1. The Adaptive Inverse Control Concept.
2. Wiener Filters.
3. Adaptive LMS Filters.
4. Adaptive Modeling.
5. Inverse Plant Modeling.
6. Adaptive Inverse Control.
7. Other Configurations for Adaptive Inverse Control.
8. Plant Disturbance Canceling.
9. System Integration.
10. Multiple-Input Multiple-Output (MIMO) Adaptive Inverse Control Systems.
11. Nonlinear Adaptive Inverse Control.
12. Pleasant Surprises.
A Stability and Misadjustment of the LMS Adaptive Filter.
B Comparative Analyses of Dither Modeling Schemes A, B, C.
C A Comparison of the Self-Tuning Regulator of Astrom and Wittenmark with the Techniques of Adaptive Inverse Control.
D Adaptive Inverse Control for Unstable Linear SISO Plants.
E Orthogonalizing Adaptive Algorithms: RLS, DFT/LMS, and DCT/LMS.
F A MIMO Application: An Adaptive Noise-Canceling System Used for Beam Control at the Stanford Linear Accelerator Center.
G Thirty Years of Adaptive Neural Networks: Perceptron Madaline, and Backpropagation.
H Neural Control Systems.
- Written by the pioneers of its subject matter, the book presents a unique blend of adaptive inverse control and signal processing
- Intuitive approach presents complex material in a highly accessible way
- Includes case studies, reference algorithms, historical background, and chapter summaries to help make the material clearer
- Features downloadable homework problems, MATLAB code, and other student/instructor resources