It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems. The emphasis is on models for both identification and control. Static and dynamic backpropagation methods for the adjustment of parameters are discussed. In the models that are introduced, multilayer and recurrent networks are interconnected in novel configurations, and hence there is a real need to study them in a unified fashion. Simulation results reveal that the identification and adaptive control schemes suggested are practically feasible. Basic concepts and definitions are introduced throughout, and theoretical questions that have to be addressed are also described. >

Identification and control of dynamical systems using neural networks

Networked control systems (NCSs) are spatially distributed systems for which the communication between sensors, actuators, and controllers is supported by a shared communication network. We review several recent results on estimation, analysis, and controller synthesis for NCSs. The results surveyed address channel limitations in terms of packet-rates, sampling, network delay, and packet dropouts. The results are presented in a tutorial fashion, comparing alternative methodologies

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A Survey of Recent Results in Networked Control Systems

By a switched system, we mean a hybrid dynamical system consisting of a family of continuous-time subsystems and a rule that orchestrates the switching between them. The article surveys developments in three basic problems regarding stability and design of switched systems. These problems are: stability for arbitrary switching sequences, stability for certain useful classes of switching sequences, and construction of stabilizing switching sequences. We also provide motivation for studying these problems by discussing how they arise in connection with various questions of interest in control theory and applications.

Basic problems in stability and design of switched systems

关于Semigroups of Linear Operators and Applications to Partial Differential Equations的两个注解

During the past several years, there have been increasing research activities in the field of stability analysis and switching stabilization for switched systems. This paper aims to briefly survey recent results in this field. First, the stability analysis for switched systems is reviewed. We focus on the stability analysis for switched linear systems under arbitrary switching, and we highlight necessary and sufficient conditions for asymptotic stability. After a brief review of the stability analysis under restricted switching and the multiple Lyapunov function theory, the switching stabilization problem is studied, and a variety of switching stabilization methods found in the literature are outlined. Then the switching stabilizability problem is investigated, that is under what condition it is possible to stabilize a switched system by properly designing switching control laws. Note that the switching stabilizability problem has been one of the most elusive problems in the switched systems literature. A necessary and sufficient condition for asymptotic stabilizability of switched linear systems is described here.

Stability and Stabilizability of Switched Linear Systems: A Survey of Recent Results

Addresses the stability analysis of a large class of nonlinear, continuous-time, finite dimensional dynamical systems which satisfy sector conditions. For such systems the authors define finite sets of extreme systems. The authors' stability results which are phrased in terms of the qualitative properties of the extreme systems provide a systematic method for the stability analysis of an important class of problems. By means of specific examples the authors demonstrate that when applicable, the present results frequently offer advantages over existing results (e.g., over existing stability results of interconnected systems). The authors show that the present results constitute robustness stability results.

Stability of interconnected systems: results without quasimonotonicity conditions

In this paper we consider retarded and neutral linear, time-delay systems with perturbations. For such systems, we present two types of sufficient conditions for asymptotic stability. One type involves norm conditions while the other type involves corner conditions. Some of our results constitute generalizations of existing results. We demonstrate the applicability of our results by means of three specific examples.

Robust stability of linear time-delay systems: retarded and neutral types

In an earlier paper, the authors introduced the idea of using higher-order spectral information for shaping the loop response in nonlinear servomechanisms. The design procedure was embodied in the multidimensional transfer functions associated with Volterra representations of the plant and its compensation. This paper extends the scope of the procedure by implementing higher-order, feedforward prefilters to excite the loop. The method is systematic in both design and realization of higher-order feedforward dynamics, and offers a potential advantage in nonlinear servomechanism performance as illustrated in a tandem motor-generator example.

On Coordinated Feedforward Excitation of Nonlinear Servomechanisms

Design and implementation of a class of neural networks

The objective of this paper is to propose a new algorithm for self-tuning control in the presence of unmodeled dynamics. It is shown (with probability one) that the resulting closed-loop system is globally stable and the mean-square tracking error is proportional to the size of unmodeled dynamics. In the absence of unmodeled dynamics, the algorithm produces the minimum-variance self-timing control. It is analytically verified that the proposed algorithm has self-stabilization property, i.e., possible occurance of instability results in mean-square bounded signals.

http://ieeexplore.ieee.org/iel5/4791299/4791300/04791344.pdf

Anthony N. Michel

Papers

Stability of interconnected systems: results without quasimonotonicity conditions

Robust stability of linear time-delay systems: retarded and neutral types

On Coordinated Feedforward Excitation of Nonlinear Servomechanisms

Design and implementation of a class of neural networks

Verification of the Self-Stabilization Mechanism in Robust Stochastic Adaptive Control using Lyapunov Function Arguments