Idaho State University. 833 South Eighth Street. Pocatello, ID ... tions-Howard Kaufman, Izhak Bar-Kana, and Kenneth Sobel (New. York: Springer-Verlag, 1994).
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In this section, the IEEE Control Systems Society publishes reviews of books in the control field and related areas. Readers are invited to send comments on these reviews for possible publication in the Technical Notes and Correspondence section of this TRANSACTIONS The CSS does not necessarily endorse the opinions of the reviewers If you have used an interesting book for a course or as a personal reference, we encourage you to share your insights with our readers All matenal published in the TRANSACTIONS is reviewed prior to by writing a review for possible publication in the TRANSACTIONS. publication Submit a completed review or a proposal for a review to. D S. Naidu Associate Editor-Book Reviews College of Engineenng Idaho State University 833 South Eighth Street Pocatello, ID 83209
Direct Adaptive Control Algorithms: Theory and Applications-Howard Kaufman, Izhak Bar-Kana, and Kenneth Sobel (New York: Springer-Verlag, 1994). Reviewed b y Zenta Iwai. Adaptive control is an advanced technology within control engineering which is intended for systems that must operate in the presence of significant plant and environmental uncertainty. However, many practicing engineers have doubts about contemporary adaptive control. They may believe that it is unreliable, overly complex, and that it requires extensive mathematical tools for design andor implementation [I]. The aim of the authors of this book is to give an answer to such questions. The book is a self-contained compendium of adaptive control techniques that have been developed and applied by the authors for over 10 years. They, in particular, intend to show that one can improve both performance and robustness of control systems by the use of a simple adaptive control algorithm. The algorithm is called “simple” because it does not use plant parameter identifiers or observers in the control loop. Roughly speaking, the proposed control system has 2-degree of freedom (2-DOF) structure. That is, the model output matching is accomplished by a feedforward adaptive compensator based on the command generator tracker (CGT) approach [2], and the stability of the closed-loop system is realized by an adaptive output feedback controller utilizing the prior knowledge about the positive realness of the plant [3].The proposed control laws are easily implementable and do not require explicit plant parameter identification. The book has been prepared in a manner such that it will be possible for readers to actually use the algorithms even though they do not thoroughly understand the complete theory. This is the result of separate emphasis on the theory and development, implementation, and application. This should appeal to a practicing control system design engineer especially. As stated above, the reader keeps in mind that, different from other books in adaptive control, this book treats limited adaptive control algorithms originally developed by the authors. Therefore, the first chapter is devoted to a general introduction which provides the intuitive background for understanding the need and the importance
The reviewer is with the Department of Mechanical Engineering, Kumamoto University, Kumamoto 860, Japan. Publisher Item Identifier S 0018-9286(96)02992-3.
of introducing such a simple adaptive controller from both fheoretical and actual application viewpoints. As mentioned in the preceding, the basic’ adaptive controller proposed in this book consists of two controllers: a feedforward controller which attains output matching between plant and reference model and a feedback controller which assures the stability of the closed-loop system. Consider the linear time invariant (LTI) plant and LTI reference model. Then we can derive sufficient conditions for the existence of the above stated 2-DOF controllers if the plant parameters are known. To put it concretely, the feedforward controller which realizes output matching can be designed- based on CGT theory if the plant and reference model satisfy some mild conditions, and the feedback controller which stabilizes the closed-loop system can be designed if the controlled plant satisfies the almost strictly positive real (ASPR) condition. The plant is said to be ASPR if there exists a static output feedback such that the resulting closedloop transfer function is strictly positive real (SPR). Chapter 2 supplies all the basic theory of direct adaptive control algorithms. The CGT theory, almost strict positive realness of the plant and a basic understanding of stability analysis which includes Lyapunov’s stability theorem and positive real analysis, are explained in Sections 2.1-2.3. These concepts serve as the basis for the proposed adaptation procedure in case of unknown plant parameters. The basic adaptive control algorithm for output tracking, which is one of the main and fundamental results in this book, is then presented based on the CGT controller structure for ASPR plants in Sections 2.4 and 2.5. It is noted that the order of the reference model can be chosen lower than the order of the controlled plant. It follows that the structure of the basic adaptive controller can be made simple by using the low-order reference model. The basic adaptive control algorithm developed and discussed in Chapter 2 requires the plant to satisfy the ASPR condition. However, most actual plants are not ASPR. Hence this condition imposes severe restrictions on the plant in relation to the practical applicability. In Chapter 3, several modifications are shown so that the basic adaptive control algorithms can be used in a much wider class of plants. First, it is shown that a feedforward compensator can easily be used so that the resulting augmented system satisfies the ASPR constraint. In this case, the resulting controlled output is a combination of the original plant output and the feedforward augmentation. Hence, some modification might be needed if the actual output is to track
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the reference model output. To this effect, the introduction of a supplementary feedforward compensator into the reference model is discussed. A unified approach to supplementary dynamics by introducing the concept of a metasystem is also discussed. The latter approach seems to be rather general compared with the former case. But it is noted that it requires the apriori design of a proper stabilizing compensator for original plant. Chapter 4 discusses a simple modification of the basic adaptive control algorithm to account for the effect of disturbances and noise that lead to a persistent nonzero error. Chapter 5 attempts to extend the applicability of the basic adaptive controllers to include linear time varying (LTV) systems and also classes of so-called “nonlinear systems linear in control.” In this case, one,cannot use the ASPR concept anymore, but the “passivity” and “almost passivity” concepts are defined and used in LTV case. In Chapter 6, matters that demand special attentions are explained when one attempts to apply adaptive control algorithms stated in the preceding chapters to practical control system design problems. Relevant issues include compensator design to satisfy the plant parameter constraints, weight selection in the algorithm, reference model selection, digital implementation, and so on. Chapter 7 presents four case studies: control of robotic manipulators, control of large
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flexible structure, drug delivery control, and control for a relaxed static stability aircraft. They illustrate the procedures for applying the adaptive control algorithms that were discussed in the previous chapters. Although the contents of the book look rather different from traditional textbooks in adaptive control, the clarity of the author’s thinking, that the adaptive control should be a practical control system design option, is reflected in every aspect of the book. This book is indeed an up-to-date text on “practical” adaptive control theory and applications, and, as such, is an excellent reference for researchers, control engineers, and graduate students alike.
REFERENCES [1] M. K. Masten and H. E. Cohen, “An advanced showcase of adaptive controller designs,” Int. J. Adaptive Contr. Signal Processing, vol. 4, pp. 89-98, 1990. [2] J. R. Broussard and M. J. O’Brien, “Feedforward control to track the output of a forced model,” IEEE Trans. Automat. Contr., vol. AC-25, pp. 851-853, 1980. [3] A. Steinberg and M. Corless, “Output feedback stabilization of uncertain dynamical systems,” IEEE Trans. Automat. Contr., vol. AC-30, pp. 1025-1027, 1985.
