Analysis And Synthesis Of Two Degrees Of Freedom Control Systems


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Two-Degree-of-Freedom Control Systems


Two-Degree-of-Freedom Control Systems

Author: László Kevickzy

language: en

Publisher: Academic Press

Release Date: 2015-06-18


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This book covers the most important issues from classical and robust control, deterministic and stochastic control, system identification, and adaptive and iterative control strategies. It covers most of the known control system methodologies using a new base, the Youla parameterization (YP). This concept is introduced and extended for TDOF control loops. The Keviczky-Banyasz parameterization (KP) method developed for closed loop systems is also presented. The book is valuable for those who want to see through the jungle of available methods by using a unified approach, and for those who want to prepare computer code with a given algorithm. - Provides comprehensive coverage of the most widely used control system methodologies - The first book to use the Youla parameterization (YP) as a common base for comparison and algorithm development - Compares YP and Keviczky-Banyasz (KB) parameterization to help you write your own computer algorithms

Analysis and Synthesis of Two Degrees of Freedom Control Systems


Analysis and Synthesis of Two Degrees of Freedom Control Systems

Author: Oscar Raúl González

language: en

Publisher:

Release Date: 1987


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Nonlinear Industrial Control Systems


Nonlinear Industrial Control Systems

Author: Michael J. Grimble

language: en

Publisher: Springer Nature

Release Date: 2020-05-19


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Nonlinear Industrial Control Systems presents a range of mostly optimisation-based methods for severely nonlinear systems; it discusses feedforward and feedback control and tracking control systems design. The plant models and design algorithms are provided in a MATLAB® toolbox that enable both academic examples and industrial application studies to be repeated and evaluated, taking into account practical application and implementation problems. The text makes nonlinear control theory accessible to readers having only a background in linear systems, and concentrates on real applications of nonlinear control. It covers: different ways of modelling nonlinear systems including state space, polynomial-based, linear parameter varying, state-dependent and hybrid; design techniques for nonlinear optimal control including generalised-minimum-variance, model predictive control, quadratic-Gaussian, factorised and H∞ design methods; design philosophies that are suitable for aerospace, automotive, marine, process-control, energy systems, robotics, servo systems and manufacturing; steps in design procedures that are illustrated in design studies to define cost-functions and cope with problems such as disturbance rejection, uncertainties and integral wind-up; and baseline non-optimal control techniques such as nonlinear Smith predictors, feedback linearization, sliding mode control and nonlinear PID. Nonlinear Industrial Control Systems is valuable to engineers in industry dealing with actual nonlinear systems. It provides students with a comprehensive range of techniques and examples for solving real nonlinear control design problems.