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Treats systems in which the digital computer plays a central role.
This volume features computational tools that can be applied directly and are explained with simple calculations, plus an emphasis on control system principles and ideas. Includes worked examples, MATLAB macros, and solutions manual.
The primary objective of the book is to provide advanced undergraduate or frrst-year graduate engineering students with a self-contained presentation of the principles fundamental to the analysis, design and implementation of computer controlled systems. The material is also suitable for self-study by practicing engineers and is intended to follow a first course in either linear systems analysis or control systerns. A secondary objective of the book is to provide engineering and/or computer science audiences with the material for a junior/senior-level course in modern systems analysis. Chapters 2, 3, 4, and 5 have been designed with this purposein rnind. The emphasis in such a course is to develop the rnathernatical tools and methods suitable for the analysis and design of real-time systems such as digital filters. Thus, engineers and/or computer scientists who know how to program computers can understand the mathematics relevant to the issue of what it is they are programrning. This is especially important for those who may work in engineering and scientific environments where, for instance, programrning difference equations for real-time applications is becorning increasingly common. A background in linear algebra should be an adequate prerequisite for the systems analysis course. Chapter 1 of the book presents a brief introduction to computer controlled systems. It describes the general issues and terminology relevant to the analysis, design, and implementation of such systems.
This book helps students, researchers, and practicing engineers to understand the theoretical framework of control and system theory for discrete-time stochastic systems so that they can then apply its principles to their own stochastic control systems and to the solution of control, filtering, and realization problems for such systems. Applications of the theory in the book include the control of ships, shock absorbers, traffic and communications networks, and power systems with fluctuating power flows. The focus of the book is a stochastic control system defined for a spectrum of probability distributions including Bernoulli, finite, Poisson, beta, gamma, and Gaussian distributions. The concepts of observability and controllability of a stochastic control system are defined and characterized. Each output process considered is, with respect to conditions, represented by a stochastic system called a stochastic realization. The existence of a control law is related to stochastic controllability while the existence of a filter system is related to stochastic observability. Stochastic control with partial observations is based on the existence of a stochastic realization of the filtration of the observed process.​
This book covers a wide spectrum of systems such as linear and nonlinear multivariable systems as well as control problems such as disturbance, uncertainty and time-delays. The purpose of this book is to provide researchers and practitioners a manual for the design and application of advanced discrete-time controllers. The book presents six different control approaches depending on the type of system and control problem. The first and second approaches are based on Sliding Mode control (SMC) theory and are intended for linear systems with exogenous disturbances. The third and fourth approaches are based on adaptive control theory and are aimed at linear/nonlinear systems with periodically varying parametric uncertainty or systems with input delay. The fifth approach is based on Iterative learning control (ILC) theory and is aimed at uncertain linear/nonlinear systems with repeatable tasks and the final approach is based on fuzzy logic control (FLC) and is intended for highly uncertain systems with heuristic control knowledge. Detailed numerical examples are provided in each chapter to illustrate the design procedure for each control method. A number of practical control applications are also presented to show the problem solving process and effectiveness with the advanced discrete-time control approaches introduced in this book.
This work presents traditional methods and current techniques of incorporating the computer into closed-loop dynamic systems control, combining conventional transfer function design and state variable concepts. Digital Control Designer - an award-winning software program which permits the solution of highly complex problems - is included (3.5 IBM-compatible disk). This edition: supplies new coverage of the Ragazzini technique; describes digital filtering, including Butterworth prototype filters; and more. A solutions manual is included for instructors.
Sliding mode control is a simple and yet robust control technique, where the system states are made to confine to a selected subset. With the increasing use of computers and discrete-time samplers in controller implementation in the recent past, discrete-time systems and computer based control have become important topics. This monograph presents an output feedback sliding mode control philosophy which can be applied to almost all controllable and observable systems, while at the same time being simple enough as not to tax the computer too much. It is shown that the solution can be found in the synergy of the multirate output sampling concept and the concept of discrete-time sliding mode control.
This work covers computers and the principles in designing digital controllers. Details on computer networking, topology, communication protocol, and a brief description of DCS are provided. New topics, such as programmable logic control (PLCs), smart sensors and fieldbus, identification and design of nonlinear controllers are also covered. The text also presents fundamentals of fuzzy logic control, design of such controllers, and use of fuzzy logic in improving the performance of conventional PID controllers.