Control and Dynamic Systems: Advances in Theory and Applications, Volume 53: High Performance Systems Techniques and Applications covers the significant research works on the issues and applications of high performance control systems techniques.
This book is divided into 11 chapters and starts with an examination of the contribution of computing power with advances in theory in global optimization. The next chapters present robust solution techniques for combined filtering and parameter estimation in discrete time and the design and analysis of model reference adaptive control techniques for both continuous and discrete time multivariable plants with additive and multiplicative unmodeled dynamics. These topics are followed by discussions of the decentralized adaptive control; robust recursive estimation of states and parameters of bilinear systems; the design of robust control systems under uncertainty cases; and the techniques for state estimation for linear stationary dynamic systems that are subject to unknown time varying plant and output disturbances. Other chapters deal with the sliding control algorithm, the techniques in robust broadband beamforming, and the different categories of robust robotic controllers. The final chapter looks into the problems and issues of performance and versatility of non-linear control and the application of artificial neural networks.
This book is of great value to process, control, mechanical, and design engineers.
This book is divided into 11 chapters and starts with an examination of the contribution of computing power with advances in theory in global optimization. The next chapters present robust solution techniques for combined filtering and parameter estimation in discrete time and the design and analysis of model reference adaptive control techniques for both continuous and discrete time multivariable plants with additive and multiplicative unmodeled dynamics. These topics are followed by discussions of the decentralized adaptive control; robust recursive estimation of states and parameters of bilinear systems; the design of robust control systems under uncertainty cases; and the techniques for state estimation for linear stationary dynamic systems that are subject to unknown time varying plant and output disturbances. Other chapters deal with the sliding control algorithm, the techniques in robust broadband beamforming, and the different categories of robust robotic controllers. The final chapter looks into the problems and issues of performance and versatility of non-linear control and the application of artificial neural networks.
This book is of great value to process, control, mechanical, and design engineers.
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