Showing papers by "Peng Shi published in 2012"

Stability and Stabilization of Switched Linear Systems With Mode-Dependent Average Dwell Time

Abstract: In this paper, the stability and stabilization problems for a class of switched linear systems with mode-dependent average dwell time (MDADT) are investigated in both continuous-time and discrete-time contexts. The proposed switching law is more applicable in practice than the average dwell time (ADT) switching in which each mode in the underlying system has its own ADT. The stability criteria for switched systems with MDADT in nonlinear setting are firstly derived, by which the conditions for stability and stabilization for linear systems are also presented. A numerical example is given to show the validity and potential of the developed techniques.

Reliable Fuzzy Control for Active Suspension Systems With Actuator Delay and Fault

Abstract: This paper is focused on reliable fuzzy H∞ controller design for active suspension systems with actuator delay and fault. The Takagi-Sugeno (T-S) fuzzy model approach is adapted in this study with the consideration of the sprung and the unsprung mass variation, the actuator delay and fault, and other suspension performances. By the utilization of the parallel-distributed compensation scheme, a reliable fuzzy H∞ performance analysis criterion is derived for the proposed T-S fuzzy model. Then, a reliable fuzzy H∞ controller is designed such that the resulting T-S fuzzy system is reliable in the sense that it is asymptotically stable and has the prescribed H∞ performance under given constraints. The existence condition of the reliable fuzzy H∞ controller is obtained in terms of linear matrix inequalities (LMIs) Finally, a quarter- vehicle suspension model is used to demonstrate the effectiveness and potential of the proposed design techniques.

A Novel Approach to Filter Design for T–S Fuzzy Discrete-Time Systems With Time-Varying Delay

Abstract: In this paper, the problem of l2- l∞ filtering for a class of discrete-time Takagi-Sugeno (T-S) fuzzy time-varying delay systems is studied. Our attention is focused on the design of full- and reduced-order filters that guarantee the filtering error system to be asymptotically stable with a prescribed H∞ performance. Sufficient conditions for the obtained filtering error system are proposed by applying an input-output approach and a two-term approximation method, which is employed to approximate the time-varying delay. The corresponding full- and reduced-order filter design is cast into a convex optimization problem, which can be efficiently solved by standard numerical algorithms. Finally, simulation examples are provided to illustrate the effectiveness of the proposed approaches.

Observer-Based Adaptive Fuzzy Backstepping Output Feedback Control of Uncertain MIMO Pure-Feedback Nonlinear Systems

Abstract: This paper is concerned with the problem of adaptive fuzzy tracking control for a class of uncertain multiple-input-multiple-output (MIMO) pure-feedback nonlinear systems with immeasurable states. The dynamic output feedback strategy begins with a state observer. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions. The filtered signals are introduced to circumvent algebraic loop problem encountered in the implementation of the controller, and an adaptive fuzzy output feedback is obtained via a backstepping recursive design technique. It is shown that the proposed control law can guarantee that all the signals of the resulting closed-loop system are semiglobally uniformly ultimately bounded and that the observer and tracking errors converge to a small neighborhood of the origin. Simulation studies are included to illustrate the effectiveness and potentials of the proposed techniques.

Neural-Network-Based Decentralized Adaptive Output-Feedback Control for Large-Scale Stochastic Nonlinear Systems

Abstract: This paper focuses on the problem of neural-network-based decentralized adaptive output-feedback control for a class of nonlinear strict-feedback large-scale stochastic systems. The dynamic surface control technique is used to avoid the explosion of computational complexity in the backstepping design process. A novel direct adaptive neural network approximation method is proposed to approximate the unknown and desired control input signals instead of the unknown nonlinear functions. It is shown that the designed controller can guarantee all the signals in the closed-loop system to be semiglobally uniformly ultimately bounded in a mean square. Simulation results are provided to demonstrate the effectiveness of the developed control design approach.

Exponential Synchronization of Neural Networks With Discrete and Distributed Delays Under Time-Varying Sampling

Abstract: This paper investigates the problem of master-slave synchronization for neural networks with discrete and distributed delays under variable sampling with a known upper bound on the sampling intervals. An improved method is proposed, which captures the characteristic of sampled-data systems. Some delay-dependent criteria are derived to ensure the exponential stability of the error systems, and thus the master systems synchronize with the slave systems. The desired sampled-data controller can be achieved by solving a set of linear matrix inequalitys, which depend upon the maximum sampling interval and the decay rate. The obtained conditions not only have less conservatism but also have less decision variables than existing results. Simulation results are given to show the effectiveness and benefits of the proposed methods.

Reliable $H_\infty$ Control for Discrete-Time Fuzzy Systems With Infinite-Distributed Delay

Abstract: In this paper, the problem of reliable H∞ control is investigated for discrete-time Takagi-Sugeno (T-S) fuzzy systems with infinite-distributed delay and actuator faults. A discrete-time homogeneous Markov chain is used to represent the stochastic behavior of actuator faults. In terms of a stochastic fuzzy Lyapunov functional, a sufficient condition is proposed to ensure that the resultant closed-loop system is exponentially stable in the mean-square sense with an H∞ performance index. Based on the derived condition, the reliable H∞ control problem is solved, and an explicit expression of the desired controller is also given. The case of no failure in the actuator is also considered. A numerical example is given to demonstrate that our results are effective and less conservative.

Fault Estimation Observer Design for Discrete-Time Takagi–Sugeno Fuzzy Systems Based on Piecewise Lyapunov Functions

Abstract: This paper studies the problem of robust fault estimation (FE) observer design for discrete-time Takagi-Sugeno (T-S) fuzzy systems via piecewise Lyapunov functions. Both the full-order FE observer (FFEO) and the reduced-order FE observer (RFEO) are presented. The objective of this paper is to establish a novel framework of the FE observer with less conservatism. First, under the multiconstrained design, an FFEO is proposed to achieve FE for discrete-time T-S fuzzy models. Then, using a specific coordinate transformation, an RFEO is constructed, which results in a new fault estimator to realize FE using current output information. Furthermore, by the piecewise Lyapunov function approach, less conservative results on both FFEO and RFEO are derived by introducing slack variables. Simulation results are presented to illustrate the advantages of the theoretic results that are obtained in this paper.

${\cal H}_{\infty}$ Model Reduction of Takagi–Sugeno Fuzzy Stochastic Systems

Abstract: This paper is concerned with the problem of H∞ model reduction for Takagi-Sugeno (T-S) fuzzy stochastic systems. For a given mean-square stable T-S fuzzy stochastic system, our attention is focused on the construction of a reduced-order model, which not only approximates the original system well with an H∞ performance but also translates it into a linear lower dimensional system. Then, the model reduction is converted into a convex optimization problem by using a linearization procedure, and a projection approach is also presented, which casts the model reduction into a sequential minimization problem subject to linear matrix inequality constraints by employing the cone complementary linearization algorithm. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed methods.

Active fault tolerant control design for reusable launch vehicle using adaptive sliding mode technique

Abstract: In this paper, the problem of active fault tolerant control for a reusable launch vehicle (RLV) with actuator fault using both adaptive and sliding mode techniques is investigated. Firstly, the kinematic equations and dynamic equations of RLV are given, which represent the characteristics of RLV in reentry flight phase. For the dynamic model of RLV in faulty case, a fault detection scheme is proposed by designing a nonlinear fault detection observer. Then, an active fault tolerant tracking strategy for RLV attitude control systems is presented by making use of both adaptive control and sliding mode control techniques, which can guarantee the asymptotic output tracking of the closed-loop attitude control systems in spite of actuator fault. Finally, simulation results are given to demonstrate the effectiveness of the developed fault tolerant control scheme.

Robust consensus algorithm for second-order multi-agent systems with external disturbances

Abstract: This article investigates the problem of robust consensus for second-order multi-agent systems with external disturbances. Based on a non-smooth backstepping control technique, a class of novel continuous non-smooth consensus algorithms are proposed for the multi-agent network with/without communication delays. The controller design is divided into two steps. First, for the kinematic subsystem, the velocity is regarded as a virtual input and designed such that the states consensus can be achieved asymptotically. Then for the dynamic subsystem, a finite-time control law is designed such that the virtual velocity can be tracked by the real velocity in a finite time. Under the proposed control law, it is shown that if the communication topology graph contains a directed spanning tree, the states consensus can be achieved asymptotically in the absence of disturbances. In the presence of disturbances, the steady-state errors of any two agents can reach a small region around the origin. By building a relationsh...

Observer-Based Fault Estimation and Accomodation for Dynamic Systems

Abstract: ntroduction.- FAFE of continuous-time Systems.- FAFE of continuous-time Linear Systems with Time Delay.- Fast FA for Loss of Actuator Effectiveness.- FFEO Based FA for Linear Systems.- RFEO Based FA for Linear Systems.- FA for T-S Fuzzy Models Based Nonlinear Systems.- Helicopter Platform Applications.- Conclusions and Future Research Directions.

Delay-dependent exponential H ∞ filtering for discrete-time switched delay systems

Abstract: This chapter is concerned with the problems of delay-dependent exponential H ∞ filtering and model reduction for discrete-time switched delay systems under average dwell time (ADT) switching signals. First, by introducing a proper factor to construct a novel Lyapunov-Krasovskii function and using ADT approach, sufficient conditions for the solvability of exponential H ∞ filtering problem, dependent on the upper and lower bounds of the time-varying delay, are obtained in terms of linear matrix inequalities (LMIs). The second objective is to construct a reduced-order model, which ensures that the resulting error system under switching signal with ADT is exponentially stable with an H ∞ norm bound. A weighting factor α is introduced to present sufficient conditions on the existence of reduced-order model in terms of strict LMIs, which lessen the computation complexity. Two numerical examples are presented to demonstrate the effectiveness of the developed results.

Analysis and Synthesis of Delta Operator Systems

Abstract: This book is devoted to analysis and design on delta operator systems. When sampling is fast, a dynamical system will become difficult to control, which can be seen in wide real world applications. Delta operator approach is very effective to deal with fast sampling systems. Moreover, it is easy to observe and analyze the control effect with different sampling periods in delta operator systems. The framework of this book has been carefully constructed for delta operator systems to handle sliding mode control, time delays, filter design, finite frequency and networked control. These problems indeed are especially important and significant in automation and control systems design. Through the clear framework of the book, readers can easily go through the learning process on delta operator systems via a precise and comfortable learning sequence. Following this enjoyable trail, readers will come out knowing how to use delta operator approach to deal with control problems under fast sampling case. This book should be a good reference for academies, post-graduates scientists and engineers working in the field of control science and control engineering.

Passive Fault-Tolerant Control Design for near-space Hypersonic Vehicle Dynamical System

Abstract: In this paper, an observer-based passive fault-tolerant control (FTC) scheme is proposed for a near-space hypersonic vehicle (NSHV) dynamical system with both parameter uncertainty and actuator faults. The parameter uncertainty is assumed to be norm-bounded, and the possible fault of each actuator is described by a variable varying within a given interval. Our aim is to design an observer-based FTC law such that, for the admissible parameter uncertainty and possible actuator faults, the resulting closed-loop system is asymptotically stable with a given disturbance attenuation level γ. The unknown gain matrices are characterized in terms of the solutions to some linear matrix inequalities (LMIs) which can be readily solved using standard software packages. The FTC scheme presented in this study is finally demonstrated via simulation on a linearized NSHV dynamical system to illustrate the effectiveness.

Sensor fault estimation and compensation for time-delay switched systems

Abstract: In this article, the problems of sensor fault estimation and compensation approaches for time-delay switched systems are investigated based on a switched descriptor observer approach. First, a novel time-delay switched descriptor state observer is proposed to estimate both the state and sensor fault. The proposed observer technique is also extended to systems with nonlinearities. Then, based on the estimation of the sensor fault, an efficient fault-tolerant operation can be realised via sensor fault compensation. Finally, an example is given to show the efficiency of the developed techniques.

Nonlinear actuator fault estimation observer

Abstract: Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy modelBased on a Takagi-Sugeno T-S fuzzy model and an inverse system method, this paper deals with the problem of actuator fault estimation for a class of nonlinear dynamic systems. Two different estimation strategies are developed. Firstly, T-S fuzzy models are used to describe nonlinear dynamic systems with an actuator fault. Then, a robust sliding mode observer is designed based on a T-S fuzzy model, and an inverse system method is used to estimate the actuator fault. Next, the second fault estimation strategy is developed. Compared with some existing techniques, such as adaptive and sliding mode methods, the one presented in this paper is easier to be implemented in practice. Finally, two numerical examples are given to demonstrate the efficiency of the proposed techniques.

Fault Detection for Discrete-Time Switched Systems with Intermittent Measurements

Abstract: This chapter deals with the problem of FD for discrete-time switched systems with intermittent measurements. The stochastic variable is assumed to be a Bernoulli distributed white sequence appearing in measured output. Attention is focused on designing a FD filter such that, for any control input and unknown inputs, the estimation error between the residual and the fault is minimized in the sense of H ∞ norm. By employing a Lyapunov-like function and ADT technique, a sufficient condition for the existence of such a filter is exploited in terms of certain LMIs. Finally, an example is provided to illustrate the effectiveness of the proposed approach.

Stability Analysis for High Frequency Networked Control Systems

Abstract: This note generalizes the stability analysis for a high frequency networked control system. The high-frequency networked control system is described by a delta operator system with a high frequency constraint. Stability conditions are given for the high frequency delta operator system. Furthermore, by developing the generalized Kalman-Yakubovic-Popov lemma, improved stability conditions are also presented in terms of linear matrix inequalities. Some experiment results are presented to illustrate the effectiveness of the developed techniques.

Delay-dependent stability analysis for discrete-time singular Markovian jump systems with time-varying delay

Abstract: This article considers the problem of delay-dependent stability analysis for a class of discrete-time singular systems with Markovian jump and time-varying delay. The transition probabilities in Markov chain are assumed to be partially unknown. In terms of linear matrix inequality approach, the delay-dependent criteria are proposed to ensure the underlying system to be regular, causal and stochastically stable. Several numerical examples are given to demonstrate the effectiveness and less conservatism of the obtained results.

Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates

Abstract: In this paper, the problem of continuous gain-scheduled fault detection (FD) is studied for a class of stochastic nonlinear systems which possesses partially known jump rates Initially, by using gradient linearization approach, the nonlinear stochastic system is described by a series of linear jump models at some selected working points Subsequently, observer-based residual generator is constructed for each jump linear system Then, a new observer-design method is proposed for each re-constructed system to design H ∞ observers that minimize the influences of the disturbances, and to formulate a new performance index that increase the sensitivity to faults Finally, continuous gain-scheduled approach is employed to design continuous FD observers on the whole nonlinear stochastic system Simulation example is given to show the effectiveness and potential of the developed techniques

Backstepping Control in Vector Form for Stochastic Hamiltonian Systems

Abstract: In this paper, the problem of adaptive tracking for a class of stochastic Hamiltonian control systems with unknown drift and diffusion functions is considered. Some difficulties come forth—the integral chain consists of vectors, and control and tracking errors are in different channels—which are rarely considered in the existing references about stochastic nonlinear controls. To resolve these problems, an adaptive backstepping controller in vector form is designed such that the closed-loop system has a unique solution that is globally bounded in probability and the fourth moment of the tracking error converges to an arbitrarily small neighborhood of zero. As an application, the modeling and the control for spring pendulum in stochastic surroundings are researched.

Stability analysis for discrete-time Markovian jump neural networks with mixed time-delays

Abstract: The problem of delay-dependent stability analysis is investigated for discrete-time Markovian jump neural networks with mixed time-delays (both discrete and infinity-distributed time delays). The Markov chain in the underlying neural networks is finite piecewise homogeneous. A delay-dependent condition is derived for the addressed neural networks to be globally asymptotically stable. As an extension, we further consider the stability analysis problem for the same type of neural networks but with partially known transition probabilities. Two numerical examples are given to demonstrate the usefulness of the derived methods.