Showing papers by "Peng Shi published in 2008"
TL;DR: Sufficient conditions for the existence of a desired filter are established in terms of linear matrix inequalities (LMIs), and the corresponding filter design is cast into a convex optimization problem which can be efficiently solved by using commercially available numerical software.
348 citations
01 Jun 2008
TL;DR: A novel adaptive neural control scheme for a class of perturbed strict-feedback nonlinear time-delay systems with unknown virtual control coefficients is presented by combining the backstepping approach and Lyapunov-Krasovskii functionals.
Abstract: This paper proposes a novel adaptive neural control scheme for a class of perturbed strict-feedback nonlinear time-delay systems with unknown virtual control coefficients. Based on the radial basis function neural network online approximation capability, an adaptive neural controller is presented by combining the backstepping approach and Lyapunov-Krasovskii functionals. The proposed controller guarantees the semiglobal boundedness of all the signals in the closed-loop system and contains minimal learning parameters. Finally, three simulation examples are given to demonstrate the effectiveness and applicability of the proposed scheme.
229 citations
TL;DR: A parameterized reduced-model is constructed and the corresponding existence conditions of such models are derived via strict LMI formulation such that the resulting model error system is exponentially stable and has a guaranteed l 2-l infin error performance.
Abstract: In this note, the model reduction problem for a class of discrete-time switched linear parameter varying systems under average dwell time switching is investigated. A parameterized reduced-model is constructed and the corresponding existence conditions of such models are derived via strict LMI formulation. The minimal average dwell time among all the subsystems and the desired reduced system are obtained such that the resulting model error system is exponentially stable and has a guaranteed l 2-l infin error performance. A numerical example is given to demonstrate the potential and effectiveness of the developed theoretical results.
202 citations
TL;DR: In this article, the authors investigated the problem of exponential H∞ filter problem for a class of discrete-time polytopic uncertain switched linear systems with average dwell time switching and derived sufficient existence conditions for the desired filter in terms of a set of linear matrix inequalities.
Abstract: In this paper, the problem of exponential H∞ filter problem for a class of discrete-time polytopic uncertain switched linear systems with average dwell time switching is investigated. The exponential stability result of the general discrete-time switched systems using a discontinuous piecewise Lyapunov function approach is first explored. Then, a new µ-dependent approach is proposed, which means the analysis or synthesis of the underlying systems is dependent on the increase degree µ of the piecewise Lyapunov function at the switching instants. A mode-dependent full-order filter is designed such that the developed filter error system is robustly exponentially stable and achieves an exponential H∞ performance. Sufficient existence conditions for the desired filter are derived and formulated in terms of a set of linear matrix inequalities, and consequently the minimal average dwell time and the corresponding filter are obtained from such conditions for a given system decay degree. A numerical example is presented to demonstrate the potential and effectiveness of the developed theoretical results.
193 citations
TL;DR: This paper is concerned with the problem of adaptive fuzzy output tracking for a class of perturbed strict-feedback nonlinear systems with time delays and unknown virtual control coefficients, and the adaptive fuzzy tracking controller is designed by using the backstepping technique and Lyapunov-Krasovskii functionals.
187 citations
TL;DR: It is proved that the bounded real lemma for discrete singular system can be described by a strict matrix inequality, which will lead to more tractable and reliable computation when applying them to design control systems.
141 citations
TL;DR: In this paper, a reduced-order switched model is constructed for a given robustly stable switched system, which has the same structural polytopic uncertainties as the original system, such that the resulting error system is robustly asymptotically stable and an H"~ error performance is guaranteed.
100 citations
01 Aug 2008
TL;DR: An improved linear-matrix-inequality-based delay-dependent exponential stability criterion is obtained without ignoring any terms in the derivative of Lyapunov-Krasovskii functional.
Abstract: This correspondence paper focuses on the problem of exponential stability for neural networks with a time-varying delay. The relationship among the time-varying delay, its upper bound, and their difference is taken into account. As a result, an improved linear-matrix-inequality-based delay-dependent exponential stability criterion is obtained without ignoring any terms in the derivative of Lyapunov-Krasovskii functional. Two numerical examples are given to demonstrate its effectiveness.
96 citations
TL;DR: In this article, the robust stability and stabilisation problems for switched linear discrete-time systems are studied, where the parameter uncertainties in the system under consideration are time-varying but norm-bounded.
Abstract: The robust stability and stabilisation problems for switched linear discrete-time systems are studied. The parameter uncertainties in the system under consideration are time-varying but norm-bounded, and the time delay is assumed to be time-varying and bounded, which covers the constant and mode-dependent constant delays as special cases. First, sufficient conditions are derived to guarantee the stability of the uncertain system. Then, a control law is designed so that the resulting closed-loop system is stable for all admissible uncertainties. A linear matrix inequality approach, together with a cone complementary linearisation algorithm, is proposed to solve the above problems. A numerical example is given to show the potential applicability of the obtained theoretic results.
89 citations
TL;DR: In this article, a new delay-dependent stability criteria is presented by using Lyapunov method, which is given in terms of linear matrix inequalities (LMIs) which can be easily solved by LMI Toolbox in Matlab.
Abstract: The problem of robust stability for a class of uncertain neutral system with time-varying delay and nonlinear uncertainties is studied in this paper. A new delay-dependent stability criteria is presented by using Lyapunov method. The criteria is given in terms of linear matrix inequalities (LMIs) which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the developed techniques.
77 citations
TL;DR: This paper deals with the problem of exponential stability for a class of discrete-time recurrent neural networks with time-varying delay by employing an improved free-weighting matrix approach and obtains a new and less conservative delay-dependent stability criterion.
Abstract: This paper deals with the problem of exponential stability for a class of discrete-time recurrent neural networks with time-varying delay by employing an improved free-weighting matrix approach. The relationship among the time-varying delay, its upper bound and their difference is taken into account. As a result, a new and less conservative delay-dependent stability criterion is obtained without ignoring any useful terms on the difference of a Lyapunov function, which is expressed in terms of linear matrix inequalities. Finally, numerical examples are given to demonstrate the effectiveness of the proposed techniques.
TL;DR: A state-feedback controller is developed that guarantees the L"2-gain of the mapping from the exogenous input noise to the regulated output is less than some prescribed value and the closed-loop system is D-stable.
TL;DR: In this paper, a robust adaptive output-feedback controller design is proposed by combining small-gain theorem, changing supply function techniques with backstepping methods, and it is shown that all the signals of the closed-loop system are uniformly bounded in biased case, and the output can be regulated to a small neighborhood of the origin in unbiased case.
Abstract: In this paper, for a class of uncertain nonlinear systems in the presence of inverse dynamics, output unmodeled dynamics and nonlinear uncertainties, a robust adaptive output-feedback controller design is proposed by combining small-gain theorem, changing supply function techniques with backstepping methods. It is shown that all the signals of the closed-loop system are uniformly bounded in biased case, and the output can be regulated to a small neighborhood of the origin in unbiased case. Furthermore, under some additional assumptions, an asymptotical result is obtained.
TL;DR: In this paper, a delay-dependent exponential stability condition is established for stochastic time-delay systems based on the delay fractioning approach, which can greatly reduce conservativeness compared with the existing results.
Abstract: The problem of concern here is the stability analysis for stochastic systems with a time delay in the state. By employing a novel Lyapunov–Krasovskii functional, a new delay-dependent exponential stability condition is established for such stochastic time-delay systems. Based on the delay fractioning approach, the developed method can greatly reduce conservativeness compared with the existing results. Numerical examples are provided to show the advantage of the proposed techniques.
TL;DR: In this article, a robust stability for uncertain neural networks with time-varying delays is proposed. But the delay-dependent and delay-derivative-dependent stability criteria are given in terms of linear matrix inequalities (LMIs).
Abstract: This paper deals with the problem of robust stability for uncertain neural networks with time-varying delays. The system possesses time-varying and norm-bounded uncertainties. The time-varying delay function in this paper is not required to be either continuously differentiable, or its derivative less than one. Based on Lyapunov–Krasovskii functional approach, new delay-dependent and delay-derivative-dependent stability criteria are presented, which are given in terms of linear matrix inequalities (LMIs). Numerical examples are given to illustrate the effectiveness and less conservativeness of the developed techniques.
TL;DR: In this paper, the problem of robust sliding mode control for a class of linear continuous time-delay systems is studied, where the parametric uncertainty considered is a modelling error type of mismatch appearing in the state.
Abstract: In this paper, the problem of robust sliding mode control for a class of linear continuous time-delay systems is studied. The parametric uncertainty considered is a modelling error type of mismatch appearing in the state. A delay-dependent sufficient condition for the existence of linear sliding surfaces is developed in terms of linear matrix inequality, based on which the corresponding reaching motion controller is designed. A numerical example is given to show the potential of the proposed techniques. Copyright © 2007 John Wiley & Sons, Ltd.
TL;DR: New stability criteria are presented in terms of linear matrix inequalities to guarantee the delayed neural networks to be robustly exponentially stable in the mean square for all admissible parameter uncertainties.
TL;DR: In this article, upper matrix bounds for the solution of the discrete algebraic Riccati equation (DARE) were derived using the matrix bound of Theorem 2.2 and Corollary 2.1.
TL;DR: Following the development of each bound, an iterative algorithm is proposed which can be used to derive tighter upper matrix bounds and numerical examples are given to demonstrate the effectiveness of the proposed results, making comparisons with existing results.
TL;DR: In this paper, robust constrained model predictive control (MPC) of systems with polytopic uncertainties is considered, and sufficient conditions for the existence of parameter-dependent Lyapunov functions are proposed in terms of linear matrix inequalities (LMIs).
Abstract: The problem of robust constrained model predictive control (MPC) of systems with polytopic uncertainties is considered in this paper. New sufficient conditions for the existence of parameter-dependent Lyapunov functions are proposed in terms of linear matrix inequalities (LMIs), which will reduce the conservativeness resulting from using a single Lyapunov function. At each sampling instant, the corresponding parameter-dependent Lyapunov function is an upper bound for a worst-case objective function, which can be minimized using the LMI convex optimization approach. Based on the solution of optimization at each sampling instant, the corresponding state feedback controller is designed, which can guarantee that the resulting closed-loop system is robustly asymptotically stable. In addition, the feedback controller will meet the specifications for systems with input or output constraints, for all admissible time-varying parameter uncertainties. Numerical examples are presented to demonstrate the effectiveness of the proposed techniques.
Journal Article•
TL;DR: Sufficient conditions are derived for robust stabilization in the sense of Lyapunov asymptotic stability and formulated in the format of linear matrix inequalities (LMIs).
Abstract: This paper addresses the problem of robust fuzzy decentralized control for a class of nonlinear large-scale systems in the presence of parametric uncertainties. The Takagi-Sugeno (T-S) fuzzy system is adopted for modeling such systems. Both fuzzy state feedback decentralized controller and fuzzy observer-based decentralized controller are developed. Sufficient conditions are derived for robust stabilization in the sense of Lyapunov asymptotic stability and formulated in the format of linear matrix inequalities (LMIs). The effectiveness of the proposed fuzzy controller is finally demonstrated through numerical simulations on a two-machine interconnected system.
TL;DR: In this article, the authors present new results pertaining to the control design of a class of linear uncertain systems with Markovian jump parameters, where an integral part of the system dynamics is a delayed state in which the time-delays are mode dependent.
Abstract: This paper presents new results pertaining to the control design of a class of linear uncertain systems with Markovian jump parameters. An integral part of the system dynamics is a delayed state in which the time-delays are mode dependent. The jumping parameters are modelled as a continuous-time, discrete-state Markov process and the uncertainties are norm-bounded. We construct an appropriate Lyapunov–Krasovskii functional and design a simultaneous ℋ2/ℋ∞ controller which minimizes a quadratic ℋ2 performance measure while satisfying a prescribed ℋ∞-norm bound on the closed-loop system. It is established that sufficient conditions for the existence of the simultaneous ℋ2/ℋ∞ controller and the associated performance upper bound are cast in the form of linear matrix inequalities. Simulation results are provided and extension to the case where the jumping rates are subject to uncertainties is presented. Copyright © 2007 John Wiley & Sons, Ltd.
TL;DR: In this article, the problem of robust H ∞ state feedback control using a delta operator approach for a class of linear fractional uncertain jump systems with time-varying delays is investigated.
Abstract: In this paper, the problem of robust H ∞ state feedback control using a delta operator approach for a class of linear fractional uncertain jump systems with time-varying delays is investigated. Based on the Lyapunov–Krasovskii functional in the delta domain, a new delay-dependent H ∞ state feedback controller which requires both robust stability and a prescribed H ∞ performance is presented in terms of linear matrix inequalities. The sampling period T appears as an explicit parameter; therefore, it is easy to observe and analyze the effect of the results with different sampling periods. Furthermore, the proposed method can unify some previous related continuous and discrete systems into the framework of delta operator systems. Numerical examples are presented to illustrate the effectiveness of the developed techniques
Journal Article•
TL;DR: In this article, new upper matrix bounds for the solution of the continuous algebraic Riccati equation (CARE) are derived and iterative algorithms are developed for obtaining sharper solution estimates.
Abstract: In this paper, new upper matrix bounds for the solution of the continuous algebraic Riccati equation (CARE) are derived. Following the derivation of each bound, iterative algorithms are developed for obtaining sharper solution estimates. These bounds improve the restriction of the results proposed in a previous paper, and are more general. The proposed bounds are always calculated if the stabilizing solution of the CARE exists. Finally, numerical examples are given to demonstrate the effectiveness of the present schemes.
TL;DR: In this article, a reduced-order switched model is constructed for a given robustly stable switched system, which has the same structural polytopic uncertainties as the original system such that the resulting error system is robustly asymptotically stable and an H1 error performance is guaranteed.
TL;DR: In this article, the problems of stochastic stability and control for a class of interconnected systems with Markovian jumping parameters were investigated using an H∞ approach, and it was shown that the problems under consideration can be solved if a set of coupled differential or algebraic Riccati equations are solvable.
Abstract: This paper investigates, by using an H∞ approach, the problems of stochastic stability and control for a class of interconnected systems with Markovian jumping parameters. Both cases of finite- and infinite-horizon are studied. It is shown that the problems under consideration can be solved if a set of coupled differential or algebraic Riccati equations are solvable.
11 Jun 2008
TL;DR: An observer-based fault estimation (FE) method is presented for a class of nonlinear networked control systems (NCSs) with Markov transfer delays and is designed to provide the estimation of unmeasurable state and the modelling uncertainty, which is used to construct a fault estimation algorithm.
Abstract: In this paper, an observer-based fault estimation (FE) method is presented for a class of nonlinear networked control systems (NCSs) with Markov transfer delays. First, the nonlinear NCSs are modelled by nonlinear discrete Takagi-Sugeno (T-S) fuzzy model with modelling uncertainty. Under some geometric conditions, the proposed nonlinear T-S model can be transformed into two subsystems with one of them having backstepping form. Then, the discrete nonlinear observer is designed to provide the estimation of unmeasurable state and the modelling uncertainty, which is used to construct a fault estimation algorithm. Finally, an example is included to show the efficiency of the proposed method.
01 Dec 2008
TL;DR: This paper presents the central finite-dimensional H∞ filters for linear systems with state and measurement delays, that are suboptimal for a given threshold g with respect to a modified Bolza-Meyer quadratic criterion including the attenuation control term with the opposite sign.
Abstract: This paper presents the central finite-dimensional H∞ filters for linear systems with state and measurement delays, that are suboptimal for a given threshold g with respect to a modified Bolza-Meyer quadratic criterion including the attenuation control term with the opposite sign. The paper first presents the central suboptimal H∞ filter for linear systems with state and measurement delays, which consists, in the general case, of an infinite set of differential equations. Then, the finite-dimensional central suboptimal H∞ filter is designed in case of linear systems with commensurable state and measurement delays, which contains a finite number of equations for any fixed filtering horizon; however, this number still grows unboundedly as time goes to infinity. To overcome that difficulty, the alternative central suboptimal H∞ filter is designed for linear systems with state and measurement delays, which is based on the alternative optimal H2 filter from [39]. Numerical simulations are conducted to verify performance of the designed central suboptimal filters for linear systems with state and measurement delays against the central suboptimal H∞ filter available for linear systems without delays.
TL;DR: In this paper, a preliminary conceptual map of the logistics cities concept has been developed which incorporates a theoretical foundation of economic development and the principles of competitiveness in the notion of trade clusters.
Abstract: This paper describes the emergence of logistics cities, which are geographical concentrations of related industries situated around one or more international trade gateways adjacent to a metropolitan area. Broadly, a logistics city comprises logistics activities and related assets combined with an integrated mix of manufacturing and assembly companies, business services, retail outlets, research and education centres, and associated government services and administration sections. This concept is currently being promoted and developed globally by several regions, and examples of these logistics cities are described in this paper. Drawing from these examples and the limited available literature, a preliminary conceptual map of the logistics cities concept has been developed which incorporates a theoretical foundation of economic development and the principles of competitiveness in the notion of trade clusters. This map has provided the basis for our further investigations and the continued development of a more detailed conceptual model that will provide a systematic knowledge base for those engaged in the development of further logistics cities. The beneficiaries of this model will be public authorities, property developers and industrial concerns, and will be used when making decisions for future logistics infrastructure, services, supporting services and related social elements.
TL;DR: In this article, lower matrix bounds are derived for the continuous algebraic Lyapunov equation (CALE) and an iterative algorithm is proposed to derive tighter matrix bounds.
Abstract: New lower matrix bounds are derived for the solution of the continuous algebraic Lyapunov equation (CALE). Following each bound derivation, an iterative algorithm is proposed to derive tighter matrix bounds. In comparison to existing results, the presented results are more concise and are always valid when the CALE has a non-negative definite solution. We finally give numerical examples to show the effectiveness of the derived bounds and make comparisons with existing results.