Using relevant mathematical proofs and case studies illustrating design and application issues, this book demonstrates this powerful technique in the light of research on neural networks, which allow the identification of nonlinear models without the complicated and costly development of models based on physical laws.

Inhalt

1. Introduction.- 2. Fundamental Concepts.- 3. Introduction to Feedback Linearisation.- 4. Dynamic Neural Networks.- 5. Nonlinear System Approximation Using Dynamic Neural Networks.- 6. Feedback Linearisation Using Dynamic Neural Networks.- 7. Case Studies.- References.