developed nonlinear multi-input multi-output (MIMO) neuroprosthetic model, capable of extracting CA3-to-CA1 spatiotemporal firing patterns during DMS performance. Main Results The MIMO model verified that specific CA3-to-CA1 firing patterns were critical for successful encoding of Sample phase information on more difficult DMS trials. This was validated by delivery of successful MIMO-derived encoding patterns via electrical stimulation to the same CA1 recording locations during the Sample phase which facilitated task performance in the subsequent delayed Match phase on difficult trials that required more precise encoding of Sample information. Significance These findings provide the first successful application of a neuroprosthesis designed to enhance and/or repair memory encoding in primate brain. PMID:24216292
Robust nonlinear variable selective control for networked systems
NASA Astrophysics Data System (ADS)
Rahmani, Behrooz
2016-10-01
This paper is concerned with the networked control of a class of uncertain nonlinear systems. In this way, Takagi-Sugeno (T-S) fuzzy modelling is used to extend the previously proposed variable selective control (VSC) methodology to nonlinear systems. This extension is based upon the decomposition of the nonlinear system to a set of fuzzy-blended locally linearised subsystems and further application of the VSC methodology to each subsystem. To increase the applicability of the T-S approach for uncertain nonlinear networked control systems, this study considers the asynchronous premise variables in the plant and the controller, and then introduces a robust stability analysis and control synthesis. The resulting optimal switching-fuzzy controller provides a minimum guaranteed cost on an H2 performance index. Simulation studies on three nonlinear benchmark problems demonstrate the effectiveness of the proposed method.
NASA Astrophysics Data System (ADS)
Radac, Mircea-Bogdan; Precup, Radu-Emil; Roman, Raul-Cristian
2017-04-01
This paper proposes the combination of two model-free controller tuning techniques, namely linear virtual reference feedback tuning (VRFT) and nonlinear state-feedback Q-learning, referred to as a new mixed VRFT-Q learning approach. VRFT is first used to find stabilising feedback controller using input-output experimental data from the process in a model reference tracking setting. Reinforcement Q-learning is next applied in the same setting using input-state experimental data collected under perturbed VRFT to ensure good exploration. The Q-learning controller learned with a batch fitted Q iteration algorithm uses two neural networks, one for the Q-function estimator and one for the controller, respectively. The VRFT-Q learning approach is validated on position control of a two-degrees-of-motion open-loop stable multi input-multi output (MIMO) aerodynamic system (AS). Extensive simulations for the two independent control channels of the MIMO AS show that the Q-learning controllers clearly improve performance over the VRFT controllers.
Adaptive Control for Uncertain Nonlinear Multi-Input Multi-Output Systems
NASA Technical Reports Server (NTRS)
Cao, Chengyu (Inventor); Hovakimyan, Naira (Inventor); Xargay, Enric (Inventor)
2014-01-01
Systems and methods of adaptive control for uncertain nonlinear multi-input multi-output systems in the presence of significant unmatched uncertainty with assured performance are provided. The need for gain-scheduling is eliminated through the use of bandwidth-limited (low-pass) filtering in the control channel, which appropriately attenuates the high frequencies typically appearing in fast adaptation situations and preserves the robustness margins in the presence of fast adaptation.
2008-05-01
en ts m et ho ds - 1s t fle xi bl e m od e ha s be en co ns id er ed fo re ac h be am an d al on g its X a nd Y...s b ee n pr es en te d. • Th e te ch ni qu e ha s b ee n va lid at ed w ith a D ar w in -ty pe sp ac ec ra ft w ith fle xi bl e ap pe nd ag es...2. 1 M ar io G ar ci a- Sa nz M ar io G ar ci a- Sa nz A
NASA Technical Reports Server (NTRS)
Acikmese, Ahmet Behcet; Carson, John M., III
2006-01-01
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees resolvability. With resolvability, initial feasibility of the finite-horizon optimal control problem implies future feasibility in a receding-horizon framework. The control consists of two components; (i) feed-forward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives and derivatives in polytopes. An illustrative numerical example is also provided.
Khazaee, Mostafa; Markazi, Amir H D; Omidi, Ehsan
2015-11-01
In this paper, a new Adaptive Fuzzy Predictive Sliding Mode Control (AFP-SMC) is presented for nonlinear systems with uncertain dynamics and unknown input delay. The control unit consists of a fuzzy inference system to approximate the ideal linearization control, together with a switching strategy to compensate for the estimation errors. Also, an adaptive fuzzy predictor is used to estimate the future values of the system states to compensate for the time delay. The adaptation laws are used to tune the controller and predictor parameters, which guarantee the stability based on a Lyapunov-Krasovskii functional. To evaluate the method effectiveness, the simulation and experiment on an overhead crane system are presented. According to the obtained results, AFP-SMC can effectively control the uncertain nonlinear systems, subject to input delays of known bound. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Fuzzy control of a fluidized bed dryer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Taprantzis, A.V.; Siettos, C.I.; Bafas, G.V.
1997-05-01
Fluidized bed dryers are utilized in almost every area of drying applications and therefore improved control strategies are always of great interest. The nonlinear character of the process, exhibited in the mathematical model and the open loop analysis, implies that a fuzzy logic controller is appropriate because, in contrast with conventional control schemes, fuzzy control inherently compensates for process nonlinearities and exhibits more robust behavior. In this study, a fuzzy logic controller is proposed; its design is based on a heuristic approach and its performance is compared against a conventional PI controller for a variety of responses. It is shownmore » that the fuzzy controller exhibits a remarkable dynamic behavior, equivalent if not better than the PI controller, for a wide range of disturbances. In addition, the proposed fuzzy controller seems to be less sensitive to the nonlinearities of the process, achieves energy savings and enables MIMO control.« less
Single-user MIMO versus multi-user MIMO in distributed antenna systems with limited feedback
NASA Astrophysics Data System (ADS)
Schwarz, Stefan; Heath, Robert W.; Rupp, Markus
2013-12-01
This article investigates the performance of cellular networks employing distributed antennas in addition to the central antennas of the base station. Distributed antennas are likely to be implemented using remote radio units, which is enabled by a low latency and high bandwidth dedicated link to the base station. This facilitates coherent transmission from potentially all available antennas at the same time. Such distributed antenna system (DAS) is an effective way to deal with path loss and large-scale fading in cellular systems. DAS can apply precoding across multiple transmission points to implement single-user MIMO (SU-MIMO) and multi-user MIMO (MU-MIMO) transmission. The throughput performance of various SU-MIMO and MU-MIMO transmission strategies is investigated in this article, employing a Long-Term evolution (LTE) standard compliant simulation framework. The previously theoretically established cell-capacity improvement of MU-MIMO in comparison to SU-MIMO in DASs is confirmed under the practical constraints imposed by the LTE standard, even under the assumption of imperfect channel state information (CSI) at the base station. Because practical systems will use quantized feedback, the performance of different CSI feedback algorithms for DASs is investigated. It is shown that significant gains in the CSI quantization accuracy and in the throughput of especially MU-MIMO systems can be achieved with relatively simple quantization codebook constructions that exploit the available temporal correlation and channel gain differences.
Radac, Mircea-Bogdan; Precup, Radu-Emil; Petriu, Emil M
2015-11-01
This paper proposes a novel model-free trajectory tracking of multiple-input multiple-output (MIMO) systems by the combination of iterative learning control (ILC) and primitives. The optimal trajectory tracking solution is obtained in terms of previously learned solutions to simple tasks called primitives. The library of primitives that are stored in memory consists of pairs of reference input/controlled output signals. The reference input primitives are optimized in a model-free ILC framework without using knowledge of the controlled process. The guaranteed convergence of the learning scheme is built upon a model-free virtual reference feedback tuning design of the feedback decoupling controller. Each new complex trajectory to be tracked is decomposed into the output primitives regarded as basis functions. The optimal reference input for the control system to track the desired trajectory is next recomposed from the reference input primitives. This is advantageous because the optimal reference input is computed straightforward without the need to learn from repeated executions of the tracking task. In addition, the optimization problem specific to trajectory tracking of square MIMO systems is decomposed in a set of optimization problems assigned to each separate single-input single-output control channel that ensures a convenient model-free decoupling. The new model-free primitive-based ILC approach is capable of planning, reasoning, and learning. A case study dealing with the model-free control tuning for a nonlinear aerodynamic system is included to validate the new approach. The experimental results are given.
Compressive Sensing for Radar and Radar Sensor Networks
2013-12-02
Zero Correlation Zone Sequence Pair Sets for MIMO Radar Inspired by recent advances in MIMO radar, we apply orthogonal phase coded waveforms to MIMO ...radar system in order to gain better range resolution and target direction finding performance [2]. We provide and investigate a generalized MIMO radar...ZCZ) sequence-Pair Set (ZCZPS). We also study the MIMO radar ambiguity function of the system using phase coded waveforms, based on which we analyze
Li, Yongming; Tong, Shaocheng
2017-06-28
In this paper, an adaptive neural networks (NNs)-based decentralized control scheme with the prescribed performance is proposed for uncertain switched nonstrict-feedback interconnected nonlinear systems. It is assumed that nonlinear interconnected terms and nonlinear functions of the concerned systems are unknown, and also the switching signals are unknown and arbitrary. A linear state estimator is constructed to solve the problem of unmeasured states. The NNs are employed to approximate unknown interconnected terms and nonlinear functions. A new output feedback decentralized control scheme is developed by using the adaptive backstepping design technique. The control design problem of nonlinear interconnected switched systems with unknown switching signals can be solved by the proposed scheme, and only a tuning parameter is needed for each subsystem. The proposed scheme can ensure that all variables of the control systems are semi-globally uniformly ultimately bounded and the tracking errors converge to a small residual set with the prescribed performance bound. The effectiveness of the proposed control approach is verified by some simulation results.
A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.
Gui, Jinsong; Zhou, Kai; Xiong, Naixue
2016-09-25
Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.
A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks
Gui, Jinsong; Zhou, Kai; Xiong, Naixue
2016-01-01
Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731
Choi, Yun Ho; Yoo, Sung Jin
2018-06-01
This paper investigates the event-triggered decentralized adaptive tracking problem of a class of uncertain interconnected nonlinear systems with unexpected actuator failures. It is assumed that local control signals are transmitted to local actuators with time-varying faults whenever predefined conditions for triggering events are satisfied. Compared with the existing control-input-based event-triggering strategy for adaptive control of uncertain nonlinear systems, the aim of this paper is to propose a tracking-error-based event-triggering strategy in the decentralized adaptive fault-tolerant tracking framework. The proposed approach can relax drastic changes in control inputs caused by actuator faults in the existing triggering strategy. The stability of the proposed event-triggering control system is analyzed in the Lyapunov sense. Finally, simulation comparisons of the proposed and existing approaches are provided to show the effectiveness of the proposed theoretical result in the presence of actuator faults. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Modeling and control of tissue compression and temperature for automation in robot-assisted surgery.
Sinha, Utkarsh; Li, Baichun; Sankaranarayanan, Ganesh
2014-01-01
Robotic surgery is being used widely due to its various benefits that includes reduced patient trauma and increased dexterity and ergonomics for the operating surgeon. Making the whole or part of the surgical procedure autonomous increases patient safety and will enable the robotic surgery platform to be used in telesurgery. In this work, an Electrosurgery procedure that involves tissue compression and application of heat such as the coaptic vessel closure has been automated. A MIMO nonlinear model characterizing the tissue stiffness and conductance under compression was feedback linearized and tuned PID controllers were used to control the system to achieve both the displacement and temperature constraints. A reference input for both the constraints were chosen as a ramp and hold trajectory which reflect the real constraints that exist in an actual surgical procedure. Our simulations showed that the controllers successfully tracked the reference trajectories with minimal deviation and in finite time horizon. The MIMO system with controllers developed in this work can be used to drive a surgical robot autonomously and perform electrosurgical procedures such as coaptic vessel closures.
Type-2 fuzzy logic control of a 2-DOF helicopter (TRMS system)
NASA Astrophysics Data System (ADS)
Zeghlache, Samir; Kara, Kamel; Saigaa, Djamel
2014-09-01
The helicopter dynamic includes nonlinearities, parametric uncertainties and is subject to unknown external disturbances. Such complicated dynamics involve designing sophisticated control algorithms that can deal with these difficulties. In this paper, a type 2 fuzzy logic PID controller is proposed for TRMS (twin rotor mimo system) control problem. Using triangular membership functions and based on a human operator experience, two controllers are designed to control the position of the yaw and the pitch angles of the TRMS. Simulation results are given to illustrate the effectiveness of the proposed control scheme.
NASA Astrophysics Data System (ADS)
Li, Jian; Zhang, Qingling; Ren, Junchao; Zhang, Yanhao
2017-10-01
This paper studies the problem of robust stability and stabilisation for uncertain large-scale interconnected nonlinear descriptor systems via proportional plus derivative state feedback or proportional plus derivative output feedback. The basic idea of this work is to use the well-known differential mean value theorem to deal with the nonlinear model such that the considered nonlinear descriptor systems can be transformed into linear parameter varying systems. By using a parameter-dependent Lyapunov function, a decentralised proportional plus derivative state feedback controller and decentralised proportional plus derivative output feedback controller are designed, respectively such that the closed-loop system is quadratically normal and quadratically stable. Finally, a hypersonic vehicle practical simulation example and numerical example are given to illustrate the effectiveness of the results obtained in this paper.
Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.
Gao, Xi jun; Chen, Zi li; Hu, Yong Jiang
2014-01-01
Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.
Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix
Xi jun, Gao; Zi li, Chen; Yong Jiang, Hu
2014-01-01
Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication. PMID:24977185
Compressive MIMO Beamforming of Data Collected in a Refractive Environment
NASA Astrophysics Data System (ADS)
Wagner, Mark; Nannuru, Santosh; Gerstoft, Peter
2017-12-01
The phenomenon of ducting is caused by abnormal atmospheric refractivity patterns and is known to allow electromagnetic waves to propagate over the horizon with unusually low propagation loss. It is unknown what effect ducting has on multiple input multiple output (MIMO) channels, particularly its effect on multipath propagation in MIMO channels. A high-accuracy angle-of-arrival and angle-of-departure estimation technique for MIMO communications, which we will refer to as compressive MIMO beamforming, was tested on simulated data then applied to experimental data taken from an over the horizon MIMO test bed located in a known ducting hot spot in Southern California. The multipath channel was estimated from the receiver data recorded over a period of 18 days, and an analysis was performed on the recorded data. The goal is to observe the evolution of the MIMO multipath channel as atmospheric ducts form and dissipate to gain some understanding of the behavior of channels in a refractive environment. This work is motivated by the idea that some multipath characteristics of MIMO channels within atmospheric ducts could yield important information about the duct.
MIMO transmit scheme based on morphological perceptron with competitive learning.
Valente, Raul Ambrozio; Abrão, Taufik
2016-08-01
This paper proposes a new multi-input multi-output (MIMO) transmit scheme aided by artificial neural network (ANN). The morphological perceptron with competitive learning (MP/CL) concept is deployed as a decision rule in the MIMO detection stage. The proposed MIMO transmission scheme is able to achieve double spectral efficiency; hence, in each time-slot the receiver decodes two symbols at a time instead one as Alamouti scheme. Other advantage of the proposed transmit scheme with MP/CL-aided detector is its polynomial complexity according to modulation order, while it becomes linear when the data stream length is greater than modulation order. The performance of the proposed scheme is compared to the traditional MIMO schemes, namely Alamouti scheme and maximum-likelihood MIMO (ML-MIMO) detector. Also, the proposed scheme is evaluated in a scenario with variable channel information along the frame. Numerical results have shown that the diversity gain under space-time coding Alamouti scheme is partially lost, which slightly reduces the bit-error rate (BER) performance of the proposed MP/CL-NN MIMO scheme. Copyright © 2016 Elsevier Ltd. All rights reserved.
CR-Calculus and adaptive array theory applied to MIMO random vibration control tests
NASA Astrophysics Data System (ADS)
Musella, U.; Manzato, S.; Peeters, B.; Guillaume, P.
2016-09-01
Performing Multiple-Input Multiple-Output (MIMO) tests to reproduce the vibration environment in a user-defined number of control points of a unit under test is necessary in applications where a realistic environment replication has to be achieved. MIMO tests require vibration control strategies to calculate the required drive signal vector that gives an acceptable replication of the target. This target is a (complex) vector with magnitude and phase information at the control points for MIMO Sine Control tests while in MIMO Random Control tests, in the most general case, the target is a complete spectral density matrix. The idea behind this work is to tailor a MIMO random vibration control approach that can be generalized to other MIMO tests, e.g. MIMO Sine and MIMO Time Waveform Replication. In this work the approach is to use gradient-based procedures over the complex space, applying the so called CR-Calculus and the adaptive array theory. With this approach it is possible to better control the process performances allowing the step-by-step Jacobian Matrix update. The theoretical bases behind the work are followed by an application of the developed method to a two-exciter two-axis system and by performance comparisons with standard methods.
A novel auto-tuning PID control mechanism for nonlinear systems.
Cetin, Meric; Iplikci, Serdar
2015-09-01
In this paper, a novel Runge-Kutta (RK) discretization-based model-predictive auto-tuning proportional-integral-derivative controller (RK-PID) is introduced for the control of continuous-time nonlinear systems. The parameters of the PID controller are tuned using RK model of the system through prediction error-square minimization where the predicted information of tracking error provides an enhanced tuning of the parameters. Based on the model-predictive control (MPC) approach, the proposed mechanism provides necessary PID parameter adaptations while generating additive correction terms to assist the initially inadequate PID controller. Efficiency of the proposed mechanism has been tested on two experimental real-time systems: an unstable single-input single-output (SISO) nonlinear magnetic-levitation system and a nonlinear multi-input multi-output (MIMO) liquid-level system. RK-PID has been compared to standard PID, standard nonlinear MPC (NMPC), RK-MPC and conventional sliding-mode control (SMC) methods in terms of control performance, robustness, computational complexity and design issue. The proposed mechanism exhibits acceptable tuning and control performance with very small steady-state tracking errors, and provides very short settling time for parameter convergence. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Parameter Design and Optimal Control of an Open Core Flywheel Energy Storage System
NASA Technical Reports Server (NTRS)
Pang, D.; Anand, D. K.; Kirk, J. A.
1996-01-01
In low earth orbit (LEO) satellite applications spacecraft power is provided by photovoltaic cells and batteries. To overcome battery shortcomings the University of Maryland, working in cooperation with NASA/GSFC and NASA/LeRC, has developed a magnetically suspended flywheel for energy storage applications. The system is referred to as an Open Core Composite Flywheel (OCCF) energy storage system. Successful application of flywheel energy storage requires integration of several technologies, viz. bearings, rotor design, motor/generator, power conditioning, and system control. In this paper we present a parameter design method which has been developed for analyzing the linear SISO model of the magnetic bearing controller for the OCCF. The objective of this continued research is to principally analyze the magnetic bearing system for nonlinear effects in order to increase the region of stability, as determined by high speed and large air gap control. This is achieved by four tasks: (1) physical modeling, design, prototyping, and testing of an improved magnetically suspended flywheel energy storage system, (2) identification of problems that limit performance and their corresponding solutions, (3) development of a design methodology for magnetic bearings, and (4) design of an optimal controller for future high speed applications. Both nonlinear SISO and MIMO models of the magnetic system were built to study limit cycle oscillations and power amplifier saturation phenomenon observed in experiments. The nonlinear models include the inductance of EM coils, the power amplifier saturation, and the physical limitation of the flywheel movement as discussed earlier. The control program EASY5 is used to study the nonlinear SISO and MIMO models. Our results have shown that the characteristics and frequency responses of the magnetic bearing system obtained from modeling are comparable to those obtained experimentally. Although magnetic saturation is shown in the bearings, there are good correlations between the theoretical model and experimental data. Both simulation and experiment confirm large variations of the magnetic bearing characteristics due to air gap growth. Therefore, the gap growth effect should be considered in the magnetic bearing system design. Additionally, the magnetic bearing control system will be compared to other design methods using not only parameter design but H-infinity optimal control and mu synthesis.
Song, Zhibao; Zhai, Junyong
2018-04-01
This paper addresses the problem of adaptive output-feedback control for a class of switched stochastic time-delay nonlinear systems with uncertain output function, where both the control coefficients and time-varying delay are unknown. The drift and diffusion terms are subject to unknown homogeneous growth condition. By virtue of adding a power integrator technique, an adaptive output-feedback controller is designed to render that the closed-loop system is bounded in probability, and the state of switched stochastic nonlinear system can be globally regulated to the origin almost surely. A numerical example is provided to demonstrate the validity of the proposed control method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo
2013-10-02
Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.
Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo
2013-01-01
Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase. PMID:24152920
Color-Space-Based Visual-MIMO for V2X Communication †
Kim, Jai-Eun; Kim, Ji-Won; Park, Youngil; Kim, Ki-Doo
2016-01-01
In this paper, we analyze the applicability of color-space-based, color-independent visual-MIMO for V2X. We aim to achieve a visual-MIMO scheme that can maintain the original color and brightness while performing seamless communication. We consider two scenarios of GCM based visual-MIMO for V2X. One is a multipath transmission using visual-MIMO networking and the other is multi-node V2X communication. In the scenario of multipath transmission, we analyze the channel capacity numerically and we illustrate the significance of networking information such as distance, reference color (symbol), and multiplexing-diversity mode transitions. In addition, in the V2X scenario of multiple access, we may achieve the simultaneous multiple access communication without node interferences by dividing the communication area using image processing. Finally, through numerical simulation, we show the superior SER performance of the visual-MIMO scheme compared with LED-PD communication and show the numerical result of the GCM based visual-MIMO channel capacity versus distance. PMID:27120603
Joint Channel and Phase Noise Estimation in MIMO-OFDM Systems
NASA Astrophysics Data System (ADS)
Ngebani, I. M.; Chuma, J. M.; Zibani, I.; Matlotse, E.; Tsamaase, K.
2017-05-01
The combination of multiple-input multiple-output (MIMO) techniques with orthogonal frequency division multiplexing (OFDM), MIMO-OFDM, is a promising way of achieving high spectral efficiency in wireless communication systems. However, the performance of MIMO-ODFM systems is highly degraded by radio frequency (RF) impairments such as phase noise. Similar to the single-input single-output (SISO) case, phase noise in MIMO-OFDM systems results in a common phase error (CPE) and inter carrier interference (ICI). In this paper the problem of joint channel and phase noise estimation in a system with multiple transmit and receive antennas where each antenna is equipped with its own independent oscillator is tackled. The technique employed makes use of a novel placement of pilot carriers in the preamble and data portion of the MIMO-OFDM frame. Numerical results using a 16 and 64 quadrature amplitude modulation QAM schemes are provided to illustrate the effectiveness of the proposed scheme for MIMO-OFDM systems.
Color-Space-Based Visual-MIMO for V2X Communication.
Kim, Jai-Eun; Kim, Ji-Won; Park, Youngil; Kim, Ki-Doo
2016-04-23
In this paper, we analyze the applicability of color-space-based, color-independent visual-MIMO for V2X. We aim to achieve a visual-MIMO scheme that can maintain the original color and brightness while performing seamless communication. We consider two scenarios of GCM based visual-MIMO for V2X. One is a multipath transmission using visual-MIMO networking and the other is multi-node V2X communication. In the scenario of multipath transmission, we analyze the channel capacity numerically and we illustrate the significance of networking information such as distance, reference color (symbol), and multiplexing-diversity mode transitions. In addition, in the V2X scenario of multiple access, we may achieve the simultaneous multiple access communication without node interferences by dividing the communication area using image processing. Finally, through numerical simulation, we show the superior SER performance of the visual-MIMO scheme compared with LED-PD communication and show the numerical result of the GCM based visual-MIMO channel capacity versus distance.
Turkdogan-Aydinol, F Ilter; Yetilmezsoy, Kaan
2010-10-15
A MIMO (multiple inputs and multiple outputs) fuzzy-logic-based model was developed to predict biogas and methane production rates in a pilot-scale 90-L mesophilic up-flow anaerobic sludge blanket (UASB) reactor treating molasses wastewater. Five input variables such as volumetric organic loading rate (OLR), volumetric total chemical oxygen demand (TCOD) removal rate (R(V)), influent alkalinity, influent pH and effluent pH were fuzzified by the use of an artificial intelligence-based approach. Trapezoidal membership functions with eight levels were conducted for the fuzzy subsets, and a Mamdani-type fuzzy inference system was used to implement a total of 134 rules in the IF-THEN format. The product (prod) and the centre of gravity (COG, centroid) methods were employed as the inference operator and defuzzification methods, respectively. Fuzzy-logic predicted results were compared with the outputs of two exponential non-linear regression models derived in this study. The UASB reactor showed a remarkable performance on the treatment of molasses wastewater, with an average TCOD removal efficiency of 93 (+/-3)% and an average volumetric TCOD removal rate of 6.87 (+/-3.93) kg TCOD(removed)/m(3)-day, respectively. Findings of this study clearly indicated that, compared to non-linear regression models, the proposed MIMO fuzzy-logic-based model produced smaller deviations and exhibited a superior predictive performance on forecasting of both biogas and methane production rates with satisfactory determination coefficients over 0.98. 2010 Elsevier B.V. All rights reserved.
Three-dimensional near-field MIMO array imaging using range migration techniques.
Zhuge, Xiaodong; Yarovoy, Alexander G
2012-06-01
This paper presents a 3-D near-field imaging algorithm that is formulated for 2-D wideband multiple-input-multiple-output (MIMO) imaging array topology. The proposed MIMO range migration technique performs the image reconstruction procedure in the frequency-wavenumber domain. The algorithm is able to completely compensate the curvature of the wavefront in the near-field through a specifically defined interpolation process and provides extremely high computational efficiency by the application of the fast Fourier transform. The implementation aspects of the algorithm and the sampling criteria of a MIMO aperture are discussed. The image reconstruction performance and computational efficiency of the algorithm are demonstrated both with numerical simulations and measurements using 2-D MIMO arrays. Real-time 3-D near-field imaging can be achieved with a real-aperture array by applying the proposed MIMO range migration techniques.
2011-09-30
channel interference mitigation for underwater acoustic MIMO - OFDM . 3) Turbo equalization for OFDM modulated physical layer network coding. 4) Blind CFO...Underwater Acoustic MIMO - OFDM . MIMO - OFDM has been actively studied for high data rate communications over the bandwidthlimited underwater acoustic...with the cochannel interference (CCI) due to parallel transmissions in MIMO - OFDM . Our proposed receiver has the following components: 1
Remote sensing using MIMO systems
Bikhazi, Nicolas; Young, William F; Nguyen, Hung D
2015-04-28
A technique for sensing a moving object within a physical environment using a MIMO communication link includes generating a channel matrix based upon channel state information of the MIMO communication link. The physical environment operates as a communication medium through which communication signals of the MIMO communication link propagate between a transmitter and a receiver. A spatial information variable is generated for the MIMO communication link based on the channel matrix. The spatial information variable includes spatial information about the moving object within the physical environment. A signature for the moving object is generated based on values of the spatial information variable accumulated over time. The moving object is identified based upon the signature.
Performance analysis of cooperative virtual MIMO systems for wireless sensor networks.
Rafique, Zimran; Seet, Boon-Chong; Al-Anbuky, Adnan
2013-05-28
Multi-Input Multi-Output (MIMO) techniques can be used to increase the data rate for a given bit error rate (BER) and transmission power. Due to the small form factor, energy and processing constraints of wireless sensor nodes, a cooperative Virtual MIMO as opposed to True MIMO system architecture is considered more feasible for wireless sensor network (WSN) applications. Virtual MIMO with Vertical-Bell Labs Layered Space-Time (V-BLAST) multiplexing architecture has been recently established to enhance WSN performance. In this paper, we further investigate the impact of different modulation techniques, and analyze for the first time, the performance of a cooperative Virtual MIMO system based on V-BLAST architecture with multi-carrier modulation techniques. Through analytical models and simulations using real hardware and environment settings, both communication and processing energy consumptions, BER, spectral efficiency, and total time delay of multiple cooperative nodes each with single antenna are evaluated. The results show that cooperative Virtual-MIMO with Binary Phase Shift Keying-Wavelet based Orthogonal Frequency Division Multiplexing (BPSK-WOFDM) modulation is a promising solution for future high data-rate and energy-efficient WSNs.
Performance Analysis of Cooperative Virtual MIMO Systems for Wireless Sensor Networks
Rafique, Zimran; Seet, Boon-Chong; Al-Anbuky, Adnan
2013-01-01
Multi-Input Multi-Output (MIMO) techniques can be used to increase the data rate for a given bit error rate (BER) and transmission power. Due to the small form factor, energy and processing constraints of wireless sensor nodes, a cooperative Virtual MIMO as opposed to True MIMO system architecture is considered more feasible for wireless sensor network (WSN) applications. Virtual MIMO with Vertical-Bell Labs Layered Space-Time (V-BLAST) multiplexing architecture has been recently established to enhance WSN performance. In this paper, we further investigate the impact of different modulation techniques, and analyze for the first time, the performance of a cooperative Virtual MIMO system based on V-BLAST architecture with multi-carrier modulation techniques. Through analytical models and simulations using real hardware and environment settings, both communication and processing energy consumptions, BER, spectral efficiency, and total time delay of multiple cooperative nodes each with single antenna are evaluated. The results show that cooperative Virtual-MIMO with Binary Phase Shift Keying-Wavelet based Orthogonal Frequency Division Multiplexing (BPSK-WOFDM) modulation is a promising solution for future high data-rate and energy-efficient WSNs. PMID:23760087
Robust control of a parallel hybrid drivetrain with a CVT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mayer, T.; Schroeder, D.
1996-09-01
In this paper the design of a robust control system for a parallel hybrid drivetrain is presented. The drivetrain is based on a continuously variable transmission (CVT) and is therefore a highly nonlinear multiple-input-multiple-output system (MIMO-System). Input-Output-Linearization offers the possibility of linearizing and of decoupling the system. Since for example the vehicle mass varies with the load and the efficiency of the gearbox depends strongly on the actual working point, an exact linearization of the plant will mostly fail. Therefore a robust control algorithm based on sliding mode is used to control the drivetrain.
Coherent optical OFDM: theory and design.
Shieh, W; Bao, H; Tang, Y
2008-01-21
Coherent optical OFDM (CO-OFDM) has recently been proposed and the proof-of-concept transmission experiments have shown its extreme robustness against chromatic dispersion and polarization mode dispersion. In this paper, we first review the theoretical fundamentals for CO-OFDM and its channel model in a 2x2 MIMO-OFDM representation. We then present various design choices for CO-OFDM systems and perform the nonlinearity analysis for RF-to-optical up-converter. We also show the receiver-based digital signal processing to mitigate self-phase-modulation (SPM) and Gordon-Mollenauer phase noise, which is equivalent to the midspan phase conjugation.
NASA Astrophysics Data System (ADS)
Takanashi, Masaki; Nishimura, Toshihiko; Ogawa, Yasutaka; Ohgane, Takeo
Ultrawide-band impulse radio (UWB-IR) technology and multiple-input multiple-output (MIMO) systems have attracted interest regarding their use in next-generation high-speed radio communication. We have studied the use of MIMO ultrawide-band (MIMO-UWB) systems to enable higher-speed radio communication. We used frequency-domain equalization based on the minimum mean square error criterion (MMSE-FDE) to reduce intersymbol interference (ISI) and co-channel interference (CCI) in MIMO-UWB systems. Because UWB systems are expected to be used for short-range wireless communication, MIMO-UWB systems will usually operate in line-of-sight (LOS) environments and direct waves will be received at the receiver side. Direct waves have high power and cause high correlations between antennas in such environments. Thus, it is thought that direct waves will adversely affect the performance of spatial filtering and equalization techniques used to enhance signal detection. To examine the feasibility of MIMO-UWB systems, we conducted MIMO-UWB system propagation measurements in LOS environments. From the measurements, we found that the arrival time of direct waves from different transmitting antennas depends on the MIMO configuration. Because we can obtain high power from the direct waves, direct wave reception is critical for maximizing transmission performance. In this paper, we present our measurement results, and propose a way to improve performance using a method of transmit (Tx) and receive (Rx) timing control. We evaluate the bit error rate (BER) performance for this form of timing control using measured channel data.
NASA Astrophysics Data System (ADS)
Ataei-Esfahani, Armin
In this dissertation, we present algorithmic procedures for sum-of-squares based stability analysis and control design for uncertain nonlinear systems. In particular, we consider the case of robust aircraft control design for a hypersonic aircraft model subject to parametric uncertainties in its aerodynamic coefficients. In recent years, Sum-of-Squares (SOS) method has attracted increasing interest as a new approach for stability analysis and controller design of nonlinear dynamic systems. Through the application of SOS method, one can describe a stability analysis or control design problem as a convex optimization problem, which can efficiently be solved using Semidefinite Programming (SDP) solvers. For nominal systems, the SOS method can provide a reliable and fast approach for stability analysis and control design for low-order systems defined over the space of relatively low-degree polynomials. However, The SOS method is not well-suited for control problems relating to uncertain systems, specially those with relatively high number of uncertainties or those with non-affine uncertainty structure. In order to avoid issues relating to the increased complexity of the SOS problems for uncertain system, we present an algorithm that can be used to transform an SOS problem with uncertainties into a LMI problem with uncertainties. A new Probabilistic Ellipsoid Algorithm (PEA) is given to solve the robust LMI problem, which can guarantee the feasibility of a given solution candidate with an a-priori fixed probability of violation and with a fixed confidence level. We also introduce two approaches to approximate the robust region of attraction (RROA) for uncertain nonlinear systems with non-affine dependence on uncertainties. The first approach is based on a combination of PEA and SOS method and searches for a common Lyapunov function, while the second approach is based on the generalized Polynomial Chaos (gPC) expansion theorem combined with the SOS method and searches for parameter-dependent Lyapunov functions. The control design problem is investigated through a case study of a hypersonic aircraft model with parametric uncertainties. Through time-scale decomposition and a series of function approximations, the complexity of the aircraft model is reduced to fall within the capability of SDP solvers. The control design problem is then formulated as a convex problem using the dual of the Lyapunov theorem. A nonlinear robust controller is searched using the combined PEA/SOS method. The response of the uncertain aircraft model is evaluated for two sets of pilot commands. As the simulation results show, the aircraft remains stable under up to 50% uncertainty in aerodynamic coefficients and can follow the pilot commands.
Model predictive control of a wind turbine modelled in Simpack
NASA Astrophysics Data System (ADS)
Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.
2014-06-01
Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to SlMPACK. This modeling approach allows to investigate the nonlinear behavior of wind loads and nonlinear drive train dynamics. Thereby the MPC's impact on specific loads and effects not covered by standard simulation tools can be assessed and investigated. Keywords. wind turbine simulation, model predictive control, multi body simulation, MIMO, load alleviation
Advanced Multiple In-Multiple Out (MIMO) Antenna Communications for Airborne Networks
2015-03-01
are airborne and both employ multiple antennas. On the other hand, the conventionally studied MIMO wireless communication is based on the premise that...architecture as the central idea, upon which our proposed solutions are based . Hence, to facilitate experiments, we also de- velop a GNU Radio/USRP based D...decoder. 2.2 Variable Rate MIMO In this part of the report we develop a variable rate MIMO scheme, based on D-BLAST transceiver architecture, to
Distributed MIMO Radar for Imaging and High Resolution Target Localization
2012-02-02
Reduction in Distributed MIMO Radar with Multi-Carrier OFDM Signals Carl Georgeson 11/23/2010 Approved 17 • 10-019 Algorithms for Target Location and...28-2012 Final Report 04/15/2009 - 11/30/2011 Distributed MIMO Radar for Imaging and High Resolution Target Localization FA9550-09-1-0303 Alexander M...error for the general case of MIMO radar with multiple waveforms with non-coherent and coherent observations; (b) finds a closed-form solution for the
The Capacity Gain of Orbital Angular Momentum Based Multiple-Input-Multiple-Output System
Zhang, Zhuofan; Zheng, Shilie; Chen, Yiling; Jin, Xiaofeng; Chi, Hao; Zhang, Xianmin
2016-01-01
Wireless communication using electromagnetic wave carrying orbital angular momentum (OAM) has attracted increasing interest in recent years, and its potential to increase channel capacity has been explored widely. In this paper, we compare the technique of using uniform linear array consist of circular traveling-wave OAM antennas for multiplexing with the conventional multiple-in-multiple-out (MIMO) communication method, and numerical results show that the OAM based MIMO system can increase channel capacity while communication distance is long enough. An equivalent model is proposed to illustrate that the OAM multiplexing system is equivalent to a conventional MIMO system with a larger element spacing, which means OAM waves could decrease the spatial correlation of MIMO channel. In addition, the effects of some system parameters, such as OAM state interval and element spacing, on the capacity advantage of OAM based MIMO are also investigated. Our results reveal that OAM waves are complementary with MIMO method. OAM waves multiplexing is suitable for long-distance line-of-sight (LoS) communications or communications in open area where the multi-path effect is weak and can be used in massive MIMO systems as well. PMID:27146453
On MIMO-UFMC in the Presence of Phase Noise and Antenna Mutual Coupling
NASA Astrophysics Data System (ADS)
Chen, Xiaoming; Zhang, Shuai; Zhang, Anxue
2017-11-01
The universal filtered multicarrier (UFMC) technique has been proposed as a waveform candidate for the fifth generation (5G) communications and beyond 5G. Compared with conventional orthogonal frequency division multiplexing (OFDM), UFMC has lower out-of-band emission and is also compatible with the multiple-input multiple-output (MIMO) technique. However, like other multicarrier waveforms, it suffers from phase noise of imperfect oscillator. In contrast to the rich literature on phase noise effect on MIMO-OFDM (where the antenna mutual coupling effect is usually omitted though), there is little work investigating the phase noise effect on MIMO-UFMC. In this paper, we study the MIMO-UFMC systems in the presence of phase noise and with/without mutual coupling effect. A phase noise mitigation scheme for MIMO-UFMC systems is presented. The scheme does not require detailed knowledge of the phase noise statistics and can effectively mitigate the phase noise within each UFMC symbol. Moreover, it is shown that at small antenna separations, the performance of the MIMO-UFMC system taking the mutual coupling effect into account is better than that when the mutual coupling effect is overlooked.
Thosar, Archana; Patra, Amit; Bhattacharyya, Souvik
2008-07-01
Design of a nonlinear control system for a Variable Air Volume Air Conditioning (VAVAC) plant through feedback linearization is presented in this article. VAVAC systems attempt to reduce building energy consumption while maintaining the primary role of air conditioning. The temperature of the space is maintained at a constant level by establishing a balance between the cooling load generated in the space and the air supply delivered to meet the load. The dynamic model of a VAVAC plant is derived and formulated as a MIMO bilinear system. Feedback linearization is applied for decoupling and linearization of the nonlinear model. Simulation results for a laboratory scale plant are presented to demonstrate the potential of keeping comfort and maintaining energy optimal performance by this methodology. Results obtained with a conventional PI controller and a feedback linearizing controller are compared and the superiority of the proposed approach is clearly established.
Nonlinear Modeling and Control of a Propellant Mixer
NASA Technical Reports Server (NTRS)
Barbieri, Enrique; Richter, Hanz; Figueroa, Fernando
2003-01-01
A mixing chamber used in rocket engine combustion testing at NASA Stennis Space Center is modeled by a second order nonlinear MIMO system. The mixer is used to condition the thermodynamic properties of cryogenic liquid propellant by controlled injection of the same substance in the gaseous phase. The three inputs of the mixer are the positions of the valves regulating the liquid and gas flows at the inlets, and the position of the exit valve regulating the flow of conditioned propellant. The outputs to be tracked and/or regulated are mixer internal pressure, exit mass flow, and exit temperature. The outputs must conform to test specifications dictated by the type of rocket engine or component being tested downstream of the mixer. Feedback linearization is used to achieve tracking and regulation of the outputs. It is shown that the system is minimum-phase provided certain conditions on the parameters are satisfied. The conditions are shown to have physical interpretation.
Li, Yanan; Yang, Chenguang; Ge, Shuzhi Sam; Lee, Tong Heng
2011-04-01
In this paper, adaptive neural network (NN) control is investigated for a class of block triangular multiinput-multioutput nonlinear discrete-time systems with each subsystem in pure-feedback form with unknown control directions. These systems are of couplings in every equation of each subsystem, and different subsystems may have different orders. To avoid the noncausal problem in the control design, the system is transformed into a predictor form by rigorous derivation. By exploring the properties of the block triangular form, implicit controls are developed for each subsystem such that the couplings of inputs and states among subsystems have been completely decoupled. The radial basis function NN is employed to approximate the unknown control. Each subsystem achieves a semiglobal uniformly ultimately bounded stability with the proposed control, and simulation results are presented to demonstrate its efficiency.
Choi, Yun Ho; Yoo, Sung Jin
2017-03-28
A minimal-approximation-based distributed adaptive consensus tracking approach is presented for strict-feedback multiagent systems with unknown heterogeneous nonlinearities and control directions under a directed network. Existing approximation-based consensus results for uncertain nonlinear multiagent systems in lower-triangular form have used multiple function approximators in each local controller to approximate unmatched nonlinearities of each follower. Thus, as the follower's order increases, the number of the approximators used in its local controller increases. However, the proposed approach employs only one function approximator to construct the local controller of each follower regardless of the order of the follower. The recursive design methodology using a new error transformation is derived for the proposed minimal-approximation-based design. Furthermore, a bounding lemma on parameters of Nussbaum functions is presented to handle the unknown control direction problem in the minimal-approximation-based distributed consensus tracking framework and the stability of the overall closed-loop system is rigorously analyzed in the Lyapunov sense.
NASA Astrophysics Data System (ADS)
Kang, Shuo; Yan, Hao; Dong, Lijing; Li, Changchun
2018-03-01
This paper addresses the force tracking problem of electro-hydraulic load simulator under the influence of nonlinear friction and uncertain disturbance. A nonlinear system model combined with the improved generalized Maxwell-slip (GMS) friction model is firstly derived to describe the characteristics of load simulator system more accurately. Then, by using particle swarm optimization (PSO) algorithm combined with the system hysteresis characteristic analysis, the GMS friction parameters are identified. To compensate for nonlinear friction and uncertain disturbance, a finite-time adaptive sliding mode control method is proposed based on the accurate system model. This controller has the ability to ensure that the system state moves along the nonlinear sliding surface to steady state in a short time as well as good dynamic properties under the influence of parametric uncertainties and disturbance, which further improves the force loading accuracy and rapidity. At the end of this work, simulation and experimental results are employed to demonstrate the effectiveness of the proposed sliding mode control strategy.
Yang, Xiong; He, Haibo
2018-05-26
In this paper, we develop a novel optimal control strategy for a class of uncertain nonlinear systems with unmatched interconnections. To begin with, we present a stabilizing feedback controller for the interconnected nonlinear systems by modifying an array of optimal control laws of auxiliary subsystems. We also prove that this feedback controller ensures a specified cost function to achieve optimality. Then, under the framework of adaptive critic designs, we use critic networks to solve the Hamilton-Jacobi-Bellman equations associated with auxiliary subsystem optimal control laws. The critic network weights are tuned through the gradient descent method combined with an additional stabilizing term. By using the newly established weight tuning rules, we no longer need the initial admissible control condition. In addition, we demonstrate that all signals in the closed-loop auxiliary subsystems are stable in the sense of uniform ultimate boundedness by using classic Lyapunov techniques. Finally, we provide an interconnected nonlinear plant to validate the present control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.
A robust adaptive observer for a class of singular nonlinear uncertain systems
NASA Astrophysics Data System (ADS)
Arefinia, Elaheh; Talebi, Heidar Ali; Doustmohammadi, Ali
2017-05-01
This paper proposes a robust adaptive observer for a class of singular nonlinear non-autonomous uncertain systems with unstructured unknown system and derivative matrices, and unknown bounded nonlinearities. Unlike many existing observers, no strong assumption such as Lipschitz condition is imposed on the recommended system. An augmented system is constructed, and the unknown bounds are calculated online using adaptive bounding technique. Considering the continuous nonlinear gain removes the chattering which may appear in practical applications such as analysis of electrical circuits and estimation of interaction force in beating heart robotic-assisted surgery. Moreover, a simple yet precise structure is attained which is easy to implement in many systems with significant uncertainties. The existence conditions of the standard form observer are obtained in terms of linear matrix inequality and the constrained generalised Sylvester's equations, and global stability is ensured. Finally, simulation results are obtained to evaluate the performance of the proposed estimator and demonstrate the effectiveness of the developed scheme.
NASA Astrophysics Data System (ADS)
Roux Oliveira, Tiago; Jacoud Peixoto, Alessandro; Hsu, Liu
2015-09-01
This paper addresses the design of a sliding mode controller for a class of high-order uncertain nonlinear plants with unmatched state-dependent nonlinearities and unknown sign of the high frequency gain, i.e., the control direction is assumed unknown. Differently from most previous studies, the control direction is allowed to switch its sign. We show that it is possible to obtain global exact tracking using only output-feedback by coupling a relay periodic switching function with a norm state observer. One significant advantage of the new scheme is its robustness and improved transient response under arbitrary changes of the control direction which have been theoretically demonstrated for jump variations and successfully tested by simulations. The proposed controller is also evaluated with a DC motor control experiment.
Ren, Yongxiong; Wang, Zhe; Xie, Guodong; Li, Long; Willner, Asher J; Cao, Yinwen; Zhao, Zhe; Yan, Yan; Ahmed, Nisar; Ashrafi, Nima; Ashrafi, Solyman; Bock, Robert; Tur, Moshe; Willner, Alan E
2016-06-01
We explore the mitigation of atmospheric turbulence effects for orbital angular momentum (OAM)-based free-space optical (FSO) communications with multiple-input multiple-output (MIMO) architecture. Such a system employs multiple spatially separated aperture elements at the transmitter/receiver, and each transmitter aperture contains multiplexed data-carrying OAM beams. We propose to use spatial diversity combined with MIMO equalization to mitigate both weak and strong turbulence distortions. In a 2×2 FSO link with each transmitter aperture containing two multiplexed OAM modes of ℓ=+1 and ℓ=+3, we experimentally show that at least two OAM data channels could be recovered under both weak and strong turbulence distortions using selection diversity assisted with MIMO equalization.
Global adaptive control for uncertain nonaffine nonlinear hysteretic systems.
Liu, Yong-Hua; Huang, Liangpei; Xiao, Dongming; Guo, Yong
2015-09-01
In this paper, the global output tracking is investigated for a class of uncertain nonlinear hysteretic systems with nonaffine structures. By combining the solution properties of the hysteresis model with the novel backstepping approach, a robust adaptive control algorithm is developed without constructing a hysteresis inverse. The proposed control scheme is further modified to tackle the bounded disturbances by adaptively estimating their bounds. It is rigorously proven that the designed adaptive controllers can guarantee global stability of the closed-loop system. Two numerical examples are provided to show the effectiveness of the proposed control schemes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Underwater Acoustic Propagation and Communications: A Coupled Research Program
2015-06-15
coding technique suitable for both SIMO and MIMO systems. 4. an adaptive OFDM modulation technique, whereby the transmitter acts in response to...timate based adaptation for SIMO and MIMO systems in a interactive turbo-equalization framework were developed and analyzed. MIMO and SISO
NASA Astrophysics Data System (ADS)
Zhu, Yi-Jun; Liang, Wang-Feng; Wang, Chao; Wang, Wen-Ya
2017-01-01
In this paper, space-collaborative constellations (SCCs) for indoor multiple-input multiple-output (MIMO) visible light communication (VLC) systems are considered. Compared with traditional VLC MIMO techniques, such as repetition coding (RC), spatial modulation (SM) and spatial multiplexing (SMP), SCC achieves the minimum average optical power for a fixed minimum Euclidean distance. We have presented a unified SCC structure for 2×2 MIMO VLC systems and extended it to larger MIMO VLC systems with more transceivers. Specifically for 2×2 MIMO VLC, a fast decoding algorithm is developed with decoding complexity almost linear in terms of the square root of the cardinality of SCC, and the expressions of symbol error rate of SCC are presented. In addition, bit mappings similar to Gray mapping are proposed for SCC. Computer simulations are performed to verify the fast decoding algorithm and the performance of SCC, and the results demonstrate that the performance of SCC is better than those of RC, SM and SMP for indoor channels in general.
Precoded spatial multiplexing MIMO system with spatial component interleaver.
Gao, Xiang; Wu, Zhanji
In this paper, the performance of precoded bit-interleaved coded modulation (BICM) spatial multiplexing multiple-input multiple-output (MIMO) system with spatial component interleaver is investigated. For the ideal precoded spatial multiplexing MIMO system with spatial component interleaver based on singular value decomposition (SVD) of the MIMO channel, the average pairwise error probability (PEP) of coded bits is derived. Based on the PEP analysis, the optimum spatial Q-component interleaver design criterion is provided to achieve the minimum error probability. For the limited feedback precoded proposed scheme with linear zero forcing (ZF) receiver, in order to minimize a bound on the average probability of a symbol vector error, a novel effective signal-to-noise ratio (SNR)-based precoding matrix selection criterion and a simplified criterion are proposed. Based on the average mutual information (AMI)-maximization criterion, the optimal constellation rotation angles are investigated. Simulation results indicate that the optimized spatial multiplexing MIMO system with spatial component interleaver can achieve significant performance advantages compared to the conventional spatial multiplexing MIMO system.
Waveform-Diverse Multiple-Input Multiple-Output Radar Imaging Measurements
NASA Astrophysics Data System (ADS)
Stewart, Kyle B.
Multiple-input multiple-output (MIMO) radar is an emerging set of technologies designed to extend the capabilities of multi-channel radar systems. While conventional radar architectures emphasize the use of antenna array beamforming to maximize real-time power on target, MIMO radar systems instead attempt to preserve some degree of independence between their received signals and to exploit this expanded matrix of target measurements in the signal-processing domain. Specifically the use of sparse “virtual” antenna arrays may allow MIMO radars to achieve gains over traditional multi-channel systems by post-processing diverse received signals to implement both transmit and receive beamforming at all points of interest within a given scene. MIMO architectures have been widely examined for use in radar target detection, but these systems may yet be ideally suited to real and synthetic aperture radar imaging applications where their proposed benefits include improved resolutions, expanded area coverage, novel modes of operation, and a reduction in hardware size, weight, and cost. While MIMO radar's theoretical benefits have been well established in the literature, its practical limitations have not received great attention thus far. The effective use of MIMO radar techniques requires a diversity of signals, and to date almost all MIMO system demonstrations have made use of time-staggered transmission to satisfy this requirement. Doing so is reliable but can be prohibitively slow. Waveform-diverse systems have been proposed as an alternative in which multiple, independent waveforms are broadcast simultaneously over a common bandwidth and separated on receive using signal processing. Operating in this way is much faster than its time-diverse equivalent, but finding a set of suitable waveforms for this technique has proven to be a difficult problem. In light of this, many have questioned the practicality of MIMO radar imaging and whether or not its theoretical benefits may be extended to real systems. Work in this writing focuses specifically on the practical aspects of MIMO radar imaging systems and provides performance data sourced from experimental measurements made using a four-channel software-defined MIMO radar platform. Demonstrations of waveform-diverse imaging data products are provided and compared directly against time-diverse equivalents in order to assess the performance of prospective MIMO waveforms. These are sourced from the pseudo-noise, short-term shift orthogonal, and orthogonal frequency multiplexing signal families while experimental results demonstrate waveform-diverse measurements of polarimetric radar cross section, top-down stationary target images, and finally volumetric MIMO synthetic aperture radar imagery. The data presented represents some of the first available concerning the overall practicality of waveform-diverse MIMO radar architectures, and results suggest that such configurations may achieve a reasonable degree of performance even in the presence of significant practical limitations.
On Non-Linear Sensitivity of Marine Biological Models to Parameter Variations
2007-01-01
M.B., 2002. Understanding uncertain enviromental systems. In: Grasman, J., van Straten, G. (Eds.), Predictability and Nonlinear Modelling in Natural...model evaluations to compute sensitivity indices. Comput. Phys. Commun. 145, 280–297. Saltelli, A., Andres, T.H., Homma, T., 1993. Some new techniques
Bellman Continuum (3rd) International Workshop (13-14 June 1988)
1988-06-01
Modelling Uncertain Problem ................. 53 David Bensoussan ,---,>Asymptotic Linearization of Uncertain Multivariable Systems by Sliding Modes...K. Ghosh .-. Robust Model Tracking for a Class of Singularly Perturbed Nonlinear Systems via Composite Control ....... 93 F. Garofalo and L. Glielmo...MODELISATION ET COMMANDE EN ECONOMIE MODELS AND CONTROL POLICIES IN ECONOMICS Qualitative Differential Games : A Viability Approach ............. 117
Active Cooperation Between Primary Users and Cognitive Radio Users in Heterogeneous Ad-Hoc Networks
2012-04-01
processing to wireless communications and networking, including space-time coding and modulation for MIMO wireless communications, MIMO - OFDM systems, and...multiinput-multioutput ( MIMO ) system that can significantly increase the link capacity and realize a new form of spatial diversity which has been termed
Evaluation of the Performance of the Distributed Phased-MIMO Sonar.
Pan, Xiang; Jiang, Jingning; Wang, Nan
2017-01-11
A broadband signal model is proposed for a distributed multiple-input multiple-output (MIMO) sonar system consisting of two transmitters and a receiving linear array. Transmitters are widely separated to illuminate the different aspects of an extended target of interest. The beamforming technique is utilized at the reception ends for enhancement of weak target echoes. A MIMO detector is designed with the estimated target position parameters within the general likelihood rate test (GLRT) framework. For the high signal-to-noise ratio case, the detection performance of the MIMO system is better than that of the phased-array system in the numerical simulations and the tank experiments. The robustness of the distributed phased-MIMO sonar system is further demonstrated in localization of a target in at-lake experiments.
Evaluation of the Performance of the Distributed Phased-MIMO Sonar
Pan, Xiang; Jiang, Jingning; Wang, Nan
2017-01-01
A broadband signal model is proposed for a distributed multiple-input multiple-output (MIMO) sonar system consisting of two transmitters and a receiving linear array. Transmitters are widely separated to illuminate the different aspects of an extended target of interest. The beamforming technique is utilized at the reception ends for enhancement of weak target echoes. A MIMO detector is designed with the estimated target position parameters within the general likelihood rate test (GLRT) framework. For the high signal-to-noise ratio case, the detection performance of the MIMO system is better than that of the phased-array system in the numerical simulations and the tank experiments. The robustness of the distributed phased-MIMO sonar system is further demonstrated in localization of a target in at-lake experiments. PMID:28085071
Shaddad, R Q; Mohammad, A B; Al-Gailani, S A; Al-Hetar, A M
2014-01-01
The optical fiber is well adapted to pass multiple wireless signals having different carrier frequencies by using radio-over-fiber (ROF) technique. However, multiple wireless signals which have the same carrier frequency cannot propagate over a single optical fiber, such as wireless multi-input multi-output (MIMO) signals feeding multiple antennas in the fiber wireless (FiWi) system. A novel optical frequency upconversion (OFU) technique is proposed to solve this problem. In this paper, the novel OFU approach is used to transmit three wireless MIMO signals over a 20 km standard single mode fiber (SMF). The OFU technique exploits one optical source to produce multiple wavelengths by delivering it to a LiNbO3 external optical modulator. The wireless MIMO signals are then modulated by LiNbO3 optical intensity modulators separately using the generated optical carriers from the OFU process. These modulators use the optical single-sideband with carrier (OSSB+C) modulation scheme to optimize the system performance against the fiber dispersion effect. Each wireless MIMO signal is with a 2.4 GHz or 5 GHz carrier frequency, 1 Gb/s data rate, and 16-quadrature amplitude modulation (QAM). The crosstalk between the wireless MIMO signals is highly suppressed, since each wireless MIMO signal is carried on a specific optical wavelength.
Wang, Jianhui; Liu, Zhi; Chen, C L Philip; Zhang, Yun
2017-10-12
Hysteresis exists ubiquitously in physical actuators. Besides, actuator failures/faults may also occur in practice. Both effects would deteriorate the transient tracking performance, and even trigger instability. In this paper, we consider the problem of compensating for actuator failures and input hysteresis by proposing a fuzzy control scheme for stochastic nonlinear systems. Compared with the existing research on stochastic nonlinear uncertain systems, it is found that how to guarantee a prescribed transient tracking performance when taking into account actuator failures and hysteresis simultaneously also remains to be answered. Our proposed control scheme is designed on the basis of the fuzzy logic system and backstepping techniques for this purpose. It is proven that all the signals remain bounded and the tracking error is ensured to be within a preestablished bound with the failures of hysteretic actuator. Finally, simulations are provided to illustrate the effectiveness of the obtained theoretical results.
Genetics-based control of a mimo boiler-turbine plant
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dimeo, R.M.; Lee, K.Y.
1994-12-31
A genetic algorithm is used to develop an optimal controller for a non-linear, multi-input/multi-output boiler-turbine plant. The algorithm is used to train a control system for the plant over a wide operating range in an effort to obtain better performance. The results of the genetic algorithm`s controller designed from the linearized plant model at a nominal operating point. Because the genetic algorithm is well-suited to solving traditionally difficult optimization problems it is found that the algorithm is capable of developing the controller based on input/output information only. This controller achieves a performance comparable to the standard linear quadratic regulator.
Boiler-turbine control system design using a genetic algorithm
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dimeo, R.; Lee, K.Y.
1995-12-01
This paper discusses the application of a genetic algorithm to control system design for a boiler-turbine plant. In particular the authors study the ability of the genetic algorithm to develop a proportional-integral (PI) controller and a state feedback controller for a non-linear multi-input/multi-output (MIMO) plant model. The plant model is presented along with a discussion of the inherent difficulties in such controller development. A sketch of the genetic algorithm (GA) is presented and its strategy as a method of control system design is discussed. Results are presented for two different control systems that have been designed with the genetic algorithm.
Neural dynamic optimization for control systems. I. Background.
Seong, C Y; Widrow, B
2001-01-01
The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the background and motivations for the development of NDO, while the two other subsequent papers of this topic present the theory of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.
Neural dynamic optimization for control systems.III. Applications.
Seong, C Y; Widrow, B
2001-01-01
For pt.II. see ibid., p. 490-501. The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper demonstrates NDO with several applications including control of autonomous vehicles and of a robot-arm, while the two other companion papers of this topic describes the background for the development of NDO and present the theory of the method, respectively.
Neural dynamic optimization for control systems.II. Theory.
Seong, C Y; Widrow, B
2001-01-01
The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the theory of NDO, while the two other companion papers of this topic explain the background for the development of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.
He, Jiale; Li, Borui; Deng, Lei; Tang, Ming; Gan, Lin; Fu, Songnian; Shum, Perry Ping; Liu, Deming
2016-06-13
In this paper, the feasibility of space division multiplexing for optical wireless fronthaul systems is experimentally demonstrated by implementing high speed MIMO-OFDM/OQAM radio signals over 20km 7-core fiber and 0.4m wireless link. Moreover, the impact of optical inter-core crosstalk in multicore fibers on the proposed MIMO-OFDM/OQAM radio over fiber system is experimentally evaluated in both SISO and MIMO configurations for comparison. The experimental results show that the inter-core crosstalk tolerance of the proposed radio over fiber system can be relaxed to -10 dB by using the proposed MIMO-OFDM/OQAM processing. These results could guide high density multicore fiber design to support a large number of antenna modules and a higher density of radio-access points for potential applications in 5G cellular system.
Physical layer security in fiber-optic MIMO-SDM systems: An overview
NASA Astrophysics Data System (ADS)
Guan, Kyle; Cho, Junho; Winzer, Peter J.
2018-02-01
Fiber-optic transmission systems provide large capacities over enormous distances but are vulnerable to simple eavesdropping attacks at the physical layer. We classify key-based and keyless encryption and physical layer security techniques and discuss them in the context of optical multiple-input-multiple-output space-division multiplexed (MIMO-SDM) fiber-optic communication systems. We show that MIMO-SDM not only increases system capacity, but also ensures the confidentiality of information transmission. Based on recent numerical and experimental results, we review how the unique channel characteristics of MIMO-SDM can be exploited to provide various levels of physical layer security.
2015-04-01
MIMO cohérents ou co-localisés, pour obtenir une compréhen- sion précise de leurs bénéfices potentiels. Le diagramme de rayonnement de l’antenne...d’expérimentations et de simulations (MESA), sont également discutés. On y trouve que les faisceaux principaux des diagrammes de rayonnement expérimen- taux...concordent avec ceux des diagrammes théoriques. On y montre que MIMO-1 a le même diagramme de rayonnement bidirectionel que la configuration radar à
2015-02-01
MIMO cohérents ou co-localisés, pour obtenir une compréhen- sion précise de leurs bénéfices potentiels. Le diagramme de rayonnement de l’antenne...d’expérimentations et de simulations (MESA), sont également discutés. On y trouve que les faisceaux principaux des diagrammes de rayonnement expérimen- taux...concordent avec ceux des diagrammes théoriques. On y montre que MIMO-1 a le même diagramme de rayonnement bidirectionel que la configuration radar à
2015-03-01
MIMO cohérents ou co-localisés, pour obtenir une compréhen- sion précise de leurs bénéfices potentiels. Le diagramme de rayonnement de l’antenne...d’expérimentations et de simulations (MESA), sont également discutés. On y trouve que les faisceaux principaux des diagrammes de rayonnement expérimen- taux...concordent avec ceux des diagrammes théoriques. On y montre que MIMO-1 a le même diagramme de rayonnement bidirectionel que la configuration radar à
Shaddad, R. Q.; Mohammad, A. B.; Al-Gailani, S. A.; Al-Hetar, A. M.
2014-01-01
The optical fiber is well adapted to pass multiple wireless signals having different carrier frequencies by using radio-over-fiber (ROF) technique. However, multiple wireless signals which have the same carrier frequency cannot propagate over a single optical fiber, such as wireless multi-input multi-output (MIMO) signals feeding multiple antennas in the fiber wireless (FiWi) system. A novel optical frequency upconversion (OFU) technique is proposed to solve this problem. In this paper, the novel OFU approach is used to transmit three wireless MIMO signals over a 20 km standard single mode fiber (SMF). The OFU technique exploits one optical source to produce multiple wavelengths by delivering it to a LiNbO3 external optical modulator. The wireless MIMO signals are then modulated by LiNbO3 optical intensity modulators separately using the generated optical carriers from the OFU process. These modulators use the optical single-sideband with carrier (OSSB+C) modulation scheme to optimize the system performance against the fiber dispersion effect. Each wireless MIMO signal is with a 2.4 GHz or 5 GHz carrier frequency, 1 Gb/s data rate, and 16-quadrature amplitude modulation (QAM). The crosstalk between the wireless MIMO signals is highly suppressed, since each wireless MIMO signal is carried on a specific optical wavelength. PMID:24772009
MURI: Impact of Oceanographic Variability on Acoustic Communications
2011-09-01
multiplexing ( OFDM ), multiple- input/multiple-output ( MIMO ) transmissions, and multi-user single-input/multiple-output (SIMO) communications. Lastly... MIMO - OFDM communications: Receiver design for Doppler distorted underwater acoustic channels,” Proc. Asilomar Conf. on Signals, Systems, and... MIMO ) will be of particular interest. Validating experimental data will be obtained during the ONR acoustic communications experiment in summer 2008
Hammad, Mohanad M; Elshenawy, Ahmed K; El Singaby, M I
2017-01-01
In this work a design for self-tuning non-linear Fuzzy Proportional Integral Derivative (FPID) controller is presented to control position and speed of Multiple Input Multiple Output (MIMO) fully-actuated Autonomous Underwater Vehicles (AUV) to follow desired trajectories. Non-linearity that results from the hydrodynamics and the coupled AUV dynamics makes the design of a stable controller a very difficult task. In this study, the control scheme in a simulation environment is validated using dynamic and kinematic equations for the AUV model and hydrodynamic damping equations. An AUV configuration with eight thrusters and an inverse kinematic model from a previous work is utilized in the simulation. In the proposed controller, Mamdani fuzzy rules are used to tune the parameters of the PID. Nonlinear fuzzy Gaussian membership functions are selected to give better performance and response in the non-linear system. A control architecture with two feedback loops is designed such that the inner loop is for velocity control and outer loop is for position control. Several test scenarios are executed to validate the controller performance including different complex trajectories with and without injection of ocean current disturbances. A comparison between the proposed FPID controller and the conventional PID controller is studied and shows that the FPID controller has a faster response to the reference signal and more stable behavior in a disturbed non-linear environment.
Elshenawy, Ahmed K.; El Singaby, M.I.
2017-01-01
In this work a design for self-tuning non-linear Fuzzy Proportional Integral Derivative (FPID) controller is presented to control position and speed of Multiple Input Multiple Output (MIMO) fully-actuated Autonomous Underwater Vehicles (AUV) to follow desired trajectories. Non-linearity that results from the hydrodynamics and the coupled AUV dynamics makes the design of a stable controller a very difficult task. In this study, the control scheme in a simulation environment is validated using dynamic and kinematic equations for the AUV model and hydrodynamic damping equations. An AUV configuration with eight thrusters and an inverse kinematic model from a previous work is utilized in the simulation. In the proposed controller, Mamdani fuzzy rules are used to tune the parameters of the PID. Nonlinear fuzzy Gaussian membership functions are selected to give better performance and response in the non-linear system. A control architecture with two feedback loops is designed such that the inner loop is for velocity control and outer loop is for position control. Several test scenarios are executed to validate the controller performance including different complex trajectories with and without injection of ocean current disturbances. A comparison between the proposed FPID controller and the conventional PID controller is studied and shows that the FPID controller has a faster response to the reference signal and more stable behavior in a disturbed non-linear environment. PMID:28683071
A Modal Approach to Compact MIMO Antenna Design
NASA Astrophysics Data System (ADS)
Yang, Binbin
MIMO (Multiple-Input Multiple-Output) technology offers new possibilities for wireless communication through transmission over multiple spatial channels, and enables linear increases in spectral efficiency as the number of the transmitting and receiving antennas increases. However, the physical implementation of such systems in compact devices encounters many physical constraints mainly from the design of multi-antennas. First, an antenna's bandwidth decreases dramatically as its electrical size reduces, a fact known as antenna Q limit; secondly, multiple antennas closely spaced tend to couple with each other, undermining MIMO performance. Though different MIMO antenna designs have been proposed in the literature, there is still a lack of a systematic design methodology and knowledge of performance limits. In this dissertation, we employ characteristic mode theory (CMT) as a powerful tool for MIMO antenna analysis and design. CMT allows us to examine each physical mode of the antenna aperture, and to access its many physical parameters without even exciting the antenna. For the first time, we propose efficient circuit models for MIMO antennas of arbitrary geometry using this modal decomposition technique. Those circuit models demonstrate the powerful physical insight of CMT for MIMO antenna modeling, and simplify MIMO antenna design problem to just the design of specific antenna structural modes and a modal feed network, making possible the separate design of antenna aperture and feeds. We therefore develop a feed-independent shape synthesis technique for optimization of broadband multi-mode apertures. Combining the shape synthesis and circuit modeling techniques for MIMO antennas, we propose a shape-first feed-next design methodology for MIMO antennas, and designed and fabricated two planar MIMO antennas, each occupying an aperture much smaller than the regular size of lambda/2 x lambda/2. Facilitated by the newly developed source formulation for antenna stored energy and recently reported work on antenna Q factor minimization, we extend the minimum Q limit to antennas of arbitrary geometry, and show that given an antenna aperture, any antenna design based on its substructure will result into minimum Q factors larger than or equal to that of the complete structure. This limit is much tighter than Chu's limit based on spherical modes, and applies to antennas of arbitrary geometry. Finally, considering the almost inevitable presence of mutual coupling effects within compact multiport antennas, we develop new decoupling networks (DN) and decoupling network synthesis techniques. An information-theoretic metric, information mismatch loss (Gammainfo), is defined for DN characterization. Based on this metric, the optimization of decoupling networks for broadband system performance is conducted, which demonstrates the limitation of the single-frequency decoupling techniques and room for improvement.
MimoSA: a system for minimotif annotation
2010-01-01
Background Minimotifs are short peptide sequences within one protein, which are recognized by other proteins or molecules. While there are now several minimotif databases, they are incomplete. There are reports of many minimotifs in the primary literature, which have yet to be annotated, while entirely novel minimotifs continue to be published on a weekly basis. Our recently proposed function and sequence syntax for minimotifs enables us to build a general tool that will facilitate structured annotation and management of minimotif data from the biomedical literature. Results We have built the MimoSA application for minimotif annotation. The application supports management of the Minimotif Miner database, literature tracking, and annotation of new minimotifs. MimoSA enables the visualization, organization, selection and editing functions of minimotifs and their attributes in the MnM database. For the literature components, Mimosa provides paper status tracking and scoring of papers for annotation through a freely available machine learning approach, which is based on word correlation. The paper scoring algorithm is also available as a separate program, TextMine. Form-driven annotation of minimotif attributes enables entry of new minimotifs into the MnM database. Several supporting features increase the efficiency of annotation. The layered architecture of MimoSA allows for extensibility by separating the functions of paper scoring, minimotif visualization, and database management. MimoSA is readily adaptable to other annotation efforts that manually curate literature into a MySQL database. Conclusions MimoSA is an extensible application that facilitates minimotif annotation and integrates with the Minimotif Miner database. We have built MimoSA as an application that integrates dynamic abstract scoring with a high performance relational model of minimotif syntax. MimoSA's TextMine, an efficient paper-scoring algorithm, can be used to dynamically rank papers with respect to context. PMID:20565705
A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance.
Zheng, Binqi; Fu, Pengcheng; Li, Baoqing; Yuan, Xiaobing
2018-03-07
The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.
A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance
Zheng, Binqi; Yuan, Xiaobing
2018-01-01
The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results. PMID:29518960
Adaptive control of nonlinear uncertain active suspension systems with prescribed performance.
Huang, Yingbo; Na, Jing; Wu, Xing; Liu, Xiaoqin; Guo, Yu
2015-01-01
This paper proposes adaptive control designs for vehicle active suspension systems with unknown nonlinear dynamics (e.g., nonlinear spring and piece-wise linear damper dynamics). An adaptive control is first proposed to stabilize the vertical vehicle displacement and thus to improve the ride comfort and to guarantee other suspension requirements (e.g., road holding and suspension space limitation) concerning the vehicle safety and mechanical constraints. An augmented neural network is developed to online compensate for the unknown nonlinearities, and a novel adaptive law is developed to estimate both NN weights and uncertain model parameters (e.g., sprung mass), where the parameter estimation error is used as a leakage term superimposed on the classical adaptations. To further improve the control performance and simplify the parameter tuning, a prescribed performance function (PPF) characterizing the error convergence rate, maximum overshoot and steady-state error is used to propose another adaptive control. The stability for the closed-loop system is proved and particular performance requirements are analyzed. Simulations are included to illustrate the effectiveness of the proposed control schemes. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Khallaf, Haitham S.; Garrido-Balsells, José M.; Shalaby, Hossam M. H.; Sampei, Seiichi
2015-12-01
The performance of multiple-input multiple-output free space optical (MIMO-FSO) communication systems, that adopt multipulse pulse position modulation (MPPM) techniques, is analyzed. Both exact and approximate symbol-error rates (SERs) are derived for both cases of uncorrelated and correlated channels. The effects of background noise, receiver shot-noise, and atmospheric turbulence are taken into consideration in our analysis. The random fluctuations of the received optical irradiance, produced by the atmospheric turbulence, is modeled by the widely used gamma-gamma statistical distribution. Uncorrelated MIMO channels are modeled by the α-μ distribution. A closed-form expression for the probability density function of the optical received irradiance is derived for the case of correlated MIMO channels. Using our analytical expressions, the degradation of the system performance with the increment of the correlation coefficients between MIMO channels is corroborated.
Massive MIMO-OFDM indoor visible light communication system downlink architecture design
NASA Astrophysics Data System (ADS)
Lang, Tian; Li, Zening; Chen, Gang
2014-10-01
Multiple-input multiple-output (MIMO) technique is now used in most new broadband communication system, and orthogonal frequency division multiplexing (OFDM) is also utilized within current 4th generation (4G) of mobile telecommunication technology. With MIMO and OFDM combined, visible light communication (VLC) system's diversity gain is increase, yet system capacity for dispersive channels is also enhanced. Moreover, with the emerging massive MIMO-OFDM VLC system, there are significant advantages than smaller systems' such as channel hardening, further increasing of energy efficiency (EE) and spectral efficiency (SE) based on law of large number. This paper addresses one of the major technological challenges, system architecture design, which was solved by semispherical beehive structure (SBS) receiver and so that diversity gain can be identified and applied in Massive MIMO VLC system. Simulation results shows that the proposed design clearly presents a spatial diversity over conventional VLC systems.
Ren, Yongxiong; Wang, Zhe; Xie, Guodong; Li, Long; Cao, Yinwen; Liu, Cong; Liao, Peicheng; Yan, Yan; Ahmed, Nisar; Zhao, Zhe; Willner, Asher; Ashrafi, Nima; Ashrafi, Solyman; Linquist, Roger D; Bock, Robert; Tur, Moshe; Molisch, Andreas F; Willner, Alan E
2015-09-15
We explore the potential of combining the advantages of multiple-input multiple-output (MIMO)-based spatial multiplexing with those of orbital angular momentum (OAM) multiplexing to increase the capacity of free-space optical (FSO) communications. We experimentally demonstrate an 80 Gbit/s FSO system with a 2×2 aperture architecture, in which each transmitter aperture contains two multiplexed data-carrying OAM modes. Inter-channel crosstalk effects are minimized by the OAM beams' inherent orthogonality and by the use of 4×4 MIMO signal processing. Our experimental results show that the bit-error rates can reach below the forward error correction limit of 3.8×10(-3) and the power penalties are less than 3.6 dB for all channels after MIMO processing. This indicates that OAM and MIMO-based spatial multiplexing could be simultaneously utilized, thereby providing the potential to enhance system performance.
Deep-subwavelength Decoupling for MIMO Antennas in Mobile Handsets with Singular Medium.
Xu, Su; Zhang, Ming; Wen, Huailin; Wang, Jun
2017-09-22
Decreasing the mutual coupling between Multi-input Multi-output (MIMO) antenna elements in a mobile handset and achieving a high data rate is a challenging topic as the 5 th -generation (5G) communication age is coming. Conventional decoupling components for MIMO antennas have to be re-designed when the geometries or frequencies of antennas have any adjustment. In this paper, we report a novel metamaterial-based decoupling strategy for MIMO antennas in mobile handsets with wide applicability. The decoupling component is made of subwavelength metal/air layers, which can be treated as singular medium over a broad frequency band. The flexible applicable property of the decoupling strategy is verified with different antennas over different frequency bands with the same metamaterial decoupling element. Finally, 1/100-wavelength 10-dB isolation is demonstrated for a 24-element MIMO antenna in mobile handsets over the frequency band from 4.55 to 4.75 GHz.
Zero-forcing pre-coding for MIMO WiMAX transceivers: Performance analysis and implementation issues
NASA Astrophysics Data System (ADS)
Cattoni, A. F.; Le Moullec, Y.; Sacchi, C.
Next generation wireless communication networks are expected to achieve ever increasing data rates. Multi-User Multiple-Input-Multiple-Output (MU-MIMO) is a key technique to obtain the expected performance, because such a technique combines the high capacity achievable using MIMO channel with the benefits of space division multiple access. In MU-MIMO systems, the base stations transmit signals to two or more users over the same channel, for this reason every user can experience inter-user interference. This paper provides a capacity analysis of an online, interference-based pre-coding algorithm able to mitigate the multi-user interference of the MU-MIMO systems in the context of a realistic WiMAX application scenario. Simulation results show that pre-coding can significantly increase the channel capacity. Furthermore, the paper presents several feasibility considerations for implementation of the analyzed technique in a possible FPGA-based software defined radio.
NASA Astrophysics Data System (ADS)
Li, Y. J.; Kokkinaki, Amalia; Darve, Eric F.; Kitanidis, Peter K.
2017-08-01
The operation of most engineered hydrogeological systems relies on simulating physical processes using numerical models with uncertain parameters and initial conditions. Predictions by such uncertain models can be greatly improved by Kalman-filter techniques that sequentially assimilate monitoring data. Each assimilation constitutes a nonlinear optimization, which is solved by linearizing an objective function about the model prediction and applying a linear correction to this prediction. However, if model parameters and initial conditions are uncertain, the optimization problem becomes strongly nonlinear and a linear correction may yield unphysical results. In this paper, we investigate the utility of one-step ahead smoothing, a variant of the traditional filtering process, to eliminate nonphysical results and reduce estimation artifacts caused by nonlinearities. We present the smoothing-based compressed state Kalman filter (sCSKF), an algorithm that combines one step ahead smoothing, in which current observations are used to correct the state and parameters one step back in time, with a nonensemble covariance compression scheme, that reduces the computational cost by efficiently exploring the high-dimensional state and parameter space. Numerical experiments show that when model parameters are uncertain and the states exhibit hyperbolic behavior with sharp fronts, as in CO2 storage applications, one-step ahead smoothing reduces overshooting errors and, by design, gives physically consistent state and parameter estimates. We compared sCSKF with commonly used data assimilation methods and showed that for the same computational cost, combining one step ahead smoothing and nonensemble compression is advantageous for real-time characterization and monitoring of large-scale hydrogeological systems with sharp moving fronts.
Ocean Variability Effects on Underwater Acoustic Communications
2011-09-01
schemes for accessing wide frequency bands. Compared with OFDM schemes, the multiband MIMO transmission combined with time reversal processing...systems, or multiple- input/multiple-output ( MIMO ) systems, decision feedback equalization and interference cancellation schemes have been integrated...unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 2 MIMO receiver also iterates channel estimation and symbol demodulation with
Optimizing the wireless power transfer over MIMO Channels
NASA Astrophysics Data System (ADS)
Wiedmann, Karsten; Weber, Tobias
2017-09-01
In this paper, the optimization of the power transfer over wireless channels having multiple-inputs and multiple-outputs (MIMO) is studied. Therefore, the transmitter, the receiver and the MIMO channel are modeled as multiports. The power transfer efficiency is described by a Rayleigh quotient, which is a function of the channel's scattering parameters and the incident waves from both transmitter and receiver side. This way, the power transfer efficiency can be maximized analytically by solving a generalized eigenvalue problem, which is deduced from the Rayleigh quotient. As a result, the maximum power transfer efficiency achievable over a given MIMO channel is obtained. This maximum can be used as a performance bound in order to benchmark wireless power transfer systems. Furthermore, the optimal operating point which achieves this maximum will be obtained. The optimal operating point will be described by the complex amplitudes of the optimal incident and reflected waves of the MIMO channel. This supports the design of the optimal transmitter and receiver multiports. The proposed method applies for arbitrary MIMO channels, taking transmitter-side and/or receiver-side cross-couplings in both near- and farfield scenarios into consideration. Special cases are briefly discussed in this paper in order to illustrate the method.
Performance of MIMO-OFDM using convolution codes with QAM modulation
NASA Astrophysics Data System (ADS)
Astawa, I. Gede Puja; Moegiharto, Yoedy; Zainudin, Ahmad; Salim, Imam Dui Agus; Anggraeni, Nur Annisa
2014-04-01
Performance of Orthogonal Frequency Division Multiplexing (OFDM) system can be improved by adding channel coding (error correction code) to detect and correct errors that occur during data transmission. One can use the convolution code. This paper present performance of OFDM using Space Time Block Codes (STBC) diversity technique use QAM modulation with code rate ½. The evaluation is done by analyzing the value of Bit Error Rate (BER) vs Energy per Bit to Noise Power Spectral Density Ratio (Eb/No). This scheme is conducted 256 subcarrier which transmits Rayleigh multipath fading channel in OFDM system. To achieve a BER of 10-3 is required 10dB SNR in SISO-OFDM scheme. For 2×2 MIMO-OFDM scheme requires 10 dB to achieve a BER of 10-3. For 4×4 MIMO-OFDM scheme requires 5 dB while adding convolution in a 4x4 MIMO-OFDM can improve performance up to 0 dB to achieve the same BER. This proves the existence of saving power by 3 dB of 4×4 MIMO-OFDM system without coding, power saving 7 dB of 2×2 MIMO-OFDM and significant power savings from SISO-OFDM system.
NASA Astrophysics Data System (ADS)
Dimas Pristovani, R.; Raden Sanggar, D.; Dadet, Pramadihanto.
2018-04-01
Push recovery is one of humanbehaviorwhich is a strategy to defend the body from anexternal force in any environment. This paper describes push recovery strategy which usesMIMO decoupled control system method. The dynamics system uses aquasi-dynamic system based on triple linear inverted pendulum model (TLIPM). The analysis of TLIPMuses zero moment point (ZMP) calculation from ZMP simplification in last research. By using this simplification of dynamics system, the control design can be simplified into 3 serial SISOwith known and uncertain disturbance models in each inverted pendulum. Each pendulum has different plan to damp the external force effect. In this experiment, PID controller (closed- loop)is used to arrange the damp characteristic.The experiment result shows thatwhen using push recovery control strategy (closed-loop control) is about 85.71% whilewithout using push recovery control strategy (open-loop control) it is about 28.57%.
Application of MIMO Techniques in sky-surface wave hybrid networking sea-state radar system
NASA Astrophysics Data System (ADS)
Zhang, L.; Wu, X.; Yue, X.; Liu, J.; Li, C.
2016-12-01
The sky-surface wave hybrid networking sea-state radar system contains of the sky wave transmission stations at different sites and several surface wave radar stations. The subject comes from the national 863 High-tech Project of China. The hybrid sky-surface wave system and the HF surface wave system work simultaneously and the HF surface wave radar (HFSWR) can work in multi-static and surface-wave networking mode. Compared with the single mode radar system, this system has advantages of better detection performance at the far ranges in ocean dynamics parameters inversion. We have applied multiple-input multiple-output(MIMO) techniques in this sea-state radar system. Based on the multiple channel and non-causal transmit beam-forming techniques, the MIMO radar architecture can reduce the size of the receiving antennas and simplify antenna installation. Besides, by efficiently utilizing the system's available degrees of freedom, it can provide a feasible approach for mitigating multipath effect and Doppler-spread clutter in Over-the-horizon Radar. In this radar, slow-time phase-coded MIMO method is used. The transmitting waveforms are phase-coded in slow-time so as to be orthogonal after Doppler processing at the receiver. So the MIMO method can be easily implemented without the need to modify the receiver hardware. After the radar system design, the MIMO experiments of this system have been completed by Wuhan University during 2015 and 2016. The experiment used Wuhan multi-channel ionospheric sounding system(WMISS) as sky-wave transmitting source and three dual-frequency HFSWR developed by the Oceanography Laboratory of Wuhan University. The transmitter system located at Chongyang with five element linear equi-spaced antenna array and Wuhan with one log-periodic antenna. The RF signals are generated by synchronized, but independent digital waveform generators - providing complete flexibility in element phase and amplitude control, and waveform type and parameters. The field experimental results show the presented method is effective. The echoes are obvious and distinguishable both in co-located MIMO mode and widely distributed MIMO mode. Key words: sky-surface wave hybrid networking; sea-state radar; MIMO; phase-coded
NASA Technical Reports Server (NTRS)
Klingelhoefer, G.; Morris, R. V.; Blumers, M.; Bernhardt, B.; Graff, T.
2011-01-01
For the advanced Moessbauer instrument MIMOS IIA, the new detector technologies and electronic components increase sensitivity and performance significantly. In combination with the high energy resolution of the SDD it is possible to perform X-ray fluorescence analysis simultaneously to Moessbauer spectroscopy. In addition to the Fe-mineralogy, information on the sample's elemental composition will be gathered. The ISRU 2010 field campaign demonstrated that in-situ Moessbauer spectroscopy is an effective tool for both science and feedstock exploration and process monitoring. Engineering tests showed that a compact nickel metal hydride battery provided sufficient power for over 12 hr of continuous operation for the MIMOS instruments.
A comparison of optimal MIMO linear and nonlinear models for brain machine interfaces
NASA Astrophysics Data System (ADS)
Kim, S.-P.; Sanchez, J. C.; Rao, Y. N.; Erdogmus, D.; Carmena, J. M.; Lebedev, M. A.; Nicolelis, M. A. L.; Principe, J. C.
2006-06-01
The field of brain-machine interfaces requires the estimation of a mapping from spike trains collected in motor cortex areas to the hand kinematics of the behaving animal. This paper presents a systematic investigation of several linear (Wiener filter, LMS adaptive filters, gamma filter, subspace Wiener filters) and nonlinear models (time-delay neural network and local linear switching models) applied to datasets from two experiments in monkeys performing motor tasks (reaching for food and target hitting). Ensembles of 100-200 cortical neurons were simultaneously recorded in these experiments, and even larger neuronal samples are anticipated in the future. Due to the large size of the models (thousands of parameters), the major issue studied was the generalization performance. Every parameter of the models (not only the weights) was selected optimally using signal processing and machine learning techniques. The models were also compared statistically with respect to the Wiener filter as the baseline. Each of the optimization procedures produced improvements over that baseline for either one of the two datasets or both.
A comparison of optimal MIMO linear and nonlinear models for brain-machine interfaces.
Kim, S-P; Sanchez, J C; Rao, Y N; Erdogmus, D; Carmena, J M; Lebedev, M A; Nicolelis, M A L; Principe, J C
2006-06-01
The field of brain-machine interfaces requires the estimation of a mapping from spike trains collected in motor cortex areas to the hand kinematics of the behaving animal. This paper presents a systematic investigation of several linear (Wiener filter, LMS adaptive filters, gamma filter, subspace Wiener filters) and nonlinear models (time-delay neural network and local linear switching models) applied to datasets from two experiments in monkeys performing motor tasks (reaching for food and target hitting). Ensembles of 100-200 cortical neurons were simultaneously recorded in these experiments, and even larger neuronal samples are anticipated in the future. Due to the large size of the models (thousands of parameters), the major issue studied was the generalization performance. Every parameter of the models (not only the weights) was selected optimally using signal processing and machine learning techniques. The models were also compared statistically with respect to the Wiener filter as the baseline. Each of the optimization procedures produced improvements over that baseline for either one of the two datasets or both.
Control strategies for systems with limited actuators
NASA Technical Reports Server (NTRS)
Marcopoli, Vincent R.; Phillips, Stephen M.
1994-01-01
This work investigates the effects of actuator saturation in multi-input, multi-output (MIMO) control systems. The adverse system behavior introduced by the saturation nonlinearity is viewed here as resulting from two mechanisms: controller windup - a problem caused by the discrepancy between the limited actuator commands and the corresponding control signals, and directionality - the problem of how to use nonlimited actuators when a limited condition exists. The tracking mode and Hanus methods are two common strategies for dealing with the windup problem. It is seen that while these methods alleviate windup, performance problems remain due to plant directionality. Though high gain conventional antiwindup as well as more general linear methods have the potential to address both windup and directionality, no systematic design method for these schemes has emerged; most approaches used in practice are application driven. An alternative method of addressing the directionality problem is presented which involves the introduction of a control direction preserving nonlinearity to the Hanus antiwindup system. A nonlinearity is subsequently proposed which reduces the conservation inherent in the former direction-preserving approach, improving performance. The concept of multivariable sensitivity is seen to play a key role in the success of the new method.
Srinivasa, Narayan; Zhang, Deying; Grigorian, Beayna
2014-03-01
This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware.
The analysis of MAI in large scale MIMO-CDMA system
NASA Astrophysics Data System (ADS)
Berceanu, Madalina-Georgiana; Voicu, Carmen; Halunga, Simona
2016-12-01
Recently, technological development imposed a rapid growth in the use of data carried by cellular services, which also implies the necessity of higher data rates and lower latency. To meet the users' demands, it was brought into discussion a series of new data processing techniques. In this paper, we approached the MIMO technology that uses multiple antennas at the receiver and transmitter ends. To study the performances obtained by this technology, we proposed a MIMO-CDMA system, where image transmission has been used instead of random data transmission to take benefit of a larger range of quality indicators. In the simulations we increased the number of antennas, we observed how the performances of the system are modified and, based on that, we were able to make a comparison between a conventional MIMO and a Large Scale MIMO system, in terms of BER and MSSIM index, which is a metric that compares the quality of the image before transmission with the received one.
NASA Astrophysics Data System (ADS)
Taoka, Hidekazu; Kishiyama, Yoshihisa; Higuchi, Kenichi; Sawahashi, Mamoru
This paper presents comparisons between common and dedicated reference signals (RSs) for channel estimation in MIMO multiplexing using codebook-based precoding for orthogonal frequency division multiplexing (OFDM) radio access in the Evolved UTRA downlink with frequency division duplexing (FDD). We clarify the best RS structure for precoding-based MIMO multiplexing based on comparisons of the structures in terms of the achievable throughput taking into account the overhead of the common and dedicated RSs and the precoding matrix indication (PMI) signal. Based on extensive simulations on the throughput in 2-by-2 and 4-by-4 MIMO multiplexing with precoding, we clarify that channel estimation based on common RSs multiplied with the precoding matrix indicated by the PMI signal achieves higher throughput compared to that using dedicated RSs irrespective of the number of spatial multiplexing streams when the number of available precoding matrices, i.e., the codebook size, is less than approximately 16 and 32 for 2-by-2 and 4-by-4 MIMO multiplexing, respectively.
Dimension-Factorized Range Migration Algorithm for Regularly Distributed Array Imaging
Guo, Qijia; Wang, Jie; Chang, Tianying
2017-01-01
The two-dimensional planar MIMO array is a popular approach for millimeter wave imaging applications. As a promising practical alternative, sparse MIMO arrays have been devised to reduce the number of antenna elements and transmitting/receiving channels with predictable and acceptable loss in image quality. In this paper, a high precision three-dimensional imaging algorithm is proposed for MIMO arrays of the regularly distributed type, especially the sparse varieties. Termed the Dimension-Factorized Range Migration Algorithm, the new imaging approach factorizes the conventional MIMO Range Migration Algorithm into multiple operations across the sparse dimensions. The thinner the sparse dimensions of the array, the more efficient the new algorithm will be. Advantages of the proposed approach are demonstrated by comparison with the conventional MIMO Range Migration Algorithm and its non-uniform fast Fourier transform based variant in terms of all the important characteristics of the approaches, especially the anti-noise capability. The computation cost is analyzed as well to evaluate the efficiency quantitatively. PMID:29113083
Cooperative MIMO communication at wireless sensor network: an error correcting code approach.
Islam, Mohammad Rakibul; Han, Young Shin
2011-01-01
Cooperative communication in wireless sensor network (WSN) explores the energy efficient wireless communication schemes between multiple sensors and data gathering node (DGN) by exploiting multiple input multiple output (MIMO) and multiple input single output (MISO) configurations. In this paper, an energy efficient cooperative MIMO (C-MIMO) technique is proposed where low density parity check (LDPC) code is used as an error correcting code. The rate of LDPC code is varied by varying the length of message and parity bits. Simulation results show that the cooperative communication scheme outperforms SISO scheme in the presence of LDPC code. LDPC codes with different code rates are compared using bit error rate (BER) analysis. BER is also analyzed under different Nakagami fading scenario. Energy efficiencies are compared for different targeted probability of bit error p(b). It is observed that C-MIMO performs more efficiently when the targeted p(b) is smaller. Also the lower encoding rate for LDPC code offers better error characteristics.
Unified tensor model for space-frequency spreading-multiplexing (SFSM) MIMO communication systems
NASA Astrophysics Data System (ADS)
de Almeida, André LF; Favier, Gérard
2013-12-01
This paper presents a unified tensor model for space-frequency spreading-multiplexing (SFSM) multiple-input multiple-output (MIMO) wireless communication systems that combine space- and frequency-domain spreadings, followed by a space-frequency multiplexing. Spreading across space (transmit antennas) and frequency (subcarriers) adds resilience against deep channel fades and provides space and frequency diversities, while orthogonal space-frequency multiplexing enables multi-stream transmission. We adopt a tensor-based formulation for the proposed SFSM MIMO system that incorporates space, frequency, time, and code dimensions by means of the parallel factor model. The developed SFSM tensor model unifies the tensorial formulation of some existing multiple-access/multicarrier MIMO signaling schemes as special cases, while revealing interesting tradeoffs due to combined space, frequency, and time diversities which are of practical relevance for joint symbol-channel-code estimation. The performance of the proposed SFSM MIMO system using either a zero forcing receiver or a semi-blind tensor-based receiver is illustrated by means of computer simulation results under realistic channel and system parameters.
NASA Astrophysics Data System (ADS)
Ishihara, Koichi; Asai, Yusuke; Kudo, Riichi; Ichikawa, Takeo; Takatori, Yasushi; Mizoguchi, Masato
2013-12-01
Multiuser multiple-input multiple-output (MU-MIMO) has been proposed as a means to improve spectrum efficiency for various future wireless communication systems. This paper reports indoor experimental results obtained for a newly developed and implemented downlink (DL) MU-MIMO orthogonal frequency division multiplexing (OFDM) transceiver for gigabit wireless local area network systems in the microwave band. In the transceiver, the channel state information (CSI) is estimated at each user and fed back to an access point (AP) on a real-time basis. At the AP, the estimated CSI is used to calculate the transmit beamforming weight for DL MU-MIMO transmission. This paper also proposes a recursive inverse matrix computation scheme for computing the transmit weight in real time. Experiments with the developed transceiver demonstrate its feasibility in a number of indoor scenarios. The experimental results clarify that DL MU-MIMO-OFDM transmission can achieve a 972-Mbit/s transmission data rate with simple digital signal processing of single-antenna users in an indoor environment.
Cooperative MIMO Communication at Wireless Sensor Network: An Error Correcting Code Approach
Islam, Mohammad Rakibul; Han, Young Shin
2011-01-01
Cooperative communication in wireless sensor network (WSN) explores the energy efficient wireless communication schemes between multiple sensors and data gathering node (DGN) by exploiting multiple input multiple output (MIMO) and multiple input single output (MISO) configurations. In this paper, an energy efficient cooperative MIMO (C-MIMO) technique is proposed where low density parity check (LDPC) code is used as an error correcting code. The rate of LDPC code is varied by varying the length of message and parity bits. Simulation results show that the cooperative communication scheme outperforms SISO scheme in the presence of LDPC code. LDPC codes with different code rates are compared using bit error rate (BER) analysis. BER is also analyzed under different Nakagami fading scenario. Energy efficiencies are compared for different targeted probability of bit error pb. It is observed that C-MIMO performs more efficiently when the targeted pb is smaller. Also the lower encoding rate for LDPC code offers better error characteristics. PMID:22163732
Feedforward Tracking Control of Flat Recurrent Fuzzy Systems
NASA Astrophysics Data System (ADS)
Gering, Stefan; Adamy, Jürgen
2014-12-01
Flatness based feedforward control has proven to be a feasible solution for the problem of tracking control, which may be applied to a broad class of nonlinear systems. If a flat output of the system is known, the control is often based on a feedforward controller generating a nominal input in combination with a linear controller stabilizing the linearized error dynamics around the trajectory. We show in this paper that the very same idea may be incorporated for tracking control of MIMO recurrent fuzzy systems. Their dynamics is given by means of linguistic differential equations but may be converted into a hybrid system representation, which then serves as the basis for controller synthesis.
Validation of a new modal performance measure for flexible controllers design
DOE Office of Scientific and Technical Information (OSTI.GOV)
Simo, J.B.; Tahan, S.A.; Kamwa, I.
1996-05-01
A new modal performance measure for power system stabilizer (PSS) optimization is proposed in this paper. The new method is based on modifying the square envelopes of oscillating modes, in order to take into account their damping ratios while minimizing the performance index. This criteria is applied to flexible controllers optimal design, on a multi-input-multi-output (MIMO) reduced-order model of a prototype power system. The multivariable model includes four generators, each having one input and one output. Linear time-response simulation and transient stability analysis with a nonlinear package confirm the superiority of the proposed criteria and illustrate its effectiveness in decentralizedmore » control.« less
2012-09-30
Estimation Methods for Underwater OFDM 5) Two Iterative Receivers for Distributed MIMO - OFDM with Large Doppler Deviations. 6) Asynchronous Multiuser...multi-input multi-output ( MIMO ) OFDM is also pursued, where it is shown that the proposed hybrid initialization enables drastically improved receiver...are investigated. 5) Two Iterative Receivers for Distributed MIMO - OFDM with Large Doppler Deviations. This work studies a distributed system with
Acoustic MIMO communications in a very shallow water channel
NASA Astrophysics Data System (ADS)
Zhou, Yuehai; Cao, Xiuling; Tong, Feng
2015-12-01
Underwater acoustic channels pose significant difficulty for the development of high speed communication due to highly limited band-width as well as hostile multipath interference. Enlightened by rapid progress of multiple input multiple output (MIMO) technologies in wireless communication scenarios, MIMO systems offer a potential solution by enabling multiple spatially parallel communication channels to improve communication performance as well as capacity. For MIMO acoustic communications, deep sea channels offer substantial spatial diversity among multiple channels that can be exploited to address simultaneous multipath and co-channel interference. At the same time, there are increasing requirements for high speed underwater communication in very shallow water area (for example, a depth less than 10 m). In this paper, a space-time multichannel adaptive receiver consisting of multiple decision feedback equalizers (DFE) is adopted as the receiver for a very shallow water MIMO acoustic communication system. The performance of multichannel DFE receivers with relatively small number of receiving elements are analyzed and compared with that of the multichannel time reversal receiver to evaluate the impact of limited spatial diversity on multi-channel equalization and time reversal processing. The results of sea trials in a very shallow water channel are presented to demonstrate the feasibility of very shallow water MIMO acoustic communication.
A Minimized MIMO-UWB Antenna with High Isolation and Triple Band-Notched Functions
NASA Astrophysics Data System (ADS)
Kong, Yuanyuan; Li, Yingsong; Yu, Kai
2016-11-01
A compact high isolation MIMO-UWB antenna with triple frequency rejection bands is proposed for UWB communication applications. The proposed MIMO-UWB antenna consists of two identical UWB antennas and each antenna element has a semicircle ring shaped radiation patch fed by a bend microstrip feeding line for covering the UWB band, which operates from 2.85 GHz to 11.79 GHz with an impedance bandwidth of 122.1 %. By etching a L-shaped slot on the ground plane, and embedding an "anchor" shaped stub into the patch and integrating an open ring under the semicircle shaped radiation patch, three notch bands are realized to suppress WiMAX (3.3-3.6 GHz), WLAN(5.725-5.825 GHz) and uplink of X-band satellite (7.9-8.4 GHz) signals. The high isolation with S21<-20 dB in most UWB band is obtained by adding a protruded decoupling structure. The design procedure of the MIMO-UWB antenna is given in detail. The proposed MIMO-UWB antenna is simulated, fabricated and measured. Experimental results demonstrate that the proposed MIMO-UWB antenna has a stable gain, good impedance match, high isolation, low envelope correlation coefficient and good radiation pattern at the UWB operating band and it can provide three designated notch bands.
Wang, Yingyang; Hu, Jianbo
2018-05-19
An improved prescribed performance controller is proposed for the longitudinal model of an air-breathing hypersonic vehicle (AHV) subject to uncertain dynamics and input nonlinearity. Different from the traditional non-affine model requiring non-affine functions to be differentiable, this paper utilizes a semi-decomposed non-affine model with non-affine functions being locally semi-bounded and possibly in-differentiable. A new error transformation combined with novel prescribed performance functions is proposed to bypass complex deductions caused by conventional error constraint approaches and circumvent high frequency chattering in control inputs. On the basis of backstepping technique, the improved prescribed performance controller with low structural and computational complexity is designed. The methodology guarantees the altitude and velocity tracking error within transient and steady state performance envelopes and presents excellent robustness against uncertain dynamics and deadzone input nonlinearity. Simulation results demonstrate the efficacy of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Model Following and High Order Augmentation for Rotorcraft Control, Applied via Partial Authority
NASA Astrophysics Data System (ADS)
Spires, James Michael
This dissertation consists of two main studies, a few small studies, and design documentation, all aimed at improving rotorcraft control by employing multi-input multi-output (MIMO) command-modelfollowing control as a baseline, together with a selectable (and de-selectable) MIMO high order compensator that augments the baseline. Two methods of MIMO command-model-following control design are compared for rotorcraft flight control. The first, Explicit Model Following (EMF), employs SISO inverse plants with a dynamic decoupling matrix, which is a purely feed-forward approach to inverting the plant. The second is Dynamic Inversion (DI), which involves both feed-forward and feedback path elements to invert the plant. The EMF design is purely linear, while the DI design has some nonlinear elements in vertical rate control. For each of these methods, an architecture is presented that provides angular rate model-following with selectable vertical rate model-following. Implementation challenges of both EMF and DI are covered, and methods of dealing with them are presented. These two MIMO model-following approaches are evaluated regarding (1) fidelity to the command model, and (2) turbulence rejection. Both are found to provide good tracking of commands and reduction of cross coupling. Next, an architecture and design methodology for high order compensator (HOC) augmentation of a baseline controller for rotorcraft is presented. With this architecture, the HOC compensator is selectable and can easily be authority-limited, which might ease certification. Also, the plant for this augmentative MIMO compensator design is a stabilized helicopter system, so good flight test data could be safely gathered for more accurate plant identification. The design methodology is carried out twice on an example helicopter model, once with turbulence rejection as the objective, and once with the additional objective of closely following pilot commands. The turbulence rejection HOC is feedback only (HOC_FB), while the combined objective HOC has both feedback and feedforward elements (HOC_FBFF). The HOC_FB was found to be better at improving turbulence rejection but generally degrades the following of pilot commands. The HOC_FBFF improves turbulence rejection relative to the Baseline controller, but not by as much as HOC_FB. However, HOC_FBFF also generally improves the following of pilot commands. Future work is suggested and facilitated in the areas of DI, MIMO EMF, and HOC augmentation. High frequency dynamics, neglected in the DI design, unexpectedly change the low frequency behavior of the DI-plant system, in addition to the expected change in high frequency dynamics. This dissertation shows why, and suggests a technique for designing a pseudo-command pre-filter that at least partially restores the intended DI-plant dynamics. For EMF, a procedure is presented that avoids use of a reducedorder model, and instead uses a full-order model or even frequency-domain flight test data. With HOC augmentation, future research might investigate the utility of adding an H? constraint to the design objective, which is known as an equal-weighting mixed-norm H2/H infinity design. Because all the formulas in the published literature either require solution of three coupled Riccati Equations (for which there is no readily available tool), or make assumptions that do not fit the present problem, appropriate equalweighting H2/H infinity design formulas are derived which involve two de-coupled Riccati Equations.
Throughput Optimization Via Adaptive MIMO Communications
2006-05-30
End-to-end matlab packet simulation platform. * Low density parity check code (LDPCC). * Field trials with Silvus DSP MIMO testbed. * High mobility...incorporate advanced LDPC (low density parity check) codes . Realizing that the power of LDPC codes come at the price of decoder complexity, we also...Channel Coding Binary Convolution Code or LDPC Packet Length 0 - 216-1, bytes Coding Rate 1/2, 2/3, 3/4, 5/6 MIMO Channel Training Length 0 - 4, symbols
Kwon, Tae-Ho; Kim, Jai-Eun; Kim, Ki-Doo
2018-05-14
In the field of communication, synchronization is always an important issue. The communication between a light-emitting diode (LED) array (LEA) and a camera is known as visual multiple-input multiple-output (MIMO), for which the data transmitter and receiver must be synchronized for seamless communication. In visual-MIMO, LEDs generally have a faster data rate than the camera. Hence, we propose an effective time-sharing-based synchronization technique with its color-independent characteristics providing the key to overcome this synchronization problem in visual-MIMO communication. We also evaluated the performance of our synchronization technique by varying the distance between the LEA and camera. A graphical analysis is also presented to compare the symbol error rate (SER) at different distances.
A Chaos MIMO-OFDM Scheme for Mobile Communication with Physical-Layer Security
NASA Astrophysics Data System (ADS)
Okamoto, Eiji
Chaos communications enable a physical-layer security, which can enhance the transmission security in combining with upper-layer encryption techniques, or can omit the upper-layer secure protocol and enlarges the transmission efficiency. However, the chaos communication usually degrades the error rate performance compared to unencrypted digital modulations. To achieve both physical-layer security and channel coding gain, we have proposed a chaos multiple-input multiple-output (MIMO) scheme in which a rate-one chaos convolution is applied to MIMO multiplexing. However, in the conventional study only flat fading is considered. To apply this scheme to practical mobile environments, i.e., multipath fading channels, we propose a chaos MIMO-orthogonal frequency division multi-plexing (OFDM) scheme and show its effectiveness through computer simulations.
An ICA based MIMO-OFDM VLC scheme
NASA Astrophysics Data System (ADS)
Jiang, Fangqing; Deng, Honggui; Xiao, Wei; Tao, Shaohua; Zhu, Kaicheng
2015-07-01
In this paper, we propose a novel ICA based MIMO-OFDM VLC scheme, where ICA is applied to convert the MIMO-OFDM channel into several SISO-OFDM channels to reduce computational complexity in channel estimation, without any spectral overhead. Besides, the FM is first investigated to further modulate the OFDM symbols to eliminate the correlation of the signals, so as to improve the separation performance of the ICA algorithm. In the 4×4MIMO-OFDM VLC simulation experiment, LOS path and NLOS paths are both considered, each transmitting signal at 100 Mb/s. Simulation results show that the BER of the proposed scheme reaches the 10-5 level at SNR=20 dB, which is a large improvement compared to the traditional schemes.
Liu, Derong; Wang, Ding; Wang, Fei-Yue; Li, Hongliang; Yang, Xiong
2014-12-01
In this paper, the infinite horizon optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems is investigated using neural-network-based online solution of Hamilton-Jacobi-Bellman (HJB) equation. By establishing an appropriate bounded function and defining a modified cost function, the optimal robust guaranteed cost control problem is transformed into an optimal control problem. It can be observed that the optimal cost function of the nominal system is nothing but the optimal guaranteed cost of the original uncertain system. A critic neural network is constructed to facilitate the solution of the modified HJB equation corresponding to the nominal system. More importantly, an additional stabilizing term is introduced for helping to verify the stability, which reinforces the updating process of the weight vector and reduces the requirement of an initial stabilizing control. The uniform ultimate boundedness of the closed-loop system is analyzed by using the Lyapunov approach as well. Two simulation examples are provided to verify the effectiveness of the present control approach.
NASA Astrophysics Data System (ADS)
Wang, W.; Wang, D.; Peng, Z. H.
2017-09-01
Without assuming that the communication topologies among the neural network (NN) weights are to be undirected and the states of each agent are measurable, the cooperative learning NN output feedback control is addressed for uncertain nonlinear multi-agent systems with identical structures in strict-feedback form. By establishing directed communication topologies among NN weights to share their learned knowledge, NNs with cooperative learning laws are employed to identify the uncertainties. By designing NN-based κ-filter observers to estimate the unmeasurable states, a new cooperative learning output feedback control scheme is proposed to guarantee that the system outputs can track nonidentical reference signals with bounded tracking errors. A simulation example is given to demonstrate the effectiveness of the theoretical results.
Robust adaptive uniform exact tracking control for uncertain Euler-Lagrange system
NASA Astrophysics Data System (ADS)
Yang, Yana; Hua, Changchun; Li, Junpeng; Guan, Xinping
2017-12-01
This paper offers a solution to the robust adaptive uniform exact tracking control for uncertain nonlinear Euler-Lagrange (EL) system. An adaptive finite-time tracking control algorithm is designed by proposing a novel nonsingular integral terminal sliding-mode surface. Moreover, a new adaptive parameter tuning law is also developed by making good use of the system tracking errors and the adaptive parameter estimation errors. Thus, both the trajectory tracking and the parameter estimation can be achieved in a guaranteed time adjusted arbitrarily based on practical demands, simultaneously. Additionally, the control result for the EL system proposed in this paper can be extended to high-order nonlinear systems easily. Finally, a test-bed 2-DOF robot arm is set-up to demonstrate the performance of the new control algorithm.
Lee, Byung Moo
2017-12-29
Massive multiple-input multiple-output (MIMO) systems can be applied to support numerous internet of things (IoT) devices using its excessive amount of transmitter (TX) antennas. However, one of the big obstacles for the realization of the massive MIMO system is the overhead of reference signal (RS), because the number of RS is proportional to the number of TX antennas and/or related user equipments (UEs). It has been already reported that antenna group-based RS overhead reduction can be very effective to the efficient operation of massive MIMO, but the method of deciding the number of antennas needed in each group is at question. In this paper, we propose a simplified determination scheme of the number of antennas needed in each group for RS overhead reduced massive MIMO to support many IoT devices. Supporting many distributed IoT devices is a framework to configure wireless sensor networks. Our contribution can be divided into two parts. First, we derive simple closed-form approximations of the achievable spectral efficiency (SE) by using zero-forcing (ZF) and matched filtering (MF) precoding for the RS overhead reduced massive MIMO systems with channel estimation error. The closed-form approximations include a channel error factor that can be adjusted according to the method of the channel estimation. Second, based on the closed-form approximation, we present an efficient algorithm determining the number of antennas needed in each group for the group-based RS overhead reduction scheme. The algorithm depends on the exact inverse functions of the derived closed-form approximations of SE. It is verified with theoretical analysis and simulation that the proposed algorithm works well, and thus can be used as an important tool for massive MIMO systems to support many distributed IoT devices.
Adaptive reconfigurable V-BLAST type equalizer for cognitive MIMO-OFDM radios
NASA Astrophysics Data System (ADS)
Ozden, Mehmet Tahir
2015-12-01
An adaptive channel shortening equalizer design for multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) radio receivers is considered in this presentation. The proposed receiver has desirable features for cognitive and software defined radio implementations. It consists of two sections: MIMO decision feedback equalizer (MIMO-DFE) and adaptive multiple Viterbi detection. In MIMO-DFE section, a complete modified Gram-Schmidt orthogonalization of multichannel input data is accomplished using sequential processing multichannel Givens lattice stages, so that a Vertical Bell Laboratories Layered Space Time (V-BLAST) type MIMO-DFE is realized at the front-end section of the channel shortening equalizer. Matrix operations, a major bottleneck for receiver operations, are accordingly avoided, and only scalar operations are used. A highly modular and regular radio receiver architecture that has a suitable structure for digital signal processing (DSP) chip and field programable gate array (FPGA) implementations, which are important for software defined radio realizations, is achieved. The MIMO-DFE section of the proposed receiver can also be reconfigured for spectrum sensing and positioning functions, which are important tasks for cognitive radio applications. In connection with adaptive multiple Viterbi detection section, a systolic array implementation for each channel is performed so that a receiver architecture with high computational concurrency is attained. The total computational complexity is given in terms of equalizer and desired response filter lengths, alphabet size, and number of antennas. The performance of the proposed receiver is presented for two-channel case by means of mean squared error (MSE) and probability of error evaluations, which are conducted for time-invariant and time-variant channel conditions, orthogonal and nonorthogonal transmissions, and two different modulation schemes.
2017-01-01
Massive multiple-input multiple-output (MIMO) systems can be applied to support numerous internet of things (IoT) devices using its excessive amount of transmitter (TX) antennas. However, one of the big obstacles for the realization of the massive MIMO system is the overhead of reference signal (RS), because the number of RS is proportional to the number of TX antennas and/or related user equipments (UEs). It has been already reported that antenna group-based RS overhead reduction can be very effective to the efficient operation of massive MIMO, but the method of deciding the number of antennas needed in each group is at question. In this paper, we propose a simplified determination scheme of the number of antennas needed in each group for RS overhead reduced massive MIMO to support many IoT devices. Supporting many distributed IoT devices is a framework to configure wireless sensor networks. Our contribution can be divided into two parts. First, we derive simple closed-form approximations of the achievable spectral efficiency (SE) by using zero-forcing (ZF) and matched filtering (MF) precoding for the RS overhead reduced massive MIMO systems with channel estimation error. The closed-form approximations include a channel error factor that can be adjusted according to the method of the channel estimation. Second, based on the closed-form approximation, we present an efficient algorithm determining the number of antennas needed in each group for the group-based RS overhead reduction scheme. The algorithm depends on the exact inverse functions of the derived closed-form approximations of SE. It is verified with theoretical analysis and simulation that the proposed algorithm works well, and thus can be used as an important tool for massive MIMO systems to support many distributed IoT devices. PMID:29286339
Real-Time Distributed Implementation of Interference Alignment with Analog Feedback
2013-01-01
manner as in Figure 5(a). As such, six OFDM symbols are transmitted for our three user 2 × 2 MIMO system. The training does not experience precoding nor...pp. 159170, August 2009. [12] O. E. Ayach, S.W. Peters, and R.W. Heath Jr., ”The feasibility of interference alignment over measured MIMO - OFDM ...A Space-Time Receiver with Joint Synchronization and Interference Cancellation in Asynchronous MIMO - OFDM Systems,” IEEE Transactions on Vehicular
Joint Waveform Optimization and Adaptive Processing for Random-Phase Radar Signals
2014-01-01
extended targets,” IEEE Journal of Selected Topics in Signal Processing, vol. 1, no. 1, pp. 42– 55, June 2007. [2] S. Sen and A. Nehorai, “ OFDM mimo ...radar compared to traditional waveforms. I. INTRODUCTION There has been much recent interest in waveform design for multiple-input, multiple-output ( MIMO ...amplitude. When the resolution capability of the MIMO radar system is of interest, the transmit waveform can be designed to sharpen the radar ambiguity
MIMO Radar - Diversity Means Superiority
2007-10-01
Jian 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ESI 8. PERFORMING ORGANIZATION Department of Electrical and...several estimators for the proposed MIMO radar system. The remainder of this report is organized as follows. Chapter 2 pres ,lt> t hc MIMO radar...A 17) with 0 denoting the Kronecker product. Substituting Equations (A 9) - (A 7) into (A ()). and after soic ( I I hIx II, nipulations, we get CRB(O
MIMO capacities and outage probabilities in spatially multiplexed optical transport systems.
Winzer, Peter J; Foschini, Gerard J
2011-08-15
With wavelength-division multiplexing (WDM) rapidly nearing its scalability limits, space-division multiplexing (SDM) seems the only option to further scale the capacity of optical transport networks. In order for SDM systems to continue the WDM trend of reducing energy and cost per bit with system capacity, integration will be key to SDM. Since integration is likely to introduce non-negligible crosstalk between multiple parallel transmission paths, multiple-input multiple output (MIMO) signal processing techniques will have to be used. In this paper, we discuss MIMO capacities in optical SDM systems, including related outage considerations which are an important part in the design of such systems. In order to achieve the low-outage standards required for optical transport networks, SDM transponders should be capable of individually addressing, and preferably MIMO processing all modes supported by the optical SDM waveguide. We then discuss the effect of distributed optical noise in MIMO SDM systems and focus on the impact of mode-dependent loss (MDL) on system capacity and system outage. Through extensive numerical simulations, we extract scaling rules for mode-average and mode-dependent loss and show that MIMO SDM systems composed of up to 128 segments and supporting up to 128 modes can tolerate up to 1 dB of per-segment MDL at 90% of the system's full capacity at an outage probability of 10(-4). © 2011 Optical Society of America
NASA Astrophysics Data System (ADS)
Qiu, Zhi-cheng; Wang, Bin; Zhang, Xian-min; Han, Jian-da
2013-04-01
This study presents a novel translating piezoelectric flexible manipulator driven by a rodless cylinder. Simultaneous positioning control and vibration suppression of the flexible manipulator is accomplished by using a hybrid driving scheme composed of the pneumatic cylinder and a piezoelectric actuator. Pulse code modulation (PCM) method is utilized for the cylinder. First, the system dynamics model is derived, and its standard multiple input multiple output (MIMO) state-space representation is provided. Second, a composite proportional derivative (PD) control algorithms and a direct adaptive fuzzy control method are designed for the MIMO system. Also, a time delay compensation algorithm, bandstop and low-pass filters are utilized, under consideration of the control hysteresis and the caused high-frequency modal vibration due to the long stroke of the cylinder, gas compression and nonlinear factors of the pneumatic system. The convergence of the closed loop system is analyzed. Finally, experimental apparatus is constructed and experiments are conducted. The effectiveness of the designed controllers and the hybrid driving scheme is verified through simulation and experimental comparison studies. The numerical simulation and experimental results demonstrate that the proposed system scheme of employing the pneumatic drive and piezoelectric actuator can suppress the vibration and achieve the desired positioning location simultaneously. Furthermore, the adopted adaptive fuzzy control algorithms can significantly enhance the control performance.
Hampson, Robert E.; Gerhardt, Greg A.; Marmarelis, Vasilis; Song, Dong; Opris, Ioan; Santos, Lucas; Berger, Theodore W.; Deadwyler, Sam A.
2012-01-01
Problem addressed Maintenance of cognitive control is a major concern for many human disease condition, therefore a major goal of human neuroprosthetics is to facilitate and/or recover cognitive function when such circumstances impair appropriate decision making. Methodology Nonhuman primates trained to perform a delayed match to sample (DMS) were employed to record mini-columnar activity in the prefrontal cortex (PFC) via custom designed conformal multielectrode arrays that provided inter-laminar recordings from neurons in PFC layer 2/3 and layer 5. Such recordings were analyzed via a previously demonstrated nonlinear multi-input multi-output (MIMO) neuroprosthesis in rodents, which extracted and characterized multi-columnar firing patterns during DMS performance. Results The MIMO model verified that the conformal recorded individual PFC minicolumns responded to entrained target selections in patterns critical for successful DMS performance. This allowed substitution of task-related layer 5 neuron firing patterns with electrical stimulation in the same recording regions during columnar transmission from layer 2/3 at the time of target selection. Such stimulation facilitated normal task performance, but more importantly, recovered performance when applied as a neuroprosthesis following pharmacological disruption of decision making in the same task. Significance and potential impact These findings provide the first successful application of a neuroprosthesis in primate brain designed specifically to restore or repair disrupted cognitive function. PMID:22976769
Worst-Case Energy Efficiency Maximization in a 5G Massive MIMO-NOMA System.
Chinnadurai, Sunil; Selvaprabhu, Poongundran; Jeong, Yongchae; Jiang, Xueqin; Lee, Moon Ho
2017-09-18
In this paper, we examine the robust beamforming design to tackle the energy efficiency (EE) maximization problem in a 5G massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) downlink system with imperfect channel state information (CSI) at the base station. A novel joint user pairing and dynamic power allocation (JUPDPA) algorithm is proposed to minimize the inter user interference and also to enhance the fairness between the users. This work assumes imperfect CSI by adding uncertainties to channel matrices with worst-case model, i.e., ellipsoidal uncertainty model (EUM). A fractional non-convex optimization problem is formulated to maximize the EE subject to the transmit power constraints and the minimum rate requirement for the cell edge user. The designed problem is difficult to solve due to its nonlinear fractional objective function. We firstly employ the properties of fractional programming to transform the non-convex problem into its equivalent parametric form. Then, an efficient iterative algorithm is proposed established on the constrained concave-convex procedure (CCCP) that solves and achieves convergence to a stationary point of the above problem. Finally, Dinkelbach's algorithm is employed to determine the maximum energy efficiency. Comprehensive numerical results illustrate that the proposed scheme attains higher worst-case energy efficiency as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.
Worst-Case Energy Efficiency Maximization in a 5G Massive MIMO-NOMA System
Jeong, Yongchae; Jiang, Xueqin; Lee, Moon Ho
2017-01-01
In this paper, we examine the robust beamforming design to tackle the energy efficiency (EE) maximization problem in a 5G massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) downlink system with imperfect channel state information (CSI) at the base station. A novel joint user pairing and dynamic power allocation (JUPDPA) algorithm is proposed to minimize the inter user interference and also to enhance the fairness between the users. This work assumes imperfect CSI by adding uncertainties to channel matrices with worst-case model, i.e., ellipsoidal uncertainty model (EUM). A fractional non-convex optimization problem is formulated to maximize the EE subject to the transmit power constraints and the minimum rate requirement for the cell edge user. The designed problem is difficult to solve due to its nonlinear fractional objective function. We firstly employ the properties of fractional programming to transform the non-convex problem into its equivalent parametric form. Then, an efficient iterative algorithm is proposed established on the constrained concave-convex procedure (CCCP) that solves and achieves convergence to a stationary point of the above problem. Finally, Dinkelbach’s algorithm is employed to determine the maximum energy efficiency. Comprehensive numerical results illustrate that the proposed scheme attains higher worst-case energy efficiency as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme. PMID:28927019
Liu, Chang; Deng, Lei; He, Jiale; Li, Di; Fu, Songnian; Tang, Ming; Cheng, Mengfan; Liu, Deming
2017-07-24
In this paper, 4 × 4 multiple-input multiple-output (MIMO) radio over 7-core fiber system based on sparse code multiple access (SCMA) and OFDM/OQAM techniques is proposed. No cyclic prefix (CP) is required by properly designing the prototype filters in OFDM/OQAM modulator, and non-orthogonally overlaid codewords by using SCMA is help to serve more users simultaneously under the condition of using equal number of time and frequency resources compared with OFDMA, resulting in the increase of spectral efficiency (SE) and system capacity. In our experiment, 11.04 Gb/s 4 × 4 MIMO SCMA-OFDM/OQAM signal is successfully transmitted over 20 km 7-core fiber and 0.4 m air distance in both uplink and downlink. As a comparison, 6.681 Gb/s traditional MIMO-OFDM signal with the same occupied bandwidth has been evaluated for both uplink and downlink transmission. The experimental results show that SE could be increased by 65.2% with no bit error rate (BER) performance degradation compared with the traditional MIMO-OFDM technique.
Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad
2018-06-01
This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Silva, João Carlos; Souto, Nuno; Cercas, Francisco; Dinis, Rui
A MMSE (Minimum Mean Square Error) DS-CDMA (Direct Sequence-Code Division Multiple Access) receiver coupled with a low-complexity iterative interference suppression algorithm was devised for a MIMO/BLAST (Multiple Input, Multiple Output / Bell Laboratories Layered Space Time) system in order to improve system performance, considering frequency selective fading channels. The scheme is compared against the simple MMSE receiver, for both QPSK and 16QAM modulations, under SISO (Single Input, Single Output) and MIMO systems, the latter with 2Tx by 2Rx and 4Tx by 4Rx (MIMO order 2 and 4 respectively) antennas. To assess its performance in an existing system, the uncoded UMTS HSDPA (High Speed Downlink Packet Access) standard was considered.
2011-01-01
reliability, e.g., Turbo Codes [2] and Low Density Parity Check ( LDPC ) codes [3]. The challenge to apply both MIMO and ECC into wireless systems is on...REPORT Fixed-point Design of theLattice-reduction-aided Iterative Detection andDecoding Receiver for Coded MIMO Systems 14. ABSTRACT 16. SECURITY...illustrates the performance of coded LR aided detectors. 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES The views, opinions
NASA Technical Reports Server (NTRS)
Schroder, Christian; Klingelhofer, Gostar; Morris, Richard V.; Yen, Albert S.; Renz, Franz; Graff, Trevor G.
2016-01-01
The miniaturized Mossbauer spectrometer MIMOS II is an off-the-shelf instrument, which has been successfully deployed during NASA's Mars Exploration Rover (MER) mission and was on-board the ESA/UK Beagle 2 Mars lander and the Russian Phobos-Grunt sample return mission. We propose to use a fully-qualified flight-spare MIMOS II instrument available from these missions for in situ asteroid characterization with the Asteroid Redirect Robotic Mission (ARRM).
NASA Astrophysics Data System (ADS)
Boski, Marcin; Paszke, Wojciech
2017-01-01
This paper deals with designing of iterative learning control schemes for uncertain systems with static nonlinearities. More specifically, the nonlinear part is supposed to be sector bounded and system matrices are assumed to range in the polytope of matrices. For systems with such nonlinearities and uncertainties the repetitive process setting is exploited to develop a linear matrix inequality based conditions for computing the feedback and feedforward (learning) controllers. These controllers guarantee acceptable dynamics along the trials and ensure convergence of the trial-to-trial error dynamics, respectively. Numerical examples illustrate the theoretical results and confirm effectiveness of the designed control scheme.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Yunlong; Wang, Hong; Guo, Lei
Here in this note, the robust stochastic stabilization and robust H_infinity control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbancemore » rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.« less
Yoo, Sung Jin; Park, Bong Seok
2017-09-06
This paper addresses a distributed connectivity-preserving synchronized tracking problem of multiple uncertain nonholonomic mobile robots with limited communication ranges. The information of the time-varying leader robot is assumed to be accessible to only a small fraction of follower robots. The main contribution of this paper is to introduce a new distributed nonlinear error surface for dealing with both the synchronized tracking and the preservation of the initial connectivity patterns among nonholonomic robots. Based on this nonlinear error surface, the recursive design methodology is presented to construct the approximation-based local adaptive tracking scheme at the robot dynamic level. Furthermore, a technical lemma is established to analyze the stability and the connectivity preservation of the total closed-loop control system in the Lyapunov sense. An example is provided to illustrate the effectiveness of the proposed methodology.
Stability of uncertain systems. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Blankenship, G. L.
1971-01-01
The asymptotic properties of feedback systems are discussed, containing uncertain parameters and subjected to stochastic perturbations. The approach is functional analytic in flavor and thereby avoids the use of Markov techniques and auxiliary Lyapunov functionals characteristic of the existing work in this area. The results are given for the probability distributions of the accessible signals in the system and are proved using the Prohorov theory of the convergence of measures. For general nonlinear systems, a result similar to the small loop-gain theorem of deterministic stability theory is given. Boundedness is a property of the induced distributions of the signals and not the usual notion of boundedness in norm. For the special class of feedback systems formed by the cascade of a white noise, a sector nonlinearity and convolution operator conditions are given to insure the total boundedness of the overall feedback system.
Liu, Yunlong; Wang, Hong; Guo, Lei
2018-03-26
Here in this note, the robust stochastic stabilization and robust H_infinity control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbancemore » rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.« less
Yong-Feng Gao; Xi-Ming Sun; Changyun Wen; Wei Wang
2017-07-01
This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.
Maruta, Kazuki; Iwakuni, Tatsuhiko; Ohta, Atsushi; Arai, Takuto; Shirato, Yushi; Kurosaki, Satoshi; Iizuka, Masataka
2016-07-08
Drastic improvements in transmission rate and system capacity are required towards 5th generation mobile communications (5G). One promising approach, utilizing the millimeter wave band for its rich spectrum resources, suffers area coverage shortfalls due to its large propagation loss. Fortunately, massive multiple-input multiple-output (MIMO) can offset this shortfall as well as offer high order spatial multiplexing gain. Multiuser MIMO is also effective in further enhancing system capacity by multiplexing spatially de-correlated users. However, the transmission performance of multiuser MIMO is strongly degraded by channel time variation, which causes inter-user interference since null steering must be performed at the transmitter. This paper first addresses the effectiveness of multiuser massive MIMO transmission that exploits the first eigenmode for each user. In Line-of-Sight (LoS) dominant channel environments, the first eigenmode is chiefly formed by the LoS component, which is highly correlated with user movement. Therefore, the first eigenmode provided by a large antenna array can improve the robustness against the channel time variation. In addition, we propose a simplified beamforming scheme based on high efficient channel state information (CSI) estimation that extracts the LoS component. We also show that this approximate beamforming can achieve throughput performance comparable to that of the rigorous first eigenmode transmission. Our proposed multiuser massive MIMO scheme can open the door for practical millimeter wave communication with enhanced system capacity.
A Unitary ESPRIT Scheme of Joint Angle Estimation for MOTS MIMO Radar
Wen, Chao; Shi, Guangming
2014-01-01
The transmit array of multi-overlapped-transmit-subarray configured bistatic multiple-input multiple-output (MOTS MIMO) radar is partitioned into a number of overlapped subarrays, which is different from the traditional bistatic MIMO radar. In this paper, a new unitary ESPRIT scheme for joint estimation of the direction of departure (DOD) and the direction of arrival (DOA) for MOTS MIMO radar is proposed. In our method, each overlapped-transmit-subarray (OTS) with the identical effective aperture is regarded as a transmit element and the characteristics that the phase delays between the two OTSs is utilized. First, the measurements corresponding to all the OTSs are partitioned into two groups which have a rotational invariance relationship with each other. Then, the properties of centro-Hermitian matrices and real-valued rotational invariance factors are exploited to double the measurement samples and reduce computational complexity. Finally, the close-formed solution of automatically paired DOAs and DODs of targets is derived in a new manner. The proposed scheme provides increased estimation accuracy with the combination of inherent advantages of MOTS MIMO radar with unitary ESPRIT. Simulation results are presented to demonstrate the effectiveness and advantage of the proposed scheme. PMID:25106023
Diversity Performance Analysis on Multiple HAP Networks.
Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue
2015-06-30
One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques.
A unitary ESPRIT scheme of joint angle estimation for MOTS MIMO radar.
Wen, Chao; Shi, Guangming
2014-08-07
The transmit array of multi-overlapped-transmit-subarray configured bistatic multiple-input multiple-output (MOTS MIMO) radar is partitioned into a number of overlapped subarrays, which is different from the traditional bistatic MIMO radar. In this paper, a new unitary ESPRIT scheme for joint estimation of the direction of departure (DOD) and the direction of arrival (DOA) for MOTS MIMO radar is proposed. In our method, each overlapped-transmit-subarray (OTS) with the identical effective aperture is regarded as a transmit element and the characteristics that the phase delays between the two OTSs is utilized. First, the measurements corresponding to all the OTSs are partitioned into two groups which have a rotational invariance relationship with each other. Then, the properties of centro-Hermitian matrices and real-valued rotational invariance factors are exploited to double the measurement samples and reduce computational complexity. Finally, the close-formed solution of automatically paired DOAs and DODs of targets is derived in a new manner. The proposed scheme provides increased estimation accuracy with the combination of inherent advantages of MOTS MIMO radar with unitary ESPRIT. Simulation results are presented to demonstrate the effectiveness and advantage of the proposed scheme.
NASA Astrophysics Data System (ADS)
Chen, Shih-Hao; Chow, Chi-Wai
2015-01-01
Multiple-input and multiple-output (MIMO) scheme can extend the transmission capacity for the light-emitting-diode (LED) based visible light communication (VLC) systems. The MIMO VLC system that uses the mobile-phone camera as the optical receiver (Rx) to receive MIMO signal from the n×n Red-Green-Blue (RGB) LED array is desirable. The key step of decoding this signal is to detect the signal direction. If the LED transmitter (Tx) is rotated, the Rx may not realize the rotation and transmission error can occur. In this work, we propose and demonstrate a novel hierarchical transmission scheme which can reduce the computation complexity of rotation detection in LED array VLC system. We use the n×n RGB LED array as the MIMO Tx. In our study, a novel two dimensional Hadamard coding scheme is proposed. Using the different LED color layers to indicate the rotation, a low complexity rotation detection method can be used for improving the quality of received signal. The detection correction rate is above 95% in the indoor usage distance. Experimental results confirm the feasibility of the proposed scheme.
Wind turbine model and loop shaping controller design
NASA Astrophysics Data System (ADS)
Gilev, Bogdan
2017-12-01
A model of a wind turbine is evaluated, consisting of: wind speed model, mechanical and electrical model of generator and tower oscillation model. Model of the whole system is linearized around of a nominal point. By using the linear model with uncertainties is synthesized a uncertain model. By using the uncertain model is developed a H∞ controller, which provide mode of stabilizing the rotor frequency and damping the tower oscillations. Finally is simulated work of nonlinear system and H∞ controller.
Mutual Coupling and Compensation in FMCW MIMO Radar Systems
NASA Astrophysics Data System (ADS)
Schmid, Christian M.; Feger, Reinhard; Wagner, Christoph; Stelzer, Andreas
2011-09-01
This paper deals with mutual coupling, its effects and the compensation thereof in frequency-modulated continuous-wave (FMCW) multiple-input multiple-output (MIMO) array radar systems. Starting with a signal model we introduce mutual coupling and its primary sources in FMCW MIMO systems. We also give a worst-case boundary of the effects that mutual coupling can have on the side lobe level of an array. A method of dealing with and compensating for these effects is covered in this paper and verified by measurements from a 77-GHz FMCW radar system.
Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.
Zhang, Qichao; Zhao, Dongbin; Wang, Ding
2018-01-01
In this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.
NASA Astrophysics Data System (ADS)
Sun, Liang; McKay, Matthew R.
2014-08-01
This paper studies the sum rate performance of a low complexity quantized CSI-based Tomlinson-Harashima (TH) precoding scheme for downlink multiuser MIMO tansmission, employing greedy user selection. The asymptotic distribution of the output signal to interference plus noise ratio of each selected user and the asymptotic sum rate as the number of users K grows large are derived by using extreme value theory. For fixed finite signal to noise ratios and a finite number of transmit antennas $n_T$, we prove that as K grows large, the proposed approach can achieve the optimal sum rate scaling of the MIMO broadcast channel. We also prove that, if we ignore the precoding loss, the average sum rate of this approach converges to the average sum capacity of the MIMO broadcast channel. Our results provide insights into the effect of multiuser interference caused by quantized CSI on the multiuser diversity gain.
A Practical, Hardware Friendly MMSE Detector for MIMO-OFDM-Based Systems
NASA Astrophysics Data System (ADS)
Kim, Hun Seok; Zhu, Weijun; Bhatia, Jatin; Mohammed, Karim; Shah, Anish; Daneshrad, Babak
2008-12-01
Design and implementation of a highly optimized MIMO (multiple-input multiple-output) detector requires cooptimization of the algorithm with the underlying hardware architecture. Special attention must be paid to application requirements such as throughput, latency, and resource constraints. In this work, we focus on a highly optimized matrix inversion free [InlineEquation not available: see fulltext.] MMSE (minimum mean square error) MIMO detector implementation. The work has resulted in a real-time field-programmable gate array-based implementation (FPGA-) on a Xilinx Virtex-2 6000 using only 9003 logic slices, 66 multipliers, and 24 Block RAMs (less than 33% of the overall resources of this part). The design delivers over 420 Mbps sustained throughput with a small 2.77-microsecond latency. The designed [InlineEquation not available: see fulltext.] linear MMSE MIMO detector is capable of complying with the proposed IEEE 802.11n standard.
Polymer (PDMS-Fe3O4) magneto-dielectric substrate for a MIMO antenna array
NASA Astrophysics Data System (ADS)
Alqadami, Abdulrahman Shueai Mohsen; Jamlos, Mohd Faizal; Soh, Ping Jack; Kamarudin, Muhammad Ramlee
2016-01-01
This paper presents the design of a 2 × 4 multiple-input multiple-output (MIMO) antenna array fabricated on a nanocomposite magneto-dielectric polymer substrate. The 10-nm iron oxide (Fe3O4) nanoparticles and polydimethylsiloxane (PDMS) composite is used as substrate to enhance the performance of a MIMO antenna array. The measured results showed up to 40.8 % enhancement in terms of bandwidth, 9.95 dB gain, and 57 % of radiation efficiency. Furthermore, it is found that the proposed magneto-dielectric (PDMS-Fe3O4) composite substrate provides excellent MIMO parameters such as correlation coefficient, diversity gain, and mutual coupling. The prototype of the proposed antenna is transparent, flexible, lightweight, and resistant against dust and corrosion. Measured results indicate that the proposed antenna is suitable for WLAN and ultra-wideband biomedical applications within frequency range of 5.33-7.70 GHz.
Li, Da-Peng; Li, Dong-Juan; Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip
2017-10-01
This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.
NASA Technical Reports Server (NTRS)
Acikmese, Behcet A.; Carson, John M., III
2005-01-01
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided.
Peng, Zhouhua; Wang, Dan; Zhang, Hongwei; Sun, Gang
2014-08-01
This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.
Han, Yaozhen; Liu, Xiangjie
2016-05-01
This paper presents a continuous higher-order sliding mode (HOSM) control scheme with time-varying gain for a class of uncertain nonlinear systems. The proposed controller is derived from the concept of geometric homogeneity and super-twisting algorithm, and includes two parts, the first part of which achieves smooth finite time stabilization of pure integrator chains. The second part conquers the twice differentiable uncertainty and realizes system robustness by employing super-twisting algorithm. Particularly, time-varying switching control gain is constructed to reduce the switching control action magnitude to the minimum possible value while keeping the property of finite time convergence. Examples concerning the perturbed triple integrator chains and excitation control for single-machine infinite bus power system are simulated respectively to demonstrate the effectiveness and applicability of the proposed approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Long, Lijun; Zhao, Jun
2015-07-01
This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.
Fuzzy Adaptive Control Design and Discretization for a Class of Nonlinear Uncertain Systems.
Zhao, Xudong; Shi, Peng; Zheng, Xiaolong
2016-06-01
In this paper, tracking control problems are investigated for a class of uncertain nonlinear systems in lower triangular form. First, a state-feedback controller is designed by using adaptive backstepping technique and the universal approximation ability of fuzzy logic systems. During the design procedure, a developed method with less computation is proposed by constructing one maximum adaptive parameter. Furthermore, adaptive controllers with nonsymmetric dead-zone are also designed for the systems. Then, a sampled-data control scheme is presented to discretize the obtained continuous-time controller by using the forward Euler method. It is shown that both proposed continuous and discrete controllers can ensure that the system output tracks the target signal with a small bounded error and the other closed-loop signals remain bounded. Two simulation examples are presented to verify the effectiveness and applicability of the proposed new design techniques.
The application of LDPC code in MIMO-OFDM system
NASA Astrophysics Data System (ADS)
Liu, Ruian; Zeng, Beibei; Chen, Tingting; Liu, Nan; Yin, Ninghao
2018-03-01
The combination of MIMO and OFDM technology has become one of the key technologies of the fourth generation mobile communication., which can overcome the frequency selective fading of wireless channel, increase the system capacity and improve the frequency utilization. Error correcting coding introduced into the system can further improve its performance. LDPC (low density parity check) code is a kind of error correcting code which can improve system reliability and anti-interference ability, and the decoding is simple and easy to operate. This paper mainly discusses the application of LDPC code in MIMO-OFDM system.
Xue, Dingyü; Li, Tingxue
2017-04-27
The parameter optimization method for multivariable systems is extended to the controller design problems for multiple input multiple output (MIMO) square fractional-order plants. The algorithm can be applied to search for the optimal parameters of integer-order controllers for fractional-order plants with or without time delays. Two examples are given to present the controller design procedures for MIMO fractional-order systems. Simulation studies show that the integer-order controllers designed are robust to plant gain variations. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Diversity Performance Analysis on Multiple HAP Networks
Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue
2015-01-01
One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques. PMID:26134102
Distributed Compressive CSIT Estimation and Feedback for FDD Multi-User Massive MIMO Systems
NASA Astrophysics Data System (ADS)
Rao, Xiongbin; Lau, Vincent K. N.
2014-06-01
To fully utilize the spatial multiplexing gains or array gains of massive MIMO, the channel state information must be obtained at the transmitter side (CSIT). However, conventional CSIT estimation approaches are not suitable for FDD massive MIMO systems because of the overwhelming training and feedback overhead. In this paper, we consider multi-user massive MIMO systems and deploy the compressive sensing (CS) technique to reduce the training as well as the feedback overhead in the CSIT estimation. The multi-user massive MIMO systems exhibits a hidden joint sparsity structure in the user channel matrices due to the shared local scatterers in the physical propagation environment. As such, instead of naively applying the conventional CS to the CSIT estimation, we propose a distributed compressive CSIT estimation scheme so that the compressed measurements are observed at the users locally, while the CSIT recovery is performed at the base station jointly. A joint orthogonal matching pursuit recovery algorithm is proposed to perform the CSIT recovery, with the capability of exploiting the hidden joint sparsity in the user channel matrices. We analyze the obtained CSIT quality in terms of the normalized mean absolute error, and through the closed-form expressions, we obtain simple insights into how the joint channel sparsity can be exploited to improve the CSIT recovery performance.
Quantification of MDL-induced signal degradation in MIMO-OFDM mode-division multiplexing systems.
Tian, Yu; Li, Juhao; Zhu, Paikun; Wu, Zhongying; Chen, Yuanxiang; He, Yongqi; Chen, Zhangyuan
2016-08-22
Mode-division multiplexing (MDM) transmission over few-mode optical fiber has emerged as a promising technology to enhance transmission capacity, in which multiple-input-multiple-output (MIMO) digital signal processing (DSP) after coherent detection is used to demultiplex the signals. Compared with conventional single-mode systems, MIMO-MDM systems suffer non-recoverable signal degradation induced by mode-dependent loss (MDL). In this paper, the MDL-induced signal degradation in orthogonal-frequency-division-multiplexing (OFDM) MDM systems is theoretically quantified in terms of mode-average error vector magnitude (EVM) through frequency domain norm analysis. A novel scalar MDL metric is proposed considering the probability distribution of the practical MDM input signals, and a closed-form expression for EVM measured after zero-force (ZF) MIMO equalization is derived. Simulation results show that the EVM estimations utilizing the novel MDL metric remain unbiased for unrepeated links. For a 6 × 100 km 20-mode MDM transmission system, the estimation accuracy is improved by more than 90% compared with that utilizing traditional condition number (CN) based MDL metric. The proposed MDL metric can be used to predict the MDL-induced SNR penalty in a theoretical manner, which will be beneficial for the design of practical MIMO-MDM systems.
Gui, Guan; Chen, Zhang-xin; Xu, Li; Wan, Qun; Huang, Jiyan; Adachi, Fumiyuki
2014-01-01
Channel estimation problem is one of the key technical issues in sparse frequency-selective fading multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) scheme. To estimate sparse MIMO channels, sparse invariable step-size normalized least mean square (ISS-NLMS) algorithms were applied to adaptive sparse channel estimation (ACSE). It is well known that step-size is a critical parameter which controls three aspects: algorithm stability, estimation performance, and computational cost. However, traditional methods are vulnerable to cause estimation performance loss because ISS cannot balance the three aspects simultaneously. In this paper, we propose two stable sparse variable step-size NLMS (VSS-NLMS) algorithms to improve the accuracy of MIMO channel estimators. First, ASCE is formulated in MIMO-OFDM systems. Second, different sparse penalties are introduced to VSS-NLMS algorithm for ASCE. In addition, difference between sparse ISS-NLMS algorithms and sparse VSS-NLMS ones is explained and their lower bounds are also derived. At last, to verify the effectiveness of the proposed algorithms for ASCE, several selected simulation results are shown to prove that the proposed sparse VSS-NLMS algorithms can achieve better estimation performance than the conventional methods via mean square error (MSE) and bit error rate (BER) metrics.
Gui, Guan; Chen, Zhang-xin; Xu, Li; Wan, Qun; Huang, Jiyan; Adachi, Fumiyuki
2014-01-01
Channel estimation problem is one of the key technical issues in sparse frequency-selective fading multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) scheme. To estimate sparse MIMO channels, sparse invariable step-size normalized least mean square (ISS-NLMS) algorithms were applied to adaptive sparse channel estimation (ACSE). It is well known that step-size is a critical parameter which controls three aspects: algorithm stability, estimation performance, and computational cost. However, traditional methods are vulnerable to cause estimation performance loss because ISS cannot balance the three aspects simultaneously. In this paper, we propose two stable sparse variable step-size NLMS (VSS-NLMS) algorithms to improve the accuracy of MIMO channel estimators. First, ASCE is formulated in MIMO-OFDM systems. Second, different sparse penalties are introduced to VSS-NLMS algorithm for ASCE. In addition, difference between sparse ISS-NLMS algorithms and sparse VSS-NLMS ones is explained and their lower bounds are also derived. At last, to verify the effectiveness of the proposed algorithms for ASCE, several selected simulation results are shown to prove that the proposed sparse VSS-NLMS algorithms can achieve better estimation performance than the conventional methods via mean square error (MSE) and bit error rate (BER) metrics. PMID:25089286
NASA Astrophysics Data System (ADS)
Lertwiram, Namzilp; Tran, Gia Khanh; Mizutani, Keiichi; Sakaguchi, Kei; Araki, Kiyomichi
Setting relays can address the shadowing problem between a transmitter (Tx) and a receiver (Rx). Moreover, the Multiple-Input Multiple-Output (MIMO) technique has been introduced to improve wireless link capacity. The MIMO technique can be applied in relay network to enhance system performance. However, the efficiency of relaying schemes and relay placement have not been well investigated with experiment-based study. This paper provides a propagation measurement campaign of a MIMO two-hop relay network in 5GHz band in an L-shaped corridor environment with various relay locations. Furthermore, this paper proposes a Relay Placement Estimation (RPE) scheme to identify the optimum relay location, i.e. the point at which the network performance is highest. Analysis results of channel capacity show that relaying technique is beneficial over direct transmission in strong shadowing environment while it is ineffective in non-shadowing environment. In addition, the optimum relay location estimated with the RPE scheme also agrees with the location where the network achieves the highest performance as identified by network capacity. Finally, the capacity analysis shows that two-way MIMO relay employing network coding has the best performance while cooperative relaying scheme is not effective due to shadowing effect weakening the signal strength of the direct link.
Output transformations and separation results for feedback linearisable delay systems
NASA Astrophysics Data System (ADS)
Cacace, F.; Conte, F.; Germani, A.
2018-04-01
The class of strict-feedback systems enjoys special properties that make it similar to linear systems. This paper proves that such a class is equivalent, under a change of coordinates, to the wider class of feedback linearisable systems with multiplicative input, when the multiplicative terms are functions of the measured variables only. We apply this result to the control problem of feedback linearisable nonlinear MIMO systems with input and/or output delays. In this way, we provide sufficient conditions under which a separation result holds for output feedback control and moreover a predictor-based controller exists. When these conditions are satisfied, we obtain that the existence of stabilising controllers for arbitrarily large delays in the input and/or the output can be proved for a wider class of systems than previously known.
A Robustly Stabilizing Model Predictive Control Algorithm
NASA Technical Reports Server (NTRS)
Ackmece, A. Behcet; Carson, John M., III
2007-01-01
A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.
Valcarcel, Alessandra M; Linn, Kristin A; Vandekar, Simon N; Satterthwaite, Theodore D; Muschelli, John; Calabresi, Peter A; Pham, Dzung L; Martin, Melissa Lynne; Shinohara, Russell T
2018-03-08
Magnetic resonance imaging (MRI) is crucial for in vivo detection and characterization of white matter lesions (WMLs) in multiple sclerosis. While WMLs have been studied for over two decades using MRI, automated segmentation remains challenging. Although the majority of statistical techniques for the automated segmentation of WMLs are based on single imaging modalities, recent advances have used multimodal techniques for identifying WMLs. Complementary modalities emphasize different tissue properties, which help identify interrelated features of lesions. Method for Inter-Modal Segmentation Analysis (MIMoSA), a fully automatic lesion segmentation algorithm that utilizes novel covariance features from intermodal coupling regression in addition to mean structure to model the probability lesion is contained in each voxel, is proposed. MIMoSA was validated by comparison with both expert manual and other automated segmentation methods in two datasets. The first included 98 subjects imaged at Johns Hopkins Hospital in which bootstrap cross-validation was used to compare the performance of MIMoSA against OASIS and LesionTOADS, two popular automatic segmentation approaches. For a secondary validation, a publicly available data from a segmentation challenge were used for performance benchmarking. In the Johns Hopkins study, MIMoSA yielded average Sørensen-Dice coefficient (DSC) of .57 and partial AUC of .68 calculated with false positive rates up to 1%. This was superior to performance using OASIS and LesionTOADS. The proposed method also performed competitively in the segmentation challenge dataset. MIMoSA resulted in statistically significant improvements in lesion segmentation performance compared with LesionTOADS and OASIS, and performed competitively in an additional validation study. Copyright © 2018 by the American Society of Neuroimaging.
LaPlace Transform1 Adaptive Control Law in Support of Large Flight Envelope Modeling Work
NASA Technical Reports Server (NTRS)
Gregory, Irene M.; Xargay, Enric; Cao, Chengyu; Hovakimyan, Naira
2011-01-01
This paper presents results of a flight test of the L1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The flight test was conducted on the subscale turbine powered Generic Transport Model that is an integral part of the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. The results presented are in support of nonlinear aerodynamic modeling and instrumentation calibration.
Development and Evaluation of a Multistatic Ultrawideband Random Noise Radar
2010-03-01
noncoherent MIMO investigates 13 a statistical diversity gain available to systems with widely separated antennas per- forming a distributed detection...design. When widely distributed antenna are operating as a MIMO radar system, research shows a noncoherent signal gain is realized, if there exists
NASA Astrophysics Data System (ADS)
Mohammed, H. A.; Sibley, M. J. N.; Mather, P. J.
2012-05-01
The merging of Orthogonal Frequency Division Multiplexing (OFDM) with Multiple-input multiple-output (MIMO) is a promising mobile air interface solution for next generation wireless local area networks (WLANs) and 4G mobile cellular wireless systems. This paper details the design of a highly robust and efficient OFDM-MIMO system to support permanent accessibility and higher data rates to users moving at high speeds, such as users travelling on trains. It has high relevance for next generation wireless local area networks (WLANs) and 4G mobile cellular wireless systems. The paper begins with a comprehensive literature review focused on both technologies. This is followed by the modelling of the OFDM-MIMO physical layer based on Simulink/Matlab that takes into consideration high vehicular mobility. Then the entire system is simulated and analysed under different encoding and channel estimation algorithms. The use of High Altitude Platform system (HAPs) technology is considered and analysed.
Channel estimation based on quantized MMP for FDD massive MIMO downlink
NASA Astrophysics Data System (ADS)
Guo, Yao-ting; Wang, Bing-he; Qu, Yi; Cai, Hua-jie
2016-10-01
In this paper, we consider channel estimation for Massive MIMO systems operating in frequency division duplexing mode. By exploiting the sparsity of propagation paths in Massive MIMO channel, we develop a compressed sensing(CS) based channel estimator which can reduce the pilot overhead. As compared with the conventional least squares (LS) and linear minimum mean square error(LMMSE) estimation, the proposed algorithm is based on the quantized multipath matching pursuit - MMP - reduced the pilot overhead and performs better than other CS algorithms. The simulation results demonstrate the advantage of the proposed algorithm over various existing methods including the LS, LMMSE, CoSaMP and conventional MMP estimators.
Li, YuHui; Jin, FeiTeng
2017-01-01
The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with the nonlinear compensation for a general longitudinal model of the airplane. First, the nonlinear mathematic model is converted to the equivalent linear model based on the feedback linearization theory. Then, the flight control law integrated with this inversion model is developed to stabilize the nonlinear system and relieve the coupling effect. Afterwards, the inversion control combined with the neural network and nonlinear portion is presented to improve the transient performance and attenuate the uncertain effects on both external disturbances and model errors. Finally, the simulation results demonstrate the effectiveness of this controller. PMID:29410680
Robust synthetic biology design: stochastic game theory approach.
Chen, Bor-Sen; Chang, Chia-Hung; Lee, Hsiao-Ching
2009-07-15
Synthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology. A robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi-Sugeno (T-S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method. http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf.
Optimal second order sliding mode control for nonlinear uncertain systems.
Das, Madhulika; Mahanta, Chitralekha
2014-07-01
In this paper, a chattering free optimal second order sliding mode control (OSOSMC) method is proposed to stabilize nonlinear systems affected by uncertainties. The nonlinear optimal control strategy is based on the control Lyapunov function (CLF). For ensuring robustness of the optimal controller in the presence of parametric uncertainty and external disturbances, a sliding mode control scheme is realized by combining an integral and a terminal sliding surface. The resulting second order sliding mode can effectively reduce chattering in the control input. Simulation results confirm the supremacy of the proposed optimal second order sliding mode control over some existing sliding mode controllers in controlling nonlinear systems affected by uncertainty. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Variable structure control of nonlinear systems through simplified uncertain models
NASA Technical Reports Server (NTRS)
Sira-Ramirez, Hebertt
1986-01-01
A variable structure control approach is presented for the robust stabilization of feedback equivalent nonlinear systems whose proposed model lies in the same structural orbit of a linear system in Brunovsky's canonical form. An attempt to linearize exactly the nonlinear plant on the basis of the feedback control law derived for the available model results in a nonlinearly perturbed canonical system for the expanded class of possible equivalent control functions. Conservatism tends to grow as modeling errors become larger. In order to preserve the internal controllability structure of the plant, it is proposed that model simplification be carried out on the open-loop-transformed system. As an example, a controller is developed for a single link manipulator with an elastic joint.
Hu, Cheng; Wang, Jingyang; Tian, Weiming; Zeng, Tao; Wang, Rui
2017-03-15
Multiple-Input Multiple-Output (MIMO) radar provides much more flexibility than the traditional radar thanks to its ability to realize far more observation channels than the actual number of transmit and receive (T/R) elements. In designing the MIMO imaging radar arrays, the commonly used virtual array theory generally assumes that all elements are on the same line. However, due to the physical size of the antennas and coupling effect between T/R elements, a certain height difference between T/R arrays is essential, which will result in the defocusing of edge points of the scene. On the other hand, the virtual array theory implies far-field approximation. Therefore, with a MIMO array designed by this theory, there will exist inevitable high grating lobes in the imaging results of near-field edge points of the scene. To tackle these problems, this paper derives the relationship between target's point spread function (PSF) and pattern of T/R arrays, by which the design criterion is presented for near-field imaging MIMO arrays. Firstly, the proper height between T/R arrays is designed to focus the near-field edge points well. Secondly, the far-field array is modified to suppress the grating lobes in the near-field area. Finally, the validity of the proposed methods is verified by two simulations and an experiment.
Hu, Cheng; Wang, Jingyang; Tian, Weiming; Zeng, Tao; Wang, Rui
2017-01-01
Multiple-Input Multiple-Output (MIMO) radar provides much more flexibility than the traditional radar thanks to its ability to realize far more observation channels than the actual number of transmit and receive (T/R) elements. In designing the MIMO imaging radar arrays, the commonly used virtual array theory generally assumes that all elements are on the same line. However, due to the physical size of the antennas and coupling effect between T/R elements, a certain height difference between T/R arrays is essential, which will result in the defocusing of edge points of the scene. On the other hand, the virtual array theory implies far-field approximation. Therefore, with a MIMO array designed by this theory, there will exist inevitable high grating lobes in the imaging results of near-field edge points of the scene. To tackle these problems, this paper derives the relationship between target’s point spread function (PSF) and pattern of T/R arrays, by which the design criterion is presented for near-field imaging MIMO arrays. Firstly, the proper height between T/R arrays is designed to focus the near-field edge points well. Secondly, the far-field array is modified to suppress the grating lobes in the near-field area. Finally, the validity of the proposed methods is verified by two simulations and an experiment. PMID:28294996
On the capacity of MIMO-OFDM based diversity and spatial multiplexing in Radio-over-Fiber system
NASA Astrophysics Data System (ADS)
El Yahyaoui, Moussa; El Moussati, Ali; El Zein, Ghaïs
2017-11-01
This paper proposes a realistic and global simulation to predict the behavior of a Radio over Fiber (RoF) system before its realization. In this work we consider a 2 × 2 Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) RoF system at 60 GHz. This system is based on Spatial Diversity (SD) which increases reliability (decreases probability of error) and Spatial Multiplexing (SMX) which increases data rate, but not necessarily reliability. The 60 GHz MIMO channel model employed in this work based on a lot of measured data and statistical analysis named Triple-S and Valenzuela (TSV) model. To the authors best knowledge; it is the first time that this type of TSV channel model has been employed for 60 GHz MIMO-RoF system. We have evaluated and compared the performance of this system according to the diversity technique, modulation schemes, and channel coding rate for Line-Of-Sight (LOS) desktop environment. The SMX coded is proposed as an intermediate system to improve the Signal to Noise Ratio (SNR) and the data rate. The resulting 2 × 2 MIMO-OFDM SMX system achieves a higher data rate up to 70 Gb/s with 64QAM and Forward Error Correction (FEC) limit of 10-3 over 25-km fiber transmission followed by 3-m wireless transmission using 7 GHz bandwidth of millimeter wave band.
NASA Astrophysics Data System (ADS)
Morant, Maria; Llorente, Roberto
2017-01-01
In this work we propose and evaluate experimentally the performance of IEEE 802.11ac WLAN standard signals in radio-over-fiber (RoF) distributed-antenna systems based on multicore fiber (MCF) for in-building WLAN connectivity. The RoF performance of WLAN signals with different bandwidth is investigated considering up to IEEE 802.11ac maximum of 160 MHz per user. We evaluate experimentally the performance of WLAN signals employing different modulation and coding schemes achieving bitrates from 78 Mbps to 1404 Mbps per user in distances up to 300 m in a 4-core MCF. The performance of the wireless standard multiple-input multiple-output (MIMO) processing algorithms included in WLAN signals applied to the RoF transmission in MCF optical systems is also evaluated. The impact on the quality of the signal from one of the cores in the MIMO processing is investigated and compared with the results achieved with single-input single-output (SISO) transmission in each core. We measured the error vector magnitude (EVM) and the OFDM data burst information of the received WLAN signals after RoF transmission for different distributed-antenna systems with uni- and bi-directional MCF communication. Finally, we compare the received EVM of a single-antenna system (SISO arrangement) with WLAN systems using two antennas (2×2 MIMO) and four antennas (4×4 MIMO).
L1 adaptive control of uncertain gear transmission servo systems with deadzone nonlinearity.
Zuo, Zongyu; Li, Xiao; Shi, Zhiguang
2015-09-01
This paper deals with the adaptive control problem of Gear Transmission Servo (GTS) systems in the presence of unknown deadzone nonlinearity and viscous friction. A global differential homeomorphism based on a novel differentiable deadzone model is proposed first. Since there exist both matched and unmatched state-dependent unknown nonlinearities, a full-state feedback L1 adaptive controller is constructed to achieve uniformly bounded transient response in addition to steady-state performance. Finally, simulation results are included to show the elimination of limit cycles, in addition to demonstrating the main results in this paper. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
2015-04-01
Measurement of radiative and nonradiative recombination rates in InGaAsP and AlGaAs light sources’, IEEE J. Quantum Electron., 1984, QE-20, (8), pp. 838–854 ELECTRONICS LETTERS 16th September 2004 Vol. 40 No. 19
NASA Astrophysics Data System (ADS)
Li, Keqiang; Gao, Feng; Li, Shengbo Eben; Zheng, Yang; Gao, Hongbo
2017-12-01
This study presents a distributed H-infinity control method for uncertain platoons with dimensionally and structurally unknown interaction topologies provided that the associated topological eigenvalues are bounded by a predesigned range.With an inverse model to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertain systems with bounded disturbances. On the basis of the eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertain part and a diagonally structured certain part by applying linear transformation. We then use a common Lyapunov method to design a distributed H-infinity controller. Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should be solved. The resulting controller can tolerate interaction topologies with eigenvalues located in a certain range. The proposed method can also ensure robustness performance and disturbance attenuation ability for the closed-loop platoon system. Hardware-in-the-loop tests are performed to validate the effectiveness of our method.
A Frequency Reconfigurable MIMO Antenna System for Cognitive Radio Applications
NASA Astrophysics Data System (ADS)
Raza, A.; Khan, Muhammad U.; Tahir, Farooq A.
2017-10-01
In this paper, a two element frequency reconfigurable multiple-input-multiple-output (MIMO) antenna system is presented. The proposed antenna consists of miniaturized patch antenna elements, loaded with varactor diodes to achieve frequency reconfigurability. The antenna has bandwidth of 30 MHz and provides a smooth frequency sweep from 2.12 GHz to 2.4 GHz by varying the reverse bias voltage of varactor diode. The antenna is designed on an FR4 substrate and occupies a space of 50×100 × 0.8 mm3. The antenna is analyzed for its far-field characteristics as well as for MIMO performance parameters. Designed antenna showed good performance and is suitable for cognitive radios (CR) applications.
Design and optimization of LTE 1800 MIMO antenna.
Wong, Huey Shin; Islam, Mohammad Tariqul; Kibria, Salehin
2014-01-01
A multiple input and multiple output (MIMO) antenna that comprises a printed microstrip antenna and a printed double-L sleeve monopole antenna for LTE 1800 wireless application is presented. The printed double-L sleeve monopole antenna is fed by a 50 ohm coplanar waveguide (CPW). A novel T-shaped microstrip feedline printed on the other side of the PCB is used to excite the waveguide's outer shell. Isolation characteristics better than -15 dB can be obtained for the proposed MIMO antenna. The proposed antenna can operate in LTE 1800 (1710 MHz-1880 MHz). This antenna exhibits omnidirectional characteristics. The efficiency of the antenna is greater than 70% and has high gain of 2.18 dBi.
Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar
Wang, Xianpeng; Wang, Wei; Li, Xin; Liu, Jing
2015-01-01
In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri–Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method. PMID:26569241
Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar.
Wang, Xianpeng; Wang, Wei; Li, Xin; Liu, Jing
2015-11-10
In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri-Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method.
Models of information exchange between radio interfaces of Wi-Fi group of standards
NASA Astrophysics Data System (ADS)
Litvinskaya, O. S.
2018-05-01
This paper offers models of information exchange between radio interfaces of the Wi-Fi group of standards by the example of a real facility management system for the oil and gas industry. Interaction between the MU-MIMO and MIMO technologies is analyzed. An optimal variant of information exchange is proposed.
High-capacity mixed fiber-wireless backhaul networks using MMW radio-over-MCF and MIMO
NASA Astrophysics Data System (ADS)
Pham, Thu A.; Pham, Hien T. T.; Le, Hai-Chau; Dang, Ngoc T.
2017-10-01
In this paper, we have proposed a high-capacity backhaul network, which is based on mixed fiber-wireless systems using millimeter-wave radio-over-multi-core fiber (MMW RoMCF) and multiple-input multiple-output (MIMO) transmission, for next generation mobile access networks. In addition, we also investigate the use of avalanche photodiode (APD) to improve capacity of the proposed backhaul downlink. We then theoretically analyze the system capacity comprehensively while considering various physical impairments including noise, MCF crosstalk, and fading modeled by Rician MIMO channel. The feasibility of the proposed backhaul architecture is verified via the numerical simulation experiments. The research results demonstrate that our developed backhaul solution can significantly enhance the backhaul capacity; the system capacity of 24 bps/Hz can be achieved with 20-km 8-core MCF and 8 × 8 MIMO transmitted over 100-m Rician fading link. It is also shown that the system performance, in term of channel capacity, strongly depend on the MCF inter-core crosstalk, which is governed by the mode coupling coefficient, the core pitch, and the bending radius.
Improved MIMO radar GMTI via cyclic-shift transmission of orthogonal frequency division signals
NASA Astrophysics Data System (ADS)
Li, Fuyou; He, Feng; Dong, Zhen; Wu, Manqing
2018-05-01
Minimum detectable velocity (MDV) and maximum detectable velocity are both important in ground moving target indication (GMTI) systems. Smaller MDV can be achieved by longer baseline via multiple-input multiple-output (MIMO) radar. Maximum detectable velocity is decided by blind velocities associated with carrier frequencies, and blind velocities can be mitigated by orthogonal frequency division signals. However, the scattering echoes from different carrier frequencies are independent, which is not good for improving MDV performance. An improved cyclic-shift transmission is applied in MIMO GMTI system in this paper. MDV performance is improved due to the longer baseline, and maximum detectable velocity performance is improved due to the mitigation of blind velocities via multiple carrier frequencies. The signal model for this mode is established, the principle of mitigating blind velocities with orthogonal frequency division signals is presented; the performance of different MIMO GMTI waveforms is analysed; and the performance of different array configurations is analysed. Simulation results by space-time-frequency adaptive processing proves that our proposed method is a valid way to improve GMTI performance.
Cheng, Sibei; Zhang, Qingjun; Bian, Mingming; Hao, Xinhong
2018-02-08
For the conventional FDA-MIMO (frequency diversity array multiple-input-multiple-output) Radar with uniform frequency offset and uniform linear array, the DOFs (degrees of freedom) of the adaptive beamformer are limited by the number of elements. A better performance-for example, a better suppression for strong interferences and a more desirable trade-off between the main lobe and side lobe-can be achieved with a greater number of DOFs. In order to obtain larger DOFs, this paper researches the signal model of the FDA-MIMO Radar with nested frequency offset and nested array, then proposes an improved adaptive beamforming method that uses the augmented matrix instead of the covariance matrix to calculate the optimum weight vectors and can be used to improve the output performances of FDA-MIMO Radar with the same element number or reduce the element number while maintain the approximate output performances such as the received beampattern, the main lobe width, side lobe depths and the output SINR (signal-to-interference-noise ratio). The effectiveness of the proposed scheme is verified by simulations.
Cheng, Sibei; Zhang, Qingjun; Bian, Mingming; Hao, Xinhong
2018-01-01
For the conventional FDA-MIMO (frequency diversity array multiple-input-multiple-output) Radar with uniform frequency offset and uniform linear array, the DOFs (degrees of freedom) of the adaptive beamformer are limited by the number of elements. A better performance—for example, a better suppression for strong interferences and a more desirable trade-off between the main lobe and side lobe—can be achieved with a greater number of DOFs. In order to obtain larger DOFs, this paper researches the signal model of the FDA-MIMO Radar with nested frequency offset and nested array, then proposes an improved adaptive beamforming method that uses the augmented matrix instead of the covariance matrix to calculate the optimum weight vectors and can be used to improve the output performances of FDA-MIMO Radar with the same element number or reduce the element number while maintain the approximate output performances such as the received beampattern, the main lobe width, side lobe depths and the output SINR (signal-to-interference-noise ratio). The effectiveness of the proposed scheme is verified by simulations. PMID:29419814
Subcarrier intensity modulation for MIMO visible light communications
NASA Astrophysics Data System (ADS)
Celik, Yasin; Akan, Aydin
2018-04-01
In this paper, subcarrier intensity modulation (SIM) is investigated for multiple-input multiple-output (MIMO) visible light communication (VLC) systems. A new modulation scheme called DC-aid SIM (DCA-SIM) is proposed for the spatial modulation (SM) transmission plan. Then, DCA-SIM is extended for multiple subcarrier case which is called DC-aid Multiple Subcarrier Modulation (DCA-MSM). Bit error rate (BER) performances of the considered system are analyzed for different MIMO schemes. The power efficiencies of DCA-SIM and DCA-MSM are shown in correlated MIMO VLC channels. The upper bound BER performances of the proposed models are obtained analytically for PSK and QAM modulation types in order to validate the simulation results. Additionally, the effect of power imbalance method on the performance of SIM is studied and remarkable power gains are obtained compared to the non-power imbalanced cases. In this work, Pulse amplitude modulation (PAM) and MSM-Index are used as benchmarks for single carrier and multiple carrier cases, respectively. And the results show that the proposed schemes outperform PAM and MSM-Index for considered single carrier and multiple carrier communication scenarios.
Robust adaptive cruise control of high speed trains.
Faieghi, Mohammadreza; Jalali, Aliakbar; Mashhadi, Seyed Kamal-e-ddin Mousavi
2014-03-01
The cruise control problem of high speed trains in the presence of unknown parameters and external disturbances is considered. In particular a Lyapunov-based robust adaptive controller is presented to achieve asymptotic tracking and disturbance rejection. The system under consideration is nonlinear, MIMO and non-minimum phase. To deal with the limitations arising from the unstable zero-dynamics we do an output redefinition such that the zero-dynamics with respect to new outputs becomes stable. Rigorous stability analyses are presented which establish the boundedness of all the internal states and simultaneously asymptotic stability of the tracking error dynamics. The results are presented for two common configurations of high speed trains, i.e. the DD and PPD designs, based on the multi-body model and are verified by several numerical simulations. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Fault detection and isolation for complex system
NASA Astrophysics Data System (ADS)
Jing, Chan Shi; Bayuaji, Luhur; Samad, R.; Mustafa, M.; Abdullah, N. R. H.; Zain, Z. M.; Pebrianti, Dwi
2017-07-01
Fault Detection and Isolation (FDI) is a method to monitor, identify, and pinpoint the type and location of system fault in a complex multiple input multiple output (MIMO) non-linear system. A two wheel robot is used as a complex system in this study. The aim of the research is to construct and design a Fault Detection and Isolation algorithm. The proposed method for the fault identification is using hybrid technique that combines Kalman filter and Artificial Neural Network (ANN). The Kalman filter is able to recognize the data from the sensors of the system and indicate the fault of the system in the sensor reading. Error prediction is based on the fault magnitude and the time occurrence of fault. Additionally, Artificial Neural Network (ANN) is another algorithm used to determine the type of fault and isolate the fault in the system.
Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall.
Hampson, Robert E; Song, Dong; Robinson, Brian S; Fetterhoff, Dustin; Dakos, Alexander S; Roeder, Brent M; She, Xiwei; Wicks, Robert T; Witcher, Mark R; Couture, Daniel E; Laxton, Adrian W; Munger-Clary, Heidi; Popli, Gautam; Sollman, Myriam J; Whitlow, Christopher T; Marmarelis, Vasilis Z; Berger, Theodore W; Deadwyler, Sam A
2018-06-01
We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient's own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval. We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information. These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.
Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall
NASA Astrophysics Data System (ADS)
Hampson, Robert E.; Song, Dong; Robinson, Brian S.; Fetterhoff, Dustin; Dakos, Alexander S.; Roeder, Brent M.; She, Xiwei; Wicks, Robert T.; Witcher, Mark R.; Couture, Daniel E.; Laxton, Adrian W.; Munger-Clary, Heidi; Popli, Gautam; Sollman, Myriam J.; Whitlow, Christopher T.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.
2018-06-01
Objective. We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient’s own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval. Approach. We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. Main results. MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information. Significance. These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.
Selvaprabhu, Poongundran; Chinnadurai, Sunil; Sarker, Md Abdul Latif; Lee, Moon Ho
2018-01-28
In this paper, we characterise the joint interference alignment (IA) and power allocation strategies for a K -user multicell multiple-input multiple-output (MIMO) Gaussian interference channel. We consider a MIMO interference channel with blind-IA through staggered antenna switching on the receiver. We explore the power allocation and feasibility condition for cooperative cell-edge (CE) mobile users (MUs) by assuming that the channel state information is unknown. The new insight behind the transmission strategy of the proposed scheme is premeditated (randomly generated transmission strategy) and partial cooperative CE MUs, where the transmitter is equipped with a conventional antenna, the receiver is equipped with a reconfigurable multimode antenna (staggered antenna switching pattern), and the receiver switches between preset T modes. Our proposed scheme assists and aligns the desired signals and interference signals to cancel the common interference signals because the received signal must have a corresponding independent signal subspace. The capacity for a K -user multicell MIMO Gaussian interference channel with reconfigurable multimode antennas is completely characterised. Furthermore, we show that the proposed K -user multicell MIMO scheduling and K -user L -cell CEUs partial cooperation algorithms elaborate the generalisation of K -user IA and power allocation strategies. The numerical results demonstrate that the proposed intercell interference scheme with partial-cooperative CE MUs achieves better capacity and signal-to-interference plus noise ratio (SINR) performance compared to noncooperative CE MUs and without intercell interference schemes.
2018-01-01
In this paper, we characterise the joint interference alignment (IA) and power allocation strategies for a K-user multicell multiple-input multiple-output (MIMO) Gaussian interference channel. We consider a MIMO interference channel with blind-IA through staggered antenna switching on the receiver. We explore the power allocation and feasibility condition for cooperative cell-edge (CE) mobile users (MUs) by assuming that the channel state information is unknown. The new insight behind the transmission strategy of the proposed scheme is premeditated (randomly generated transmission strategy) and partial cooperative CE MUs, where the transmitter is equipped with a conventional antenna, the receiver is equipped with a reconfigurable multimode antenna (staggered antenna switching pattern), and the receiver switches between preset T modes. Our proposed scheme assists and aligns the desired signals and interference signals to cancel the common interference signals because the received signal must have a corresponding independent signal subspace. The capacity for a K-user multicell MIMO Gaussian interference channel with reconfigurable multimode antennas is completely characterised. Furthermore, we show that the proposed K-user multicell MIMO scheduling and K-user L-cell CEUs partial cooperation algorithms elaborate the generalisation of K-user IA and power allocation strategies. The numerical results demonstrate that the proposed intercell interference scheme with partial-cooperative CE MUs achieves better capacity and signal-to-interference plus noise ratio (SINR) performance compared to noncooperative CE MUs and without intercell interference schemes. PMID:29382100
Impact of nonzero boresight pointing error on ergodic capacity of MIMO FSO communication systems.
Boluda-Ruiz, Rubén; García-Zambrana, Antonio; Castillo-Vázquez, Beatriz; Castillo-Vázquez, Carmen
2016-02-22
A thorough investigation of the impact of nonzero boresight pointing errors on the ergodic capacity of multiple-input/multiple-output (MIMO) free-space optical (FSO) systems with equal gain combining (EGC) reception under different turbulence models, which are modeled as statistically independent, but not necessarily identically distributed (i.n.i.d.) is addressed in this paper. Novel closed-form asymptotic expressions at high signal-to-noise ratio (SNR) for the ergodic capacity of MIMO FSO systems are derived when different geometric arrangements of the receive apertures at the receiver are considered in order to reduce the effect of nonzero inherent boresight displacement, which is inevitably present when more than one receive aperture is considered. As a result, the asymptotic ergodic capacity of MIMO FSO systems is evaluated over log-normal (LN), gamma-gamma (GG) and exponentiated Weibull (EW) atmospheric turbulence in order to study different turbulence conditions, different sizes of receive apertures as well as different aperture averaging conditions. It is concluded that the use of single-input/multiple-output (SIMO) and MIMO techniques can significantly increase the ergodic capacity respect to the direct path link when the inherent boresight displacement takes small values, i.e. when the spacing among receive apertures is not too big. The effect of nonzero additional boresight errors, which is due to the thermal expansion of the building, is evaluated in multiple-input/single-output (MISO) and single-input/single-output (SISO) FSO systems. Simulation results are further included to confirm the analytical results.
Li, Yongming; Tong, Shaocheng
2017-12-01
In this paper, an adaptive fuzzy output constrained control design approach is addressed for multi-input multioutput uncertain stochastic nonlinear systems in nonstrict-feedback form. The nonlinear systems addressed in this paper possess unstructured uncertainties, unknown gain functions and unknown stochastic disturbances. Fuzzy logic systems are utilized to tackle the problem of unknown nonlinear uncertainties. The barrier Lyapunov function technique is employed to solve the output constrained problem. In the framework of backstepping design, an adaptive fuzzy control design scheme is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.
Nonlinear climatic sensitivity to greenhouse gases over past 4 glacial/interglacial cycles.
Lo, Li; Chang, Sheng-Pu; Wei, Kuo-Yen; Lee, Shih-Yu; Ou, Tsong-Hua; Chen, Yi-Chi; Chuang, Chih-Kai; Mii, Horng-Sheng; Burr, George S; Chen, Min-Te; Tung, Ying-Hung; Tsai, Meng-Chieh; Hodell, David A; Shen, Chuan-Chou
2017-07-04
The paleoclimatic sensitivity to atmospheric greenhouse gases (GHGs) has recently been suggested to be nonlinear, however a GHG threshold value associated with deglaciation remains uncertain. Here, we combine a new sea surface temperature record spanning the last 360,000 years from the southern Western Pacific Warm Pool with records from five previous studies in the equatorial Pacific to document the nonlinear relationship between climatic sensitivity and GHG levels over the past four glacial/interglacial cycles. The sensitivity of the responses to GHG concentrations rises dramatically by a factor of 2-4 at atmospheric CO 2 levels of >220 ppm. Our results suggest that the equatorial Pacific acts as a nonlinear amplifier that allows global climate to transition from deglacial to full interglacial conditions once atmospheric CO 2 levels reach threshold levels.
Radio-over-optical waveguide system-on-wafer for massive delivery capacity 5G MIMO access networks
NASA Astrophysics Data System (ADS)
Binh, Le N.
2017-01-01
Delivering maximum information capacity over MIMO antennae systems beam steering is critical so as to achieve the flexibility via beam steering, maximizing the number of users or community of users in Gb/s rate per user over distributed cloud-based optical-wireless access networks. This paper gives an overview of (i) demands of optical - wireless delivery with high flexibility, especially the beam steering of multi-Tbps information channels to information hungry community of users via virtualized beam steering MIMO antenna systems at the free-license mmW region; (ii) Proposing a novel photonic planar integrated waveguide systems composing several passive and active, passive and amplification photonic devices so as to generate mmW carrier and embedded baseband information channels to feed to antenna elements; (iii) Integration techniques to generate a radio over optical waveguide (RoOW) system-on-wafer (SoW) comprising MIMO planar antenna elements and associate photonic integrated circuits for both up- and down- links; (iv) Challenges encountered in the implementation of the SoW in both wireless and photonic domains; (v) Photonic modulation techniques to achieve maximum transmission capacity per wavelength per MIMO antenna system. (vi) A view on control-feedback systems for fast and accurate generation of phase pattern for MIMO beam steering via a bank of optical phase modulators to mmW carrier phases and their preservation in the converted mmW domain . (vi) The overall operational principles of the novel techniques and technologies based on the coherent mixing of two lightwave channels The entire SoW can be implemented on SOI Si-photonic technology or via hybrid integration. These technological developments and their pros- and cons- will be discussed to achieve 50Tera-bps over the extended 110 channel Cband single mode fiber with mmW centered at 58.6GHz and 7GHz free-license band.
Control of nonlinear flexible space structures
NASA Astrophysics Data System (ADS)
Shi, Jianjun
With the advances made in computer technology and efficiency of numerical algorithms over last decade, the MPC strategies have become quite popular among control community. However, application of MPC or GPC to flexible space structure control has not been explored adequately in the literature. The work presented in this thesis primarily focuses on application of GPC to control of nonlinear flexible space structures. This thesis is particularly devoted to the development of various approximate dynamic models, design and assessment of candidate controllers, and extensive numerical simulations for a realistic multibody flexible spacecraft, namely, Jupiter Icy Moons Orbiter (JIMO)---a Prometheus class of spacecraft proposed by NASA for deep space exploratory missions. A stable GPC algorithm is developed for Multi-Input-Multi-Output (MIMO) systems. An end-point weighting (penalty) is used in the GPC cost function to guarantee the nominal stability of the closed-loop system. A method is given to compute the desired end-point state from the desired output trajectory. The methodologies based on Fake Algebraic Riccati Equation (FARE) and constrained nonlinear optimization, are developed for synthesis of state weighting matrix. This makes this formulation more practical. A stable reconfigurable GPC architecture is presented and its effectiveness is demonstrated on both aircraft as well as spacecraft model. A representative in-orbit maneuver is used for assessing the performance of various control strategies using various design models. Different approximate dynamic models used for analysis include linear single body flexible structure, nonlinear single body flexible structure, and nonlinear multibody flexible structure. The control laws evaluated include traditional GPC, feedback linearization-based GPC (FLGPC), reconfigurable GPC, and nonlinear dissipative control. These various control schemes are evaluated for robust stability and robust performance in the presence of parametric uncertainties and input disturbances. Finally, the conclusions are made with regard to the efficacy of these controllers and potential directions for future research.
NASA Astrophysics Data System (ADS)
Luo, Jianjun; Wei, Caisheng; Dai, Honghua; Yuan, Jianping
2018-03-01
This paper focuses on robust adaptive control for a class of uncertain nonlinear systems subject to input saturation and external disturbance with guaranteed predefined tracking performance. To reduce the limitations of classical predefined performance control method in the presence of unknown initial tracking errors, a novel predefined performance function with time-varying design parameters is first proposed. Then, aiming at reducing the complexity of nonlinear approximations, only two least-square-support-vector-machine-based (LS-SVM-based) approximators with two design parameters are required through norm form transformation of the original system. Further, a novel LS-SVM-based adaptive constrained control scheme is developed under the time-vary predefined performance using backstepping technique. Wherein, to avoid the tedious analysis and repeated differentiations of virtual control laws in the backstepping technique, a simple and robust finite-time-convergent differentiator is devised to only extract its first-order derivative at each step in the presence of external disturbance. In this sense, the inherent demerit of backstepping technique-;explosion of terms; brought by the recursive virtual controller design is conquered. Moreover, an auxiliary system is designed to compensate the control saturation. Finally, three groups of numerical simulations are employed to validate the effectiveness of the newly developed differentiator and the proposed adaptive constrained control scheme.
Multivariable feedback design - Concepts for a classical/modern synthesis
NASA Technical Reports Server (NTRS)
Doyle, J. C.; Stein, G.
1981-01-01
This paper presents a practical design perspective on multivariable feedback control problems. It reviews the basic issue - feedback design in the face of uncertainties - and generalizes known single-input, single-output (SISO) statements and constraints of the design problem to multiinput, multioutput (MIMO) cases. Two major MIMO design approaches are then evaluated in the context of these results.
Design and Optimization of LTE 1800 MIMO Antenna
Wong, Huey Shin; Islam, Mohammad Tariqul
2014-01-01
A multiple input and multiple output (MIMO) antenna that comprises a printed microstrip antenna and a printed double-L sleeve monopole antenna for LTE 1800 wireless application is presented. The printed double-L sleeve monopole antenna is fed by a 50 ohm coplanar waveguide (CPW). A novel T-shaped microstrip feedline printed on the other side of the PCB is used to excite the waveguide's outer shell. Isolation characteristics better than −15 dB can be obtained for the proposed MIMO antenna. The proposed antenna can operate in LTE 1800 (1710 MHz–1880 MHz). This antenna exhibits omnidirectional characteristics. The efficiency of the antenna is greater than 70% and has high gain of 2.18 dBi. PMID:24967440
Lei, Yi; Li, Jianqiang; Wu, Rui; Fan, Yuting; Fu, Songnian; Yin, Feifei; Dai, Yitang; Xu, Kun
2017-06-01
Based on the observed random fluctuation phenomenon of speckle pattern across multimode fiber (MMF) facet and received optical power distribution across three output ports, we experimentally investigate the statistic characteristics of a 3×3 radio frequency multiple-input multiple-output (MIMO) channel enabled by mode division multiplexing in a conventional 50 µm MMF using non-mode-selective three-dimensional waveguide photonic lanterns as mode multiplexer and demultiplexer. The impacts of mode coupling on the MIMO channel coefficients, channel matrix, and channel capacity have been analyzed over different fiber lengths. The results indicate that spatial multiplexing benefits from the greater fiber length with stronger mode coupling, despite a higher optical loss.
MIMO-OFDM WDM PON with DM-VCSEL for femtocells application.
Othman, M B; Deng, Lei; Pang, Xiaodan; Caminos, J; Kozuch, W; Prince, K; Yu, Xianbin; Jensen, Jesper Bevensee; Monroy, I Tafur
2011-12-12
We report on experimental demonstration of 2x2 MIMO-OFDM 5.6-GHz radio over fiber signaling over 20 km WDM-PON with directly modulated (DM) VCSELs for femtocells application. MIMO-OFDM algorithms effectively compensate for impairments in the wireless link. Error-free signal demodulation of 64 subcarrier 4-QAM signals modulated at 198.5 Mb/s net data rate is achieved after fiber and 2 m indoor wireless transmission. We report BER of 7x10(-3) at the receiver for 16-QAM signals modulated at 397 Mb/s after 1 m of wireless transmission. Performance dependence on different wireless transmission path lengths, antenna separation, and number of subcarriers have been investigated. © 2011 Optical Society of America
Mitigation Approaches for Optical Imaging through Clouds and Fog
2009-11-01
Spatially Multiplexed Optical MIMO Imaging System in Cloudy Turbulent Atmosphere ...This atmospheric attenuation imposes a big challenge on laser imaging systems , and it can be as severe as 300 dB/km in heavy fog [3]. As a result, the...MIT Lincoln Lab [8][9][10]. In this report, we propose MIMO imaging systems and investigate their performance under various atmospheric conditions
Scalable System Design for Covert MIMO Communications
2014-06-01
Sample based resolution of the QRD and equalization processes in the MIMO receiver, for NQR = 11...55 5.1 NQR calculation parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.2 Resources available on Xilinx Virtex-7 FPGAs...carried out for Na ∈ [2 3 4]. Extrapolation is used to determine trends as a function of the number of QRD blocks instantiated NQR and Na. This section
NASA Astrophysics Data System (ADS)
Mazoochi, M.; Pourmina, M. A.; Bakhshi, H.
2015-03-01
The core aim of this work is the maximization of the achievable data rate of the secondary user pairs (SU pairs), while ensuring the QoS of primary users (PUs). All users are assumed to be equipped with multiple antennas. It is assumed that when PUs are present, the direct communications between SU pairs introduces intolerable interference to PUs and thereby SUs transmit signal using the cooperation of other SUs and avoid transmitting in the direct channel. In brief, an adaptive cooperative strategy for multiple-input/multiple-output (MIMO) cognitive radio networks is proposed. At the presence of PUs, the issue of joint relay selection and power allocation in Underlay MIMO Cooperative Cognitive Radio Networks (U-MIMO-CCRN) is addressed. The optimal approach for determining the power allocation and the cooperating SU is proposed. Besides, the outage probability of the proposed communication protocol is further derived. Due to high complexity of the optimal approach, a low-complexity approach is further proposed and its performance is evaluated using simulations. The simulation results reveal that the performance loss due to the low-complexity approach is only about 14%, while the complexity is greatly reduced.
A study on the achievable data rate in massive MIMO system
NASA Astrophysics Data System (ADS)
Salh, Adeeb; Audah, Lukman; Shah, Nor Shahida M.; Hamzah, Shipun A.
2017-09-01
The achievable high data rates depend on the ability of massive multi-input-multi-output (MIMO) for the fifth-generation (5G) cellular networks, where the massive MIMO systems can support very high energy and spectral efficiencies. A major challenge in mobile broadband networks is how to support the throughput in the future 5G, where the highlight of 5G expected to provide high speed internet for every user. The performance massive MIMO system increase with linear minimum mean square error (MMSE), zero forcing (ZF) and maximum ratio transmission (MRT) when the number of antennas increases to infinity, by deriving the closed-form approximation for achievable data rate expressions. Meanwhile, the high signal-to-noise ratio (SNR) can be mitigated by using MMSE, ZF and MRT, which are used to suppress the inter-cell interference signals between neighboring cells. The achievable sum rate for MMSE is improved based on the distributed users inside cell, mitigated the inter-cell interference caused when send the same signal by other cells. By contrast, MMSE is better than ZF in perfect channel state information (CSI) for approximately 20% of the achievable sum rate.
Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter.
Bolisetti, Siva Karteek; Patwary, Mohammad; Ahmed, Khawza; Soliman, Abdel-Hamid; Abdel-Maguid, Mohamed
2015-01-01
The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the target detection performance of a MIMO radar detector in the presence of clutter. The number of samples that are required to be processed by a radar target detector regulates the amount of processing burden while achieving a given detection reliability. While Subspace Compressive GLRT (SSC-GLRT) detector is known to give optimised radar target detection performance with reduced computational complexity, it however suffers a significant deterioration in target detection performance in the presence of clutter. In this paper we provide evidence that the proposed mathematical model for SSC-GLRT detector outperforms the existing detectors in the presence of clutter. The performance analysis of the existing detectors and the proposed SSC-GLRT detector for MIMO radar in the presence of clutter are provided in this paper.
Computer Simulation and Field Experiment for Downlink Multiuser MIMO in Mobile WiMAX System.
Yamaguchi, Kazuhiro; Nagahashi, Takaharu; Akiyama, Takuya; Matsue, Hideaki; Uekado, Kunio; Namera, Takakazu; Fukui, Hiroshi; Nanamatsu, Satoshi
2015-01-01
The transmission performance for a downlink mobile WiMAX system with multiuser multiple-input multiple-output (MU-MIMO) systems in a computer simulation and field experiment is described. In computer simulation, a MU-MIMO transmission system can be realized by using the block diagonalization (BD) algorithm, and each user can receive signals without any signal interference from other users. The bit error rate (BER) performance and channel capacity in accordance with modulation schemes and the number of streams were simulated in a spatially correlated multipath fading environment. Furthermore, we propose a method for evaluating the transmission performance for this downlink mobile WiMAX system in this environment by using the computer simulation. In the field experiment, the received power and downlink throughput in the UDP layer were measured on an experimental mobile WiMAX system developed in Azumino City in Japan. In comparison with the simulated and experimented results, the measured maximum throughput performance in the downlink had almost the same performance as the simulated throughput. It was confirmed that the experimental mobile WiMAX system for MU-MIMO transmission successfully increased the total channel capacity of the system.
Dominguez-Rodriguez, Alberto; Burillo-Putze, Guillermo; Garcia-Saiz, Maria Del Mar; Aldea-Perona, Ana; Harmand, Magali González-Colaço; Mirò, Oscar; Abreu-Gonzalez, Pedro
2017-04-01
Morphine has been used for several decades in cases of acute pulmonary edema (APE) due to the anxiolytic and vasodilatory properties of the drug. The non-specific depression of the central nervous system is probably the most significant factor for the changes in hemodynamics in APE. Retrospective studies have shown both negative and neutral effects in patients with APE and therefore some authors have suggested benzodiazepines as an alternative treatment. The use of intravenous morphine in the treatment of APE remains controversial. The MIdazolan versus MOrphine in APE trial (MIMO) is a multicenter, prospective, open-label, randomized study designed to evaluate the efficacy and safety of morphine in patients with APE. The MIMO trial will evaluate as a primary endpoint whether intravenous morphine administration improves clinical outcomes defined as in-hospital mortality. Secondary endpoint evaluation will be mechanical ventilation, cardiopulmonary resuscitation, intensive care unit admission rate, intensive care unit length of stay, and hospitalization length. In the emergency department, morphine is still used for APE in spite of poor scientific background data. The data from the MIMO trial will establish the effect-and especially the risk-when using morphine for APE.
Computer Simulation and Field Experiment for Downlink Multiuser MIMO in Mobile WiMAX System
Yamaguchi, Kazuhiro; Nagahashi, Takaharu; Akiyama, Takuya; Matsue, Hideaki; Uekado, Kunio; Namera, Takakazu; Fukui, Hiroshi; Nanamatsu, Satoshi
2015-01-01
The transmission performance for a downlink mobile WiMAX system with multiuser multiple-input multiple-output (MU-MIMO) systems in a computer simulation and field experiment is described. In computer simulation, a MU-MIMO transmission system can be realized by using the block diagonalization (BD) algorithm, and each user can receive signals without any signal interference from other users. The bit error rate (BER) performance and channel capacity in accordance with modulation schemes and the number of streams were simulated in a spatially correlated multipath fading environment. Furthermore, we propose a method for evaluating the transmission performance for this downlink mobile WiMAX system in this environment by using the computer simulation. In the field experiment, the received power and downlink throughput in the UDP layer were measured on an experimental mobile WiMAX system developed in Azumino City in Japan. In comparison with the simulated and experimented results, the measured maximum throughput performance in the downlink had almost the same performance as the simulated throughput. It was confirmed that the experimental mobile WiMAX system for MU-MIMO transmission successfully increased the total channel capacity of the system. PMID:26421311
Channel Acquisition for Massive MIMO-OFDM With Adjustable Phase Shift Pilots
NASA Astrophysics Data System (ADS)
You, Li; Gao, Xiqi; Swindlehurst, A. Lee; Zhong, Wen
2016-03-01
We propose adjustable phase shift pilots (APSPs) for channel acquisition in wideband massive multiple-input multiple-output (MIMO) systems employing orthogonal frequency division multiplexing (OFDM) to reduce the pilot overhead. Based on a physically motivated channel model, we first establish a relationship between channel space-frequency correlations and the channel power angle-delay spectrum in the massive antenna array regime, which reveals the channel sparsity in massive MIMO-OFDM. With this channel model, we then investigate channel acquisition, including channel estimation and channel prediction, for massive MIMO-OFDM with APSPs. We show that channel acquisition performance in terms of sum mean square error can be minimized if the user terminals' channel power distributions in the angle-delay domain can be made non-overlapping with proper phase shift scheduling. A simplified pilot phase shift scheduling algorithm is developed based on this optimal channel acquisition condition. The performance of APSPs is investigated for both one symbol and multiple symbol data models. Simulations demonstrate that the proposed APSP approach can provide substantial performance gains in terms of achievable spectral efficiency over the conventional phase shift orthogonal pilot approach in typical mobility scenarios.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Yimin; Lv, Hui, E-mail: lvhui207@gmail.com
In this paper, we consider the control problem of a class of uncertain fractional-order chaotic systems preceded by unknown backlash-like hysteresis nonlinearities based on backstepping control algorithm. We model the hysteresis by using a differential equation. Based on the fractional Lyapunov stability criterion and the backstepping algorithm procedures, an adaptive neural network controller is driven. No knowledge of the upper bound of the disturbance and system uncertainty is required in our controller, and the asymptotical convergence of the tracking error can be guaranteed. Finally, we give two simulation examples to confirm our theoretical results.
Radac, Mircea-Bogdan; Precup, Radu-Emil; Roman, Raul-Cristian
2018-02-01
This paper proposes a combined Virtual Reference Feedback Tuning-Q-learning model-free control approach, which tunes nonlinear static state feedback controllers to achieve output model reference tracking in an optimal control framework. The novel iterative Batch Fitted Q-learning strategy uses two neural networks to represent the value function (critic) and the controller (actor), and it is referred to as a mixed Virtual Reference Feedback Tuning-Batch Fitted Q-learning approach. Learning convergence of the Q-learning schemes generally depends, among other settings, on the efficient exploration of the state-action space. Handcrafting test signals for efficient exploration is difficult even for input-output stable unknown processes. Virtual Reference Feedback Tuning can ensure an initial stabilizing controller to be learned from few input-output data and it can be next used to collect substantially more input-state data in a controlled mode, in a constrained environment, by compensating the process dynamics. This data is used to learn significantly superior nonlinear state feedback neural networks controllers for model reference tracking, using the proposed Batch Fitted Q-learning iterative tuning strategy, motivating the original combination of the two techniques. The mixed Virtual Reference Feedback Tuning-Batch Fitted Q-learning approach is experimentally validated for water level control of a multi input-multi output nonlinear constrained coupled two-tank system. Discussions on the observed control behavior are offered. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
A joint swarm intelligence algorithm for multi-user detection in MIMO-OFDM system
NASA Astrophysics Data System (ADS)
Hu, Fengye; Du, Dakun; Zhang, Peng; Wang, Zhijun
2014-11-01
In the multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, traditional multi-user detection (MUD) algorithms that usually used to suppress multiple access interference are difficult to balance system detection performance and the complexity of the algorithm. To solve this problem, this paper proposes a joint swarm intelligence algorithm called Ant Colony and Particle Swarm Optimisation (AC-PSO) by integrating particle swarm optimisation (PSO) and ant colony optimisation (ACO) algorithms. According to simulation results, it has been shown that, with low computational complexity, the MUD for the MIMO-OFDM system based on AC-PSO algorithm gains comparable MUD performance with maximum likelihood algorithm. Thus, the proposed AC-PSO algorithm provides a satisfactory trade-off between computational complexity and detection performance.
A channel estimation scheme for MIMO-OFDM systems
NASA Astrophysics Data System (ADS)
He, Chunlong; Tian, Chu; Li, Xingquan; Zhang, Ce; Zhang, Shiqi; Liu, Chaowen
2017-08-01
In view of the contradiction of the time-domain least squares (LS) channel estimation performance and the practical realization complexity, a reduced complexity channel estimation method for multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) based on pilot is obtained. This approach can transform the complexity of MIMO-OFDM channel estimation problem into a simple single input single output-orthogonal frequency division multiplexing (SISO-OFDM) channel estimation problem and therefore there is no need for large matrix pseudo-inverse, which greatly reduces the complexity of algorithms. Simulation results show that the bit error rate (BER) performance of the obtained method with time orthogonal training sequences and linear minimum mean square error (LMMSE) criteria is better than that of time-domain LS estimator and nearly optimal performance.
Xu, Shidong; Sun, Guanghui; Sun, Weichao
2017-01-01
In this paper, the problem of robust dissipative control is investigated for uncertain flexible spacecraft based on Takagi-Sugeno (T-S) fuzzy model with saturated time-delay input. Different from most existing strategies, T-S fuzzy approximation approach is used to model the nonlinear dynamics of flexible spacecraft. Simultaneously, the physical constraints of system, like input delay, input saturation, and parameter uncertainties, are also taken care of in the fuzzy model. By employing Lyapunov-Krasovskii method and convex optimization technique, a novel robust controller is proposed to implement rest-to-rest attitude maneuver for flexible spacecraft, and the guaranteed dissipative performance enables the uncertain closed-loop system to reject the influence of elastic vibrations and external disturbances. Finally, an illustrative design example integrated with simulation results are provided to confirm the applicability and merits of the developed control strategy. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Klingelhoefer, Goestar; Morris, Richard; Blumers, Mathias; Girones-Lopez, Jordi; Bernhardt, Bodo; Henkel, Hartmut; D'Uston, Claude; Brueckner, Johannes; Rodionov, Daniel; Strueder, Lothar
The Miniaturised Mössbauer Spectrometers MIMOS II on board the two NASA Mars Exploration Rovers (MER) have now collected valuable scientific data for more than ten years [1-4]. This mission has demonstrated that Mössbauer spectroscopy is extremely valuable for the in situ exploration of extraterrestrial bodies and the study of Fe-bearing samples. A MIMOS instrument was also on the scientific payload of the Russian mission Phobos Grunt [5]. The instrument MIMOS IIA originally developed for the ESA ExoMars mission (now 2018) will use newly de-signed Si-Drift detectors with circular geometry (SDD) [6,7] allowing high resolution X-ray fluorescence spectroscopy simultaneously to Mössbauer measurements. The new design of the improved MIMOS II instrument is reduced in total mass (less than 400 g). The sensorhead of MIMOS IIA will be equipped with a ring of Silicon Drift Detectors (SDD) optimized for the backscatter geometry of the miniaturized Mössbauer spectrometer. The main goal of the new detector system design was to combine high energy resolution at high counting rates and large detector area while making maximum use of the area close to the collimator of the 57Co Mössbauer source. The active area per SDD segment is 2x45 mm2. The energy resolution at 5.9 keV is < 280 eV at room temperature and 131 eV FWHM at -40oC. This performance will increase the signal to noise ratio (SNR) and reduce the integration time of Mössbauer measurement by a factor of up to 10. In addition to the Mössbauer analysis simultaneous acquisition of the X-ray fluorescence spectrum will provide data on the sample's elemental composition [7]. Preliminary studies at room temperature and normal pressure show detection of X-rays down to ~1 keV. A new control- and readout electronics for MIMOS IIA allows spectra acquisition at highest possible countrates available at about 360 mm2 total detector area. A prototype of MIMOS IIA has been tested successfully during a field test at Mauna Kea, Hawaii, as part of the international NASA JSC lead In-Situ Resource Utilization field tests 2010 and 2012. Acknowledgment: Funded by german space agency DLR under contract 50 QX 0603 and 50QX0802. References: [1] Klingelhöfer et al., J. Geophys. Res. 108(E12) (2003) [2] Klingelhöfer et al., Science 306 (2004) 1740-1745. [3] Morris et al., Science 305 (2004) 833-836. [4] Morris et al., J. Geophys. Res. 111 (2006) [5] Rodionov et al., Solar System Research Vol. 44, No. 5 (2010) pp. 362-370 [6] P. Lechner et al., Nucl. Instr. and Meth. A 377 (1996) 346-351 [7] M. Blumers et al., Nucl. Instr. and Meth. A 624 (2010) 277-281
An Optimization Framework for Dynamic Hybrid Energy Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wenbo Du; Humberto E Garcia; Christiaan J.J. Paredis
A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problemmore » takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.« less
MURI: Impact of Oceanographic Variability on Acoustic Communications
2012-09-30
ACSSC.2010.5757934 (2010). [published] [50] K. Tu, T.M. Duman, J.G. Proakis, and M. Stojanovic, “Cooperative MIMO - OFDM communications: Receiver...considered across bands of frequencies in the range 1-50 kHz. Multiple source and receiver cases ( MIMO ) will be of particular interest. Validating...Parabolic Equation (PE) acoustic models. Communication receiver design has included processors for orthogonal frequency division multiplexing ( OFDM
On the Implementation of Iterative Detection in Real-World MIMO Wireless Systems
2003-12-01
multientr~es et multisorties (MIMO) permettent une exploitation remarquable du spectre comparativement aux syst~mes traditionnels A antenne unique...vecteurs symboliques pilotes connus cause une perte de rendement n~gligeable comparativement au cas hypothdtique des connaissances des voies parfaites...useful design guidelines for iterative systems. it does not provide any fundamental understanding as to how the design of the detector can improve the
A MIMO-Inspired Rapidly Switchable Photonic Interconnect Architecture (Postprint)
2009-07-01
capabilities of future systems. Highspeed optical processing has been looked to as a means for eliminating this interconnect bottleneck. Presented...here are the results of a study for a novel optical (integrated photonic) processor which would allow for a high-speed, secure means for arbitrarily...regarded as a Multiple Input Multiple Output (MIMO) architecture. 15. SUBJECT TERMS Free-space optical interconnects, Optical Phased Arrays, High-Speed
Aeroservoelastic Model Validation and Test Data Analysis of the F/A-18 Active Aeroelastic Wing
NASA Technical Reports Server (NTRS)
Brenner, Martin J.; Prazenica, Richard J.
2003-01-01
Model validation and flight test data analysis require careful consideration of the effects of uncertainty, noise, and nonlinearity. Uncertainty prevails in the data analysis techniques and results in a composite model uncertainty from unmodeled dynamics, assumptions and mechanics of the estimation procedures, noise, and nonlinearity. A fundamental requirement for reliable and robust model development is an attempt to account for each of these sources of error, in particular, for model validation, robust stability prediction, and flight control system development. This paper is concerned with data processing procedures for uncertainty reduction in model validation for stability estimation and nonlinear identification. F/A-18 Active Aeroelastic Wing (AAW) aircraft data is used to demonstrate signal representation effects on uncertain model development, stability estimation, and nonlinear identification. Data is decomposed using adaptive orthonormal best-basis and wavelet-basis signal decompositions for signal denoising into linear and nonlinear identification algorithms. Nonlinear identification from a wavelet-based Volterra kernel procedure is used to extract nonlinear dynamics from aeroelastic responses, and to assist model development and uncertainty reduction for model validation and stability prediction by removing a class of nonlinearity from the uncertainty.
Lean vs Agile in the Context of Complexity Management in Organizations
ERIC Educational Resources Information Center
Putnik, Goran D.; Putnik, Zlata
2012-01-01
Purpose: The objective of this paper is to provide a deeper insight into the relationship of the issue "lean vs agile" in order to inform managers towards more coherent decisions especially in a dynamic, unpredictable, uncertain, non-linear environment. Design/methodology/approach: The methodology is an exploratory study based on secondary data…
USDA-ARS?s Scientific Manuscript database
The fuzzy logic algorithm has the ability to describe knowledge in a descriptive human-like manner in the form of simple rules using linguistic variables, and provides a new way of modeling uncertain or naturally fuzzy hydrological processes like non-linear rainfall-runoff relationships. Fuzzy infe...
Generalized Predictive and Neural Generalized Predictive Control of Aerospace Systems
NASA Technical Reports Server (NTRS)
Kelkar, Atul G.
2000-01-01
The research work presented in this thesis addresses the problem of robust control of uncertain linear and nonlinear systems using Neural network-based Generalized Predictive Control (NGPC) methodology. A brief overview of predictive control and its comparison with Linear Quadratic (LQ) control is given to emphasize advantages and drawbacks of predictive control methods. It is shown that the Generalized Predictive Control (GPC) methodology overcomes the drawbacks associated with traditional LQ control as well as conventional predictive control methods. It is shown that in spite of the model-based nature of GPC it has good robustness properties being special case of receding horizon control. The conditions for choosing tuning parameters for GPC to ensure closed-loop stability are derived. A neural network-based GPC architecture is proposed for the control of linear and nonlinear uncertain systems. A methodology to account for parametric uncertainty in the system is proposed using on-line training capability of multi-layer neural network. Several simulation examples and results from real-time experiments are given to demonstrate the effectiveness of the proposed methodology.
Approximate N-Player Nonzero-Sum Game Solution for an Uncertain Continuous Nonlinear System.
Johnson, Marcus; Kamalapurkar, Rushikesh; Bhasin, Shubhendu; Dixon, Warren E
2015-08-01
An approximate online equilibrium solution is developed for an N -player nonzero-sum game subject to continuous-time nonlinear unknown dynamics and an infinite horizon quadratic cost. A novel actor-critic-identifier structure is used, wherein a robust dynamic neural network is used to asymptotically identify the uncertain system with additive disturbances, and a set of critic and actor NNs are used to approximate the value functions and equilibrium policies, respectively. The weight update laws for the actor neural networks (NNs) are generated using a gradient-descent method, and the critic NNs are generated by least square regression, which are both based on the modified Bellman error that is independent of the system dynamics. A Lyapunov-based stability analysis shows that uniformly ultimately bounded tracking is achieved, and a convergence analysis demonstrates that the approximate control policies converge to a neighborhood of the optimal solutions. The actor, critic, and identifier structures are implemented in real time continuously and simultaneously. Simulations on two and three player games illustrate the performance of the developed method.
Wang, Ning; Sun, Jing-Chao; Han, Min; Zheng, Zhongjiu; Er, Meng Joo
2017-09-06
In this paper, for a general class of uncertain nonlinear (cascade) systems, including unknown dynamics, which are not feedback linearizable and cannot be solved by existing approaches, an innovative adaptive approximation-based regulation control (AARC) scheme is developed. Within the framework of adding a power integrator (API), by deriving adaptive laws for output weights and prediction error compensation pertaining to single-hidden-layer feedforward network (SLFN) from the Lyapunov synthesis, a series of SLFN-based approximators are explicitly constructed to exactly dominate completely unknown dynamics. By the virtue of significant advancements on the API technique, an adaptive API methodology is eventually established in combination with SLFN-based adaptive approximators, and it contributes to a recursive mechanism for the AARC scheme. As a consequence, the output regulation error can asymptotically converge to the origin, and all other signals of the closed-loop system are uniformly ultimately bounded. Simulation studies and comprehensive comparisons with backstepping- and API-based approaches demonstrate that the proposed AARC scheme achieves remarkable performance and superiority in dealing with unknown dynamics.
NASA Astrophysics Data System (ADS)
Choi, Junil; Love, David J.; Bidigare, Patrick
2014-10-01
The concept of deploying a large number of antennas at the base station, often called massive multiple-input multiple-output (MIMO), has drawn considerable interest because of its potential ability to revolutionize current wireless communication systems. Most literature on massive MIMO systems assumes time division duplexing (TDD), although frequency division duplexing (FDD) dominates current cellular systems. Due to the large number of transmit antennas at the base station, currently standardized approaches would require a large percentage of the precious downlink and uplink resources in FDD massive MIMO be used for training signal transmissions and channel state information (CSI) feedback. To reduce the overhead of the downlink training phase, we propose practical open-loop and closed-loop training frameworks in this paper. We assume the base station and the user share a common set of training signals in advance. In open-loop training, the base station transmits training signals in a round-robin manner, and the user successively estimates the current channel using long-term channel statistics such as temporal and spatial correlations and previous channel estimates. In closed-loop training, the user feeds back the best training signal to be sent in the future based on channel prediction and the previously received training signals. With a small amount of feedback from the user to the base station, closed-loop training offers better performance in the data communication phase, especially when the signal-to-noise ratio is low, the number of transmit antennas is large, or prior channel estimates are not accurate at the beginning of the communication setup, all of which would be mostly beneficial for massive MIMO systems.
Magnetic MIMO Signal Processing and Optimization for Wireless Power Transfer
NASA Astrophysics Data System (ADS)
Yang, Gang; Moghadam, Mohammad R. Vedady; Zhang, Rui
2017-06-01
In magnetic resonant coupling (MRC) enabled multiple-input multiple-output (MIMO) wireless power transfer (WPT) systems, multiple transmitters (TXs) each with one single coil are used to enhance the efficiency of simultaneous power transfer to multiple single-coil receivers (RXs) by constructively combining their induced magnetic fields at the RXs, a technique termed "magnetic beamforming". In this paper, we study the optimal magnetic beamforming design in a multi-user MIMO MRC-WPT system. We introduce the multi-user power region that constitutes all the achievable power tuples for all RXs, subject to the given total power constraint over all TXs as well as their individual peak voltage and current constraints. We characterize each boundary point of the power region by maximizing the sum-power deliverable to all RXs subject to their minimum harvested power constraints. For the special case without the TX peak voltage and current constraints, we derive the optimal TX current allocation for the single-RX setup in closed-form as well as that for the multi-RX setup. In general, the problem is a non-convex quadratically constrained quadratic programming (QCQP), which is difficult to solve. For the case of one single RX, we show that the semidefinite relaxation (SDR) of the problem is tight. For the general case with multiple RXs, based on SDR we obtain two approximate solutions by applying time-sharing and randomization, respectively. Moreover, for practical implementation of magnetic beamforming, we propose a novel signal processing method to estimate the magnetic MIMO channel due to the mutual inductances between TXs and RXs. Numerical results show that our proposed magnetic channel estimation and adaptive beamforming schemes are practically effective, and can significantly improve the power transfer efficiency and multi-user performance trade-off in MIMO MRC-WPT systems.
Nonlinear Modeling of Causal Interrelationships in Neuronal Ensembles
Zanos, Theodoros P.; Courellis, Spiros H.; Berger, Theodore W.; Hampson, Robert E.; Deadwyler, Sam A.; Marmarelis, Vasilis Z.
2009-01-01
The increasing availability of multiunit recordings gives new urgency to the need for effective analysis of “multidimensional” time-series data that are derived from the recorded activity of neuronal ensembles in the form of multiple sequences of action potentials—treated mathematically as point-processes and computationally as spike-trains. Whether in conditions of spontaneous activity or under conditions of external stimulation, the objective is the identification and quantification of possible causal links among the neurons generating the observed binary signals. A multiple-input/multiple-output (MIMO) modeling methodology is presented that can be used to quantify the neuronal dynamics of causal interrelationships in neuronal ensembles using spike-train data recorded from individual neurons. These causal interrelationships are modeled as transformations of spike-trains recorded from a set of neurons designated as the “inputs” into spike-trains recorded from another set of neurons designated as the “outputs.” The MIMO model is composed of a set of multiinput/single-output (MISO) modules, one for each output. Each module is the cascade of a MISO Volterra model and a threshold operator generating the output spikes. The Laguerre expansion approach is used to estimate the Volterra kernels of each MISO module from the respective input–output data using the least-squares method. The predictive performance of the model is evaluated with the use of the receiver operating characteristic (ROC) curve, from which the optimum threshold is also selected. The Mann–Whitney statistic is used to select the significant inputs for each output by examining the statistical significance of improvements in the predictive accuracy of the model when the respective inputs is included. Illustrative examples are presented for a simulated system and for an actual application using multiunit data recordings from the hippocampus of a behaving rat. PMID:18701382
Robust THP Transceiver Designs for Multiuser MIMO Downlink with Imperfect CSIT
NASA Astrophysics Data System (ADS)
Ubaidulla, P.; Chockalingam, A.
2009-12-01
We present robust joint nonlinear transceiver designs for multiuser multiple-input multiple-output (MIMO) downlink in the presence of imperfections in the channel state information at the transmitter (CSIT). The base station (BS) is equipped with multiple transmit antennas, and each user terminal is equipped with one or more receive antennas. The BS employs Tomlinson-Harashima precoding (THP) for interuser interference precancellation at the transmitter. We consider robust transceiver designs that jointly optimize the transmit THP filters and receive filter for two models of CSIT errors. The first model is a stochastic error (SE) model, where the CSIT error is Gaussian-distributed. This model is applicable when the CSIT error is dominated by channel estimation error. In this case, the proposed robust transceiver design seeks to minimize a stochastic function of the sum mean square error (SMSE) under a constraint on the total BS transmit power. We propose an iterative algorithm to solve this problem. The other model we consider is a norm-bounded error (NBE) model, where the CSIT error can be specified by an uncertainty set. This model is applicable when the CSIT error is dominated by quantization errors. In this case, we consider a worst-case design. For this model, we consider robust (i) minimum SMSE, (ii) MSE-constrained, and (iii) MSE-balancing transceiver designs. We propose iterative algorithms to solve these problems, wherein each iteration involves a pair of semidefinite programs (SDPs). Further, we consider an extension of the proposed algorithm to the case with per-antenna power constraints. We evaluate the robustness of the proposed algorithms to imperfections in CSIT through simulation, and show that the proposed robust designs outperform nonrobust designs as well as robust linear transceiver designs reported in the recent literature.
Efficient two-dimensional compressive sensing in MIMO radar
NASA Astrophysics Data System (ADS)
Shahbazi, Nafiseh; Abbasfar, Aliazam; Jabbarian-Jahromi, Mohammad
2017-12-01
Compressive sensing (CS) has been a way to lower sampling rate leading to data reduction for processing in multiple-input multiple-output (MIMO) radar systems. In this paper, we further reduce the computational complexity of a pulse-Doppler collocated MIMO radar by introducing a two-dimensional (2D) compressive sensing. To do so, we first introduce a new 2D formulation for the compressed received signals and then we propose a new measurement matrix design for our 2D compressive sensing model that is based on minimizing the coherence of sensing matrix using gradient descent algorithm. The simulation results show that our proposed 2D measurement matrix design using gradient decent algorithm (2D-MMDGD) has much lower computational complexity compared to one-dimensional (1D) methods while having better performance in comparison with conventional methods such as Gaussian random measurement matrix.
NASA Astrophysics Data System (ADS)
Igarashi, Koji; Park, Kyung Jun; Tsuritani, Takahiro; Morita, Itsuro; Kim, Byoung Yoon
2018-02-01
We show all-fiber-based selective mode multiplexers and demultiplexers for weakly-coupled mode-division multiplexed systems. We fabricate a set of six-mode multiplexer and demultiplexer based on fiber mode selective couplers, and experimentally evaluate the performance for the six-mode dual-polarization (DP) quadrature phase shift keying (QPSK) optical signals. In the mode multiplexer and demultiplexer, the mode couplings between the lower three modes and the higher three modes are suppressed to be less than -20 dB, which enables us to apply partial 6 ×6 MIMO equalizers even for the six-mode demultiplexing. For the six-mode DP-QPSK signals, the penalty of optical signal-to-noise ratio by replacing the full 12 ×12MIMO to the partial 6 ×6 MIMO is suppressed by less than 1 dB.
Zhou, Xian; Zhong, Kangping; Gao, Yuliang; Sui, Qi; Dong, Zhenghua; Yuan, Jinhui; Wang, Liang; Long, Keping; Lau, Alan Pak Tao; Lu, Chao
2015-04-06
Discrete multi-tone (DMT) modulation is an attractive modulation format for short-reach applications to achieve the best use of available channel bandwidth and signal noise ratio (SNR). In order to realize polarization-multiplexed DMT modulation with direct detection, we derive an analytical transmission model for dual polarizations with intensity modulation and direct diction (IM-DD) in this paper. Based on the model, we propose a novel polarization-interleave-multiplexed DMT modulation with direct diction (PIM-DMT-DD) transmission system, where the polarization de-multiplexing can be achieved by using a simple multiple-input-multiple-output (MIMO) equalizer and the transmission performance is optimized over two distinct received polarization states to eliminate the singularity issue of MIMO demultiplexing algorithms. The feasibility and effectiveness of the proposed PIM-DMT-DD system are investigated via theoretical analyses and simulation studies.
Gkonis, Panagiotis K.; Seimeni, Maria A.; Asimakis, Nikolaos P.; Kaklamani, Dimitra I.; Venieris, Iakovos S.
2014-01-01
The goal of the study presented in this paper is to investigate the performance of a new subcarrier allocation strategy for Orthogonal Frequency Division Multiple Access (OFDMA) multicellular networks which employ Multiple Input Multiple Output (MIMO) architecture. For this reason, a hybrid system-link level simulator has been developed executing independent Monte Carlo (MC) simulations in parallel. Up to two tiers of cells around the central cell are taken into consideration and increased loading per cell. The derived results indicate that this strategy can provide up to 12% capacity gain for 16-QAM modulation and two tiers of cells around the central cell in a symmetric 2 × 2 MIMO configuration. This gain is derived when comparing the proposed strategy to the traditional approach of allocating subcarriers that maximize only the desired user's signal. PMID:24683351
Composite Intelligent Learning Control of Strict-Feedback Systems With Disturbance.
Xu, Bin; Sun, Fuchun
2018-02-01
This paper addresses the dynamic surface control of uncertain nonlinear systems on the basis of composite intelligent learning and disturbance observer in presence of unknown system nonlinearity and time-varying disturbance. The serial-parallel estimation model with intelligent approximation and disturbance estimation is built to obtain the prediction error and in this way the composite law for weights updating is constructed. The nonlinear disturbance observer is developed using intelligent approximation information while the disturbance estimation is guaranteed to converge to a bounded compact set. The highlight is that different from previous work directly toward asymptotic stability, the transparency of the intelligent approximation and disturbance estimation is included in the control scheme. The uniformly ultimate boundedness stability is analyzed via Lyapunov method. Through simulation verification, the composite intelligent learning with disturbance observer can efficiently estimate the effect caused by system nonlinearity and disturbance while the proposed approach obtains better performance with higher accuracy.
Observed-Based Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems With Dead-Zone.
Tong, Shaocheng; Sui, Shuai; Li, Yongming
2015-12-01
In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict-feedback form. The considered switched systems contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, a switched fuzzy state observer is designed and thus the immeasurable states are obtained by it. By applying the adaptive backstepping design principle and the average dwell time method, an adaptive fuzzy output-feedback tracking control approach is developed. It is proved that the proposed control approach can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.
Adaptive Fuzzy Output Feedback Control for Switched Nonlinear Systems With Unmodeled Dynamics.
Tong, Shaocheng; Li, Yongming
2017-02-01
This paper investigates a robust adaptive fuzzy control stabilization problem for a class of uncertain nonlinear systems with arbitrary switching signals that use an observer-based output feedback scheme. The considered switched nonlinear systems possess the unstructured uncertainties, unmodeled dynamics, and without requiring the states being available for measurement. A state observer which is independent of switching signals is designed to solve the problem of unmeasured states. Fuzzy logic systems are used to identify unknown lumped nonlinear functions so that the problem of unstructured uncertainties can be solved. By combining adaptive backstepping design principle and small-gain approach, a novel robust adaptive fuzzy output feedback stabilization control approach is developed. The stability of the closed-loop system is proved via the common Lyapunov function theory and small-gain theorem. Finally, the simulation results are given to demonstrate the validity and performance of the proposed control strategy.
Jointly Optimal Design for MIMO Radar Frequency-Hopping Waveforms Using Game Theory
2016-04-01
Washington University in St . Louis St . Louis, MO, USA Using a colocated multiple input/multiple output (MIMO) radar system, we consider the problem of...Authors’ address: Preston M. Green Department of Electrical and Systems Engineering, Washington University in St . Louis, St . Louis, MO, 63130...engineering from Washington University in St . Louis, under the guidance of Dr. Arye Nehorai, in 2012 and 2015, respectively. His research interests
High Throughput via Cross-Layer Interference Alignment for Mobile Ad Hoc Networks
2013-08-26
MIMO zero-forcing receiver in the presence of channel estimation error,” IEEE Transactions on Wireless Communications , vol. 6 , no. 3, pp. 805–810, Mar...Robert W. Heath, Nachiappan Valliappan. Antenna Subset Modulation for Secure Millimeter-Wave Wireless Communication , IEEE Transactions on...in MIMO Interference Alignment Networks, IEEE Transactions on Wireless Communications , (02 2012): 0. doi: 10.1109/TWC.2011.120511.111088 TOTAL: 2
Energy Efficient Signal Detection for Army Applications Based on Ordering
2011-09-01
Systems, (07 2010): 0. doi: 10.1109/TAES.2010.5545189 2011/09/03 18:03:52 35 Qian He, Rick S. Blum, Alexander M. Haimovich. Noncoherent MIMO Radar for...Conference Proceeding publications (other than abstracts): PaperReceived . Noncoherent Versus Coherent MIMO Radar for Joint TargetPosition and Velocity... noncoherent signal detection for networked sensors using ordered transmissions, 2011 45th Annual Conference on Information Sciences and Systems (CISS
Deng, Peng; Kavehrad, Mohsen; Liu, Zhiwen; Zhou, Zhou; Yuan, Xiuhua
2013-07-01
We study the average capacity performance for multiple-input multiple-output (MIMO) free-space optical (FSO) communication systems using multiple partially coherent beams propagating through non-Kolmogorov strong turbulence, assuming equal gain combining diversity configuration and the sum of multiple gamma-gamma random variables for multiple independent partially coherent beams. The closed-form expressions of scintillation and average capacity are derived and then used to analyze the dependence on the number of independent diversity branches, power law α, refractive-index structure parameter, propagation distance and spatial coherence length of source beams. Obtained results show that, the average capacity increases more significantly with the increase in the rank of MIMO channel matrix compared with the diversity order. The effect of the diversity order on the average capacity is independent of the power law, turbulence strength parameter and spatial coherence length, whereas these effects on average capacity are gradually mitigated as the diversity order increases. The average capacity increases and saturates with the decreasing spatial coherence length, at rates depending on the diversity order, power law and turbulence strength. There exist optimal values of the spatial coherence length and diversity configuration for maximizing the average capacity of MIMO FSO links over a variety of atmospheric turbulence conditions.
Wang, Ziyang; Zhao, Luyu; Cai, Yuanming; Zheng, Shufeng; Yin, Yingzeng
2018-02-16
In this paper, a method to reduce the inevitable mutual coupling between antennas in an extremely closely spaced two-element MIMO antenna array is proposed. A suspended meta-surface composed periodic square split ring resonators (SRRs) is placed above the antenna array for decoupling. The meta-surface is equivalent to a negative permeability medium, along which wave propagation is rejected. By properly designing the rejection frequency band of the SRR unit, the mutual coupling between the antenna elements in the MIMO antenna system can be significantly reduced. Two prototypes of microstrip antenna arrays at 5.8 GHz band with and without the metasurface have been fabricated and measured. The matching bandwidths of antennas with reflection coefficient smaller than -15 dB for the arrays without and with the metasurface are 360 MHz and 900 MHz respectively. Using the meta-surface, the isolation between elements is increased from around 8 dB to more than 27 dB within the band of interest. Meanwhile, the total efficiency and peak gain of each element, the envelope correlation coefficient (ECC) between the two elements are also improved by considerable amounts. All the results demonstrate that the proposed method is very efficient for enhancing the performance of MIMO antenna arrays.
Zhang, Yongshun; Zheng, Guimei; Feng, Cunqian; Tang, Jun
2017-01-01
In this paper, we focus on the problem of two-dimensional direction of arrival (2D-DOA) estimation for monostatic MIMO Radar with electromagnetic vector received sensors (MIMO-EMVSs) under the condition of gain and phase uncertainties (GPU) and mutual coupling (MC). GPU would spoil the invariance property of the EMVSs in MIMO-EMVSs, thus the effective ESPRIT algorithm unable to be used directly. Then we put forward a C-SPD ESPRIT-like algorithm. It estimates the 2D-DOA and polarization station angle (PSA) based on the instrumental sensors method (ISM). The C-SPD ESPRIT-like algorithm can obtain good angle estimation accuracy without knowing the GPU. Furthermore, it can be applied to arbitrary array configuration and has low complexity for avoiding the angle searching procedure. When MC and GPU exist together between the elements of EMVSs, in order to make our algorithm feasible, we derive a class of separated electromagnetic vector receiver and give the S-SPD ESPRIT-like algorithm. It can solve the problem of GPU and MC efficiently. And the array configuration can be arbitrary. The effectiveness of our proposed algorithms is verified by the simulation result. PMID:29072588
Zhang, Dong; Zhang, Yongshun; Zheng, Guimei; Feng, Cunqian; Tang, Jun
2017-10-26
In this paper, we focus on the problem of two-dimensional direction of arrival (2D-DOA) estimation for monostatic MIMO Radar with electromagnetic vector received sensors (MIMO-EMVSs) under the condition of gain and phase uncertainties (GPU) and mutual coupling (MC). GPU would spoil the invariance property of the EMVSs in MIMO-EMVSs, thus the effective ESPRIT algorithm unable to be used directly. Then we put forward a C-SPD ESPRIT-like algorithm. It estimates the 2D-DOA and polarization station angle (PSA) based on the instrumental sensors method (ISM). The C-SPD ESPRIT-like algorithm can obtain good angle estimation accuracy without knowing the GPU. Furthermore, it can be applied to arbitrary array configuration and has low complexity for avoiding the angle searching procedure. When MC and GPU exist together between the elements of EMVSs, in order to make our algorithm feasible, we derive a class of separated electromagnetic vector receiver and give the S-SPD ESPRIT-like algorithm. It can solve the problem of GPU and MC efficiently. And the array configuration can be arbitrary. The effectiveness of our proposed algorithms is verified by the simulation result.
Nasir, Jamal; Jamaluddin, Mohd. Haizal; Ahmad Khan, Aftab; Kamarudin, Muhammad Ramlee; Leow, Chee Yen; Owais, Owais
2017-01-01
An L-shaped dual-band multiple-input multiple-output (MIMO) rectangular dielectric resonator antenna (RDRA) for long term evolution (LTE) applications is proposed. The presented antenna can transmit and receive information independently using fundamental TE111 and higher order TE121 modes of the DRA. TE111 degenerate mode covers LTE band 2 (1.85–1.99 GHz), 3 (1.71–1.88 GHz), and 9 (1.7499–1.7849 GHz) at fr = 1.8 GHz whereas TE121 covers LTE band 7 (2.5–2.69 GHz) at fr = 2.6 GHz, respectively. An efficient design method has been used to reduce mutual coupling between ports by changing the effective permittivity values of DRA by introducing a cylindrical air-gap at an optimal position in the dielectric resonator. This air-gap along with matching strips at the corners of the dielectric resonator keeps the isolation at a value more than 17 dB at both the bands. The diversity performance has also been evaluated by calculating the envelope correlation coefficient, diversity gain, and mean effective gain of the proposed design. MIMO performance has been evaluated by measuring the throughput of the proposed MIMO antenna. Experimental results successfully validate the presented design methodology in this work. PMID:28098807
Nasir, Jamal; Jamaluddin, Mohd Haizal; Ahmad Khan, Aftab; Kamarudin, Muhammad Ramlee; Yen, Bruce Leow Chee; Owais, Owais
2017-01-13
An L-shaped dual-band multiple-input multiple-output (MIMO) rectangular dielectric resonator antenna (RDRA) for long term evolution (LTE) applications is proposed. The presented antenna can transmit and receive information independently using fundamental TE 111 and higher order TE 121 modes of the DRA. TE 111 degenerate mode covers LTE band 2 (1.85-1.99 GHz), 3 (1.71-1.88 GHz), and 9 (1.7499-1.7849 GHz) at f r = 1.8 GHz whereas TE 121 covers LTE band 7 (2.5-2.69 GHz) at f r = 2.6 GHz, respectively. An efficient design method has been used to reduce mutual coupling between ports by changing the effective permittivity values of DRA by introducing a cylindrical air-gap at an optimal position in the dielectric resonator. This air-gap along with matching strips at the corners of the dielectric resonator keeps the isolation at a value more than 17 dB at both the bands. The diversity performance has also been evaluated by calculating the envelope correlation coefficient, diversity gain, and mean effective gain of the proposed design. MIMO performance has been evaluated by measuring the throughput of the proposed MIMO antenna. Experimental results successfully validate the presented design methodology in this work.
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.
Wang, Ruijia; Chen, Jie; Wang, Xing; Sun, Bing
2017-01-09
Retransmission deception jamming seriously degrades the Synthetic Aperture Radar (SAR) detection efficiency and can mislead SAR image interpretation by forming false targets. In order to suppress retransmission deception jamming, this paper proposes a novel multiple input and multiple output (MIMO) SAR structure range direction MIMO SAR, whose multiple channel antennas are vertical to the azimuth. First, based on the multiple channels of range direction MIMO SAR, the orthogonal frequency division multiplexing (OFDM) linear frequency modulation (LFM) signal was adopted as the transmission signal of each channel, which is defined as a sub-band signal. This sub-band signal corresponds to the transmission channel. Then, all of the sub-band signals are modulated with random initial phases and concurrently transmitted. The signal form is more complex and difficult to intercept. Next, the echoes of the sub-band signal are utilized to synthesize a wide band signal after preprocessing. The proposed method will increase the signal to interference ratio and peak amplitude ratio of the signal to resist retransmission deception jamming. Finally, well-focused SAR imagery is obtained using a conventional imaging method where the retransmission deception jamming strength is degraded and defocused. Simulations demonstrated the effectiveness of the proposed method.
Wang, Ruijia; Chen, Jie; Wang, Xing; Sun, Bing
2017-01-01
Retransmission deception jamming seriously degrades the Synthetic Aperture Radar (SAR) detection efficiency and can mislead SAR image interpretation by forming false targets. In order to suppress retransmission deception jamming, this paper proposes a novel multiple input and multiple output (MIMO) SAR structure range direction MIMO SAR, whose multiple channel antennas are vertical to the azimuth. First, based on the multiple channels of range direction MIMO SAR, the orthogonal frequency division multiplexing (OFDM) linear frequency modulation (LFM) signal was adopted as the transmission signal of each channel, which is defined as a sub-band signal. This sub-band signal corresponds to the transmission channel. Then, all of the sub-band signals are modulated with random initial phases and concurrently transmitted. The signal form is more complex and difficult to intercept. Next, the echoes of the sub-band signal are utilized to synthesize a wide band signal after preprocessing. The proposed method will increase the signal to interference ratio and peak amplitude ratio of the signal to resist retransmission deception jamming. Finally, well-focused SAR imagery is obtained using a conventional imaging method where the retransmission deception jamming strength is degraded and defocused. Simulations demonstrated the effectiveness of the proposed method. PMID:28075367
Morgenstern, Hai; Rafaely, Boaz; Noisternig, Markus
2017-03-01
Spherical microphone arrays (SMAs) and spherical loudspeaker arrays (SLAs) facilitate the study of room acoustics due to the three-dimensional analysis they provide. More recently, systems that combine both arrays, referred to as multiple-input multiple-output (MIMO) systems, have been proposed due to the added spatial diversity they facilitate. The literature provides frameworks for designing SMAs and SLAs separately, including error analysis from which the operating frequency range (OFR) of an array is defined. However, such a framework does not exist for the joint design of a SMA and a SLA that comprise a MIMO system. This paper develops a design framework for MIMO systems based on a model that addresses errors and highlights the importance of a matched design. Expanding on a free-field assumption, errors are incorporated separately for each array and error bounds are defined, facilitating error analysis for the system. The dependency of the error bounds on the SLA and SMA parameters is studied and it is recommended that parameters should be chosen to assure matched OFRs of the arrays in MIMO system design. A design example is provided, demonstrating the superiority of a matched system over an unmatched system in the synthesis of directional room impulse responses.
Finite-time output feedback stabilization of high-order uncertain nonlinear systems
NASA Astrophysics Data System (ADS)
Jiang, Meng-Meng; Xie, Xue-Jun; Zhang, Kemei
2018-06-01
This paper studies the problem of finite-time output feedback stabilization for a class of high-order nonlinear systems with the unknown output function and control coefficients. Under the weaker assumption that output function is only continuous, by using homogeneous domination method together with adding a power integrator method, introducing a new analysis method, the maximal open sector Ω of output function is given. As long as output function belongs to any closed sector included in Ω, an output feedback controller can be developed to guarantee global finite-time stability of the closed-loop system.
Device design and signal processing for multiple-input multiple-output multimode fiber links
NASA Astrophysics Data System (ADS)
Appaiah, Kumar; Vishwanath, Sriram; Bank, Seth R.
2012-01-01
Multimode fibers (MMFs) are limited in data rate capabilities owing to modal dispersion. However, their large core diameter simplifies alignment and packaging, and makes them attractive for short and medium length links. Recent research has shown that the use of signal processing and techniques such as multiple-input multiple-output (MIMO) can greatly improve the data rate capabilities of multimode fibers. In this paper, we review recent experimental work using MIMO and signal processing for multimode fibers, and the improvements in data rates achievable with these techniques. We then present models to design as well as simulate the performance benefits obtainable with arrays of lasers and detectors in conjunction with MIMO, using channel capacity as the metric to optimize. We also discuss some aspects related to complexity of the algorithms needed for signal processing and discuss techniques for low complexity implementation.
Explosive hazard detection using MIMO forward-looking ground penetrating radar
NASA Astrophysics Data System (ADS)
Shaw, Darren; Ho, K. C.; Stone, Kevin; Keller, James M.; Popescu, Mihail; Anderson, Derek T.; Luke, Robert H.; Burns, Brian
2015-05-01
This paper proposes a machine learning algorithm for subsurface object detection on multiple-input-multiple-output (MIMO) forward-looking ground-penetrating radar (FLGPR). By detecting hazards using FLGPR, standoff distances of up to tens of meters can be acquired, but this is at the degradation of performance due to high false alarm rates. The proposed system utilizes an anomaly detection prescreener to identify potential object locations. Alarm locations have multiple one-dimensional (ML) spectral features, two-dimensional (2D) spectral features, and log-Gabor statistic features extracted. The ability of these features to reduce the number of false alarms and increase the probability of detection is evaluated for both co-polarizations present in the Akela MIMO array. Classification is performed by a Support Vector Machine (SVM) with lane-based cross-validation for training and testing. Class imbalance and optimized SVM kernel parameters are considered during classifier training.
MIMO equalization with adaptive step size for few-mode fiber transmission systems.
van Uden, Roy G H; Okonkwo, Chigo M; Sleiffer, Vincent A J M; de Waardt, Hugo; Koonen, Antonius M J
2014-01-13
Optical multiple-input multiple-output (MIMO) transmission systems generally employ minimum mean squared error time or frequency domain equalizers. Using an experimental 3-mode dual polarization coherent transmission setup, we show that the convergence time of the MMSE time domain equalizer (TDE) and frequency domain equalizer (FDE) can be reduced by approximately 50% and 30%, respectively. The criterion used to estimate the system convergence time is the time it takes for the MIMO equalizer to reach an average output error which is within a margin of 5% of the average output error after 50,000 symbols. The convergence reduction difference between the TDE and FDE is attributed to the limited maximum step size for stable convergence of the frequency domain equalizer. The adaptive step size requires a small overhead in the form of a lookup table. It is highlighted that the convergence time reduction is achieved without sacrificing optical signal-to-noise ratio performance.
Compressed Sensing in On-Grid MIMO Radar.
Minner, Michael F
2015-01-01
The accurate detection of targets is a significant problem in multiple-input multiple-output (MIMO) radar. Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. The sparsity constraints needed to apply the techniques of Compressive Sensing to problems in radar systems have led to discretizations of the target scene in various domains, such as azimuth, time delay, and Doppler. Building upon recent work, we investigate the feasibility of on-grid Compressive Sensing-based MIMO radar via a threefold azimuth-delay-Doppler discretization for target detection and parameter estimation. We utilize a colocated random sensor array and transmit distinct linear chirps to a small scene with few, slowly moving targets. Relying upon standard far-field and narrowband assumptions, we analyze the efficacy of various recovery algorithms in determining the parameters of the scene through numerical simulations, with particular focus on the ℓ 1-squared Nonnegative Regularization method.
NASA Technical Reports Server (NTRS)
Guo, Tong-Yi; Hwang, Chyi; Shieh, Leang-San
1994-01-01
This paper deals with the multipoint Cauer matrix continued-fraction expansion (MCFE) for model reduction of linear multi-input multi-output (MIMO) systems with various numbers of inputs and outputs. A salient feature of the proposed MCFE approach to model reduction of MIMO systems with square transfer matrices is its equivalence to the matrix Pade approximation approach. The Cauer second form of the ordinary MCFE for a square transfer function matrix is generalized in this paper to a multipoint and nonsquare-matrix version. An interesting connection of the multipoint Cauer MCFE method to the multipoint matrix Pade approximation method is established. Also, algorithms for obtaining the reduced-degree matrix-fraction descriptions and reduced-dimensional state-space models from a transfer function matrix via the multipoint Cauer MCFE algorithm are presented. Practical advantages of using the multipoint Cauer MCFE are discussed and a numerical example is provided to illustrate the algorithms.
NASA Astrophysics Data System (ADS)
Pereira, Carlos; Chartois, Yannick; Pousset, Yannis; Vauzelle, Rodolphe
2006-09-01
Modelling of the environment is an important factor in electromagnetic wave propagation simulation, performed by a 3D ray-tracing method. The aim of this work is to study the effect of indoor environment modelling accuracy on MIMO (Multiple Input Multiple Output) channel characterisation. The first of the two environments investigated is the hall of our building, while the second one is a more confined environment and represents the floor of our laboratory. For these two indoor environments, three description levels are proposed in order to establish geometrical and electrical modelling impact on MIMO channel characterisation. Results are obtained by analysing the capacity and variation in correlation in relation to the polarisation, the presence of LOS (Line of sight) or NLOS configurations, the spacing between antennae and the number of transmitter and receiver antennae. To cite this article: C. Pereira et al., C. R. Physique 7 (2006).
The miniaturised Moessbauer spectrometer MIMOS II: future developments.
NASA Astrophysics Data System (ADS)
Rodionov, D.; Blumers, M.; Klingelhöfer, G.; Bernhardt, B.; Fleischer, I.; Schröder, C.; Morris, R.; Girones Lopez, J.
2007-08-01
In January 2004, the first in situ extraterrestrial Mössbauer spectrum was received from the Martian surface. At the present time (May 2007) two Miniaturized Mössbauer Spectrometers (MIMOS II) on board of the two Mars Exploration Rovers "Spirit" and "Opportunity" continue to collect valuable scientific data. Both spectrometers are operational after more than 3 years of work. Originally, the mission was expected to last for 90 days. To date more than 600 spectra were obtained with a total integration time for both rovers exceeding 260 days. The MER mission has proven that Mössbauer spectroscopy is a valuable technique for the in situ exploration of extraterrestrial bodies and the study of Fe-bearing samples. The Mössbauer team at the University of Mainz has accumulated a lot of experience and learned many lessons during last three years. All that makes MIMOS II a feasible choice for the future missions to Mars and other targets. Currently MIMOS II is on the scientific payload of two missions: Phobos Grunt (Russian Space Agency) and ExoMars (European Space Agency). Phobos Grunt is scheduled to launch in 2009. The main goals of the mission are: a) Phobos regolith sample return, b) Phobos in situ study, c) Mars and Phobos remote sensing. MIMOS II will be installed on the arm of a landing module. Currently, we are manufacturing an engineering model for testing purposes. The ESA "ExoMars" mission involves the development of a MER-like rover with more complex scientific payload (Pasteur exobiology instruments, including a drilling system). Its aim is to further characterise the biological environment in preparation for robotic missions and eventually human exploration. Data from the mission will provide invaluable input to the field of exobiology - the study of the origin, the evolution and distribution of life in the universe. The launch date is scheduled for 2013. Like on MER, the MIMOS II instrument will be mounted on a robotic arm. Advanced and improved version of MIMOS II instrument is under development for those and other future missions. The new design includes additional mass reduction (total mass is planned to be ~320 g). The dimensions of the electronic-board will be minimized by using state of the art digital electronics. A new ring-detector system (Si- Drift detectors) will be used, thus greatly improving energy resolution. We expect an energy resolution of around 140-160 eV for temperatures lower than 250 K. This will increase the signal to noise ratio by a factor of 10 and, therefore, integration times will be reduced significantly. In addition to the Mössbauer data, simultaneous acquisition of an X-ray fluorescence spectrum will be possible, thus providing data on a sample's elemental composition. New firmware will be developed to optimize the instrument's performance.
Explicit asymmetric bounds for robust stability of continuous and discrete-time systems
NASA Technical Reports Server (NTRS)
Gao, Zhiqiang; Antsaklis, Panos J.
1993-01-01
The problem of robust stability in linear systems with parametric uncertainties is considered. Explicit stability bounds on uncertain parameters are derived and expressed in terms of linear inequalities for continuous systems, and inequalities with quadratic terms for discrete-times systems. Cases where system parameters are nonlinear functions of an uncertainty are also examined.
Soft sensor modeling based on variable partition ensemble method for nonlinear batch processes
NASA Astrophysics Data System (ADS)
Wang, Li; Chen, Xiangguang; Yang, Kai; Jin, Huaiping
2017-01-01
Batch processes are always characterized by nonlinear and system uncertain properties, therefore, the conventional single model may be ill-suited. A local learning strategy soft sensor based on variable partition ensemble method is developed for the quality prediction of nonlinear and non-Gaussian batch processes. A set of input variable sets are obtained by bootstrapping and PMI criterion. Then, multiple local GPR models are developed based on each local input variable set. When a new test data is coming, the posterior probability of each best performance local model is estimated based on Bayesian inference and used to combine these local GPR models to get the final prediction result. The proposed soft sensor is demonstrated by applying to an industrial fed-batch chlortetracycline fermentation process.
Wang, Ding; Liu, Derong; Zhang, Yun; Li, Hongyi
2018-01-01
In this paper, we aim to tackle the neural robust tracking control problem for a class of nonlinear systems using the adaptive critic technique. The main contribution is that a neural-network-based robust tracking control scheme is established for nonlinear systems involving matched uncertainties. The augmented system considering the tracking error and the reference trajectory is formulated and then addressed under adaptive critic optimal control formulation, where the initial stabilizing controller is not needed. The approximate control law is derived via solving the Hamilton-Jacobi-Bellman equation related to the nominal augmented system, followed by closed-loop stability analysis. The robust tracking control performance is guaranteed theoretically via Lyapunov approach and also verified through simulation illustration. Copyright © 2017 Elsevier Ltd. All rights reserved.
Liang, Lihua; Yuan, Jia; Zhang, Songtao; Zhao, Peng
2018-01-01
This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller.
Liang, Lihua; Zhang, Songtao; Zhao, Peng
2018-01-01
This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller. PMID:29709008
NASA Astrophysics Data System (ADS)
Zhang, Kai; Gao, Guanjun; Zhang, Jie; Fei, Aimei; Cvijetic, Milorad
2018-07-01
We have investigated and proposed the use of optical phase conjugation (OPC) technique to mitigate the impact of fiber nonlinearities in mode-division multiplexed transmission systems. Numerical simulations are performed for three wavelengths, each loaded with 200 Gb/s dual-polarization 16-level quadrature amplitude modulation (DP-16QAM) format, in weakly guided two-mode fiber. It is known that differential mode group delay (DMGD) in mode-division multiplexed (MDM) transmission systems could be beneficial for system performance of MDM system with MIMO compensation in place. On the other side, for MDM system with OPC in place, the presence of DMGD may limit the overall benefits since signal power evolution per spatial modes should be symmetrical at the system midpoint in order to realize an effective compensation of the nonlinear effects. Our simulation results show that in the reference case (in the absence of DMGD), the employment of OPC module would lead to an average Q-factor improvement of approximately 10 dB. At the same time, in the presence of DMGD, an average Q-factor improvement would be ∼2.8 dB for WDM case. In addition, due to asymmetrical signal power map, the penalties induced by a periodic amplification process cannot be ideally compensated by the midpoint insertion of OPC. However, by accounting the impacts of both DMGD and asymmetrical signal power map, the insertion of the OPC system will still lead to an average Q-factor improvement of ∼1 dB for WDM channel arrangement.
An efficient deterministic-probabilistic approach to modeling regional groundwater flow: 1. Theory
Yen, Chung-Cheng; Guymon, Gary L.
1990-01-01
An efficient probabilistic model is developed and cascaded with a deterministic model for predicting water table elevations in regional aquifers. The objective is to quantify model uncertainty where precise estimates of water table elevations may be required. The probabilistic model is based on the two-point probability method which only requires prior knowledge of uncertain variables mean and coefficient of variation. The two-point estimate method is theoretically developed and compared with the Monte Carlo simulation method. The results of comparisons using hypothetical determinisitic problems indicate that the two-point estimate method is only generally valid for linear problems where the coefficients of variation of uncertain parameters (for example, storage coefficient and hydraulic conductivity) is small. The two-point estimate method may be applied to slightly nonlinear problems with good results, provided coefficients of variation are small. In such cases, the two-point estimate method is much more efficient than the Monte Carlo method provided the number of uncertain variables is less than eight.
An Efficient Deterministic-Probabilistic Approach to Modeling Regional Groundwater Flow: 1. Theory
NASA Astrophysics Data System (ADS)
Yen, Chung-Cheng; Guymon, Gary L.
1990-07-01
An efficient probabilistic model is developed and cascaded with a deterministic model for predicting water table elevations in regional aquifers. The objective is to quantify model uncertainty where precise estimates of water table elevations may be required. The probabilistic model is based on the two-point probability method which only requires prior knowledge of uncertain variables mean and coefficient of variation. The two-point estimate method is theoretically developed and compared with the Monte Carlo simulation method. The results of comparisons using hypothetical determinisitic problems indicate that the two-point estimate method is only generally valid for linear problems where the coefficients of variation of uncertain parameters (for example, storage coefficient and hydraulic conductivity) is small. The two-point estimate method may be applied to slightly nonlinear problems with good results, provided coefficients of variation are small. In such cases, the two-point estimate method is much more efficient than the Monte Carlo method provided the number of uncertain variables is less than eight.
Robust Stabilization of Uncertain Systems Based on Energy Dissipation Concepts
NASA Technical Reports Server (NTRS)
Gupta, Sandeep
1996-01-01
Robust stability conditions obtained through generalization of the notion of energy dissipation in physical systems are discussed in this report. Linear time-invariant (LTI) systems which dissipate energy corresponding to quadratic power functions are characterized in the time-domain and the frequency-domain, in terms of linear matrix inequalities (LMls) and algebraic Riccati equations (ARE's). A novel characterization of strictly dissipative LTI systems is introduced in this report. Sufficient conditions in terms of dissipativity and strict dissipativity are presented for (1) stability of the feedback interconnection of dissipative LTI systems, (2) stability of dissipative LTI systems with memoryless feedback nonlinearities, and (3) quadratic stability of uncertain linear systems. It is demonstrated that the framework of dissipative LTI systems investigated in this report unifies and extends small gain, passivity, and sector conditions for stability. Techniques for selecting power functions for characterization of uncertain plants and robust controller synthesis based on these stability results are introduced. A spring-mass-damper example is used to illustrate the application of these methods for robust controller synthesis.
Compressive Channel Estimation and Tracking for Large Arrays in mm Wave Picocells
2014-01-01
abling sophisticated adaptation, including frequency-selective spatiotemporal processing (e.g., per subcarrier beamforming in OFDM systems). This approach...subarrays are certainly required for more advanced functionalities such as multiuser MIMO [17], spatial multiplexing [18], [19], [20], [21], [22], and...case, a regu- larly spaced 2D array), an estimate of the N2t,1D × N2r,1D MIMO channel matrix H can be efficiently arrived at by estimating the spatial
Interference Alignment With Partial CSI Feedback in MIMO Cellular Networks
NASA Astrophysics Data System (ADS)
Rao, Xiongbin; Lau, Vincent K. N.
2014-04-01
Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. However, most existing IA designs require full channel state information (CSI) at the transmitters, which would lead to significant CSI signaling overhead. There are two techniques, namely CSI quantization and CSI feedback filtering, to reduce the CSI feedback overhead. In this paper, we consider IA processing with CSI feedback filtering in MIMO cellular networks. We introduce a novel metric, namely the feedback dimension, to quantify the first order CSI feedback cost associated with the CSI feedback filtering. The CSI feedback filtering poses several important challenges in IA processing. First, there is a hidden partial CSI knowledge constraint in IA precoder design which cannot be handled using conventional IA design methodology. Furthermore, existing results on the feasibility conditions of IA cannot be applied due to the partial CSI knowledge. Finally, it is very challenging to find out how much CSI feedback is actually needed to support IA processing. We shall address the above challenges and propose a new IA feasibility condition under partial CSIT knowledge in MIMO cellular networks. Based on this, we consider the CSI feedback profile design subject to the degrees of freedom requirements, and we derive closed-form trade-off results between the CSI feedback cost and IA performance in MIMO cellular networks.
Tsampasis, Eleftherios; Gkonis, Panagiotis K; Trakadas, Panagiotis; Zahariadis, Theodοre
2018-01-08
The goal of this study was to investigate the performance of a realistic wireless sensor nodes deployment in order to support modern building management systems (BMSs). A three-floor building orientation is taken into account, where each node is equipped with a multi-antenna system while a central base station (BS) collects and processes all received information. The BS is also equipped with multiple antennas; hence, a multiple input-multiple output (MIMO) system is formulated. Due to the multiple reflections during transmission in the inner of the building, a wideband code division multiple access (WCDMA) physical layer protocol has been considered, which has already been adopted for third-generation (3G) mobile networks. Results are presented for various MIMO orientations, where the mean transmission power per node is considered as an output metric for a specific signal-to-noise ratio (SNR) requirement and number of resolvable multipath components. In the first set of presented results, the effects of multiple access interference on overall transmission power are highlighted. As the number of mobile nodes per floor or the requested transmission rate increases, MIMO systems of a higher order should be deployed in order to maintain transmission power at adequate levels. In the second set of results, a comparison is performed among transmission in diversity combining and spatial multiplexing mode, which clearly indicate that the first case is the most appropriate solution for indoor communications.
Liu, Hesen; Zhu, Lin; Pan, Zhuohong; ...
2015-09-14
One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. our paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-outputmore » (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. Our results demonstrate that the measurement-based model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.« less
Tian, Jiayi; Zhang, Shifeng; Zhang, Yinhui; Li, Tong
2018-03-01
Since motion control plant (y (n) =f(⋅)+d) was repeatedly used to exemplify how active disturbance rejection control (ADRC) works when it was proposed, the integral chain system subject to matched disturbances is always regarded as a canonical form and even misconstrued as the only form that ADRC is applicable to. In this paper, a systematic approach is first presented to apply ADRC to a generic nonlinear uncertain system with mismatched disturbances and a robust output feedback autopilot for an airbreathing hypersonic vehicle (AHV) is devised based on that. The key idea is to employ the feedback linearization (FL) and equivalent input disturbance (EID) technique to decouple nonlinear uncertain system into several subsystems in canonical form, thus it would be much easy to directly design classical/improved linear/nonlinear ADRC controller for each subsystem. It is noticed that all disturbances are taken into account when implementing FL rather than just omitting that in previous research, which greatly enhances controllers' robustness against external disturbances. For autopilot design, ADRC strategy enables precise tracking for velocity and altitude reference command in the presence of severe parametric perturbations and atmospheric disturbances only using measurable output information. Bounded-input-bounded-output (BIBO) stable is analyzed for closed-loop system. To illustrate the feasibility and superiority of this novel design, a series of comparative simulations with some prominent and representative methods are carried out on a benchmark longitudinal AHV model. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Flight Test of L1 Adaptive Control Law: Offset Landings and Large Flight Envelope Modeling Work
NASA Technical Reports Server (NTRS)
Gregory, Irene M.; Xargay, Enric; Cao, Chengyu; Hovakimyan, Naira
2011-01-01
This paper presents new results of a flight test of the L1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The flight test was conducted on the subscale turbine powered Generic Transport Model that is an integral part of the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. The results presented include control law evaluation for piloted offset landing tasks as well as results in support of nonlinear aerodynamic modeling and real-time dynamic modeling of the departure-prone edges of the flight envelope.
The Cramér-Rao Bounds and Sensor Selection for Nonlinear Systems with Uncertain Observations.
Wang, Zhiguo; Shen, Xiaojing; Wang, Ping; Zhu, Yunmin
2018-04-05
This paper considers the problems of the posterior Cramér-Rao bound and sensor selection for multi-sensor nonlinear systems with uncertain observations. In order to effectively overcome the difficulties caused by uncertainty, we investigate two methods to derive the posterior Cramér-Rao bound. The first method is based on the recursive formula of the Cramér-Rao bound and the Gaussian mixture model. Nevertheless, it needs to compute a complex integral based on the joint probability density function of the sensor measurements and the target state. The computation burden of this method is relatively high, especially in large sensor networks. Inspired by the idea of the expectation maximization algorithm, the second method is to introduce some 0-1 latent variables to deal with the Gaussian mixture model. Since the regular condition of the posterior Cramér-Rao bound is unsatisfied for the discrete uncertain system, we use some continuous variables to approximate the discrete latent variables. Then, a new Cramér-Rao bound can be achieved by a limiting process of the Cramér-Rao bound of the continuous system. It avoids the complex integral, which can reduce the computation burden. Based on the new posterior Cramér-Rao bound, the optimal solution of the sensor selection problem can be derived analytically. Thus, it can be used to deal with the sensor selection of a large-scale sensor networks. Two typical numerical examples verify the effectiveness of the proposed methods.
Transient Stability Assessment of Power Systems With Uncertain Renewable Generation: Preprint
DOE Office of Scientific and Technical Information (OSTI.GOV)
Villegas Pico, Hugo Nestor; Aliprantis, Dionysios C.; Lin, Xiaojun
2017-08-09
The transient stability of a power system depends heavily on its operational state at the moment of a fault. In systems where the penetration of renewable generation is significant, the dispatch of the conventional fleet of synchronous generators is uncertain at the time of dynamic security analysis. Hence, the assessment of transient stability requires the solution of a system of nonlinear ordinary differential equations with unknown initial conditions and inputs. To this end, we set forth a computational framework that relies on Taylor polynomials, where variables are associated with the level of renewable generation. This paper describes the details ofmore » the method and illustrates its application on a nine-bus test system.« less
NASA Astrophysics Data System (ADS)
Habibi, Hamed; Rahimi Nohooji, Hamed; Howard, Ian
2017-09-01
Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.
Self tuning control of wind-diesel power systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mufti, M.D.; Balasubramanian, R.; Tripathy, S.C.
1995-12-31
This paper proposes some effective self-tuning control strategies for isolated Wind-Diesel power generation systems. Detailed modeling and studies on both single-input single-output (SISO) as well as multi-input multi-output (MIMO) self tuning regulators, applied to a typical system, are reported. Further, the effect of introducing a Super-conducting Magnetic Energy Storage (SMES) unit on the system performance has been investigated. The MIMO self-tuning regulator controlling the hybrid system and the SMES in a coordinated manner exhibits the best performance.
Proportional plus integral MIMO controller for regulation and tracking with anti-wind-up features
DOE Office of Scientific and Technical Information (OSTI.GOV)
Puleston, P.F.; Mantz, R.J.
1993-11-01
A proportional plus integral matrix control structure for MIMO systems is proposed. Based on a standard optimal control structure with integral action, it permits a greater degree of independence of the design and tuning of the regulating and tracking features, without considerably increasing the controller complexity. Fast recovery from load disturbances is achieved, while large overshoots associated with set-point changes and reset wind-up problems can be reduced. A simple effective procedure for practical tuning is introduced.
NASA Astrophysics Data System (ADS)
Edalati, L.; Khaki Sedigh, A.; Aliyari Shooredeli, M.; Moarefianpour, A.
2018-02-01
This paper deals with the design of adaptive fuzzy dynamic surface control for uncertain strict-feedback nonlinear systems with asymmetric time-varying output constraints in the presence of input saturation. To approximate the unknown nonlinear functions and overcome the problem of explosion of complexity, a Fuzzy logic system is combined with the dynamic surface control in the backstepping design technique. To ensure the output constraints satisfaction, an asymmetric time-varying Barrier Lyapunov Function (BLF) is used. Moreover, by applying the minimal learning parameter technique, the number of the online parameters update for each subsystem is reduced to 2. Hence, the semi-globally uniformly ultimately boundedness (SGUUB) of all the closed-loop signals with appropriate tracking error convergence is guaranteed. The effectiveness of the proposed control is demonstrated by two simulation examples.
Attitude control/momentum management and payload pointing in advanced space vehicles
NASA Technical Reports Server (NTRS)
Parlos, Alexander G.; Jayasuriya, Suhada
1990-01-01
The design and evaluation of an attitude control/momentum management system for highly asymmetric spacecraft configurations are presented. The preliminary development and application of a nonlinear control system design methodology for tracking control of uncertain systems, such as spacecraft payload pointing systems are also presented. Control issues relevant to both linear and nonlinear rigid-body spacecraft dynamics are addressed, whereas any structural flexibilities are not taken into consideration. Results from the first task indicate that certain commonly used simplifications in the equations of motions result in unstable attitude control systems, when used for highly asymmetric spacecraft configurations. An approach is suggested circumventing this problem. Additionally, even though preliminary results from the second task are encouraging, the proposed nonlinear control system design method requires further investigation prior to its application and use as an effective payload pointing system design technique.
Multilevel adaptive control of nonlinear interconnected systems.
Motallebzadeh, Farzaneh; Ozgoli, Sadjaad; Momeni, Hamid Reza
2015-01-01
This paper presents an adaptive backstepping-based multilevel approach for the first time to control nonlinear interconnected systems with unknown parameters. The system consists of a nonlinear controller at the first level to neutralize the interaction terms, and some adaptive controllers at the second level, in which the gains are optimally tuned using genetic algorithm. The presented scheme can be used in systems with strong couplings where completely ignoring the interactions leads to problems in performance or stability. In order to test the suitability of the method, two case studies are provided: the uncertain double and triple coupled inverted pendulums connected by springs with unknown parameters. The simulation results show that the method is capable of controlling the system effectively, in both regulation and tracking tasks. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Park, Jisang
In this dissertation, we investigate MIMO stability margin inference of a large number of controllers using pre-established stability margins of a small number of nu-gap-wise adjacent controllers. The generalized stability margin and the nu-gap metric are inherently able to handle MIMO system analysis without the necessity of repeating multiple channel-by-channel SISO analyses. This research consists of three parts: (i) development of a decision support tool for inference of the stability margin, (ii) computational considerations for yielding the maximal stability margin with the minimal nu-gap metric in a less conservative manner, and (iii) experiment design for estimating the generalized stability margin with an assured error bound. A modern problem from aerospace control involves the certification of a large set of potential controllers with either a single plant or a fleet of potential plant systems, with both plants and controllers being MIMO and, for the moment, linear. Experiments on a limited number of controller/plant pairs should establish the stability and a certain level of margin of the complete set. We consider this certification problem for a set of controllers and provide algorithms for selecting an efficient subset for testing. This is done for a finite set of candidate controllers and, at least for SISO plants, for an infinite set. In doing this, the nu-gap metric will be the main tool. We provide a theorem restricting a radius of a ball in the parameter space so that the controller can guarantee a prescribed level of stability and performance if parameters of the controllers are contained in the ball. Computational examples are given, including one of certification of an aircraft engine controller. The overarching aim is to introduce truly MIMO margin calculations and to understand their efficacy in certifying stability over a set of controllers and in replacing legacy single-loop gain and phase margin calculations. We consider methods for the computation of; maximal MIMO stability margins bP̂,C, minimal nu-gap metrics deltanu , and the maximal difference between these two values, through the use of scaling and weighting functions. We propose simultaneous scaling selections that attempt to maximize the generalized stability margin and minimize the nu-gap. The minimization of the nu-gap by scaling involves a non-convex optimization. We modify the XY-centering algorithm to handle this non-convexity. This is done for applications in controller certification. Estimating the generalized stability margin with an accurate error bound has significant impact on controller certification. We analyze an error bound of the generalized stability margin as the infinity norm of the MIMO empirical transfer function estimate (ETFE). Input signal design to reduce the error on the estimate is also studied. We suggest running the system for a certain amount of time prior to recording of each output data set. The assured upper bound of estimation error can be tuned by the amount of the pre-experiment.
Song, Qi; Song, Yong-Duan
2011-12-01
This paper investigates the position and velocity tracking control problem of high-speed trains with multiple vehicles connected through couplers. A dynamic model reflecting nonlinear and elastic impacts between adjacent vehicles as well as traction/braking nonlinearities and actuation faults is derived. Neuroadaptive fault-tolerant control algorithms are developed to account for various factors such as input nonlinearities, actuator failures, and uncertain impacts of in-train forces in the system simultaneously. The resultant control scheme is essentially independent of system model and is primarily data-driven because with the appropriate input-output data, the proposed control algorithms are capable of automatically generating the intermediate control parameters, neuro-weights, and the compensation signals, literally producing the traction/braking force based upon input and response data only--the whole process does not require precise information on system model or system parameter, nor human intervention. The effectiveness of the proposed approach is also confirmed through numerical simulations.
Limitations and tradeoffs in synchronization of large-scale networks with uncertain links
Diwadkar, Amit; Vaidya, Umesh
2016-01-01
The synchronization of nonlinear systems connected over large-scale networks has gained popularity in a variety of applications, such as power grids, sensor networks, and biology. Stochastic uncertainty in the interconnections is a ubiquitous phenomenon observed in these physical and biological networks. We provide a size-independent network sufficient condition for the synchronization of scalar nonlinear systems with stochastic linear interactions over large-scale networks. This sufficient condition, expressed in terms of nonlinear dynamics, the Laplacian eigenvalues of the nominal interconnections, and the variance and location of the stochastic uncertainty, allows us to define a synchronization margin. We provide an analytical characterization of important trade-offs between the internal nonlinear dynamics, network topology, and uncertainty in synchronization. For nearest neighbour networks, the existence of an optimal number of neighbours with a maximum synchronization margin is demonstrated. An analytical formula for the optimal gain that produces the maximum synchronization margin allows us to compare the synchronization properties of various complex network topologies. PMID:27067994
Tolerance of the frequency deviation of LO sources at a MIMO system
NASA Astrophysics Data System (ADS)
Xiao, Jiangnan; Li, Xingying; Zhang, Zirang; Xu, Yuming; Chen, Long; Yu, Jianjun
2015-11-01
We analyze and simulate the tolerance of frequency offset at a W-band optical-wireless transmission system. The transmission system adopts optical polarization division multiplexing (PDM), and multiple-input multiple-output (MIMO) reception. The transmission signal adopts optical quadrature phase shift keying (QPSK) modulation, and the generation of millimeter-wave is based on the optical heterodyning technique. After 20-km single-mode fiber-28 (SMF-28) transmission, tens of Gb/s millimeter-wave signal is delivered. At the receiver, two millimeter-wave signals are down-converted into electrical intermediate-frequency (IF) signals in the analog domain by mixing with two electrical local oscillators (LOs) with different frequencies. We investigate the different frequency LO effect on the 2×2 MIMO system performance for the first time, finding that the process during DSP of implementing frequency offset estimation (FOE) before cascaded multi-modulus-algorithm (CMMA) equalization can get rid of the inter-channel interference (ICI) and improve system bit-error-ratio (BER) performance in this type of transmission system.
Equivalent ZF precoding scheme for downlink indoor MU-MIMO VLC systems
NASA Astrophysics Data System (ADS)
Fan, YangYu; Zhao, Qiong; Kang, BoChao; Deng, LiJun
2018-01-01
In indoor visible light communication (VLC) systems, the channels of photo detectors (PDs) at one user are highly correlated, which determines the choice of spatial diversity model for individual users. In a spatial diversity model, the signals received by PDs belonging to one user carry the same information, and can be combined directly. Based on the above, we propose an equivalent zero-forcing (ZF) precoding scheme for multiple-user multiple-input single-output (MU-MIMO) VLC systems by transforming an indoor MU-MIMO VLC system into an indoor multiple-user multiple-input single-output (MU-MISO) VLC system through simply processing. The power constraints of light emitting diodes (LEDs) are also taken into account. Comprehensive computer simulations in three scenarios indicate that our scheme can not only reduce the computational complexity, but also guarantee the system performance. Furthermore, the proposed scheme does not require noise information in the calculating of the precoding weights, and has no restrictions on the numbers of APs and PDs.
Applications of active adaptive noise control to jet engines
NASA Technical Reports Server (NTRS)
Shoureshi, Rahmat; Brackney, Larry
1993-01-01
During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.
Hardware Implementation of a MIMO Decoder Using Matrix Factorization Based Channel Estimation
NASA Astrophysics Data System (ADS)
Islam, Mohammad Tariqul; Numan, Mostafa Wasiuddin; Misran, Norbahiah; Ali, Mohd Alauddin Mohd; Singh, Mandeep
2011-05-01
This paper presents an efficient hardware realization of multiple-input multiple-output (MIMO) wireless communication decoder that utilizes the available resources by adopting the technique of parallelism. The hardware is designed and implemented on Xilinx Virtex™-4 XC4VLX60 field programmable gate arrays (FPGA) device in a modular approach which simplifies and eases hardware update, and facilitates testing of the various modules independently. The decoder involves a proficient channel estimation module that employs matrix factorization on least squares (LS) estimation to reduce a full rank matrix into a simpler form in order to eliminate matrix inversion. This results in performance improvement and complexity reduction of the MIMO system. Performance evaluation of the proposed method is validated through MATLAB simulations which indicate 2 dB improvement in terms of SNR compared to LS estimation. Moreover complexity comparison is performed in terms of mathematical operations, which shows that the proposed approach appreciably outperforms LS estimation at a lower complexity and represents a good solution for channel estimation technique.
LEA Detection and Tracking Method for Color-Independent Visual-MIMO
Kim, Jai-Eun; Kim, Ji-Won; Kim, Ki-Doo
2016-01-01
Communication performance in the color-independent visual-multiple input multiple output (visual-MIMO) technique is deteriorated by light emitting array (LEA) detection and tracking errors in the received image because the image sensor included in the camera must be used as the receiver in the visual-MIMO system. In this paper, in order to improve detection reliability, we first set up the color-space-based region of interest (ROI) in which an LEA is likely to be placed, and then use the Harris corner detection method. Next, we use Kalman filtering for robust tracking by predicting the most probable location of the LEA when the relative position between the camera and the LEA varies. In the last step of our proposed method, the perspective projection is used to correct the distorted image, which can improve the symbol decision accuracy. Finally, through numerical simulation, we show the possibility of robust detection and tracking of the LEA, which results in a symbol error rate (SER) performance improvement. PMID:27384563
Chen, Wei; Oetomo, Sidarto Bambang; Tetteroo, Daniel; Versteegh, Frank; Mamagkaki, Thelxi; Pereira, Mariana Serras; Janssen, Lindy; van Meurs, Andrea
2015-05-01
Premature infants are subject to numerous interventions ranging from a simple diaper change to surgery while residing in neonatal intensive care units. These neonates often suffer from pain, distress, and discomfort during the first weeks of their lives. Although pharmacological pain treatment often is available, it cannot always be applied to relieve a neonate from pain or discomfort. This paper describes a nonpharmacological solution, called Mimo, which provides comfort through mediation of a parent's physiological features to the distressed neonate via an intelligent pillow system embedded with sensing and actuating functions. We present the design, the implementation, and the evaluation of the prototype. Clinical tests at Máxima Medical Center in the Netherlands show that among the nine of ten infants who showed discomfort following diaper change, a shorter recovery time to baseline skin conductance analgesimeter values could be measured when the maternal heartbeat vibration in the Mimo was switched ON and in seven of these ten a shorter crying time was measured.
Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo
2018-01-01
In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar. PMID:29518957
Sai, Xiaowei; Li, Yan; Yang, Chen; Li, Wei; Qiu, Jifang; Hong, Xiaobin; Zuo, Yong; Guo, Hongxiang; Tong, Weijun; Wu, Jian
2017-11-01
Elliptical-core few mode fiber (EC-FMF) is used in a mode division multiplexing (MDM) transmission system to release multiple-input-multiple-output (MIMO) digital-signal-processing, which reduces the cost and the complexity of the receiver. However, EC-FMF does not match with conventional multiplexers/de-multiplexers (MUXs/DeMUXs) such as a photonic lantern, leading to extra mode coupling loss and crosstalk. We design elliptical-core mode-selective photonic lanterns (EC-MSPLs) with six modes, which can match well with EC-FMF in MIMO-free MDM systems. Simulation of the EC-MSPL using the beam propagation method was demonstrated employing a combination of either step-index or graded-index fibers with six different sizes of cores, and the taper transition length of 8 cm or 4 cm. Through numerical simulations and optimizations, both types of photonic lanterns can realize low loss transmission and low crosstalk of below -20.0 dB for all modes.
Robust predictive control with optimal load tracking for critical applications. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tse, J.; Bentsman, J.; Miller, N.
1994-09-01
This report derives a multi-input multi-output (MIMO) version of a two-degree-of-freedom receding-horizon control law based on mixed H{sub 2}/H{infinity} minimization. First, the integrand in the frequency domain representation of the MIMO performance criterion is decomposed into disturbance and reference spectra. Then the controller is derived which minimizes the peak of the disturbance spectrum and the integral of the reference spectrum on the unit circle. The resulting two-degree-of-freedom MIMO control strategy, referred to as the minimax predictive multivariable control (MPC), is shown to have worst-case-disturbance-rejection and robust-stability properties superior to those of purely H{sub 2}-optimal controllers, such as Generalized Predictive Controlmore » (GPC), for identical horizons. An attractive feature of the receding horizon structure of MPC is that it can, in ways similar to GPC, directly incorporate input constraints and pre-programmed reference inputs, which are nontrivial tasks in the standard H{infinity} design.« less
Real-Time Spatio-Temporal Twice Whitening for MIMO Energy Detector
DOE Office of Scientific and Technical Information (OSTI.GOV)
Humble, Travis S; Mitra, Pramita; Barhen, Jacob
2010-01-01
While many techniques exist for local spectrum sensing of a primary user, each represents a computationally demanding task to secondary user receivers. In software-defined radio, computational complexity lengthens the time for a cognitive radio to recognize changes in the transmission environment. This complexity is even more significant for spatially multiplexed receivers, e.g., in SIMO and MIMO, where the spatio-temporal data sets grow in size with the number of antennae. Limits on power and space for the processor hardware further constrain SDR performance. In this report, we discuss improvements in spatio-temporal twice whitening (STTW) for real-time local spectrum sensing by demonstratingmore » a form of STTW well suited for MIMO environments. We implement STTW on the Coherent Logix hx3100 processor, a multicore processor intended for low-power, high-throughput software-defined signal processing. These results demonstrate how coupling the novel capabilities of emerging multicore processors with algorithmic advances can enable real-time, software-defined processing of large spatio-temporal data sets.« less
LEA Detection and Tracking Method for Color-Independent Visual-MIMO.
Kim, Jai-Eun; Kim, Ji-Won; Kim, Ki-Doo
2016-07-02
Communication performance in the color-independent visual-multiple input multiple output (visual-MIMO) technique is deteriorated by light emitting array (LEA) detection and tracking errors in the received image because the image sensor included in the camera must be used as the receiver in the visual-MIMO system. In this paper, in order to improve detection reliability, we first set up the color-space-based region of interest (ROI) in which an LEA is likely to be placed, and then use the Harris corner detection method. Next, we use Kalman filtering for robust tracking by predicting the most probable location of the LEA when the relative position between the camera and the LEA varies. In the last step of our proposed method, the perspective projection is used to correct the distorted image, which can improve the symbol decision accuracy. Finally, through numerical simulation, we show the possibility of robust detection and tracking of the LEA, which results in a symbol error rate (SER) performance improvement.
Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo
2018-03-07
In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.
MIMO-OFDM signal optimization for SAR imaging radar
NASA Astrophysics Data System (ADS)
Baudais, J.-Y.; Méric, S.; Riché, V.; Pottier, É.
2016-12-01
This paper investigates the optimization of the coded orthogonal frequency division multiplexing (OFDM) transmitted signal in a synthetic aperture radar (SAR) context. We propose to design OFDM signals to achieve range ambiguity mitigation. Indeed, range ambiguities are well known to be a limitation for SAR systems which operates with pulsed transmitted signal. The ambiguous reflected signal corresponding to one pulse is then detected when the radar has already transmitted the next pulse. In this paper, we demonstrate that the range ambiguity mitigation is possible by using orthogonal transmitted wave as OFDM pulses. The coded OFDM signal is optimized through genetic optimization procedures based on radar image quality parameters. Moreover, we propose to design a multiple-input multiple-output (MIMO) configuration to enhance the noise robustness of a radar system and this configuration is mainly efficient in the case of using orthogonal waves as OFDM pulses. The results we obtain show that OFDM signals outperform conventional radar chirps for range ambiguity suppression and for robustness enhancement in 2 ×2 MIMO configuration.
Stochastic Control Synthesis of Systems with Structured Uncertainty
NASA Technical Reports Server (NTRS)
Padula, Sharon L. (Technical Monitor); Crespo, Luis G.
2003-01-01
This paper presents a study on the design of robust controllers by using random variables to model structured uncertainty for both SISO and MIMO feedback systems. Once the parameter uncertainty is prescribed with probability density functions, its effects are propagated through the analysis leading to stochastic metrics for the system's output. Control designs that aim for satisfactory performances while guaranteeing robust closed loop stability are attained by solving constrained non-linear optimization problems in the frequency domain. This approach permits not only to quantify the probability of having unstable and unfavorable responses for a particular control design but also to search for controls while favoring the values of the parameters with higher chance of occurrence. In this manner, robust optimality is achieved while the characteristic conservatism of conventional robust control methods is eliminated. Examples that admit closed form expressions for the probabilistic metrics of the output are used to elucidate the nature of the problem at hand and validate the proposed formulations.
A Computer Model of the Evaporator for the Development of an Automatic Control System
NASA Astrophysics Data System (ADS)
Kozin, K. A.; Efremov, E. V.; Kabrysheva, O. P.; Grachev, M. I.
2016-08-01
For the implementation of a closed nuclear fuel cycle it is necessary to carry out a series of experimental studies to justify the choice of technology. In addition, the operation of the radiochemical plant is impossible without high-quality automatic control systems. In the technologies of spent nuclear fuel reprocessing, the method of continuous evaporation is often used for a solution conditioning. Therefore, the effective continuous technological process will depend on the operation of the evaporation equipment. Its essential difference from similar devices is a small size. In this paper the method of mathematic simulation is applied for the investigation of one-effect evaporator with an external heating chamber. Detailed modelling is quite difficult because the phase equilibrium dynamics of the evaporation process is not described. Moreover, there is a relationship with the other process units. The results proved that the study subject is a MIMO plant, nonlinear over separate control channels and not selfbalancing. Adequacy was tested using the experimental data obtained at the laboratory evaporation unit.
NASA Technical Reports Server (NTRS)
Chen, Ping-Chih (Inventor)
2013-01-01
This invention is a ground flutter testing system without a wind tunnel, called Dry Wind Tunnel (DWT) System. The DWT system consists of a Ground Vibration Test (GVT) hardware system, a multiple input multiple output (MIMO) force controller software, and a real-time unsteady aerodynamic force generation software, that is developed from an aerodynamic reduced order model (ROM). The ground flutter test using the DWT System operates on a real structural model, therefore no scaled-down structural model, which is required by the conventional wind tunnel flutter test, is involved. Furthermore, the impact of the structural nonlinearities on the aeroelastic stability can be included automatically. Moreover, the aeroservoelastic characteristics of the aircraft can be easily measured by simply including the flight control system in-the-loop. In addition, the unsteady aerodynamics generated computationally is interference-free from the wind tunnel walls. Finally, the DWT System can be conveniently and inexpensively carried out as a post GVT test with the same hardware, only with some possible rearrangement of the shakers and the inclusion of additional sensors.
Nonlinear control of linear parameter varying systems with applications to hypersonic vehicles
NASA Astrophysics Data System (ADS)
Wilcox, Zachary Donald
The focus of this dissertation is to design a controller for linear parameter varying (LPV) systems, apply it specifically to air-breathing hypersonic vehicles, and examine the interplay between control performance and the structural dynamics design. Specifically a Lyapunov-based continuous robust controller is developed that yields exponential tracking of a reference model, despite the presence of bounded, nonvanishing disturbances. The hypersonic vehicle has time varying parameters, specifically temperature profiles, and its dynamics can be reduced to an LPV system with additive disturbances. Since the HSV can be modeled as an LPV system the proposed control design is directly applicable. The control performance is directly examined through simulations. A wide variety of applications exist that can be effectively modeled as LPV systems. In particular, flight systems have historically been modeled as LPV systems and associated control tools have been applied such as gain-scheduling, linear matrix inequalities (LMIs), linear fractional transformations (LFT), and mu-types. However, as the type of flight environments and trajectories become more demanding, the traditional LPV controllers may no longer be sufficient. In particular, hypersonic flight vehicles (HSVs) present an inherently difficult problem because of the nonlinear aerothermoelastic coupling effects in the dynamics. HSV flight conditions produce temperature variations that can alter both the structural dynamics and flight dynamics. Starting with the full nonlinear dynamics, the aerothermoelastic effects are modeled by a temperature dependent, parameter varying state-space representation with added disturbances. The model includes an uncertain parameter varying state matrix, an uncertain parameter varying non-square (column deficient) input matrix, and an additive bounded disturbance. In this dissertation, a robust dynamic controller is formulated for a uncertain and disturbed LPV system. The developed controller is then applied to a HSV model, and a Lyapunov analysis is used to prove global exponential reference model tracking in the presence of uncertainty in the state and input matrices and exogenous disturbances. Simulations with a spectrum of gains and temperature profiles on the full nonlinear dynamic model of the HSV is used to illustrate the performance and robustness of the developed controller. In addition, this work considers how the performance of the developed controller varies over a wide variety of control gains and temperature profiles and are optimized with respect to different performance metrics. Specifically, various temperature profile models and related nonlinear temperature dependent disturbances are used to characterize the relative control performance and effort for each model. Examining such metrics as a function of temperature provides a potential inroad to examine the interplay between structural/thermal protection design and control development and has application for future HSV design and control implementation.
Modeling and control of non-square MIMO system using relay feedback.
Kalpana, D; Thyagarajan, T; Gokulraj, N
2015-11-01
This paper proposes a systematic approach for the modeling and control of non-square MIMO systems in time domain using relay feedback. Conventionally, modeling, selection of the control configuration and controller design of non-square MIMO systems are performed using input/output information of direct loop, while the output of undesired responses that bears valuable information on interaction among the loops are not considered. However, in this paper, the undesired response obtained from relay feedback test is also taken into consideration to extract the information about the interaction between the loops. The studies are performed on an Air Path Scheme of Turbocharged Diesel Engine (APSTDE) model, which is a typical non-square MIMO system, with input and output variables being 3 and 2 respectively. From the relay test response, the generalized analytical expressions are derived and these analytical expressions are used to estimate unknown system parameters and also to evaluate interaction measures. The interaction is analyzed by using Block Relative Gain (BRG) method. The model thus identified is later used to design appropriate controller to carry out closed loop studies. Closed loop simulation studies were performed for both servo and regulatory operations. Integral of Squared Error (ISE) performance criterion is employed to quantitatively evaluate performance of the proposed scheme. The usefulness of the proposed method is demonstrated on a lab-scale Two-Tank Cylindrical Interacting System (TTCIS), which is configured as a non-square system. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Autonomous Vehicle Systems Laboratory Research Capability Expansion Program
2017-12-03
currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. University of the Incarnate Word 4301 Broadway, Box #T-2 San Antonio...autonomous control , collaboration, and decision-making in unstructured, dynamic, and uncertain nonlinear environments for autonomous ground and air...vehicle systems. To fulfill the research goal, the PI has initiated fundamental research in the areas of autonomous rotorcraft control and
Robust leader-follower formation tracking control of multiple underactuated surface vessels
NASA Astrophysics Data System (ADS)
Peng, Zhou-hua; Wang, Dan; Lan, Wei-yao; Sun, Gang
2012-09-01
This paper is concerned with the formation control problem of multiple underactuated surface vessels moving in a leader-follower formation. The formation is achieved by the follower to track a virtual target defined relative to the leader. A robust adaptive target tracking law is proposed by using neural network and backstepping techniques. The advantage of the proposed control scheme is that the uncertain nonlinear dynamics caused by Coriolis/centripetal forces, nonlinear damping, unmodeled hydrodynamics and disturbances from the environment can be compensated by on line learning. Based on Lyapunov analysis, the proposed controller guarantees the tracking errors converge to a small neighborhood of the origin. Simulation results demonstrate the effectiveness of the control strategy.
NASA Technical Reports Server (NTRS)
Graff, Trevor G.; Morris, R. V.; Klingelhofer, G.; Blumers, M.
2013-01-01
Field testing and scientific investigations were conducted on the Mauna Kea Volcano, Hawaii, as part of the 2012 Moon and Mars Analog Mission Activities (MMAMA). Measurements were conducted using both stand-alone and rover-mounted instruments to determine the geophysical and geochemical properties of the field site, as well as provide operational constraints and science considerations for future robotic and human missions [1]. Reported here are the results from the two MIMOS instruments deployed as part of this planetary analog field test.
Achievable degrees of freedom of MIMO two-way relay interference channel with delayed CSIT
NASA Astrophysics Data System (ADS)
Li, Qingyun; Wu, Gang; Li, Shaoqian
2016-10-01
In this paper, assuming each node has delayed channel state information at the transmitter (CSIT), we investigate the achievable degrees of freedom (DOF) of MIMO two-way relay interference channel in frequency division duplex (FDD) systems, where there are K user pairs (i.e., 2K users) and each user in a user pair exchanges messages with the other user in the same user pair simultaneously via an intermediate relay. We propose a two-stage transmission scheme and derive the closed-form expressions for its achievable DOF.
A new DOD and DOA estimation method for MIMO radar
NASA Astrophysics Data System (ADS)
Gong, Jian; Lou, Shuntian; Guo, Yiduo
2018-04-01
The battlefield electromagnetic environment is becoming more and more complex, and MIMO radar will inevitably be affected by coherent and non-stationary noise. To solve this problem, an angle estimation method based on oblique projection operator and Teoplitz matrix reconstruction is proposed. Through the reconstruction of Toeplitz, nonstationary noise is transformed into Gauss white noise, and then the oblique projection operator is used to separate independent and correlated sources. Finally, simulations are carried out to verify the performance of the proposed algorithm in terms of angle estimation performance and source overload.
NASA Astrophysics Data System (ADS)
Wang, Huiqin; Wang, Xue; Cao, Minghua
2017-02-01
The spatial correlation extensively exists in the multiple-input multiple-output (MIMO) free space optical (FSO) communication systems due to the channel fading and the antenna space limitation. Wilkinson's method was utilized to investigate the impact of spatial correlation on the MIMO FSO communication system employing multipulse pulse-position modulation. Simulation results show that the existence of spatial correlation reduces the ergodic channel capacity, and the reception diversity is more competent to resist this kind of performance degradation.
NASA Technical Reports Server (NTRS)
Joshi, S. M.
1985-01-01
Robustness properties are investigated for two types of controllers for large flexible space structures, which use collocated sensors and actuators. The first type is an attitude controller which uses negative definite feedback of measured attitude and rate, while the second type is a damping enhancement controller which uses only velocity (rate) feedback. It is proved that collocated attitude controllers preserve closed loop global asymptotic stability when linear actuator/sensor dynamics satisfying certain phase conditions are present, or monotonic increasing nonlinearities are present. For velocity feedback controllers, the global asymptotic stability is proved under much weaker conditions. In particular, they have 90 phase margin and can tolerate nonlinearities belonging to the (0,infinity) sector in the actuator/sensor characteristics. The results significantly enhance the viability of both types of collocated controllers, especially when the available information about the large space structure (LSS) parameters is inadequate or inaccurate.
Intelligent Tracking Control for a Class of Uncertain High-Order Nonlinear Systems.
Zhao, Xudong; Shi, Peng; Zheng, Xiaolong; Zhang, Jianhua
2016-09-01
This brief is concerned with the problem of intelligent tracking control for a class of high-order nonlinear systems with completely unknown nonlinearities. An intelligent adaptive control algorithm is presented by combining the adaptive backstepping technique with the neural networks' approximation ability. It is shown that the practical output tracking performance of the system is achieved using the proposed state-feedback controller under two mild assumptions. In particular, by introducing a parameter in the derivations, the tracking error between the time-varying target signal and the output can be reduced via tuning the controller design parameters. Moreover, in order to solve the problem of overparameterization, which is a common issue in adaptive control design, a controller with one adaptive law is also designed. Finally, simulation results are given to show the effectiveness of the theoretical approaches and the potential of the proposed new design techniques.
Neilson, Peter D; Neilson, Megan D
2005-09-01
Adaptive model theory (AMT) is a computational theory that addresses the difficult control problem posed by the musculoskeletal system in interaction with the environment. It proposes that the nervous system creates motor maps and task-dependent synergies to solve the problems of redundancy and limited central resources. These lead to the adaptive formation of task-dependent feedback/feedforward controllers able to generate stable, noninteractive control and render nonlinear interactions unobservable in sensory-motor relationships. AMT offers a unified account of how the nervous system might achieve these solutions by forming internal models. This is presented as the design of a simulator consisting of neural adaptive filters based on cerebellar circuitry. It incorporates a new network module that adaptively models (in real time) nonlinear relationships between inputs with changing and uncertain spectral and amplitude probability density functions as is the case for sensory and motor signals.
Gao, Qing; Feng, Gang; Xi, Zhiyu; Wang, Yong; Qiu, Jianbin
2014-09-01
In this paper, a novel dynamic sliding mode control scheme is proposed for a class of uncertain stochastic nonlinear time-delay systems represented by Takagi-Sugeno fuzzy models. The key advantage of the proposed scheme is that two very restrictive assumptions in most existing sliding mode control approaches for stochastic fuzzy systems have been removed. It is shown that the closed-loop control system trajectories can be driven onto the sliding surface in finite time almost certainly. It is also shown that the stochastic stability of the resulting sliding motion can be guaranteed in terms of linear matrix inequalities; moreover, the sliding-mode controller can be obtained simultaneously. Simulation results illustrating the advantages and effectiveness of the proposed approaches are also provided.
Backstepping Design of Adaptive Neural Fault-Tolerant Control for MIMO Nonlinear Systems.
Gao, Hui; Song, Yongduan; Wen, Changyun
In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.
Reliability, Risk and Cost Trade-Offs for Composite Designs
NASA Technical Reports Server (NTRS)
Shiao, Michael C.; Singhal, Surendra N.; Chamis, Christos C.
1996-01-01
Risk and cost trade-offs have been simulated using a probabilistic method. The probabilistic method accounts for all naturally-occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry and loading conditions. The probability density function of first buckling load for a set of uncertain variables is computed. The probabilistic sensitivity factors of uncertain variables to the first buckling load is calculated. The reliability-based cost for a composite fuselage panel is defined and minimized with respect to requisite design parameters. The optimization is achieved by solving a system of nonlinear algebraic equations whose coefficients are functions of probabilistic sensitivity factors. With optimum design parameters such as the mean and coefficient of variation (representing range of scatter) of uncertain variables, the most efficient and economical manufacturing procedure can be selected. In this paper, optimum values of the requisite design parameters for a predetermined cost due to failure occurrence are computationally determined. The results for the fuselage panel analysis show that the higher the cost due to failure occurrence, the smaller the optimum coefficient of variation of fiber modulus (design parameter) in longitudinal direction.
Talaei, Behzad; Jagannathan, Sarangapani; Singler, John
2018-04-01
In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.
Multi-functional Chassis-based Antennas Using Characteristic Mode Theory
NASA Astrophysics Data System (ADS)
Kishor, Krishna Kumar
Designing antennas for handheld devices is quite challenging primarily due to the limited real-estate available, and the fact that internal antennas occupy a large volume. With the need to support a variety of radio systems such as GSM, LTE and WiFi that operate in a wide range of frequency bands, multi-band, wideband and frequency reconfigurable antenna designs have been explored in the literature. Moreover, to support higher data rates, the Long Term Evolution Advanced (LTE-A) standard has been introduced, which requires supporting multiple input multiple output (MIMO) antenna technology and carrier aggregation (CA) on a handheld device. Both of these benefit from the use of multiple antennas or multi-port antennas, but with the limited space available, adding more internal antennas may not be easily possible. Additionally, to realize the benefits of these technologies the multiple antenna ports have to be well isolated from each other. This thesis explores the utilization of the ground plane (or chassis) of a handheld device as an antenna to meet some of these challenges. To achieve this, the theory of characteristic modes (TCM) for conducting bodies is relied upon, to determine the eigen-currents supported on the chassis. The orthogonality properties of these eigencurrents, and their corresponding far-field eigenfields (electric and magnetic) makes TCM a good tool to design multiple antennas with high isolation. This is demonstrated in this thesis via the design of four chassis-based antennas that have different functionalities. The first design is a two port MIMO antenna utilizing a combination of eigenmodes to achieve port isolation. The second design is a pattern reconfigurable MIMO antenna that can operate in two states at 2.28 GHz. The third design is a four port antenna that operates in three frequency bands, with two bands below 1 GHz for CA and the remaining two ports for MIMO communication. The final design is a five port antenna that supports MIMO operation in two frequency bands along with an additional port for CA in the third band. The four designs have been experimentally verified, validating the use of TCM as a versatile tool to design multi-functional chassis-based antennas.
Fast convergent frequency-domain MIMO equalizer for few-mode fiber communication systems
NASA Astrophysics Data System (ADS)
He, Xuan; Weng, Yi; Wang, Junyi; Pan, Z.
2018-02-01
Space division multiplexing using few-mode fibers has been extensively explored to sustain the continuous traffic growth. In few-mode fiber optical systems, both spatial and polarization modes are exploited to transmit parallel channels, thus increasing the overall capacity. However, signals on spatial channels inevitably suffer from the intrinsic inter-modal coupling and large accumulated differential mode group delay (DMGD), which causes spatial modes de-multiplex even harder. Many research articles have demonstrated that frequency domain adaptive multi-input multi-output (MIMO) equalizer can effectively compensate the DMGD and demultiplex the spatial channels with digital signal processing (DSP). However, the large accumulated DMGD usually requires a large number of training blocks for the initial convergence of adaptive MIMO equalizers, which will decrease the overall system efficiency and even degrade the equalizer performance in fast-changing optical channels. Least mean square (LMS) algorithm is always used in MIMO equalization to dynamically demultiplex the spatial signals. We have proposed to use signal power spectral density (PSD) dependent method and noise PSD directed method to improve the convergence speed of adaptive frequency domain LMS algorithm. We also proposed frequency domain recursive least square (RLS) algorithm to further increase the convergence speed of MIMO equalizer at cost of greater hardware complexity. In this paper, we will compare the hardware complexity and convergence speed of signal PSD dependent and noise power directed algorithms against the conventional frequency domain LMS algorithm. In our numerical study of a three-mode 112 Gbit/s PDM-QPSK optical system with 3000 km transmission, the noise PSD directed and signal PSD dependent methods could improve the convergence speed by 48.3% and 36.1% respectively, at cost of 17.2% and 10.7% higher hardware complexity. We will also compare the frequency domain RLS algorithm against conventional frequency domain LMS algorithm. Our numerical study shows that, in a three-mode 224 Gbit/s PDM-16-QAM system with 3000 km transmission, the RLS algorithm could improve the convergence speed by 53.7% over conventional frequency domain LMS algorithm.
Bayesian inference of nonlinear unsteady aerodynamics from aeroelastic limit cycle oscillations
NASA Astrophysics Data System (ADS)
Sandhu, Rimple; Poirel, Dominique; Pettit, Chris; Khalil, Mohammad; Sarkar, Abhijit
2016-07-01
A Bayesian model selection and parameter estimation algorithm is applied to investigate the influence of nonlinear and unsteady aerodynamic loads on the limit cycle oscillation (LCO) of a pitching airfoil in the transitional Reynolds number regime. At small angles of attack, laminar boundary layer trailing edge separation causes negative aerodynamic damping leading to the LCO. The fluid-structure interaction of the rigid, but elastically mounted, airfoil and nonlinear unsteady aerodynamics is represented by two coupled nonlinear stochastic ordinary differential equations containing uncertain parameters and model approximation errors. Several plausible aerodynamic models with increasing complexity are proposed to describe the aeroelastic system leading to LCO. The likelihood in the posterior parameter probability density function (pdf) is available semi-analytically using the extended Kalman filter for the state estimation of the coupled nonlinear structural and unsteady aerodynamic model. The posterior parameter pdf is sampled using a parallel and adaptive Markov Chain Monte Carlo (MCMC) algorithm. The posterior probability of each model is estimated using the Chib-Jeliazkov method that directly uses the posterior MCMC samples for evidence (marginal likelihood) computation. The Bayesian algorithm is validated through a numerical study and then applied to model the nonlinear unsteady aerodynamic loads using wind-tunnel test data at various Reynolds numbers.
Bayesian inference of nonlinear unsteady aerodynamics from aeroelastic limit cycle oscillations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sandhu, Rimple; Poirel, Dominique; Pettit, Chris
2016-07-01
A Bayesian model selection and parameter estimation algorithm is applied to investigate the influence of nonlinear and unsteady aerodynamic loads on the limit cycle oscillation (LCO) of a pitching airfoil in the transitional Reynolds number regime. At small angles of attack, laminar boundary layer trailing edge separation causes negative aerodynamic damping leading to the LCO. The fluid–structure interaction of the rigid, but elastically mounted, airfoil and nonlinear unsteady aerodynamics is represented by two coupled nonlinear stochastic ordinary differential equations containing uncertain parameters and model approximation errors. Several plausible aerodynamic models with increasing complexity are proposed to describe the aeroelastic systemmore » leading to LCO. The likelihood in the posterior parameter probability density function (pdf) is available semi-analytically using the extended Kalman filter for the state estimation of the coupled nonlinear structural and unsteady aerodynamic model. The posterior parameter pdf is sampled using a parallel and adaptive Markov Chain Monte Carlo (MCMC) algorithm. The posterior probability of each model is estimated using the Chib–Jeliazkov method that directly uses the posterior MCMC samples for evidence (marginal likelihood) computation. The Bayesian algorithm is validated through a numerical study and then applied to model the nonlinear unsteady aerodynamic loads using wind-tunnel test data at various Reynolds numbers.« less
Adaptive Critic Nonlinear Robust Control: A Survey.
Wang, Ding; He, Haibo; Liu, Derong
2017-10-01
Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.
NASA Astrophysics Data System (ADS)
Song, Jia; Wang, Lun; Cai, Guobiao; Qi, Xiaoqiang
2015-06-01
Near space hypersonic vehicle model is nonlinear, multivariable and couples in the reentry process, which are challenging for the controller design. In this paper, a nonlinear fractional order proportion integral derivative (NFOPIλDμ) active disturbance rejection control (ADRC) strategy based on a natural selection particle swarm (NSPSO) algorithm is proposed for the hypersonic vehicle flight control. The NFOPIλDμ ADRC method consists of a tracking-differentiator (TD), an NFOPIλDμ controller and an extended state observer (ESO). The NFOPIλDμ controller designed by combining an FOPIλDμ method and a nonlinear states error feedback control law (NLSEF) is to overcome concussion caused by the NLSEF and conversely compensate the insufficiency for relatively simple and rough signal processing caused by the FOPIλDμ method. The TD is applied to coordinate the contradiction between rapidity and overshoot. By attributing all uncertain factors to unknown disturbances, the ESO can achieve dynamic feedback compensation for these disturbances and thus reduce their effects. Simulation results show that the NFOPIλDμ ADRC method can make the hypersonic vehicle six-degree-of-freedom nonlinear model track desired nominal signals accurately and fast, has good stability, dynamic properties and strong robustness against external environmental disturbances.
Low-mobility channel tracking for MIMO-OFDM communication systems
NASA Astrophysics Data System (ADS)
Pagadarai, Srikanth; Wyglinski, Alexander M.; Anderson, Christopher R.
2013-12-01
It is now well understood that by exploiting the available additional spatial dimensions, multiple-input multiple-output (MIMO) communication systems provide capacity gains, compared to a single-input single-output systems without increasing the overall transmit power or requiring additional bandwidth. However, these large capacity gains are feasible only when the perfect knowledge of the channel is available to the receiver. Consequently, when the channel knowledge is imperfect, as is common in practical settings, the impact of the achievable capacity needs to be evaluated. In this study, we begin with a general MIMO framework at the outset and specialize it to the case of orthogonal frequency division multiplexing (OFDM) systems by decoupling channel estimation from data detection. Cyclic-prefixed OFDM systems have attracted widespread interest due to several appealing characteristics not least of which is the fact that a single-tap frequency-domain equalizer per subcarrier is sufficient due to the circulant structure of the resulting channel matrix. We consider a low-mobility wireless channel which exhibits inter-block channel variations and apply Kalman tracking when MIMO-OFDM communication is performed. Furthermore, we consider the signal transmission to contain a stream of training and information symbols followed by information symbols alone. By relying on predicted channel states when training symbols are absent, we aim to understand how the improvements in channel capacity are affected by imperfect channel knowledge. We show that the Kalman recursion procedure can be simplified by the optimal minimum mean square error training design. Using the simplified recursion, we derive capacity upper and lower bounds to evaluate the performance of the system.
Synthesis of Nonlinear Guidance Laws for Missiles with Uncertain Dynamics
2007-11-01
and Astronautics, Progress in Astronautics and Aeronautics, Volume 199, 2002. 2. Gurfil , M. Jodorkovsky and M. Guelman, Neoclassical Guidance for...658-666, July-August 2002. 19. P. Gurfil , “Robust Guidance for Electro-Optical Missiles,” IEEE Transactions on Aerospace and Electronic Systems, Vol...edition, Upper Saddle River, NJ: Prentice-Hall, 2002. 23. P. Gurfil , ”Zero-Miss Distance Guidance Law Based on Line-of-Sight Rate Measuremenbt Only
A Highly Reliable and Cost-Efficient Multi-Sensor System for Land Vehicle Positioning.
Li, Xu; Xu, Qimin; Li, Bin; Song, Xianghui
2016-05-25
In this paper, we propose a novel positioning solution for land vehicles which is highly reliable and cost-efficient. The proposed positioning system fuses information from the MEMS-based reduced inertial sensor system (RISS) which consists of one vertical gyroscope and two horizontal accelerometers, low-cost GPS, and supplementary sensors and sources. First, pitch and roll angle are accurately estimated based on a vehicle kinematic model. Meanwhile, the negative effect of the uncertain nonlinear drift of MEMS inertial sensors is eliminated by an H∞ filter. Further, a distributed-dual-H∞ filtering (DDHF) mechanism is adopted to address the uncertain nonlinear drift of the MEMS-RISS and make full use of the supplementary sensors and sources. The DDHF is composed of a main H∞ filter (MHF) and an auxiliary H∞ filter (AHF). Finally, a generalized regression neural network (GRNN) module with good approximation capability is specially designed for the MEMS-RISS. A hybrid methodology which combines the GRNN module and the AHF is utilized to compensate for RISS position errors during GPS outages. To verify the effectiveness of the proposed solution, road-test experiments with various scenarios were performed. The experimental results illustrate that the proposed system can achieve accurate and reliable positioning for land vehicles.
A Highly Reliable and Cost-Efficient Multi-Sensor System for Land Vehicle Positioning
Li, Xu; Xu, Qimin; Li, Bin; Song, Xianghui
2016-01-01
In this paper, we propose a novel positioning solution for land vehicles which is highly reliable and cost-efficient. The proposed positioning system fuses information from the MEMS-based reduced inertial sensor system (RISS) which consists of one vertical gyroscope and two horizontal accelerometers, low-cost GPS, and supplementary sensors and sources. First, pitch and roll angle are accurately estimated based on a vehicle kinematic model. Meanwhile, the negative effect of the uncertain nonlinear drift of MEMS inertial sensors is eliminated by an H∞ filter. Further, a distributed-dual-H∞ filtering (DDHF) mechanism is adopted to address the uncertain nonlinear drift of the MEMS-RISS and make full use of the supplementary sensors and sources. The DDHF is composed of a main H∞ filter (MHF) and an auxiliary H∞ filter (AHF). Finally, a generalized regression neural network (GRNN) module with good approximation capability is specially designed for the MEMS-RISS. A hybrid methodology which combines the GRNN module and the AHF is utilized to compensate for RISS position errors during GPS outages. To verify the effectiveness of the proposed solution, road-test experiments with various scenarios were performed. The experimental results illustrate that the proposed system can achieve accurate and reliable positioning for land vehicles. PMID:27231917
NASA Astrophysics Data System (ADS)
Manfredi, Sabato
2016-06-01
Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.
MIMO: an efficient tool for molecular interaction maps overlap
2013-01-01
Background Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps. Results Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database. Conclusions MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways. PMID:23672344
Practical 3-D Beam Pattern Based Channel Modeling for Multi-Polarized Massive MIMO Systems.
Aghaeinezhadfirouzja, Saeid; Liu, Hui; Balador, Ali
2018-04-12
In this paper, a practical non-stationary three-dimensional (3-D) channel models for massive multiple-input multiple-output (MIMO) systems, considering beam patterns for different antenna elements, is proposed. The beam patterns using dipole antenna elements with different phase excitation toward the different direction of travels (DoTs) contributes various correlation weights for rays related towards/from the cluster, thus providing different elevation angle of arrivals (EAoAs) and elevation angle of departures (EAoDs) for each antenna element. These include the movements of the user that makes our channel to be a non-stationary model of clusters at the receiver (RX) on both the time and array axes. In addition, their impacts on 3-D massive MIMO channels are investigated via statistical properties including received spatial correlation. Additionally, the impact of elevation/azimuth angles of arrival on received spatial correlation is discussed. Furthermore, experimental validation of the proposed 3-D channel models on azimuth and elevation angles of the polarized antenna are specifically evaluated and compared through simulations. The proposed 3-D generic models are verified using relevant measurement data.
MIMO signal progressing with RLSCMA algorithm for multi-mode multi-core optical transmission system
NASA Astrophysics Data System (ADS)
Bi, Yuan; Liu, Bo; Zhang, Li-jia; Xin, Xiang-jun; Zhang, Qi; Wang, Yong-jun; Tian, Qing-hua; Tian, Feng; Mao, Ya-ya
2018-01-01
In the process of transmitting signals of multi-mode multi-core fiber, there will be mode coupling between modes. The mode dispersion will also occur because each mode has different transmission speed in the link. Mode coupling and mode dispersion will cause damage to the useful signal in the transmission link, so the receiver needs to deal received signal with digital signal processing, and compensate the damage in the link. We first analyzes the influence of mode coupling and mode dispersion in the process of transmitting signals of multi-mode multi-core fiber, then presents the relationship between the coupling coefficient and dispersion coefficient. Then we carry out adaptive signal processing with MIMO equalizers based on recursive least squares constant modulus algorithm (RLSCMA). The MIMO equalization algorithm offers adaptive equalization taps according to the degree of crosstalk in cores or modes, which eliminates the interference among different modes and cores in space division multiplexing(SDM) transmission system. The simulation results show that the distorted signals are restored efficiently with fast convergence speed.
Practical 3-D Beam Pattern Based Channel Modeling for Multi-Polarized Massive MIMO Systems †
Aghaeinezhadfirouzja, Saeid; Liu, Hui
2018-01-01
In this paper, a practical non-stationary three-dimensional (3-D) channel models for massive multiple-input multiple-output (MIMO) systems, considering beam patterns for different antenna elements, is proposed. The beam patterns using dipole antenna elements with different phase excitation toward the different direction of travels (DoTs) contributes various correlation weights for rays related towards/from the cluster, thus providing different elevation angle of arrivals (EAoAs) and elevation angle of departures (EAoDs) for each antenna element. These include the movements of the user that makes our channel to be a non-stationary model of clusters at the receiver (RX) on both the time and array axes. In addition, their impacts on 3-D massive MIMO channels are investigated via statistical properties including received spatial correlation. Additionally, the impact of elevation/azimuth angles of arrival on received spatial correlation is discussed. Furthermore, experimental validation of the proposed 3-D channel models on azimuth and elevation angles of the polarized antenna are specifically evaluated and compared through simulations. The proposed 3-D generic models are verified using relevant measurement data. PMID:29649177
Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar
Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping
2015-01-01
A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters’ outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results. PMID:26694385
Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping
2015-12-14
A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters' outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results.
NASA Astrophysics Data System (ADS)
Zelený, J.; Pérez-Fontán, F.; Pechac, P.; Mariño-Espiñeira, P.
2017-05-01
In civil surveillance applications, unmanned aerial vehicles (UAV) are being increasingly used in floods, fires, and law enforcement scenarios. In order to transfer large amounts of information from UAV-mounted cameras, relays, or sensors, large bandwidths are needed in comparison to those required for remotely commanding the UAV. This demands the use of higher-frequency bands, in all probability in the vicinity of 2 or 5 GHz. Novel hardware developments need propagation channel models for the ample range of operational scenarios envisaged, including multiple-input, multiple-output (MIMO) deployments. These configurations may enable a more robust transmission by increasing either the carrier-to-noise ratio statistics or the achievable capacity. In this paper, a 2 × 2 MIMO propagation channel model for an open-field environment capable of synthesizing a narrowband time series at 2 GHz is described. Maximal ratio combining diversity and capacity improvements are also evaluated through synthetic series and compared with measurement results. A simple flat, open scenario was evaluated based on which other, more complex environments can be modeled.
Diversity-optimal power loading for intensity modulated MIMO optical wireless communications.
Zhang, Yan-Yu; Yu, Hong-Yi; Zhang, Jian-Kang; Zhu, Yi-Jun
2016-04-18
In this paper, we consider the design of space code for an intensity modulated direct detection multi-input-multi-output optical wireless communication (IM/DD MIMO-OWC) system, in which channel coefficients are independent and non-identically log-normal distributed, with variances and means known at the transmitter and channel state information available at the receiver. Utilizing the existing space code design criterion for IM/DD MIMO-OWC with a maximum likelihood (ML) detector, we design a diversity-optimal space code (DOSC) that maximizes both large-scale diversity and small-scale diversity gains and prove that the spatial repetition code (RC) with a diversity-optimized power allocation is diversity-optimal among all the high dimensional nonnegative space code schemes under a commonly used optical power constraint. In addition, we show that one of significant advantages of the DOSC is to allow low-complexity ML detection. Simulation results indicate that in high signal-to-noise ratio (SNR) regimes, our proposed DOSC significantly outperforms RC, which is the best space code currently available for such system.
MIMO Radar System for Respiratory Monitoring Using Tx and Rx Modulation with M-Sequence Codes
NASA Astrophysics Data System (ADS)
Miwa, Takashi; Ogiwara, Shun; Yamakoshi, Yoshiki
The importance of respiratory monitoring systems during sleep have increased due to early diagnosis of sleep apnea syndrome (SAS) in the home. This paper presents a simple respiratory monitoring system suitable for home use having 3D ranging of targets. The range resolution and azimuth resolution are obtained by a stepped frequency transmitting signal and MIMO arrays with preferred pair M-sequence codes doubly modulating in transmission and reception, respectively. Due to the use of these codes, Gold sequence codes corresponding to all the antenna combinations are equivalently modulated in receiver. The signal to interchannel interference ratio of the reconstructed image is evaluated by numerical simulations. The results of experiments on a developed prototype 3D-MIMO radar system show that this system can extract only the motion of respiration of a human subject 2m apart from a metallic rotatable reflector. Moreover, it is found that this system can successfully measure the respiration information of sleeping human subjects for 96.6 percent of the whole measurement time except for instances of large posture change.
NASA Astrophysics Data System (ADS)
Chau, J. L.; Urco, J. M.; Milla, M. A.; Vierinen, J.
2017-12-01
We have recently implemented Multiple-input multiple-output (MIMO) radar techniques to resolve temporal and spatial ambiguities of ionospheric and atmospheric irregularities, with improve capabilities than previously experiments using single-input multi-output (SIMO) techniques. SIMO techniques in the atmospheric and ionospheric coherent scatter radar field are usually called aperture synthesis radar imaging. Our implementations have done at the Jicamarca Radio Observatory (JRO) in Lima, Peru, and at the Middle Atmosphere Alomar Radar System (MAARSY) in Andenes, Norway, to study equatorial electrojet (EEJ) field-aligned irregularities and polar mesospheric summer echoes (PMSE), respectively. Figure 1 shows an example of a configuration used at MAARSY and the comparison between the SIMO and MIMO resulting antenna point spread functions, respectively. Although in this work we present the details of the implementations at each facility, we will focus on the observed peculiarities of each phenomenon, making emphasis in the underlying physical mechanisms that govern their existence and their spatial and temporal modulation. For example, what are the typical horizontal scales of PMSE variability in both intensity and wind field?
2 × 2 MIMO OFDM/OQAM radio signals over an elliptical core few-mode fiber.
Mo, Qi; He, Jiale; Yu, Dawei; Deng, Lei; Fu, Songnian; Tang, Ming; Liu, Deming
2016-10-01
We experimentally demonstrate a 4.46 Gb/s2×2 multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM)/OQAM radio signal over a 2 km elliptical core 3-mode fiber, together with 0.4 m wireless transmission. Meanwhile, to cope with differential channel delay (DCD) among involved MIMO channels, we propose a time-offset crosstalk cancellation algorithm to extend the DCD tolerance from 10 to 60 ns without using a circle prefix (CP), leading to an 18.7% improvement of spectral efficiency. For the purpose of comparison, we also examine the transmission performance of CP-OFDM signals with different lengths of CPs, under the same system configuration. The proposed algorithm is also effective for the DCD compensation of a radio signal over a 2 km 7-core fiber. These results not only demonstrate the feasibility of space division multiplexing for RoF application but also validate that the elliptical core few-mode fiber can provide the same independent channels as the multicore fiber.
Experimental Evaluation of Adaptive Modulation and Coding in MIMO WiMAX with Limited Feedback
NASA Astrophysics Data System (ADS)
Mehlführer, Christian; Caban, Sebastian; Rupp, Markus
2007-12-01
We evaluate the throughput performance of an OFDM WiMAX (IEEE 802.16-2004, Section 8.3) transmission system with adaptive modulation and coding (AMC) by outdoor measurements. The standard compliant AMC utilizes a 3-bit feedback for SISO and Alamouti coded MIMO transmissions. By applying a 6-bit feedback and spatial multiplexing with individual AMC on the two transmit antennas, the data throughput can be increased significantly for large SNR values. Our measurements show that at small SNR values, a single antenna transmission often outperforms an Alamouti transmission. We found that this effect is caused by the asymmetric behavior of the wireless channel and by poor channel knowledge in the two-transmit-antenna case. Our performance evaluation is based on a measurement campaign employing the Vienna MIMO testbed. The measurement scenarios include typical outdoor-to-indoor NLOS, outdoor-to-outdoor NLOS, as well as outdoor-to-indoor LOS connections. We found that in all these scenarios, the measured throughput is far from its achievable maximum; the loss is mainly caused by a too simple convolutional coding.
Neural robust stabilization via event-triggering mechanism and adaptive learning technique.
Wang, Ding; Liu, Derong
2018-06-01
The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Lin, Tsung-Chih
2010-12-01
In this paper, a novel direct adaptive interval type-2 fuzzy-neural tracking control equipped with sliding mode and Lyapunov synthesis approach is proposed to handle the training data corrupted by noise or rule uncertainties for nonlinear SISO nonlinear systems involving external disturbances. By employing adaptive fuzzy-neural control theory, the update laws will be derived for approximating the uncertain nonlinear dynamical system. In the meantime, the sliding mode control method and the Lyapunov stability criterion are incorporated into the adaptive fuzzy-neural control scheme such that the derived controller is robust with respect to unmodeled dynamics, external disturbance and approximation errors. In comparison with conventional methods, the advocated approach not only guarantees closed-loop stability but also the output tracking error of the overall system will converge to zero asymptotically without prior knowledge on the upper bound of the lumped uncertainty. Furthermore, chattering effect of the control input will be substantially reduced by the proposed technique. To illustrate the performance of the proposed method, finally simulation example will be given.
Breast Cancer Nodes Detection Using Ultrasonic Microscale Subarrayed MIMO RADAR
Siwamogsatham, Siwaruk; Pomalaza-Ráez, Carlos
2014-01-01
This paper proposes the use of ultrasonic microscale subarrayed MIMO RADARs to estimate the position of breast cancer nodes. The transmit and receive antenna arrays are divided into subarrays. In order to increase the signal diversity each subarray is assigned a different waveform from an orthogonal set. High-frequency ultrasonic transducers are used since a breast is considered to be a superficial structure. Closed form expressions for the optimal Neyman-Pearson detector are derived. The combination of the waveform diversity present in the subarrayed deployment and traditional phased-array RADAR techniques provides promising results. PMID:25309591
Respiration and heartbeat monitoring using a distributed pulsed MIMO radar.
Walterscheid, Ingo; Smith, Graeme E
2017-07-01
This paper addresses non-contact monitoring of physiological signals induced by respiration and heartbeat. To detect the tiny physiological movements of the chest or other parts of the torso, a Mulitple-Input Multiple-Output (MIMO) radar is used. The spatially distributed transmitters and receivers are able to detect the chest surface movements of one or multiple persons in a room. Due to several bistatic measurements at the same time a robust detection and measuring of the breathing and heartbeat rate is possible. Using an appropriate geometrical configuration of the sensors even a localization of the person is feasible.
Dynamic modeling and parameter estimation of a radial and loop type distribution system network
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jun Qui; Heng Chen; Girgis, A.A.
1993-05-01
This paper presents a new identification approach to three-phase power system modeling and model reduction taking power system network as multi-input, multi-output (MIMO) processes. The model estimate can be obtained in discrete-time input-output form, discrete- or continuous-time state-space variable form, or frequency-domain impedance transfer function matrix form. An algorithm for determining the model structure of this MIMO process is described. The effect of measurement noise on the approach is also discussed. This approach has been applied on a sample system and simulation results are also presented in this paper.
Application of Financial Risk-reward Theory to Link and Network Optimization
2011-10-01
OFDM systems the matrices V k and U k are Fourier matrices which diagonalize a circulant or block-circulant matrix Hk [18]. In multi-antenna systems...probability α=Pr(η r <=t) Figure 13: Mean link spectral efficiency as a function of target link spectral efficiency ηt and outage probability ζ in a MIMO ...in a MIMO channel. Distribution A: Approved for public release; distribution is unlimited. 41 (75) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 2 4 6 8
Reliable actuators for twin rotor MIMO system
NASA Astrophysics Data System (ADS)
Rao, Vidya S.; V. I, George; Kamath, Surekha; Shreesha, C.
2017-11-01
Twin Rotor MIMO System (TRMS) is a bench mark system to test flight control algorithms. One of the perturbations on TRMS which is likely to affect the control system is actuator failure. Therefore, there is a need for a reliable control system, which includes H infinity controller along with redundant actuators. Reliable control refers to the design of a control system to tolerate failures of a certain set of actuators or sensors while retaining desired control system properties. Output of reliable controller has to be transferred to the redundant actuator effectively to make the TRMS reliable even under actual actuator failure.
Liu, Jian; Liu, Kexin; Liu, Shutang
2017-01-01
In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results. PMID:28467431
Liu, Jian; Liu, Kexin; Liu, Shutang
2017-01-01
In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.
Adaptive control of an exoskeleton robot with uncertainties on kinematics and dynamics.
Brahmi, Brahim; Saad, Maarouf; Ochoa-Luna, Cristobal; Rahman, Mohammad H
2017-07-01
In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynamics. The adaptation design is based on Time Delay Estimation (TDE). The proposed strategy does not necessitate the well-defined dynamic and kinematic models of the system robot. The updated laws are designed using Lyapunov-function to solve the adaptation problem systematically, proving the close loop stability and ensuring the convergence asymptotically of the outputs tracking errors. Experiments results show the effectiveness and feasibility of JSTDE technique to deal with the variation of the unknown nonlinear dynamics and kinematics of the exoskeleton model.
LMI-Based Generation of Feedback Laws for a Robust Model Predictive Control Algorithm
NASA Technical Reports Server (NTRS)
Acikmese, Behcet; Carson, John M., III
2007-01-01
This technical note provides a mathematical proof of Corollary 1 from the paper 'A Nonlinear Model Predictive Control Algorithm with Proven Robustness and Resolvability' that appeared in the 2006 Proceedings of the American Control Conference. The proof was omitted for brevity in the publication. The paper was based on algorithms developed for the FY2005 R&TD (Research and Technology Development) project for Small-body Guidance, Navigation, and Control [2].The framework established by the Corollary is for a robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems that guarantees the resolvability of the associated nite-horizon optimal control problem in a receding-horizon implementation. Additional details of the framework are available in the publication.
Adaptive integral dynamic surface control of a hypersonic flight vehicle
NASA Astrophysics Data System (ADS)
Aslam Butt, Waseem; Yan, Lin; Amezquita S., Kendrick
2015-07-01
In this article, non-linear adaptive dynamic surface air speed and flight path angle control designs are presented for the longitudinal dynamics of a flexible hypersonic flight vehicle. The tracking performance of the control design is enhanced by introducing a novel integral term that caters to avoiding a large initial control signal. To ensure feasibility, the design scheme incorporates magnitude and rate constraints on the actuator commands. The uncertain non-linear functions are approximated by an efficient use of the neural networks to reduce the computational load. A detailed stability analysis shows that all closed-loop signals are uniformly ultimately bounded and the ? tracking performance is guaranteed. The robustness of the design scheme is verified through numerical simulations of the flexible flight vehicle model.
Liu, Wei; Huang, Jie
2018-03-01
This paper studies the cooperative global robust output regulation problem for a class of heterogeneous second-order nonlinear uncertain multiagent systems with jointly connected switching networks. The main contributions consist of the following three aspects. First, we generalize the result of the adaptive distributed observer from undirected jointly connected switching networks to directed jointly connected switching networks. Second, by performing a new coordinate and input transformation, we convert our problem into the cooperative global robust stabilization problem of a more complex augmented system via the distributed internal model principle. Third, we solve the stabilization problem by a distributed state feedback control law. Our result is illustrated by the leader-following consensus problem for a group of Van der Pol oscillators.
Low-Complexity Polynomial Channel Estimation in Large-Scale MIMO With Arbitrary Statistics
NASA Astrophysics Data System (ADS)
Shariati, Nafiseh; Bjornson, Emil; Bengtsson, Mats; Debbah, Merouane
2014-10-01
This paper considers pilot-based channel estimation in large-scale multiple-input multiple-output (MIMO) communication systems, also known as massive MIMO, where there are hundreds of antennas at one side of the link. Motivated by the fact that computational complexity is one of the main challenges in such systems, a set of low-complexity Bayesian channel estimators, coined Polynomial ExpAnsion CHannel (PEACH) estimators, are introduced for arbitrary channel and interference statistics. While the conventional minimum mean square error (MMSE) estimator has cubic complexity in the dimension of the covariance matrices, due to an inversion operation, our proposed estimators significantly reduce this to square complexity by approximating the inverse by a L-degree matrix polynomial. The coefficients of the polynomial are optimized to minimize the mean square error (MSE) of the estimate. We show numerically that near-optimal MSEs are achieved with low polynomial degrees. We also derive the exact computational complexity of the proposed estimators, in terms of the floating-point operations (FLOPs), by which we prove that the proposed estimators outperform the conventional estimators in large-scale MIMO systems of practical dimensions while providing a reasonable MSEs. Moreover, we show that L needs not scale with the system dimensions to maintain a certain normalized MSE. By analyzing different interference scenarios, we observe that the relative MSE loss of using the low-complexity PEACH estimators is smaller in realistic scenarios with pilot contamination. On the other hand, PEACH estimators are not well suited for noise-limited scenarios with high pilot power; therefore, we also introduce the low-complexity diagonalized estimator that performs well in this regime. Finally, we ...
NASA Astrophysics Data System (ADS)
Papaioannou, S.; Kalfas, G.; Vagionas, C.; Mitsolidou, C.; Maniotis, P.; Miliou, A.; Pleros, N.
2018-01-01
Analog optical fronthaul for 5G network architectures is currently being promoted as a bandwidth- and energy-efficient technology that can sustain the data-rate, latency and energy requirements of the emerging 5G era. This paper deals with a new optical fronthaul architecture that can effectively synergize optical transceiver, optical add/drop multiplexer and optical beamforming integrated photonics towards a DSP-assisted analog fronthaul for seamless and medium-transparent 5G small-cell networks. Its main application targets include dense and Hot-Spot Area networks, promoting the deployment of mmWave massive MIMO Remote Radio Heads (RRHs) that can offer wireless data-rates ranging from 25Gbps up to 400Gbps depending on the fronthaul technology employed. Small-cell access and resource allocation is ensured via a Medium-Transparent (MT-) MAC protocol that enables the transparent communication between the Central Office and the wireless end-users or the lamp-posts via roof-top-located V-band massive MIMO RRHs. The MTMAC is analysed in detail with simulation and analytical theoretical results being in good agreement and confirming its credentials to satisfy 5G network latency requirements by guaranteeing latency values lower than 1 ms for small- to midload conditions. Its extension towards supporting optical beamforming capabilities and mmWave massive MIMO antennas is discussed, while its performance is analysed for different fiber fronthaul link lengths and different optical channel capacities. Finally, different physical layer network architectures supporting the MT-MAC scheme are presented and adapted to different 5G use case scenarios, starting from PON-overlaid fronthaul solutions and gradually moving through Spatial Division Multiplexing up to Wavelength Division Multiplexing transport as the user density increases.
The Miniaturized Moessbauer Spectrometers MIMOS II on MER: Four Years of Operation - A Summary
NASA Technical Reports Server (NTRS)
Fleischer, I.; Klingelhoefer, G.; Morris, R. V.; Rodionov, D.; Blumers, M.; Bernhardt, B.; Schroeder, C.; Ming, D. W.; Yen, A. S.; Cohen, B. A.;
2008-01-01
The two Miniaturized Moessbauer Spectrometers (MIMOS II) on board the two Mars Exploration Rovers Spirit and Opportunity have now been collecting important scientific data for more than four years. The spectrometers provide information about Fe-bearing mineral phases and determine Fe oxidation states. The total amount of targets analized exceeds 600, the total integration time exceeds 260 days for both rovers. Since landing, more than five half-lives of the Co-57 MB sources have past (intensity at the time of landing approx. 150 mCi). Current integration times are about 50 hours in order to achieve reasonable statistics as opposed to 8 hours at the beginning of the mission. In total, 13 different mineral phases were detected: Olivine, pyroxene, hematite, magnetite and nanophase ferric oxide were detected at both landing sites. At Gusev, ilmenite, goethite, a ferric sulfate phase and a yet unassigned phase (in the rock Fuzzy Smith) were detected. At Meridiani, jarosite, metallic iron in meteoritic samples (kamacite), troilite, and an unassigned ferric phase were detected. Jarosite and goethite are of special interest, as these minerals are indicators for water activity. In this abstract, an overview of Moessbauer results will be given, with a focus on data obtained since the last martian winter. The MER mission has proven that Moessbauer spectroscopy is a valuable tool for the in situ exploration of extraterrestrial bodies and for the study of Febearing samples. The experience gained through the MER mission makes MIMOS II a obvious choice for future missions to Mars and other targets. Currently, MIMOS II is on the scientific payload of two approved future missions: Phobos Grunt (Russian Space Agency; 2009) and ExoMars (European Space Agency; 2013).
Bazargan-Lari, Y; Eghtesad, M; Khoogar, A; Mohammad-Zadeh, A
2014-09-01
Despite some successful dynamic simulation of self-impact double pendulum (SIDP)-as humanoid robots legs or arms- studies, there is limited information available about the control of one leg locomotion. The main goal of this research is to improve the reliability of the mammalians leg locomotion and building more elaborated models close to the natural movements, by modeling the swing leg as a SIDP. This paper also presents the control design for a SIDP by a nonlinear model-based control method. To achieve this goal, the available data of normal human gait will be taken as the desired trajectories of the hip and knee joints. The model is characterized by the constraint that occurs at the knee joint (the lower joint of the model) in both dynamic modeling and control design. Since the system dynamics is nonlinear, the MIMO Input-Output Feedback Linearization method will be employed for control purposes. The first constraint in forward impact simulation happens at 0.5 rad where the speed of the upper link is increased to 2.5 rad/sec. and the speed of the lower link is reduced to -5 rad/sec. The subsequent constraints occur rather moderately. In the case of both backward and forward constraints simulation, the backward impact occurs at -0.5 rad and the speeds of the upper and lower links increase to 2.2 and 1.5 rad/sec., respectively. The designed controller performed suitably well and regulated the system accurately.
Large-Scale Multiantenna Multisine Wireless Power Transfer
NASA Astrophysics Data System (ADS)
Huang, Yang; Clerckx, Bruno
2017-11-01
Wireless Power Transfer (WPT) is expected to be a technology reshaping the landscape of low-power applications such as the Internet of Things, Radio Frequency identification (RFID) networks, etc. Although there has been some progress towards multi-antenna multi-sine WPT design, the large-scale design of WPT, reminiscent of massive MIMO in communications, remains an open challenge. In this paper, we derive efficient multiuser algorithms based on a generalizable optimization framework, in order to design transmit sinewaves that maximize the weighted-sum/minimum rectenna output DC voltage. The study highlights the significant effect of the nonlinearity introduced by the rectification process on the design of waveforms in multiuser systems. Interestingly, in the single-user case, the optimal spatial domain beamforming, obtained prior to the frequency domain power allocation optimization, turns out to be Maximum Ratio Transmission (MRT). In contrast, in the general weighted sum criterion maximization problem, the spatial domain beamforming optimization and the frequency domain power allocation optimization are coupled. Assuming channel hardening, low-complexity algorithms are proposed based on asymptotic analysis, to maximize the two criteria. The structure of the asymptotically optimal spatial domain precoder can be found prior to the optimization. The performance of the proposed algorithms is evaluated. Numerical results confirm the inefficiency of the linear model-based design for the single and multi-user scenarios. It is also shown that as nonlinear model-based designs, the proposed algorithms can benefit from an increasing number of sinewaves.
Zhang, Yajun; Chai, Tianyou; Wang, Hong
2011-11-01
This paper presents a novel nonlinear control strategy for a class of uncertain single-input and single-output discrete-time nonlinear systems with unstable zero-dynamics. The proposed method combines adaptive-network-based fuzzy inference system (ANFIS) with multiple models, where a linear robust controller, an ANFIS-based nonlinear controller and a switching mechanism are integrated using multiple models technique. It has been shown that the linear controller can ensure the boundedness of the input and output signals and the nonlinear controller can improve the dynamic performance of the closed loop system. Moreover, it has also been shown that the use of the switching mechanism can simultaneously guarantee the closed loop stability and improve its performance. As a result, the controller has the following three outstanding features compared with existing control strategies. First, this method relaxes the assumption of commonly-used uniform boundedness on the unmodeled dynamics and thus enhances its applicability. Second, since ANFIS is used to estimate and compensate the effect caused by the unmodeled dynamics, the convergence rate of neural network learning has been increased. Third, a "one-to-one mapping" technique is adapted to guarantee the universal approximation property of ANFIS. The proposed controller is applied to a numerical example and a pulverizing process of an alumina sintering system, respectively, where its effectiveness has been justified.
Lyapunov-based control of limit cycle oscillations in uncertain aircraft systems
NASA Astrophysics Data System (ADS)
Bialy, Brendan
Store-induced limit cycle oscillations (LCO) affect several fighter aircraft and is expected to remain an issue for next generation fighters. LCO arises from the interaction of aerodynamic and structural forces, however the primary contributor to the phenomenon is still unclear. The practical concerns regarding this phenomenon include whether or not ordnance can be safely released and the ability of the aircrew to perform mission-related tasks while in an LCO condition. The focus of this dissertation is the development of control strategies to suppress LCO in aircraft systems. The first contribution of this work (Chapter 2) is the development of a controller consisting of a continuous Robust Integral of the Sign of the Error (RISE) feedback term with a neural network (NN) feedforward term to suppress LCO behavior in an uncertain airfoil system. The second contribution of this work (Chapter 3) is the extension of the development in Chapter 2 to include actuator saturation. Suppression of LCO behavior is achieved through the implementation of an auxiliary error system that features hyperbolic functions and a saturated RISE feedback control structure. Due to the lack of clarity regarding the driving mechanism behind LCO, common practice in literature and in Chapters 2 and 3 is to replicate the symptoms of LCO by including nonlinearities in the wing structure, typically a nonlinear torsional stiffness. To improve the accuracy of the system model a partial differential equation (PDE) model of a flexible wing is derived (see Appendix F) using Hamilton's principle. Chapters 4 and 5 are focused on developing boundary control strategies for regulating the bending and twisting deformations of the derived model. The contribution of Chapter 4 is the construction of a backstepping-based boundary control strategy for a linear PDE model of an aircraft wing. The backstepping-based strategy transforms the original system to a exponentially stable system. A Lyapunov-based stability analysis is then used to show boundedness of the wing bending dynamics. A Lyapunov-based boundary control strategy for an uncertain nonlinear PDE model of an aircraft wing is developed in Chapter 5. In this chapter, a proportional feedback term is coupled with an gradient-based adaptive update law to ensure asymptotic regulation of the flexible states.
NASA Astrophysics Data System (ADS)
Taverniers, Søren; Tartakovsky, Daniel M.
2017-11-01
Predictions of the total energy deposited into a brain tumor through X-ray irradiation are notoriously error-prone. We investigate how this predictive uncertainty is affected by uncertainty in both the location of the region occupied by a dose-enhancing iodinated contrast agent and the agent's concentration. This is done within the probabilistic framework in which these uncertain parameters are modeled as random variables. We employ the stochastic collocation (SC) method to estimate statistical moments of the deposited energy in terms of statistical moments of the random inputs, and the global sensitivity analysis (GSA) to quantify the relative importance of uncertainty in these parameters on the overall predictive uncertainty. A nonlinear radiation-diffusion equation dramatically magnifies the coefficient of variation of the uncertain parameters, yielding a large coefficient of variation for the predicted energy deposition. This demonstrates that accurate prediction of the energy deposition requires a proper treatment of even small parametric uncertainty. Our analysis also reveals that SC outperforms standard Monte Carlo, but its relative efficiency decreases as the number of uncertain parameters increases from one to three. A robust GSA ameliorates this problem by reducing this number.
Design of inside cut von koch fractal UWB MIMO antenna
NASA Astrophysics Data System (ADS)
Tharani, V.; Shanmuga Priya, N.; Rajesh, A.
2017-11-01
An Inside Cut Hexagonal Von Koch fractal MIMO antenna is designed for UWB applications and its characteristics behaviour are studied. Self-comparative and space filling properties of Koch fractal structure are utilized in the antenna design which leads to the desired miniaturization and wideband characteristics. The hexagonal shaped Von Koch Fractal antenna with Defected Ground Structure (DGS) is designed on FR4 substrate with a compact size of 30mm x 20mm x 1.6mm. The antenna achieves a maximum of -44dB and -51dB at 7.1GHz for 1-element and 2-element case respectively.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gurvitis, Leonid
2009-01-01
An upper bound on the ergodic capacity of MIMO channels was introduced recently in [1]. This upper bound amounts to the maximization on the simplex of some multilinear polynomial p({lambda}{sub 1}, ..., {lambda}{sub n}) with non-negative coefficients. In general, such maximizations problems are NP-HARD. But if say, the functional log(p) is concave on the simplex and can be efficiently evaluated, then the maximization can also be done efficiently. Such log-concavity was conjectured in [1]. We give in this paper self-contained proof of the conjecture, based on the theory of H-Stable polynomials.
He, Zhixue; Li, Xiang; Luo, Ming; Hu, Rong; Li, Cai; Qiu, Ying; Fu, Songnian; Yang, Qi; Yu, Shaohua
2016-05-02
We propose and experimentally demonstrate two independent component analysis (ICA) based channel equalizers (CEs) for 6 × 6 MIMO-OFDM transmission over few-mode fiber. Compared with the conventional channel equalizer based on training symbols (TSs-CE), the proposed two ICA-based channel equalizers (ICA-CE-I and ICA-CE-II) can achieve comparable performances, while requiring much less training symbols. Consequently, the overheads for channel equalization can be substantially reduced from 13.7% to 0.4% and 2.6%, respectively. Meanwhile, we also experimentally investigate the convergence speed of the proposed ICA-based CEs.
Analysis of a Near Field MIMO Wireless Channel Using 5.6 GHz Dipole Antennas
NASA Astrophysics Data System (ADS)
Maricar, Mohamed Ismaeel; Gradoni, Gabriele; Greedy, Steve; Ivrlac, Michel T.; Nossek, Josef A.; Phang, Sendy; Creagh, Stephen C.; Tanner, Gregor; Thomas, David W. P.
2016-05-01
Understanding the impact of interference upon the performance of a multiple input multiple output (MIMO) based device is of paramount importance in ensuring a design is both resilient and robust. In this work the effect of element-element interference in the creation of multiple channels of a wireless link approaching the near-field regime is studied. The elements of the 2-antenna transmit- and receive-arrays are chosen to be identical folded dipole antennas operating at 5.6 GHz. We find that two equally strong channels can be created even if the antennas interact at sub-wavelength distances, thus confirming previous theoretical predictions.
Robust Transceiver Design for Multiuser MIMO Downlink with Channel Uncertainties
NASA Astrophysics Data System (ADS)
Miao, Wei; Li, Yunzhou; Chen, Xiang; Zhou, Shidong; Wang, Jing
This letter addresses the problem of robust transceiver design for the multiuser multiple-input-multiple-output (MIMO) downlink where the channel state information at the base station (BS) is imperfect. A stochastic approach which minimizes the expectation of the total mean square error (MSE) of the downlink conditioned on the channel estimates under a total transmit power constraint is adopted. The iterative algorithm reported in [2] is improved to handle the proposed robust optimization problem. Simulation results show that our proposed robust scheme effectively reduces the performance loss due to channel uncertainties and outperforms existing methods, especially when the channel errors of the users are different.
Multilayer Perceptron for Robust Nonlinear Interval Regression Analysis Using Genetic Algorithms
2014-01-01
On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets. PMID:25110755
Multilayer perceptron for robust nonlinear interval regression analysis using genetic algorithms.
Hu, Yi-Chung
2014-01-01
On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets.
Nonlinear dynamics analysis of the spur gear system for railway locomotive
NASA Astrophysics Data System (ADS)
Wang, Junguo; He, Guangyue; Zhang, Jie; Zhao, Yongxiang; Yao, Yuan
2017-02-01
Considering the factors such as the nonlinearity backlash, static transmission error and time-varying meshing stiffness, a three-degree-of-freedom torsional vibration model of spur gear transmission system for a typical locomotive is developed, in which the wheel/rail adhesion torque is considered as uncertain but bounded parameter. Meantime, the Ishikawa method is used for analysis and calculation of the time-varying mesh stiffness of the gear pair in meshing process. With the help of bifurcation diagrams, phase plane diagrams, Poincaré maps, time domain response diagrams and amplitude-frequency spectrums, the effects of the pinion speed and stiffness on the dynamic behavior of gear transmission system for locomotive are investigated in detail by using the numerical integration method. Numerical examples reveal various types of nonlinear phenomena and dynamic evolution mechanism involving one-period responses, multi-periodic responses, bifurcation and chaotic responses. Some research results present useful information to dynamic design and vibration control of the gear transmission system for railway locomotive.
Spatial Lattice Modulation for MIMO Systems
NASA Astrophysics Data System (ADS)
Choi, Jiwook; Nam, Yunseo; Lee, Namyoon
2018-06-01
This paper proposes spatial lattice modulation (SLM), a spatial modulation method for multipleinput-multiple-output (MIMO) systems. The key idea of SLM is to jointly exploit spatial, in-phase, and quadrature dimensions to modulate information bits into a multi-dimensional signal set that consists oflattice points. One major finding is that SLM achieves a higher spectral efficiency than the existing spatial modulation and spatial multiplexing methods for the MIMO channel under the constraint ofM-ary pulseamplitude-modulation (PAM) input signaling per dimension. In particular, it is shown that when the SLM signal set is constructed by using dense lattices, a significant signal-to-noise-ratio (SNR) gain, i.e., a nominal coding gain, is attainable compared to the existing methods. In addition, closed-form expressions for both the average mutual information and average symbol-vector-error-probability (ASVEP) of generic SLM are derived under Rayleigh-fading environments. To reduce detection complexity, a low-complexity detection method for SLM, which is referred to as lattice sphere decoding, is developed by exploiting lattice theory. Simulation results verify the accuracy of the conducted analysis and demonstrate that the proposed SLM techniques achieve higher average mutual information and lower ASVEP than do existing methods.
Multicoordination Control Strategy Performance in Hybrid Power Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pezzini, Paolo; Bryden, Kenneth M.; Tucker, David
This paper evaluates a state-space methodology of a multi-input multi-output (MIMO) control strategy using a 2 × 2 tightly coupled scenario applied to a physical gas turbine fuel cell hybrid power system. A centralized MIMO controller was preferred compared to a decentralized control approach because previous simulation studies showed that the coupling effect identified during the simultaneous control of the turbine speed and cathode airflow was better minimized. The MIMO controller was developed using a state-space dynamic model of the system that was derived using first-order transfer functions empirically obtained through experimental tests. The controller performance was evaluated in termsmore » of disturbance rejection through perturbations in the gas turbine operation, and setpoint tracking maneuver through turbine speed and cathode airflow steps. The experimental results illustrate that a multicoordination control strategy was able to mitigate the coupling of each actuator to each output during the simultaneous control of the system, and improved the overall system performance during transient conditions. On the other hand, the controller showed different performance during validation in simulation environment compared to validation in the physical facility, which will require a better dynamic modeling of the system for the implementation of future multivariable control strategies.« less
Multicoordination Control Strategy Performance in Hybrid Power Systems
Pezzini, Paolo; Bryden, Kenneth M.; Tucker, David
2018-04-11
This paper evaluates a state-space methodology of a multi-input multi-output (MIMO) control strategy using a 2 × 2 tightly coupled scenario applied to a physical gas turbine fuel cell hybrid power system. A centralized MIMO controller was preferred compared to a decentralized control approach because previous simulation studies showed that the coupling effect identified during the simultaneous control of the turbine speed and cathode airflow was better minimized. The MIMO controller was developed using a state-space dynamic model of the system that was derived using first-order transfer functions empirically obtained through experimental tests. The controller performance was evaluated in termsmore » of disturbance rejection through perturbations in the gas turbine operation, and setpoint tracking maneuver through turbine speed and cathode airflow steps. The experimental results illustrate that a multicoordination control strategy was able to mitigate the coupling of each actuator to each output during the simultaneous control of the system, and improved the overall system performance during transient conditions. On the other hand, the controller showed different performance during validation in simulation environment compared to validation in the physical facility, which will require a better dynamic modeling of the system for the implementation of future multivariable control strategies.« less
Han, Dahai; Gu, Yanjie; Zhang, Min
2017-08-10
An optimized scheme of pulse symmetrical position-orthogonal space-time block codes (PSP-OSTBC) is proposed and applied with m-pulse positions modulation (m-PPM) without the use of a complex decoding algorithm in an optical multi-input multi-output (MIMO) ultraviolet (UV) communication system. The proposed scheme breaks through the limitation of the traditional Alamouti code and is suitable for high-order m-PPM in a UV scattering channel, verified by both simulation experiments and field tests with specific parameters. The performances of 1×1, 2×1, and 2×2 PSP-OSTBC systems with 4-PPM are compared experimentally as the optimal tradeoff between modification and coding in practical application. Meanwhile, the feasibility of the proposed scheme for 8-PPM is examined by a simulation experiment as well. The results suggest that the proposed scheme makes the system insensitive to the influence of path loss with a larger channel capacity, and a higher diversity gain and coding gain with a simple decoding algorithm will be achieved by employing the orthogonality of m-PPM in an optical-MIMO-based ultraviolet scattering channel.
Adaptive limited feedback for interference alignment in MIMO interference channels.
Zhang, Yang; Zhao, Chenglin; Meng, Juan; Li, Shibao; Li, Li
2016-01-01
It is very important that the radar sensor network has autonomous capabilities such as self-managing, etc. Quite often, MIMO interference channels are applied to radar sensor networks, and for self-managing purpose, interference management in MIMO interference channels is critical. Interference alignment (IA) has the potential to dramatically improve system throughput by effectively mitigating interference in multi-user networks at high signal-to-noise (SNR). However, the implementation of IA predominantly relays on perfect and global channel state information (CSI) at all transceivers. A large amount of CSI has to be fed back to all transmitters, resulting in a proliferation of feedback bits. Thus, IA with limited feedback has been introduced to reduce the sum feedback overhead. In this paper, by exploiting the advantage of heterogeneous path loss, we first investigate the throughput of IA with limited feedback in interference channels while each user transmits multi-streams simultaneously, then we get the upper bound of sum rate in terms of the transmit power and feedback bits. Moreover, we propose a dynamic feedback scheme via bit allocation to reduce the throughput loss due to limited feedback. Simulation results demonstrate that the dynamic feedback scheme achieves better performance in terms of sum rate.
IRCI-Free MIMO-OFDM SAR Using Circularly Shifted Zadoff-Chu Sequences
NASA Astrophysics Data System (ADS)
Cao, Yun-He; Xia, Xiang-Gen
2015-05-01
Cyclic prefix (CP) based MIMO-OFDM radar has been recently proposed for distributed transmit antennas, where there is no inter-range-cell interference (IRCI). It can collect full spatial diversity and each transmitter transmits signals with the same frequency band, i.e., the range resolution is not reduced. However, it needs to transmit multiple OFDM pulses consecutively to obtain range profiles for a single swath, which may be too long in time for a reasonable swath width. In this letter, we propose a CP based MIMO-OFDM synthetic aperture radar (SAR) system, where each transmitter transmits only a single OFDM pulse to obtain range profiles for a swath and has the same frequency band, thus the range resolution is not reduced. It is IRCI free and can collect the full spatial diversity if the transmit antennas are distributed. Our main idea is to use circularly shifted Zadoff-Chu sequences as the weighting coefficients in the OFDM pulses for different transmit antennas and apply spatial filters with multiple receive antennas to divide the whole swath into multiple subswaths, and then each subswath is reconstructed/imaged using our proposed IRCI free range reconstruction method.
Li, Longsheng; Bi, Meihua; Miao, Xin; Fu, Yan; Hu, Weisheng
2018-01-22
In this paper, we firstly demonstrate an advanced arraying scheme in the TDM-based analog mobile fronthaul system to enhance the signal fidelity, in which the segment of the antenna carrier signal (AxC) with an appropriate length is served as the granularity for TDM aggregation. Without introducing extra processing, the entire system can be realized by simple DSP. The theoretical analysis is presented to verify the feasibility of this scheme, and to evaluate its effectiveness, the experiment with ~7-GHz bandwidth and 20 8 × 8 MIMO group signals are conducted. Results show that the segment-wise TDM is completely compatible with the MIMO-interleaved arraying, which is employed in an existing TDM scheme to improve the bandwidth efficiency. Moreover, compared to the existing TDM schemes, our scheme can not only satisfy the latency requirement of 5G but also significantly reduce the multiplexed signal bandwidth, hence providing higher signal fidelity in the bandwidth-limited fronthaul system. The experimental result of EVM verifies that 256-QAM is supportable using the segment-wise TDM arraying with only 250-ns latency, while with the ordinary TDM arraying, only 64-QAM is bearable.
NASA Astrophysics Data System (ADS)
Sarkar, Debdeep; Srivastava, Kumar Vaibhav
2017-02-01
In this paper, the concept of cross-correlation Green's functions (CGF) is used in conjunction with the finite difference time domain (FDTD) technique for calculation of envelope correlation coefficient (ECC) of any arbitrary MIMO antenna system over wide frequency band. Both frequency-domain (FD) and time-domain (TD) post-processing techniques are proposed for possible application with this FDTD-CGF scheme. The FDTD-CGF time-domain (FDTD-CGF-TD) scheme utilizes time-domain signal processing methods and exhibits significant reduction in ECC computation time as compared to the FDTD-CGF frequency domain (FDTD-CGF-FD) scheme, for high frequency-resolution requirements. The proposed FDTD-CGF based schemes can be applied for accurate and fast prediction of wideband ECC response, instead of the conventional scattering parameter based techniques which have several limitations. Numerical examples of the proposed FDTD-CGF techniques are provided for two-element MIMO systems involving thin-wire half-wavelength dipoles in parallel side-by-side as well as orthogonal arrangements. The results obtained from the FDTD-CGF techniques are compared with results from commercial electromagnetic solver Ansys HFSS, to verify the validity of proposed approach.
NASA Astrophysics Data System (ADS)
Xi, Songnan; Zoltowski, Michael D.
2008-04-01
Multiuser multiple-input multiple-output (MIMO) systems are considered in this paper. We continue our research on uplink transmit beamforming design for multiple users under the assumption that the full multiuser channel state information, which is the collection of the channel state information between each of the users and the base station, is known not only to the receiver but also to all the transmitters. We propose an algorithm for designing optimal beamforming weights in terms of maximizing the signal-to-interference-plus-noise ratio (SINR). Through statistical modeling, we decouple the original mathematically intractable optimization problem and achieved a closed-form solution. As in our previous work, the minimum mean-squared error (MMSE) receiver with successive interference cancellation (SIC) is adopted for multiuser detection. The proposed scheme is compared with an existing jointly optimized transceiver design, referred to as the joint transceiver in this paper, and our previously proposed eigen-beamforming algorithm. Simulation results demonstrate that our algorithm, with much less computational burden, accomplishes almost the same performance as the joint transceiver for spatially independent MIMO channel and even better performance for spatially correlated MIMO channels. And it always works better than our previously proposed eigen beamforming algorithm.
NASA Astrophysics Data System (ADS)
Truong, Bui Ngoc Minh; Nam, Doan Ngoc Chi; Ahn, Kyoung Kwan
2013-09-01
Dielectric electro-active polymer (DEAP) materials are attractive since they are low cost, lightweight and have a large deformation capability. They have no operating noise, very low electric power consumption and higher performance and efficiency than competing technologies. However, DEAP materials generally have strong hysteresis as well as uncertain and nonlinear characteristics. These disadvantages can limit the efficiency in the use of DEAP materials. To address these limitations, this research will present the combination of the Preisach model and the dynamic nonlinear autoregressive exogenous (NARX) fuzzy model-based adaptive particle swarm optimization (APSO) identification algorithm for modeling and identification of the nonlinear behavior of one typical type of DEAP actuator. Firstly, open loop input signals are applied to obtain nonlinear features and to investigate the responses of the DEAP actuator system. Then, a Preisach model can be combined with a dynamic NARX fuzzy structure to estimate the tip displacement of a DEAP actuator. To optimize all unknown parameters of the designed combination, an identification scheme based on a least squares method and an APSO algorithm is carried out. Finally, experimental validation research is carefully completed, and the effectiveness of the proposed model is evaluated by employing various input signals.
Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.
Zhang, Yanjun; Tao, Gang; Chen, Mou
2016-09-01
This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.
Wind Turbine Load Mitigation based on Multivariable Robust Control and Blade Root Sensors
NASA Astrophysics Data System (ADS)
Díaz de Corcuera, A.; Pujana-Arrese, A.; Ezquerra, J. M.; Segurola, E.; Landaluze, J.
2014-12-01
This paper presents two H∞ multivariable robust controllers based on blade root sensors' information for individual pitch angle control. The wind turbine of 5 MW defined in the Upwind European project is the reference non-linear model used in this research work, which has been modelled in the GH Bladed 4.0 software package. The main objective of these controllers is load mitigation in different components of wind turbines during power production in the above rated control zone. The first proposed multi-input multi-output (MIMO) individual pitch H" controller mitigates the wind effect on the tower side-to-side acceleration and reduces the asymmetrical loads which appear in the rotor due to its misalignment. The second individual pitch H" multivariable controller mitigates the loads on the three blades reducing the wind effect on the bending flapwise and edgewise momentums in the blades. The designed H" controllers have been validated in GH Bladed and an exhaustive analysis has been carried out to calculate fatigue load reduction on wind turbine components, as well as to analyze load mitigation in some extreme cases.
Zhu, Long; Wang, Andong; Chen, Shi; Liu, Jun; Mo, Qi; Du, Cheng; Wang, Jian
2017-10-16
Twisted light carrying orbital angular momentum (OAM) is a special kind of structured light that has a helical phase front, a phase singularity, and a doughnut intensity profile. Beyond widespread developments in manipulation, microscopy, metrology, astronomy, nonlinear and quantum optics, OAM-carrying twisted light has seen emerging application of optical communications in free space and specially designed fibers. Instead of specialty fibers, here we show the direct use of a conventional graded-index multi-mode fiber (MMF) for OAM communications. By exploiting fiber-compatible mode exciting and filtering elements, we excite the first four OAM mode groups in an MMF. We demonstrate 2.6-km MMF transmission using four data-carrying OAM mode groups (OAM 0,1 , OAM +1,1 /OAM -1,1 , OAM +2,1 , OAM +3,1 ). Moreover, we demonstrate two data-carrying OAM mode groups multiplexing transmission over the 2.6-km MMF with low-level crosstalk free of multiple-input multiple-output digital signal processing (MIMO-DSP). The demonstrations may open up new perspectives to fiber-based OAM communication/non-communication applications using already existing conventional fibers.
Harrison, W.D.; Cox, L.H.; Hock, R.; March, R.S.; Pettit, E.C.
2009-01-01
Conventional and reference-surface mass-balance data from Gulkana and Wolverine Glaciers, Alaska, USA, are used to address the questions of how rapidly these glaciers are adjusting (or 'responding') to climate, whether their responses are stable, and whether the glaciers are likely to survive in today's climate. Instability means that a glacier will eventually vanish, or at least become greatly reduced in volume, if the climate stabilizes at its present state. A simple non-linear theory of response is presented for the analysis. The response of Gulkana Glacier is characterized by a timescale of several decades, but its stability and therefore its survival in today's climate are uncertain. Wolverine seems to be responding to climate more slowly, on the timescale of one to several centuries. Its stability is also uncertain, but a slower response time would make it more susceptible to climate changes.
Orbit control of a stratospheric satellite with parameter uncertainties
NASA Astrophysics Data System (ADS)
Xu, Ming; Huo, Wei
2016-12-01
When a stratospheric satellite travels by prevailing winds in the stratosphere, its cross-track displacement needs to be controlled to keep a constant latitude orbital flight. To design the orbit control system, a 6 degree-of-freedom (DOF) model of the satellite is established based on the second Lagrangian formulation, it is proven that the input/output feedback linearization theory cannot be directly implemented for the orbit control with this model, thus three subsystem models are deduced from the 6-DOF model to develop a sequential nonlinear control strategy. The control strategy includes an adaptive controller for the balloon-tether subsystem with uncertain balloon parameters, a PD controller based on feedback linearization for the tether-sail subsystem, and a sliding mode controller for the sail-rudder subsystem with uncertain sail parameters. Simulation studies demonstrate that the proposed control strategy is robust to uncertainties and satisfies high precision requirements for the orbit flight of the satellite.
NASA Astrophysics Data System (ADS)
Xu, Kun; Xu, Guo-Qing; Zheng, Chun-Hua
2016-04-01
The wheel-rail adhesion control for regenerative braking systems of high speed electric multiple unit trains is crucial to maintaining the stability, improving the adhesion utilization, and achieving deep energy recovery. There remain technical challenges mainly because of the nonlinear, uncertain, and varying features of wheel-rail contact conditions. This research analyzes the torque transmitting behavior during regenerative braking, and proposes a novel methodology to detect the wheel-rail adhesion stability. Then, applications to the wheel slip prevention during braking are investigated, and the optimal slip ratio control scheme is proposed, which is based on a novel optimal reference generation of the slip ratio and a robust sliding mode control. The proposed methodology achieves the optimal braking performance without the wheel-rail contact information. Numerical simulation results for uncertain slippery rails verify the effectiveness of the proposed methodology.
Li, Xiao-Jian; Yang, Guang-Hong
2018-01-01
This paper is concerned with the adaptive decentralized fault-tolerant tracking control problem for a class of uncertain interconnected nonlinear systems with unknown strong interconnections. An algebraic graph theory result is introduced to address the considered interconnections. In addition, to achieve the desirable tracking performance, a neural-network-based robust adaptive decentralized fault-tolerant control (FTC) scheme is given to compensate the actuator faults and system uncertainties. Furthermore, via the Lyapunov analysis method, it is proven that all the signals of the resulting closed-loop system are semiglobally bounded, and the tracking errors of each subsystem exponentially converge to a compact set, whose radius is adjustable by choosing different controller design parameters. Finally, the effectiveness and advantages of the proposed FTC approach are illustrated with two simulated examples.
Controller Synthesis for Periodically Forced Chaotic Systems
NASA Astrophysics Data System (ADS)
Basso, Michele; Genesio, Roberto; Giovanardi, Lorenzo
Delayed feedback controllers are an appealing tool for stabilization of periodic orbits in chaotic systems. Despite their conceptual simplicity, specific and reliable design procedures are difficult to obtain, partly also because of their inherent infinite-dimensional structure. This chapter considers the use of finite dimensional linear time invariant controllers for stabilization of periodic solutions in a general class of sinusoidally forced nonlinear systems. For such controllers — which can be interpreted as rational approximations of the delayed ones — we provide a computationally attractive synthesis technique based on Linear Matrix Inequalities (LMIs), by mixing results concerning absolute stability of nonlinear systems and robustness of uncertain linear systems. The resulting controllers prove to be effective for chaos suppression in electronic circuits and systems, as shown by two different application examples.
Distributed Synchronization Control of Multiagent Systems With Unknown Nonlinearities.
Su, Shize; Lin, Zongli; Garcia, Alfredo
2016-01-01
This paper revisits the distributed adaptive control problem for synchronization of multiagent systems where the dynamics of the agents are nonlinear, nonidentical, unknown, and subject to external disturbances. Two communication topologies, represented, respectively, by a fixed strongly-connected directed graph and by a switching connected undirected graph, are considered. Under both of these communication topologies, we use distributed neural networks to approximate the uncertain dynamics. Decentralized adaptive control protocols are then constructed to solve the cooperative tracker problem, the problem of synchronization of all follower agents to a leader agent. In particular, we show that, under the proposed decentralized control protocols, the synchronization errors are ultimately bounded, and their ultimate bounds can be reduced arbitrarily by choosing the control parameter appropriately. Simulation study verifies the effectiveness of our proposed protocols.
Optimal control of nonlinear continuous-time systems in strict-feedback form.
Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani
2015-10-01
This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.
NASA Astrophysics Data System (ADS)
Yang, Jingyu; Lin, Jiahui; Liu, Yuejun; Yang, Kang; Zhou, Lanwei; Chen, Guoping
2017-08-01
It is well known that intelligent control theory has been used in many research fields, novel modeling method (DROMM) is used for flexible rectangular active vibration control, and then the validity of new model is confirmed by comparing finite element model with new model. In this paper, taking advantage of the dynamics of flexible rectangular plate, a two-loop sliding mode (TSM) MIMO approach is introduced for designing multiple-input multiple-output continuous vibration control system, which can overcome uncertainties, disturbances or unstable dynamics. An illustrative example is given in order to show the feasibility of the method. Numerical simulations and experiment confirm the effectiveness of the proposed TSM MIMO controller.
Sanad, Mohamed; Hassan, Noha
2014-01-01
A dual resonant antenna configuration is developed for multistandard multifunction mobile handsets and portable computers. Only two wideband resonant antennas can cover most of the LTE spectrums in portable communication equipment. The bandwidth that can be covered by each antenna exceeds 70% without using any matching or tuning circuits, with efficiencies that reach 80%. Thus, a dual configuration of them is capable of covering up to 39 LTE (4G) bands besides the existing 2G and 3G bands. 2×2 MIMO configurations have been also developed for the two wideband antennas with a maximum isolation and a minimum correlation coefficient between the primary and the diversity antennas.
NASA Technical Reports Server (NTRS)
Schroeder, C.; Klingelhoefer, G; Morris, R. V.; Yen, A. S.; Renz, F.; Graff, T. G.
2016-01-01
The miniaturized Moessbauer spectrometer MIMOS II is an off-the-shelf instrument with proven flight heritage. It has been successfully deployed during NASA’s Mars Exploration Rover (MER) mission and was on-board the UK-led Beagle 2 Mars lander and the Russian Phobos-Grunt sample return mission. A Moessbauer spectrometer has been suggested for ASTEX, a DLR Near-Earth Asteroid (NEA) mission study, and the potential payload to be hosted by the Asteroid Redirect Mission (ARM). Here we make the case for in situ asteroid characterization with Moessbauer spectroscopy on the ARM employing one of three available fully-qualified flight-spare Moessbauer instruments.
Linearly polarized vector modes: enabling MIMO-free mode-division multiplexing.
Wang, Lixian; Nejad, Reza Mirzaei; Corsi, Alessandro; Lin, Jiachuan; Messaddeq, Younès; Rusch, Leslie; LaRochelle, Sophie
2017-05-15
We experimentally investigate mode-division multiplexing in an elliptical ring core fiber (ERCF) that supports linearly polarized vector modes (LPV). Characterization show that the ERCF exhibits good polarization maintaining properties over eight LPV modes with effective index difference larger than 1 × 10 -4 . The ERCF further displays stable mode power and polarization extinction ratio when subjected to external perturbations. Crosstalk between the LPV modes, after propagating through 0.9 km ERCF, is below -14 dB. By using six LPV modes as independent data channels, we achieved the transmission of 32 Gbaud QPSK over 0.9 km ERCF without any multiple-input-multiple-output (MIMO) or polarization-division multiplexing (PDM) signal processing.
Improved disturbance rejection for predictor-based control of MIMO linear systems with input delay
NASA Astrophysics Data System (ADS)
Shi, Shang; Liu, Wenhui; Lu, Junwei; Chu, Yuming
2018-02-01
In this paper, we are concerned with the predictor-based control of multi-input multi-output (MIMO) linear systems with input delay and disturbances. By taking the future values of disturbances into consideration, a new improved predictive scheme is proposed. Compared with the existing predictive schemes, our proposed predictive scheme can achieve a finite-time exact state prediction for some smooth disturbances including the constant disturbances, and a better disturbance attenuation can also be achieved for a large class of other time-varying disturbances. The attenuation of mismatched disturbances for second-order linear systems with input delay is also investigated by using our proposed predictor-based controller.
Covariance Matrix Estimation for Massive MIMO
NASA Astrophysics Data System (ADS)
Upadhya, Karthik; Vorobyov, Sergiy A.
2018-04-01
We propose a novel pilot structure for covariance matrix estimation in massive multiple-input multiple-output (MIMO) systems in which each user transmits two pilot sequences, with the second pilot sequence multiplied by a random phase-shift. The covariance matrix of a particular user is obtained by computing the sample cross-correlation of the channel estimates obtained from the two pilot sequences. This approach relaxes the requirement that all the users transmit their uplink pilots over the same set of symbols. We derive expressions for the achievable rate and the mean-squared error of the covariance matrix estimate when the proposed method is used with staggered pilots. The performance of the proposed method is compared with existing methods through simulations.
40-Gb/s PDM-QPSK signal transmission over 160-m wireless distance at W-band.
Xiao, Jiangnan; Yu, Jianjun; Li, Xinying; Xu, Yuming; Zhang, Ziran; Chen, Long
2015-03-15
We experimentally demonstrate a W-band optical-wireless transmission system over 160-m wireless distance with a bit rate up to 40 Gb/s. The optical-wireless transmission system adopts optical polarization-division-multiplexing (PDM), multiple-input multiple-output (MIMO) reception and antenna polarization diversity. Using this system, we experimentally demonstrate the 2×2 MIMO wireless delivery of 20- and 40-Gb/s PDM quadrature-phase-shift-keying (PDM-QPSK) signals over 640- and 160-m wireless links, respectively. The bit-error ratios (BERs) of these transmission systems are both less than the forward-error-correction (FEC) threshold of 3.8×10-3.
Flight Test of an L(sub 1) Adaptive Controller on the NASA AirSTAR Flight Test Vehicle
NASA Technical Reports Server (NTRS)
Gregory, Irene M.; Xargay, Enric; Cao, Chengyu; Hovakimyan, Naira
2010-01-01
This paper presents results of a flight test of the L-1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The flight test was conducted on the subscale turbine powered Generic Transport Model that is an integral part of the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. The results presented are for piloted tasks performed during the flight test.
Li, Xinying; Yu, Jianjun; Dong, Ze; Zhang, Junwen; Chi, Nan; Yu, Jianguo
2013-03-01
We experimentally investigate the interference in multiple-input multiple-output (MIMO) wireless transmission by adjusting the relative locations of horn antennas (HAs) in a 100 GHz optical wireless integration system, which can deliver a 50 Gb/s polarization-division-multiplexing quadrature-phase-shift-keying signal over 80 km single-mode fiber-28 and a 2×2 MIMO wireless link. For the parallel 2×2 MIMO wireless link, each receiver HA can only get wireless power from the corresponding transmitter HA, while for the crossover ones, the receiver HA can get wireless power from two transmitter HAs. At the wireless receiver, polarization demultiplexing is realized by the constant modulus algorithm (CMA) in the digital-signal-processing part. Compared to the parallel case, wireless interference causes about 2 dB optical signal-to-noise ratio penalty at a bit-error ratio (BER) of 3.8×10(-3) for the crossover cases if similar CMA taps are employed. The increase in CMA tap length can reduce wireless interference and improve BER performance. Furthermore, more CMA taps should be adopted to overcome the severe wireless interference when two pairs of transmitter and receiver HAs have different wireless distances.
Link Correlation Based Transmit Sector Antenna Selection for Alamouti Coded OFDM
NASA Astrophysics Data System (ADS)
Ahn, Chang-Jun
In MIMO systems, the deployment of a multiple antenna technique can enhance the system performance. However, since the cost of RF transmitters is much higher than that of antennas, there is growing interest in techniques that use a larger number of antennas than the number of RF transmitters. These methods rely on selecting the optimal transmitter antennas and connecting them to the respective. In this case, feedback information (FBI) is required to select the optimal transmitter antenna elements. Since FBI is control overhead, the rate of the feedback is limited. This motivates the study of limited feedback techniques where only partial or quantized information from the receiver is conveyed back to the transmitter. However, in MIMO/OFDM systems, it is difficult to develop an effective FBI quantization method for choosing the space-time, space-frequency, or space-time-frequency processing due to the numerous subchannels. Moreover, MIMO/OFDM systems require antenna separation of 5 ∼ 10 wavelengths to keep the correlation coefficient below 0.7 to achieve a diversity gain. In this case, the base station requires a large space to set up multiple antennas. To reduce these problems, in this paper, we propose the link correlation based transmit sector antenna selection for Alamouti coded OFDM without FBI.
Antenna Allocation in MIMO Radar with Widely Separated Antennas for Multi-Target Detection
Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong
2014-01-01
In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes. PMID:25350505
Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.
Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong
2014-10-27
In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.
Chargé, Pascal; Bazzi, Oussama; Ding, Yuehua
2018-01-01
A parametric scheme for spatially correlated sparse multiple-input multiple-output (MIMO) channel path delay estimation in scattering environments is presented in this paper. In MIMO outdoor communication scenarios, channel impulse responses (CIRs) of different transmit–receive antenna pairs are often supposed to be sparse due to a few significant scatterers, and share a common sparse pattern, such that path delays are assumed to be equal for every transmit–receive antenna pair. In some existing works, an exact common support condition is exploited, where the path delays are considered equal for every transmit–receive antenna pair, meanwhile ignoring the influence of scattering. A more realistic channel model is proposed in this paper, where due to scatterers in the environment, the received signals are modeled as clusters of multi-rays around a nominal or mean time delay at different antenna elements, resulting in a non-strictly exact common support phenomenon. A method for estimating the channel mean path delays is then derived based on the subspace approach, and the tracking of the effective dimension of the signal subspace that changes due to the wireless environment. The proposed method shows an improved channel mean path delays estimation performance in comparison with the conventional estimation methods. PMID:29734797
Spatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO
NASA Astrophysics Data System (ADS)
Gao, Zhen; Dai, Linglong; Wang, Zhaocheng; Chen, Sheng
2015-12-01
This paper proposes a spatially common sparsity based adaptive channel estimation and feedback scheme for frequency division duplex based massive multi-input multi-output (MIMO) systems, which adapts training overhead and pilot design to reliably estimate and feed back the downlink channel state information (CSI) with significantly reduced overhead. Specifically, a non-orthogonal downlink pilot design is first proposed, which is very different from standard orthogonal pilots. By exploiting the spatially common sparsity of massive MIMO channels, a compressive sensing (CS) based adaptive CSI acquisition scheme is proposed, where the consumed time slot overhead only adaptively depends on the sparsity level of the channels. Additionally, a distributed sparsity adaptive matching pursuit algorithm is proposed to jointly estimate the channels of multiple subcarriers. Furthermore, by exploiting the temporal channel correlation, a closed-loop channel tracking scheme is provided, which adaptively designs the non-orthogonal pilot according to the previous channel estimation to achieve an enhanced CSI acquisition. Finally, we generalize the results of the multiple-measurement-vectors case in CS and derive the Cramer-Rao lower bound of the proposed scheme, which enlightens us to design the non-orthogonal pilot signals for the improved performance. Simulation results demonstrate that the proposed scheme outperforms its counterparts, and it is capable of approaching the performance bound.
Mohydeen, Ali; Chargé, Pascal; Wang, Yide; Bazzi, Oussama; Ding, Yuehua
2018-05-06
A parametric scheme for spatially correlated sparse multiple-input multiple-output (MIMO) channel path delay estimation in scattering environments is presented in this paper. In MIMO outdoor communication scenarios, channel impulse responses (CIRs) of different transmit⁻receive antenna pairs are often supposed to be sparse due to a few significant scatterers, and share a common sparse pattern, such that path delays are assumed to be equal for every transmit⁻receive antenna pair. In some existing works, an exact common support condition is exploited, where the path delays are considered equal for every transmit⁻receive antenna pair, meanwhile ignoring the influence of scattering. A more realistic channel model is proposed in this paper, where due to scatterers in the environment, the received signals are modeled as clusters of multi-rays around a nominal or mean time delay at different antenna elements, resulting in a non-strictly exact common support phenomenon. A method for estimating the channel mean path delays is then derived based on the subspace approach, and the tracking of the effective dimension of the signal subspace that changes due to the wireless environment. The proposed method shows an improved channel mean path delays estimation performance in comparison with the conventional estimation methods.
Morgenstern, Hai; Rafaely, Boaz; Zotter, Franz
2015-11-01
Spatial attributes of room acoustics have been widely studied using microphone and loudspeaker arrays. However, systems that combine both arrays, referred to as multiple-input multiple-output (MIMO) systems, have only been studied to a limited degree in this context. These systems can potentially provide a powerful tool for room acoustics analysis due to the ability to simultaneously control both arrays. This paper offers a theoretical framework for the spatial analysis of enclosed sound fields using a MIMO system comprising spherical loudspeaker and microphone arrays. A system transfer function is formulated in matrix form for free-field conditions, and its properties are studied using tools from linear algebra. The system is shown to have unit-rank, regardless of the array types, and its singular vectors are related to the directions of arrival and radiation at the microphone and loudspeaker arrays, respectively. The formulation is then generalized to apply to rooms, using an image source method. In this case, the rank of the system is related to the number of significant reflections. The paper ends with simulation studies, which support the developed theory, and with an extensive reflection analysis of a room impulse response, using the platform of a MIMO system.
Fuzzy control for a nonlinear mimo-liquid level problem
DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, R. E.; Mortensen, F. N.; Wantuck, P. J.
2001-01-01
Nonlinear systems are very common in the chemical process industries. Control of these systems, particularly multivariable systems, is extremely difficult. In many chemical plants, because of this difficulty, control is seldom optimal. Quite often, the best control is obtained in the manual mode using experienced operators. Liquid level control is probably one of the most common control problems in a chemical plant. Liquid level is important in heat exchanger control where heat and mass transfer rates can be controlled by the amount of liquid covering the tubes. Distillation columns, mixing tanks, and surge tanks are other examples where liquid levelmore » control is very important. The problem discussed in this paper is based on the simultaneous level control of three tanks connected in series. Each tank holds slightly less than 0.01 m{sup 3} of liquid. All three tanks are connected, Liquid is pumped into the first and the third tanks to maintain their levels. The third tank in the series drains to the system exit. The levels in the first and third tank control the level in the middle tank. The level in the middle tank affects the levels in the two end tanks. Many other chemical plant systems can be controlled in a manner similar to this three-tank system. For example, in any distillation column liquid level control problems can be represented as a total condenser with liquid level control, a reboiler with liquid level control, with the interactive column in between. The solution to the three-tank-problem can provide insight into many of the nonlinear control problems in the chemical process industries. The system was tested using the fuzzy logic controller and a proportional-integral (PI) controller, in both the setpoint tracking mode and disturbance rejection mode. The experimental results are discussed and comparisons between fuzzy controller and the standard PI controller are made.« less
Du, Guanyao; Yu, Jianjun
2016-01-01
This paper investigates the system achievable rate for the multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system with an energy harvesting (EH) relay. Firstly we propose two protocols, time switching-based decode-and-forward relaying (TSDFR) and a flexible power splitting-based DF relaying (PSDFR) protocol by considering two practical receiver architectures, to enable the simultaneous information processing and energy harvesting at the relay. In PSDFR protocol, we introduce a temporal parameter to describe the time division pattern between the two phases which makes the protocol more flexible and general. In order to explore the system performance limit, we discuss the system achievable rate theoretically and formulate two optimization problems for the proposed protocols to maximize the system achievable rate. Since the problems are non-convex and difficult to solve, we first analyze them theoretically and get some explicit results, then design an augmented Lagrangian penalty function (ALPF) based algorithm for them. Numerical results are provided to validate the accuracy of our analytical results and the effectiveness of the proposed ALPF algorithm. It is shown that, PSDFR outperforms TSDFR to achieve higher achievable rate in such a MIMO-OFDM relaying system. Besides, we also investigate the impacts of the relay location, the number of antennas and the number of subcarriers on the system performance. Specifically, it is shown that, the relay position greatly affects the system performance of both protocols, and relatively worse achievable rate is achieved when the relay is placed in the middle of the source and the destination. This is different from the MIMO-OFDM DF relaying system without EH. Moreover, the optimal factor which indicates the time division pattern between the two phases in the PSDFR protocol is always above 0.8, which means that, the common division of the total transmission time into two equal phases in previous work applying PS-based receiver is not optimal.
NASA Technical Reports Server (NTRS)
Klingelhoefer, G.; Morris, R. V.; Blumers, M; Bernhardt, B.; Graff, T.
2014-01-01
The 2010 and 2012 In-Situ Resource Utilization Analogue Test (ISRU) [1] on the Mauna Kea volcano in Hawai'i was coordinated by the Northern Centre for Advanced Technology (NORCAT) in collaboration with the Canadian Space Agency (CSA), the German Aerospace Center (DLR), and the National Aeronautics and Space Administration (NASA), through the PISCES program. Several instruments were tested as reference candidates for future analogue testing at the new field test site at the Mauna Kea volcano in Hawai'i. The fine-grained, volcanic nature of the material is a suitable lunar and martian analogue, and can be used to test excavation, site preparation, and resource utilization techniques. The 2010 location Pu'u Hiwahine, a cinder cone located below the summit of Mauna Kea (19deg45'39.29" N, 155deg28'14.56" W) at an elevation of 2800 m, provides a large number of slopes, rock avalanches, etc. to perform mobility tests, site preparation or resource prospecting. Besides hardware testing of technologies and systems related to resource identification, also in situ science measurements played a significant role in integration of ISRU and science instruments. For the advanced Mössbauer instrument MIMOS IIA, the new detector technologies and electronic components increase sensitivity and performance significantly. In combination with the high energy resolution of the SDD it is possible to perform Xray fluorescence analysis simultaneously to Mössbauer spectroscopy. In addition to the Fe-mineralogy, information on the sample's elemental composition will be gathered. The 2010 and 2012 field campaigns demonstrated that in-situ Mössbauer spectroscopy is an effective tool for both science and feedstock exploration and process monitoring. Engineering tests showed that a compact nickel metal hydride battery provided sufficient power for over 12 hr of continuous operation for the MIMOS instruments.
Miniaturised Space Payloads for Outdoor Environmental Applications
NASA Astrophysics Data System (ADS)
de Souza, P. A.
2012-12-01
The need for portable, robust and acurate sensors has increased in recent years resulting from industrial and environmental needs. This paper describes a number of applications of engineering copies of those Moessbauer spectrometers (MIMOS II) used by Mars Exploration Rovers, and the use of portable XRF spectrometers in the analysis of heavy metals in sediments. MIMOS II has been applied in the characterisation of Fe-bearing phases in airborne particles in industrialised urban centres, The results have allowed an identification of sources or air pollution in near-real-time. The results help to combine production parameters with pollution impact in the urban area. MIMOS II became a powerful tool because its constructive requirements to flight has produced a robust, power efficient, miniaturised, and light. On the limitation side, the technique takes sometime to produce a good result and the instrument requires a radioactive source to operate. MIMOS II Team has reported a new generation of this instrument incorporating a XRF spectrometer using the radioactive source to generate fluorescence emissions from sample. The author, and its research group, adapted a portable XRF spectrometer to an autonomous underwater vehicle (AUV) and conducted heavy metals survey in sediments across the Derwent Estuary in Tasmania, Australia. The AUV lands on suitable locations underwater, makes the chemical analysis and decide based on the result to move to a closer location, should high concentration of chemicals of interest be found, or to another distant location otherwise. Beyond environmental applications, these instruments were applied in archaeology and in industrial process control.oessbauer spectra recorded on airborne particles (Total Suspended Particles) collected at Ilha do Boi, VItoria, ES, Brazil. SIRO's Autonomous Underwater Vehicle carring a miniaturised XRF spectrometer for underwater chemistry. Students involved in this Project: Mr Jeremy Breen and Mr Andrew Davie. Collaborators: Dr. Greg Timms (CSIRO) and Dr. Robert Ollington (UTAS). This AUV us 1.2m long.
Long-time uncertainty propagation using generalized polynomial chaos and flow map composition
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luchtenburg, Dirk M., E-mail: dluchten@cooper.edu; Brunton, Steven L.; Rowley, Clarence W.
2014-10-01
We present an efficient and accurate method for long-time uncertainty propagation in dynamical systems. Uncertain initial conditions and parameters are both addressed. The method approximates the intermediate short-time flow maps by spectral polynomial bases, as in the generalized polynomial chaos (gPC) method, and uses flow map composition to construct the long-time flow map. In contrast to the gPC method, this approach has spectral error convergence for both short and long integration times. The short-time flow map is characterized by small stretching and folding of the associated trajectories and hence can be well represented by a relatively low-degree basis. The compositionmore » of these low-degree polynomial bases then accurately describes the uncertainty behavior for long integration times. The key to the method is that the degree of the resulting polynomial approximation increases exponentially in the number of time intervals, while the number of polynomial coefficients either remains constant (for an autonomous system) or increases linearly in the number of time intervals (for a non-autonomous system). The findings are illustrated on several numerical examples including a nonlinear ordinary differential equation (ODE) with an uncertain initial condition, a linear ODE with an uncertain model parameter, and a two-dimensional, non-autonomous double gyre flow.« less