1 Introduction to the Monograph. - 1. 1 Background and Motivation: Transient Response Control. - 1. 2 Organization of the Monograph. - 2 Iterative Learning Control: An Overview. - 2. 1 Introduction. - 2. 2 Literature Review. - 2. 3 Problem Formulation. - 3 Linear Time-Invariant Learning Control. - 3. 1 Convergence with Zero Error. - 3. 2 Convergence with Non-Zero Error. - 3. 3 The Nature of the Solution. - 4 LTI Learning Control via Parameter Estimation. - 4. 1 System Description. - 4. 2 Main Result. - 4. 3 Comments. - 5 Finite-Horizon Learning Control. - 5. 1 l?-Optimal Learning Control with Memory. - 5. 2 Learning Convergence in One Step. - 5. 3 Learning Control with Multirate Sampling. - 5. 4 Examples. - 5. 5 Comments and Extensions. - 6 Nonlinear Learning Control. - 6. 1 Learning Control for Nonlinear Systems. - 6. 2 Learning Controller for a Class of Nonlinear Systems. - 7 Artificial Neural Networks for Iterative Learning Control. - 7. 1 Neural Network Controllers. - 7. 2 Static Learning Controller Using an ANN. - 7. 3 Dynamical Learning Controller Using an ANN. - 7. 4 Reinforcement Learning Controller Using an ANN. - 8 Conclusion. - 8. 1 Summary. - 8. 2 Directions for Future Research. - Appendix A: Some Basic Results on Multirate Sampling. - A. 1 Introduction. - A. 3 Basic Result. - Appendix B: Tutorial on Artificial Neural Networks. - B. 1 An Introduction to Neural Networks. - B. 1. 1 Neurons. - B. 1. 2 Interconnection Topology. - B. 1. 3 Learning Laws. - B. 2 Historical Background. - B. 3 Properties of Neural Networks. - B. 3. 1 Pattern Classification and Associative Memory. - B. 3. 2 Self-Organization and Feature Extraction. - B. 3. 3 Optimization. - B. 3. 4 Nonlinear Mappings. - B. 4 Neural Nets and Computers. - B. 5 Derivation of Backpropagation. - B. 6 Neural Network References. - References. Language: English