An advanced and practical discussion of control systems design and applications is given in this well-written text. Working from the control systems theory developed in volume 1 [1], volume 2 examines various design techniques used in stochastic, multivariable, and adaptive control systems and their implementation using digital (stored control program) computer systems. Given its style and lack of exercises, this volume would not be appropriate for the classroom (the author notes that volume 1 is the instructional text). Rather, volume 2 would best be used as a reference for advanced study by experienced practitioners in the field who have an appropriate background in control systems theory, basic calculus, and analog signal processing.

The book is divided into five major sections. The first three sections discuss stochastic, interconnected, and multivariable control systems. This general organization presents a logical development from single-input single-output control systems, to single-input systems with feedback or feedforward adjustments, to a system with multiple interacting inputs and multiple outputs. This stepwise development of control system design provides a logical bridge from deterministic control theory to practical issues engineers confront in real-world designs.

The fourth section considers adaptive control systems, which dynamically tune their behavior in response to the environment. In such systems, adjustments are selected by identifying a model that is representative of the behavior or by attempting to have the system match the behavior of a reference model; the basic difference is whether the control parameters are calculated in advance. This material makes up a substantial portion of the text, since adaptive control systems, while difficult to design and implement, are the most useful in solving real design problems.

The final section considers the effects of instrumentation in control systems and presents several brief case studies of control systems. The use of instrumentation presents several additional problems for the control system designer. In addition to the inherent problem of noise in the system, digital instrumentation can introduce quantization sampling errors, and noise filtering may also affect the signal. Likewise, the accuracy and rate of response of the actuators implementing the commands must be considered when making control decisions. For many digital systems, these design problems can be analyzed using computer-aided design (CAD) methods, and examples show the application of CAD methods to several control system design problems.

On the whole, this text provides the reader with a thorough discussion of the advanced control system design issues. The text has been translated into several languages, and the various editions and revisions, along with its classroom use by the author, have served to make it well organized and polished. For example, a graphical outline shows how the material in each chapter of both volumes relates to signal processing and control system design and implementation. Also, a useful list of abbreviations and symbols has been included at the beginning of the text. Aside from its direct use, the list of abbreviations and symbols means that the author has used a consistent nomenclature throughout the text, which is a significant benefit when presenting a wide variety of material in a highly technical field. The only noticeable shortcoming of the text is its reference to material from the first volume. Although it is reasonable not to duplicate material presented in the first volume, the bibliographic references for both volumes should be included, since they are cited in the text.