This well-respected, market-leading text discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude. Both classical and modern control methods are described and applied to illustrative examples. The strengths and limitations of each method are explored to help the reader develop solid designs with the least effort. Two new chapters have been added to the third edition offering a review of feedback control systems and an overview of digital control systems. Updated to be fully compatible with MATLAB versions 4 and 5, the text thoroughly integrates MATLAB statements and problems to offer readers a complete design picture. The new edition contains up-to-date material on state-space design and twice as many end-of-chapter problems to give students more opportunities to practice the material.

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This book is about the use of digital computers in hte real-time control of dynamic systems such as servomechanisms, chemical processes, and vehicles that mover over water, land, air or space. The material requires some understanding of controls. The special topics of discrete and sampled-data system analysis are introduced, and considerable emphasis is given to the z-transform and the close connections between the z-transform and the Laplace transform.

The book's emphasis is on designing digital controls to achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude. Both transform (classical control and state-space (modern control) methods are described and applied to illustrative examples. the transform methods emphasized are the root-locus method of evans and frequency response. The root-locus method can be used virtually unchanged for the discrete case; however, Bode's frequency response methods require modification for use with discrete systems. The state-space methods developed are the technique of pole assignment augmented by an estimator (observer) and optimal quadratic loss control. The optimal control problems use the steady-state constant-gain solutions; the results of the separateion theorem in the presence of noise are stated but not proved.

Each of these design methods-classical and modern alike - has advantages and disadvantages, strengths and limitations. It is our philosophy that a designer must understand all of them to develop a satisfactory design with the least effort.

Closely related to the mainstream of ideas for designing linear systems that result in satisfactory dynamic response are the issues of sample-rate selection, model identification, and consideration of nonlinear phonomena. Sample-rate selection is discussed in the context of evaluating the increase in a least-squared performance measures as the sample rate is reduced. The topic of model making is treated as measurment of frequency response, as well as least-sqwuared parameter estimation. Finally, every designer should be aware that all models are nonlinear and be fimiliar with the concepts of the describing functions of nonlinear systems, methods of studying stability of nonlinear systems, and the basic concepts of nonlinear design.