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Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the application of the ideas presented. The second edition is thoroughly revised to throw light on recent developments in theory and applications with new chapters on: multimodel adaptive control with switching, direct and indirect adaptive regulation and adaptive feedforward disturbance compensation. Many algorithms are newly presented in MATLAB® m-file format to facilitate their employment in real systems. Classroom-tested slides for instructors to use in teaching this material are also now provided. All of this supplementary electronic material can be downloaded from fill in URL. The core material is also up-dated and re-edited to keep its perspective in line with modern ideas and more closely to associate algorithms with their applications giving the reader a solid grounding in: synthesis and analysis of parameter adaptation algorithms, recursive plant model identification in open and closed loop, robust digital control for adaptive control; • robust parameter adaptation algorithms, practical considerations and applications, including flexible transmission systems, active vibration control and broadband disturbance rejection and a supplementary introduction on hot dip galvanizing and a phosphate drying furnace. Control researchers and applied mathematicians will find Adaptive Control of significant and enduring interest and its use of example and application will appeal to practitioners working with unknown- and variable-parameter plant. Praise for the first edition: …well written, interesting and easy to follow, so that it constitutes a valuable addition to the monographies in adaptive control for discrete-time linear systems… suitable (at least in part) for use in graduate courses in adaptive control.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction to Adaptive Control

The aim of this introductory chapter is to emphasize the basic concepts pertinent to adaptive control and to present the significant adaptive control schemes. The final part of the chapter reviews briefly the various applications considered throughout the book.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 2. Discrete-Time System Models for Control

This chapter reviews the discrete-time systems models which will be used throughout the book as well as the computation of predictors in a deterministic and stochastic environment.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 3. Parameter Adaptation Algorithms—Deterministic Environment

Parameter adaptation algorithms are the key step for building an adaptive control system. An extensive coverage of the subject is provided in this chapter. Both synthesis and analysis of the parameter adaptation algorithms in a deterministic environment will be considered. Stability and convergence issues will be emphasized.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 4. Parameter Adaptation Algorithms—Stochastic Environment

This chapter is dedicated to the analysis of parameter adaptation algorithms in a stochastic environment. Techniques based on averaging and martingales will be used in order to assess the behavior of the algorithms.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 5. Recursive Plant Model Identification in Open Loop

Plant model identification in open loop is a preliminary step for building an adaptive control system. Using the parameter adaptation algorithms presented in Chaps. 3 and 4 as well as the predictor structures presented in Chap. 2, one can develop recursive identification methods. The chapter presents a number of recursive identification methods and the associated model validation techniques. The problems of input design and model order selection are also addressed. The methodology is illustrated by the identification of a flexible transmission.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 6. Adaptive Prediction

This chapter is dedicated to the design of adaptive predictors. The direct and indirect approach in a deterministic and stochastic environment are considered.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 7. Digital Control Strategies

Building an adaptive control system supposes that in the case in which the plant parameters are known, a controller achieving the desired performances can be designed. Therefore this chapter reviews a number of digital control strategies used for the design of the underlying controller whose parameters will be adapted. Pole placement, tracking and regulation with independent objectives, minimum variance control, generalized predictive control and linear quadratic control are presented in detail.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 8. Robust Digital Control Design

An adaptive control system has to be built on top of a robust digital control system. Therefore robustness issues for the underlying controller and the shaping of the sensitivity functions for various possible values of the plant parameters are very important. After a review of some basic robustness concepts, a methodology for shaping the sensitivity functions is presented. Its application is illustrated in the context of adaptive control of a flexible transmission.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 9. Recursive Plant Model Identification in Closed Loop

Iterative combination of identification in closed loop and robust control redesign leads to a two time scale adaptive control system very appealing in practice. The chapter is dedicated to the presentation of recursive algorithms for plant identification in closed-loop operation and their application. Two classes of algorithms will be presented, analyzed and evaluated experimentally: closed-loop output error algorithms and filtered open-loop recursive identification algorithms. Specific techniques for model validation in the context of identification in closed loop will also be presented. The performance of the various algorithms will be illustrated by simulation and by their application to the identification in closed loop and controller re-design of a flexible transmission control system.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 10. Robust Parameter Estimation

In practice a number of the hypotheses used for the development of parameter adaptation algorithms are violated. Therefore a number of modifications have to be introduced in order to accommodate these situations safely. The chapter presents and analyses several modifications of the parameter adaption algorithms which have been used in applications.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 11. Direct Adaptive Control

Direct adaptive control covers schemes where the parameters of the controller are directly updated from a signal error (adaption error) reflecting the performance error. The chapter presents strategies for direct adaptive control in a deterministic and in a stochastic environment and the corresponding analysis. This includes adaptive tracking and regulation with independent objectives, adaptive minimum variance control and their extensions. Robustification of direct adaptive control schemes is also discussed.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 12. Indirect Adaptive Control

Indirect adaptive control is a widely applicable adaptive control strategy. In real-time, it combines plant model parameter estimation in closed loop with the redesign of the controller. Adaptive pole placement and its robustified version, together with adaptive generalized predictive control constitute the core of the chapter. Adaptive linear quadratic control is also presented. Application of various strategies for the indirect adaptive control of a flexible transmission illustrates the methodology presented in this chapter.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 13. Multimodel Adaptive Control with Switching

The principles of adaptive control with switching are presented. This method insures high control performance in the presence of large and abrupt parameter variations. The stability of this type of adaptive control is studied and shown to be guaranteed with a minimum dwell-time between switchings. An application of adaptive control with switching and tuning to a flexible transmission system is presented. The advantages of this scheme with respect to classical adaptive control and fixed robust control are illustrated via some experimental results. The use of CLOE adaptation in the adaptive control with switching will also improve the performance of the system in the tuning phase.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 14. Adaptive Regulation—Rejection of Unknown Disturbances

This chapter addresses the problem of attenuation (rejection) of unknown disturbances without measuring them by using a feedback approach. In this context, the disturbance model is unknown and time varying while the model of the plant is known (obtained by system identification) and almost invariant. This requires an adaptive approach. The term “adaptive regulation” has been coined to characterize this control paradigm. Direct and indirect adaptive regulation strategies using the internal model principle and the Youla-Kucera parameterization will be presented. The evaluation of the methodology is done in real time on an active vibration control system using an inertial actuator.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 15. Adaptive Feedforward Compensation of Disturbances

Adaptive feedforward broadband vibration (or noise) compensation is currently used when an image (a correlated measurement) of the disturbance is available. However, in most of the systems there is a “positive” feedback coupling, between the compensator system and the measurement of the image of the disturbances, which cannot be ignored. The feedforward filter should compensate for the effect of the disturbance while assuring the stability of the internal “positive” feedback loop. Algorithms for adaptive feedforward compensation in the context of this internal positive feedback will be presented and analyzed. The algorithms are evaluated in real time on an active vibration control (AVC) system using an inertial actuator.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Chapter 16. Practical Aspects

The chapter examines the impact of practical aspects upon the design and implementation of the adaptive control systems. This involves: choice of the sampling frequency and anti-aliasing filters, taking into account the digital-to-analog converter, handling the possible actuator saturation, taking in account the computational delay, choice of the performance, numerically safe implementation of the parameter adaptation algorithms, initialization of the adaptive control scheme, and supervision.
Ioan Doré Landau, Rogelio Lozano, Mohammed M’Saad, Alireza Karimi

Backmatter

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