Adaptive Control for Partially Known Systems
Theory and Applications
Carlos A.Canudas De Wit(Author)
Elsevier (Publisher)
Published in December 1988
Book
Hardback
282 pages
978-0-444-87136-7 (ISBN)
Description
Adaptive control has been considered as an alternative in designing high-performance control systems, from the beginning of the 1950s. Since then, most of the adaptive control schemes have been formulated either in the continuous-time or in the discrete-time framework. Both approaches commonly use ``black-box'' models for describing the process to be controlled; models with known structure but unknown parameters. These models have the advantage that they are general but also the disadvantage that many parameters have to be estimated. There are in practice, however, many adaptive problems where the system can be described as partially known in the sense that part of the system dynamics is known and another part unknown. This is the kind of system considered in this book. Most of the adaptive algorithms that are reliable - in the sense that they guarantee closed-loop stability and some performance behaviour - require to a certain extent some system knowledge and a checking procedure for the caution update of the parameter estimates.
Adaptive control has been considered as an alternative in designing high-performance control systems, from the beginning of the 1950s. Since then, most of the adaptive control schemes have been formulated either in the continuous-time or in the discrete-time framework. Both approaches commonly use ``black-box'' models for describing the process to be controlled; models with known structure but unknown parameters. These models have the advantage that they are general but also the disadvantage that many parameters have to be estimated. There are in practice, however, many adaptive problems where the system can be described as partially known in the sense that part of the system dynamics is known and another part unknown. This is the kind of system considered in this book. Most of the adaptive algorithms that are reliable - in the sense that they guarantee closed-loop stability and some performance behaviour - require to a certain extent some system knowledge and a checking procedure for the caution update of the parameter estimates.
Adaptive control has been considered as an alternative in designing high-performance control systems, from the beginning of the 1950s. Since then, most of the adaptive control schemes have been formulated either in the continuous-time or in the discrete-time framework. Both approaches commonly use ``black-box'' models for describing the process to be controlled; models with known structure but unknown parameters. These models have the advantage that they are general but also the disadvantage that many parameters have to be estimated. There are in practice, however, many adaptive problems where the system can be described as partially known in the sense that part of the system dynamics is known and another part unknown. This is the kind of system considered in this book. Most of the adaptive algorithms that are reliable - in the sense that they guarantee closed-loop stability and some performance behaviour - require to a certain extent some system knowledge and a checking procedure for the caution update of the parameter estimates.
More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 240 mm
ISBN-13
978-0-444-87136-7 (9780444871367)
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Schweitzer Classification
Content
1. Introduction. Adaptive control schemes. Adaptive control in partially known plants - Short survey. A priori plant knowledge - A classification. The expected benefits. The hybrid approach - An overview. PART I: THEORY. 2. Hybrid Estimation. Plant description and identifiability properties. The estimation scheme. Estimator properties. Selection of the design parameters. Conclusions and final remarks. 3. Hybrid Estimation in Presence of Bounded Disturbances. Introduction and background. A new estimation algorithm. User guidelines and some examples. Final remarks. 4. Hybrid Estimation for Systems with Variable Time-Delay. Plant model. Parameter estimation. Conclusions. 5. Hybrid Adaptive Control for Partially Known Systems. Fixed control strategy. Estimation scheme and adaptive control law. Modified persistently excited (M-PE) signal algebra. Closed-loop stability. Concluding remarks. 6. Conclusions and Further Research. Resume. The contributions. Further research. PART II: APPLICATIONS. 7. Adaptive Friction Compensation with Application to Robotics. Mathematical models. Friction beating - some strategies. Linear control design. Adaptive friction compensation. Experiments. Conclusions and further research. 8. Adaptive Control in Flexible Arms. Arm model. Payload mass and friction estimation. Control policies. Simulation results. Conclusions and recommendations for future research. 9. Adaptive Robust Control of Robots with Flexible Joints. Robot model. Control design. Robust considerations and stability issues. Parameter estimation. References. Appendices. Subject Index.