front cover of Analysis and Design of Reset Control Systems
Analysis and Design of Reset Control Systems
Yuqian Guo
The Institution of Engineering and Technology, 2016
Reset control is concerned with how to reset a system when it is disturbed to overcome the inherent limitations of linear feedback control and to improve robustness. It has found applications in many practical systems including flexible mechanical systems, tapespeed control systems and high precision positioning systems.
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Essentials of Non-linear Control Theory
J.R. Leigh
The Institution of Engineering and Technology, 1983
The book is concerned with understanding the structure of nonlinear dynamic systems within a control engineering context After a discussion of theoretical foundations, the development moves to specific techniques (describing function method, phase plane portrait, linearisation methods). The treatment then becomes oriented to qualitative analysis and maintains this emphasis to the end of the book. The broad aim is to develop methods that will allow the topology of system behaviour to be visualised. The main tools are Lyapunov methods, extending to include recent work on system decomposition. A bibliography lists both earlier seminal and recent literature to allow the reader to follow up particular aspects.
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Frequency-Domain Control Design for High-Performance Systems
John O'Brien
The Institution of Engineering and Technology, 2012
Frequency-Domain Control Design for High-Performance Systems serves as a practical guide for the control engineer, and attempts to bridge the gap between industrial and academic control theory. Frequency-domain techniques rooted in classical control theory are presented with new approaches in nonlinear compensation that result in robust, high-performance closed-loop systems. Illustrative examples using data from actual control designs are included.
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The Inverted Pendulum in Control Theory and Robotics
From theory to new innovations
Olfa Boubaker
The Institution of Engineering and Technology, 2018
The inverted pendulum is a classic problem in dynamics and control theory and is widely used as a benchmark for testing control algorithms. It is also an area of active study, with many new innovations and applications - for example the problem is solved in the technology of the Segway, a self-balancing transportation device.
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Nonlinear and Adaptive Control Systems
Zhengtao Ding
The Institution of Engineering and Technology, 2013
An adaptive system for linear systems with unknown parameters is a nonlinear system. The analysis of such adaptive systems requires similar techniques to analyse nonlinear systems. Therefore it is natural to treat adaptive control as a part of nonlinear control systems. Nonlinear and Adaptive Control Systems treats nonlinear control and adaptive controlin a unified framework, presenting the major results at a moderate mathematical level, suitable for MSc students and engineers with undergraduate degrees. Topics covered include introduction to nonlinear systems; state space models; describing functions forcommon nonlinear components; stability theory; feedback linearization; adaptive control; nonlinear observer design; backstepping design; disturbance rejection and output regulation; and control applications, including harmonic estimation and rejection inpower distribution systems, observer and control design for circadian rhythms, and discrete-time implementation of continuous-timenonlinear control laws.
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Non-linear Predictive Control
Theory and practice
Basil Kouvaritakis
The Institution of Engineering and Technology, 2001
Model-based predictive control (MPC) has proved to be a fertile area of research. It has gained enormous success within industry, especially in the context of process control. Nonlinear model-based predictive control (NMPC) is of particular interest as this best represents the dynamics of most real plant. This book collects together the important results which have emerged in this field, illustrating examples by means of simulations on industrial models. In particular there are contributions on feedback linearisation, differential flatness, control Lyapunov functions, output feedback, and neural networks. The international contributors to the book are all respected leaders within the field, which makes for essential reading for advanced students, researchers and industrialists in the field of control of complex systems.
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