Functional Adaptive Control : An Intelligent Systems Approach

Simon G Fabri

ISBN 10: 185233438X / ISBN 13: 9781852334383

Edité par Springer London Feb 2001, 2001

A propos de cet article

Neuware - The field of intelligent control has recently emerged as a response to the challenge of controlling highly complex and uncertain nonlinear systems. It attempts to endow the controller with the key properties of adaptation, learn ing and autonomy. The field is still immature and there exists a wide scope for the development of new methods that enhance the key properties of in telligent systems and improve the performance in the face of increasingly complex or uncertain conditions. The work reported in this book represents a step in this direction. A num ber of original neural network-based adaptive control designs are introduced for dealing with plants characterized by unknown functions, nonlinearity, multimodal behaviour, randomness and disturbances. The proposed schemes achieve high levels of performance by enhancing the controller's capability for adaptation, stabilization, management of uncertainty, and learning. Both deterministic and stochastic plants are considered. In the deterministic case, implementation, stability and convergence is sues are addressed from the perspective of Lyapunov theory. When compared with other schemes, the methods presented lead to more efficient use of com putational storage and improved adaptation for continuous-time systems, and more global stability results with less prior knowledge in discrete-time sys tems.

N° de réf. du vendeur 9781852334383

Détails bibliographiques

• Titre: Functional Adaptive Control : An Intelligent Systems Approach
• Éditeur: Springer London Feb 2001
• Date de parution: 2001
• Langue: anglais
• ISBN à 10 chiffres: 185233438X
• ISBN à 13 chiffres: 9781852334383
• Reliure: Buch
• État de l'article: Neu
• Dimensions: 242 L x 165 H x 24 P (en millimètres) 242 millimètres de largeur par 165 millimètres de hauteur par 24 millimètres de profondeur
• Poids: 573 grammes

A propos de ce titre

Synopsis

The field of intelligent control has recently emerged as a response to the challenge of controlling highly complex and uncertain nonlinear systems. It attempts to endow the controller with the key properties of adaptation, learn- ing and autonomy. The field is still immature and there exists a wide scope for the development of new methods that enhance the key properties of in- telligent systems and improve the performance in the face of increasingly complex or uncertain conditions. The work reported in this book represents a step in this direction. A num- ber of original neural network-based adaptive control designs are introduced for dealing with plants characterized by unknown functions, nonlinearity, multimodal behaviour, randomness and disturbances. The proposed schemes achieve high levels of performance by enhancing the controller's capability for adaptation, stabilization, management of uncertainty, and learning. Both deterministic and stochastic plants are considered. In the deterministic case, implementation, stability and convergence is- sues are addressed from the perspective of Lyapunov theory. When compared with other schemes, the methods presented lead to more efficient use of com- putational storage and improved adaptation for continuous-time systems, and more global stability results with less prior knowledge in discrete-time sys- tems.

Présentation de l'éditeur

Unique in its systematic approach to stochastic systems, this book presents a wide range of techniques that lead to novel strategies for effecting intelligent control of complex systems that are typically characterised by uncertainty, nonlinear dynamics, component failure, unpredictable disturbances, multi-modality and high dimensional spaces.