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Plant control systems are subject to the undesirable influence of exogenous commands and disturbances. To track and reject these the authors have designed a feedback control system based on embedding a model of them within the controller itself - the "internal model".
From a review of the principles of internal-model-based feedback control design, this book moves on to expound recent enhancements to such designs and then to their implementation in systems operating under conditions of great uncertainty.
The case studies presented involve control systems coping with a high degree of nonlinear behaviour. The key issues addressed in each are the design of an adaptive internal model for the specific tracking task and of stabilizing control capable of steering the tracking error to zero while keeping all internal states bounded for any arbitrarily large but bounded envelope of initial data and uncertain parameters. Nested saturated controls form the basis of novel tools for asymptotic analysis and design.
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Volume 1
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Course Held at the Department for Automation and Information July 1972
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This book focuses on methods that relate, in one form or another, to the “small-gain theorem”. It is aimed at readers who are interested in learning methods for the design of feedback laws for linear and nonlinear multivariable systems in the presence of model uncertainties. With worked examples throughout, it includes both introductory material and more advanced topics.
Divided into two parts, the first covers relevant aspects of linear-systems theory, the second, nonlinear theory. In order to deepen readers’ understanding, simpler single-input–single-output systems generally precede treatment of more complex multi-input–multi-output (MIMO) systems and linear systems precede nonlinear systems. This approach is used throughout, including in the final chapters, which explain the latest advanced ideas governing the stabilization, regulation, and tracking of nonlinear MIMO systems. Two major design problems are considered, both in the presence of model uncertainties: asymptotic stabilization with a “guaranteed region of attraction” of a given equilibrium point and asymptotic rejection of the effect of exogenous (disturbance) inputs on selected regulated outputs.
Much of the introductory instructional material in this book has been developed for teaching students, while the final coverage of nonlinear MIMO systems offers readers a first coordinated treatment of completely novel results. The worked examples presented provide the instructor with ready-to-use material to help students to understand the mathematical theory.
Readers should be familiar with the fundamentals of linear-systems and control theory. This book is a valuable resource for students following postgraduate programs in systems and control, as well as engineers working on the control of robotic, mechatronic and power systems.
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