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Nonlinear Industrial Control Systems

Optimal Polynomial Systems and State-Space Approach

  • Michael J. Grimble
  • Paweł Majecki
Book

Table of contents

  1. Front Matter
    Pages i-xxx
  2. Introduction and Linear Systems

    1. Front Matter
      Pages 1-1
    2. Michael J. Grimble, Paweł Majecki
      Pages 3-63
    3. Michael J. Grimble, Paweł Majecki
      Pages 65-125
  3. Polynomial Systems Nonlinear Control

    1. Front Matter
      Pages 127-127
    2. Michael J. Grimble, Paweł Majecki
      Pages 129-158
    3. Michael J. Grimble, Paweł Majecki
      Pages 159-197
    4. Michael J. Grimble, Paweł Majecki
      Pages 199-246
    5. Michael J. Grimble, Paweł Majecki
      Pages 247-290
    6. Michael J. Grimble, Paweł Majecki
      Pages 291-344
  4. State-Space Systems Nonlinear Control

    1. Front Matter
      Pages 345-345
    2. Michael J. Grimble, Paweł Majecki
      Pages 347-375
    3. Michael J. Grimble, Paweł Majecki
      Pages 377-423
    4. Michael J. Grimble, Paweł Majecki
      Pages 425-468
    5. Michael J. Grimble, Paweł Majecki
      Pages 469-549
  5. Estimation, Condition Monitoring and Fault Detection for Nonlinear Systems

    1. Front Matter
      Pages 551-551
    2. Michael J. Grimble, Paweł Majecki
      Pages 553-596
    3. Michael J. Grimble, Paweł Majecki
      Pages 597-641
  6. Industrial Applications

    1. Front Matter
      Pages 643-643
    2. Michael J. Grimble, Paweł Majecki
      Pages 645-697
    3. Michael J. Grimble, Paweł Majecki
      Pages 699-759
  7. Back Matter
    Pages 761-764

About this book

Introduction

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 (downloadable from www.springer.com/978-1-4471-7455-4) 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.


Keywords

Aerospace Engineering Automotive Control Control Control Applications Control Engineering MATLAB® Maritime Engineering NGMV Nonlinear Control Nonlinear Generalized Minimum Variance Nonlinear Systems OJ0000 Optimal Control Optimisation Process Control Smith Predictor State Space Control

Authors and affiliations

  • Michael J. Grimble
    • 1
  • Paweł Majecki
    • 2
  1. 1.Department of Electronic and Electrical EngineeringUniversity of StrathclydeGlasgowUK
  2. 2.Industrial Systems and Control LimitedGlasgowUK

Bibliographic information