Decentralized stabilization of Markovian jump interconnected systems with unknown interconnections and measurement errors

This paper investigates the decentralized output feedback control problem for Markovian jump interconnected systems with unknown interconnections and measurement errors. Different from some existing results, the global operation modes of all subsystems are not required to be completely accessible for the decentralized control system. A decentralized dynamic output feedback controller is constructed using neighboring mode information and local outputs, where the measurement errors between actual and measured outputs are considered. Subsequently, a new design method is developed such that the resultant closed‐loop system is stochastically stable and satisfying an L_∞‐norm constraint. Sufficient conditions are formulated by linear matrix inequalities, and the controller gains are characterized in terms of the solution of a convex optimization problem. Finally, an example is given to illustrate the effectiveness of the proposed theoretical results.     

Decentralized control: Status and outlook

This paper reviews state of the art in the area of decentralized networked control systems with an emphasis on event-triggered approach. The models or agents with the dynamics of linear continuous-time time-invariant state-space systems are considered. They serve for the framework for network phenomena within two basic structures. The I/O-oriented systems as well as the interaction-oriented systems with disjoint subsystems are distinguished. The focus is laid on the presentation of recent decentralized control design and co-design methods which offer effective tools to overcome specific difficulties caused mainly by network imperfections. Such side-effects include communication constraints, variable sampling, time-varying transmission delays, packet dropouts, and quantizations. Decentralized time-triggered methods are briefly discussed. The review is deals mainly with decentralized event-triggered methods. Particularly, the stabilizing controller–observer event-based controller design as well as the decentralized state controller co-design are presented within the I/O-oriented structures of large scale complex systems. The sampling instants depend in this case only on a local information offered by the local feedback loops. Minimum sampling time conditions are discussed. Special attention is focused on interaction-oriented system architecture. Model-based approach combined with event-based state feedback controller design is presented, where the event thresholds are fully decentralized. Finally, several selected open decentralized control problems are briefly offered as recent research challenges.     

Neural Net-Based H ∞ Control for a Class of Nonlinear Systems

A novel neural net-based approach for H _∞ control design of a class of nonlinear continuous-time systems is presented. In the proposed frameworks, the nonlinear system models are approximated by multilayer neural networks. The neural networks are piecewisely interpolated to generate a linear differential inclusion models by which a linear state feedback H _∞ control law can be constructed. It is shown that finding the permissible control gain matrices can be transformed to a standard linear matrix inequality problem and solved using the available computer software. This revised version was published online in June 2006 with corrections to the Cover Date.     

Decentralized control of linear multivariable systems

This paper studies the effect of decentralized feedback on the closed-loop properties of jointly controllable, jointly observablek-channel linear systems. Channel interactions within such systems are described by means of suitably defined directed graphs. The concept of a complete system is introduced. Complete systems prove to be precisely those systems which can be made both controllable and observable through a single channel by applying nondynamic decentralized feedback to all channels. Explicit conditions are derived for determining when the closed-loop spectrum of ak-channel linear system can be freely assigned or stabilized with decentralized control.     

Observer-based networked control for continuous-time systems with random sensor delays

This paper is concerned with the networked control system design for continuous-time systems with random measurement, where the measurement channel is assumed to subject to random sensor delay. A design scheme for the observer-based output feedback controller is proposed to render the closed-loop networked system exponentially mean-square stable with H_∞ performance requirement. The technique employed is based on appropriate delay systems approach combined with a matrix variable decoupling technique. The design method is fulfilled through solving linear matrix inequalities. A numerical example is used to verify the effectiveness and the merits of the present results.     

H∞control of interconnected nonlinear sampled-data systems with parametric uncertainty

This paper studies the problem of robust control design for a class of interconnected uncertain systems under sampled measurements. The class of system under consideration is described by a state space model containing unknown cone bounded nonlinear interaction and time-varying norm-bounded parameter uncertainties in both state and output equations. Our attention is focused on the design of linear dynamic output feedback controllers using sampled measurements. We address the problem of robust H_∞ control in which both robust stability and a prescribed H_∞ performance are required to be achieved irrespective of the uncertainties and nonlinearities. The H_∞ performance measure involves both continuous-time and discrete-time signals. It has been shown that the above problems can be recast into H_∞ syntheses for related N decoupled linear sampled-data systems without parameter uncertainties and unknown nonlinearities, which can be solved in terms of Riccati differential equations with finite discrete jumps. A numerical example is given to show the potential of the proposed technique.     

On the design of multivariable PID controllers via LMI approach

In this paper, we study the design problem of multivariable PID controllers which guarantee the stability of the closed loop systems, H₂ or H_∞ performance specifications, or maximum output control requirement, respectively. Algorithms based on iterative linear matrix inequality technique are developed to find the feedback gains of PID controllers corresponding to the above mentioned four cases. A numerical example on the design of PID controllers for aircraft is provided to illustrate the effectiveness of the proposed method.     

State feedback control of continuous-time T-S fuzzy systems via switched fuzzy controllers

This paper studies the problem of state feedback control of continuous-time T-S fuzzy systems. Switched fuzzy controllers are exploited in the control design, which are switched based on the values of membership functions, and the control scheme is an extension of the parallel distributed compensation (PDC) scheme. Sufficient conditions for designing switched state feedback controllers are obtained with meeting an H_∞ norm bound requirement and quadratic D stability constraints. It is shown that the new control design method provides less conservative results than the corresponding ones via the parallel distributed compensation (PDC) scheme. A numerical example is given to illustrate the effectiveness of the proposed method.     

Robust decentralized fast-output sampling technique based power system stabilizer for a multi-machine power system

Power-system stabilizers (PSSs) are added to excitation systems to enhance the damping during low-frequency oscillations. In this paper, the design of robust decentralized PSS for four machines with a 10-bus system using fast-output sampling feedback is proposed. The nonlinear model of a multimachine system is linearized at different operating points, and 16 linear state space models are obtained. For all of these plants, a common stabilizing state feedback gain, F, is obtained. A robust decentralized fast-output sampling feedback gain which realizes this state feedback gain is obtained using LMI approach. This method does not require all the states of the system for feedback and is easily implementable. This robust decentralized fast-output sampling control is applied to a nonlinear plant model of several machines at different operating (equilibrium) points. This method yields encouraging results for the design of power-system stabilizers.     

参数不确定广义大系统的保性能分散控制

对一类范数有界时不变参数不确定的连续广义大系统和一个二次型性能指标,研究了其保性能分散控制问题.目的是设计一状态反馈分散控制器,使得对所有容许的不确定性,闭环系统不仅是鲁棒稳定的,而且性能指标有一上界.应用线性矩阵不等式方法,给出了一个用线性矩阵不等式表达的保性能分散控制器存在的充分条件;在此条件可解时,给出了保性能分散控制律的表达式.最后,举例说明了该方法的应用.     

时变不确定性关联系统的分散鲁棒稳定控制器设计

对一类满足匹配条件的时变不确定性关联大系统,给出了其可分散状态反馈镇定的充分条件即一组线性矩不等式（ＬＭＩ）有解,在此基础上,通过求解一凸优化问题,指出了具有较小反馈益的分散稳定化状态反馈控制律的设计方法,文中的仿真示例说明了该方法的有铲笥和优越性。     

Controllability under decentralized information structure

In this paper, the controllability under decentralized information structure is studied for linear continuous-time systems. It is defined as follows. A system is controllable under the decentralized information structure if there exists a decentralized control law which transfers any unknown initial state to the origin in a finite time interval Necessary and sufficient conditions of the controllability under the decentralized information structure are given. It is also shown that the controllability under the decentralized information structure is a necessary condition of the pole-assignability with a local dynamic feedback control law.     

2 guaranteed cost control for uncertain continuous-time linear systems

This paper proposes a solution to the ₂ guaranteed cost control problem for uncertain, continuous-time linear systems. It consists of the determination of a constant state feedback stabilizing matrix gain and a ₂-norm upper bound, valid for all feasible models. The uncertainties are only assumed to be convex-bounded, a concept which generalizes the important case of interval matrices uncertainties. The results follow from a new parameterization of all stabilizing gains over a convex set. As an additional property, the above mentioned ₂-norm upper bound reduces to the minimum ₂ cost in case of precisely known linear systems.     

Resilient decentralized stabilization of interconnected time‐delay systems with polytopic uncertainties

Decentralized delay‐dependent local stability and resilient feedback stabilization methods are developed for a class of linear interconnected continuous‐time systems. The subsystems are time‐delay plants which are subjected to convex‐bounded parametric uncertainties and additive feedback gain perturbations while allowing time‐varying delays to occur within the local subsystems and across the interconnections. The delay‐dependent local stability conditions are established at the subsystem level through the construction of appropriate Lyapunov–Krasovskii functional. We characterize decentralized linear matrix inequalities (LMIs)‐based delay‐dependent stability conditions by deploying an injection procedure such that every local subsystem is delay‐dependent robustly asymptotically stable with an γ‐level ??₂‐gain. Resilient decentralized state‐feedback stabilization schemes are designed, which takes into account additive gain perturbations such that the family of closed‐loop feedback subsystems enjoys the delay‐dependent asymptotic stability with a prescribed γ‐level ??₂‐gain for each subsystem. The decentralized feedback gains are determined by convex optimization over LMIs. All the developed results are tested on representative examples. Copyright © 2010 John Wiley & Sons, Ltd.     

Sparse structured non-fragile H ∞ controller design for linear systems

This paper presents a study on the problem of designing non-fragile H _∞ controllers with sparse structures for linear continuous-time systems. A new algorithm is proposed to define and further design sparse structured controllers. Firstly, sparse structures are specified from a given fully parameterized H _∞ controller. Then, a three-step design procedure for non-fragile dynamic output feedback H _∞ controllers with the sparse structures is provided. The resulting designs guarantee that the closed-loop system is asymptotically stable and the H _∞ performance from the disturbance to the regulated output is less than a prescribed level. A numerical example is given to illustrate the design methods.     

Decentralized adaptive backstepping stabilization of interconnected systems with dynamic input and output interactions

So far there is still no result available for backstepping based decentralized adaptive stabilization of unknown systems with interactions directly depending on subsystem inputs, even though such interactions commonly exist in practice. In this paper, we provide a solution to this problem by considering both input and output dynamic interactions. To clearly illustrate our approaches, we will start with linear systems and then extend the results to nonlinear systems. Each local controller, designed simply based on the model of each subsystem by using the standard adaptive backstepping technique without any modification, only employs local information to generate control signals. It is shown that the designed decentralized adaptive backstepping controllers can globally stabilize the overall interconnected system asymptotically. The L₂ and L_∞ norms of the system outputs are also established as functions of design parameters. This implies that the transient system performance can be adjusted by choosing suitable design parameters.     

Control of linear systems subjected to exogenous disturbances: Combined feedback

A new approach is proposed to the rejection of bounded exogenous disturbances in linear control systems via use of the so-called combined feedback of the form u = Kx + K₁w. Along with the static linear state feedback, this control law contains a linear feedback from the vector of disturbances (or some of its components) whose instantaneous values are assumed to be available. The control design procedure is based on the linear matrix inequality technique; it is characterized by simplicity and ease of implementation and reduces to solving convex optimization problems. The combined feedback design is also performed in the sparse formulation, which can be thought of as a desire to reduce the control resource required to handle the system.     

Decentralized H∞ control for large-scale interconnected nonlinear time-delay systems via LMI approach

In this paper, the problem of H_∞ control of nonlinear large-scale systems with interval time-varying delays in interconnection is considered. The time delays are assumed to be any continuous functions belonging to a given interval involved in both the state and observation output. By constructing a set of new Lyapunov–Krasovskii functionals, which are mainly based on the information of the lower and upper delay bounds, a new delay-dependent sufficient condition for the existence of decentralized H_∞ control is established in terms of linear matrix inequalities (LMIs). The approach is applied to decentralized H_∞ control of uncertain linear systems with interval time-varying delay. Numerical examples are given to show the effectiveness of the obtained results.     

Worst case control of uncertain jumping systems with multi-state and input delay information

In this paper, the problem of worst case (also called H_∞) Control for a class of uncertain systems with Markovian jump parameters and multiple delays in the state and input is investigated. The jumping parameters are modelled as a continuous-time, discrete-state Markov process and the parametric uncertainties are assumed to be real, time-varying and norm-bounded that appear in the state, input and delayed-state matrices. The time-delay factors are unknowns and time-varying with known bounds. Complete results for instantaneous and delayed state feedback control designs are developed which guarantee the weak-delay dependent stochastic stability with a prescribed H_∞-performance. The solutions are provided in terms of a finite set of coupled linear matrix inequalities (LMIs). Application of the developed theory to a typical example has been presented.