Algebraic Identification and Estimation Methods in Feedback Control Systems

<p><i>Algebraic Identification and Estimation Methods in Feedback Control Systems</i> presents a model-based algebraic approach to online parameter and state estimation in uncertain dynamic feedback control systems. This approach evades the mathematical intricacies of the traditional stochastic approach, proposing a direct model-based scheme with several easy-to-implement computational advantages. The approach can be used with continuous and discrete, linear and nonlinear, mono-variable and multi-variable systems. The estimators based on this approach are not of asymptotic nature, and do not require any statistical knowledge of the corrupting noises to achieve good performance in a noisy environment. These estimators are fast, robust to structured perturbations, and easy to combine with classical or sophisticated control laws.</p> <p>This book uses module theory, differential algebra, and operational calculus in an easy-to-understand manner and also details how to apply these in the context of feedback control systems. A wide variety of examples, including mechanical systems, power converters, electric motors, and chaotic systems, are also included to illustrate the algebraic methodology. </p> <p>Key features:</p> <ul> <li>Presents a radically new approach to online parameter and state estimation.</li> <li>Enables the reader to master the use and understand the consequences of the highly theoretical differential algebraic viewpoint in control systems theory.</li> <li>Includes examples in a variety of physical applications with experimental results.</li> <li>Covers the latest developments and applications.</li> </ul> <p><i>Algebraic Identification and Estimation Methods in Feedback Control Systems</i> is a comprehensive reference for researchers and practitioners working in the area of automatic control, and is also a useful source of information for graduate and undergraduate students.</p>