Systems Structure and Control

Abstract

The title of the book System, Structure and Control encompasses broad field of theory and applications of many different control approaches applied on different classes of dynamic systems. Output and state feedback control include among others robust control, optimal control or intelligent control methods such as fuzzy or neural network approach, dynamic systems are e.g. linear or nonlinear with or without time delay, fixed or uncertain, onedimensional or multidimensional. The applications cover all branches of human activities including any kind of industry, economics, biology, social sciences etc. Naturally it is not purpose of this book in few chapters neither to provide a comprehensive survey of all the above mentioned disciplines nor to give a detailed study of any of them. Nevertheless, the following 11 chapters demonstrate that even today after several decades of intensive effort of many researchers and practitioners the area of control of dynamic systems still brings new challenging problems and produces solutions of many of them.The brief outline of the volume is as follows.In chapter 1 a new method for design of state-derivative feedback control of linear systems is presented. State-derivative feedback can be considered as a generalization of classical state feedback in those applications where state derivative is easier to obtain then the direct state, e.g. in vibration attenuation control of many mechanical systems including car suspension systems, bridge cables or landing gear components. In the contribution an extension of known methods for descriptor systems with polytopic parameter uncertainty is presented.Chapter 2 is concerned with the problem of stability analysis of linear systems with time delays. Such systems naturally occur very often, e.g. in network control or remote control via satellite. Time-delayed systems are of great interest for many decades but still many questions remain unanswered or achieved results are too conservative. Here an improved time-domain delay-dependent (i.e. taking into account the magnitude of time delay) approach result for both continuous and discrete time systems is presented. The obtained result is also applied on stability analysis of large scale systems.The problem of state observation of nonlinear systems using differential neural network is addressed in chapter 3. State observation is very important in those applications where we would like to use the advantages of state feedback but the states are not accessible. Many different techniques have been already used to solve the problem. In the contribution approximation properties of a class of dynamic neural networks are used for state observation of uncertain nonlinear systems affected by bounded external perturbations.In chapter 4 sliding mode control is designed and applied on control of electric power systems. Such systems are modeled as complex large-scale systems which are difficult to control. Sliding mode control is one of the most used and effective control approaches to nonlinear systems, especiall...