Non-fragile decentralized H∞ controller design for uncertain linear systems

Considering the design problem of non-fragile decentralized H∞ controller with gain variations, the dynamic feedback controller by measurement feedback for uncertain linear systems is constructed and studied. The parameter uncertainties are considered to be unknown but norm bounded. The design procedures are investigated in terms of positive definite solutions to modify algebraic Riccati inequalities. Using information exchange among local controllers, the designed non-fragile decentralized H∞ controllers guarantee that the uncertain closed-loop linear systems are stable and with H∞ -norm bound on disturbance attenuation. A sufficient condition that there are such non-fragile H∞ controllers is obtained by algebraic Riccati inequalities. The approaches to solve modified algebraic Riccati inequalities are carried out preliminarily. Finally, a numerical example to show the validity of the proposed approach is given.     

Delay-dependent decentralized H∞ filtering for uncertain interconnected systems

This article considers delay dependent decentralized H∞ filtering for a class of uncertain intercon nected systems,where the uncertainties are assumed to be time varying and satisfy the norm-bounded conditions.First,combining the Lyapunov-Krasovskii functional approach and the delay integral inequality of matrices,a sufficient condition of the existence of the robust decentralized H∞ filter is derived,which makes the error systems asymptotically stable and satisfies the H∞ norm of the transfer function from noise input to error output less than the specified up-bound on the basis of the form of uncertainties.Then,the above sufficient condition is transformed to a system of easily solvable LMIs via a series of equivalent transformation.Finally,the numerical simulation shows the efficiency of the main results.     

Robust H∞ controller design for sampled-data systems with parametric uncertainties

This article investigates the problem of robust H∞ controller design for sampled-data systems with time-varying norm-bounded parameter uncertainties in the state matrices. Attention is focused on the design of a causal sampled-data controller, which guarantees the asymptotical stability of the closed-loop system and reduces the effect of the disturbance input on the controlled output to a prescribed H∞ performance bound for all admissible uncertainties. Sufficient condition for the solvability of the problem is established in terms of linear matrix inequalities (LMIs). It is shown that the desired H∞ controller can be constructed by solving certain LMIs. An illustrative example is given to demonstrate the effectiveness of the proposed method.     

Robust H∞ output feedback controller design for uncertain discrete-time switched systems via switched Lyapunov functions

The H∞ output feedback control problem for uncertain discrete-time switched systems is reasearched. A new characterization of stability and H∞ performance for the switched system under arbitrary switching is obtained by using switched Lyapunov function.Then,based on the characterization,a linear matrix inequality (LMI)approach is developed to design a switched output feedback controller which guarantees the stability and H∞ performance of the closed-loop system.A numerical example is presented to demonstrate the application of the proposed method.     

Fault-tolerant control of linear uncertain systems using H∞ robust predictive control

The robust fault-tolerant control problem of linear uncertain systems is studied. It is shown that a solution for this problem can be obtained from a H∞ robust predictive controller (RMPC) by the method of linear matrix inequality (LMI). This approach has the advantages of both H∞ control and MPC: the robustness and ability to handle constraints explicitly. The robust closed-loop stability of the linear uncertain system with input and output constraints is proven under an actuator and sensor faults condition. Finally, satisfactory results of simulation experiments verify the validity of this algorithm.     

Delay-dependent robust H∞ control for uncertain discrete time-delay fuzzy systems

The robust H∞ control problem of norm bounded uncertain discrete Takagi-Sugeno (T-S) fuzzy tems with state delay is addressed. First, by constructing an appropriate basis-dependent Lyapunov-Krasovskii function, a new delay-dependent sufficient condition on robust H∞-disturbance attenuation is presented, in which both robust stability and prescribed H∞ performance are guaranteed to be achieved. Then based on the condition, a delay-dependent robust H∞ controller design scheme is developed in term of a convex algorithm. Finally, examples are given to illustrate the effectiveness of the proposed method.     

Krein space approach to robust H∞ filtering for linear uncertain systems

A novel Krein space approach to robust H ∞ filtering for linear uncertain systems is developed. The parameter uncertainty, entering into both states and measurement equations, satisfies an energy-type constraint. Then a Krein space approach is used to tackle the robust H ∞ filtering problem. To this end, a new Krein space formal system is designed according to the original sum quadratic constraint (SQC) without introducing any nonzero factors into it and, consequently, the estimate recursion is obtained through the filter gain in Krein space. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.     

Delay-dependent robust H∞ control of convex polyhedral uncertain fuzzy systems

The robust H∞ control problem for a class of uncertain Takagi-Sugeno fuzzy systems with time-varying state delays is studied. The uncertain parameters are supposed to reside in a polytope. Based on the delay-dependent Lyapunov functional method, a new delay-dependent robust H∞ fuzzy controller, which depends on the size of the delays and the derivative of the delays, is presented in term of linear matrix inequalities (LMIs). For all admissible uncertainties and delays, the controller guarantees not only the asymptotic stability of the system but also the prescribed H∞ attenuation level. In addition, the effectiveness of the proposed design method is demonstrated by a numerical example.     

Robust reliable H∞ control for discrete-time Markov jump linear systems with actuator failures

The robust reliable H∞ control problem for discrete-time Markovian jump systems with actuator failures is studied.A more practical model of actuator failures than outage is considered.Based on the state feedback method,the resulting closed-loop systems are reliable in that they remain robust stochastically stable and satisfy a certain level of Hex disturbance attenuation not only when all actuators are operational,but also in case of some actuator failures.The solvability condition of controllers can be equivalent to a feasibility problem of coupled linear matrix inequalities (LMIs).A numerical example is also given to illustrate the design procedures and their effectiveness.     

Robust H∞ control for networked control systems

The robust H∞ control for networked control systems with both stochastic network-induced delay and data packet dropout is studied.When data are transmitted over network,the stochastic data packet dropout process can be described by a two-state Markov chain.The networked control systems with stochastic network-induced delay and data packet dropout are modeled as a discrete time Markov jump linear system with two operation modes.The sufficient condition of robust H∞ control for networked control systems stabilized by state feedback controller is presented in terms of linear matrix inequality.The state feedback controller can be constructed via the solution of a set of linear matrix inequalities.An example is given to verify the effectiveness of the method proposed.     

Receding horizon H∞ control for constrained time-delay systems

A receding horizon H∞ control algorithm is presented for linear discrete time-delay system in the presence of constrained input and disturbances. Disturbance attenuation level is optimized at each time instant, and the receding optimization problem includes several linear matrix inequality constraints. When the convex hull is applied to denote the saturating input, the algorithm has better performance. The numerical example can verify this result.     

Neural network-based H∞ filtering for nonlinear systems with time-delays

A novel H∞ design methodology for a neural network-based nonlinear filtering scheme is addressed.Firstly,neural networks are employed to approximate the nonlinearities.Next,the nonlinear dynamic system is represented by the mode-dependent linear difference inclusion (LDI).Finally,based on the LDI model,a neural network-based nonlinear filter (NNBNF) is developed to minimize the upper bound of H∞ gain index of the estimation error under some linear matrix inequality (LMI) constraints.Compared with the existing nonlinear filters,NNBNF is time-invariant and numerically tractable.The validity and applicability of the proposed approach are successfully demonstrated in an illustrative example.     

Receding horizon H∞ control for discrete-time Markovian jump linear systems

Receding horizon H∞ control scheme which can deal with both the H∞ disturbance attenuation and mean square stability is proposed for a class of discrete-time Markovian jump linear systems when minimizing a given quadratic performance criteria. First, a control law is established for jump systems based on pontryagin’s minimum principle and it can be constructed through numerical solution of iterative equations. The aim of this control strategy is to obtain an optimal control which can minimize the cost function under the worst disturbance at every sampling time. Due to the difficulty of the assurance of stability, then the above mentioned approach is improved by determining terminal weighting matrix which satisfies cost monotonicity condition. The control move which is calculated by using this type of terminal weighting matrix as boundary condition naturally guarantees the mean square stability of the closed-loop system. A sufficient condition for the existence of the terminal weighting matrix is presented in linear matrix inequality (LMI) form which can be solved efficiently by available software toolbox. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.     

Novel l_2-l_∞ controller design for LPV discrete time-delay systems

1.INTRODUCTION Manyreal worldsystemscanbemodeledaslinearpa rameter varying(LPV)systems[1],whosestate spacerepresentationmatricesarefunctionsofasetof parametersthataremeasurableinrealtime.Recent ly,manyresearchersathomeandabroadhavebeen engagedinthestabilityanalysisandgainscheduling controlofLPVsystemsextensivelyandagreatnum berofimportantresultshavebeenreportedinthelit erature(see,forinstance,Refs.[1～7]andtheref erencestherein).Mostoftheseresultsfocusoncon tinuous timecases,while…     

Robust H∞ controller design for a class of nonlinear fuzzy time-delay systems

The problem of fuzzy modeling for state and input time-delays systems with a class of nonlinear uncertainties by fuzzy T-S model is addressed. By using the linear matrix inequality (LMI) method, the problem of fuzzy robust H∞ controller design for the system is studied. Assuming that the nonlinear uncertain functions in the model considered are gain-bounded, a sufficient condition for the robustly asymptotic stability of the closed-loop system is obtained via Lyapunov stability theory. By solving the LMI, a feedback control law which guarantees the robustly asymptotic stability of the closed-loop system is constructed and the effect of the disturbance input on the controlled output is ruduced to a prescribed level.     

Neural network-based H∞ filtering for nonlinear systems with time-delays

A novel H∞ design methodology for a neural network-based nonlinear filtering scheme is addressed. Firstly, neural networks are employed to approximate the nonlinearities. Next, the nonlinear dynamic system is represented by the mode-dependent linear difference inclusion （LDI）. Finally, based on the LDI model, a neural network-based nonlinear filter （NNBNF） is developed to minimize the upper bound of H∞ gain index of the estimation error under some linear matrix inequality （LMI） constraints. Compared with the existing nonlinear filters, NNBNF is time-invariant and numerically tractable. The validity and applicability of the proposed approach are successfully demonstrated in an illustrative example.     

H∞ tracking design for a class of decentralized nonlinear systems via fuzzy adaptive observer

imulation results substantiate the effectiveness of the proposed scheme.     

H_∞ control for stochastic systems with time-delay

1.INTRODUCTION Physicalplantsareunavoidabletobeaffectedbydis turbance,time delayanduncertainty,whichmay makesomeunwantedinfluenceonthesystem’sper formanceandevenresultininstability.Howtoavoid andcounteractsuchdisadvantagesthroughfeedback designhasbeenaresearchtopicunderintensiveinves tigationrecently[1～7].Inpractice,twokindsofdisturbancesareoften encountered:stochastic(orrandom)disturbanceand deterministicdisturbance.Forthestochasticdistur bance,systemsunderconsiderationaremodeledand st…     

Robust H_∞ reliable control for uncertain singular systems with state delay

1 .INTRODUCTIONSingular systems have comprehensive practical back-ground,a great deal of results based on the theory ofregular systems have beenextendedtothe area of sin-gular systems[1 ,2]. However , in practical applica-tions ,since faults of control components often occur ,ani mportant reliability requirement for the design ofreliable systems is to guarantee the stability and basicperformance of the plant by a single controller whichcan tolerate sensor and actuator faults . Such the so-…