Iterative Learning Control with Passive Incomplete Information

Description

This book presents an in-depth discussion of iterative learning control (ILC) with passive incomplete information, highlighting the incomplete input and output data resulting from practical factors such as data dropout, transmission disorder, communication delay, etc.—a cutting-edge topic in connection with the practical applications of ILC. It describes in detail three data dropout models: the random sequence model, Bernoulli variable model, and Markov chain model—for both linear and nonlinear stochastic systems. Further, it proposes and analyzes two major compensation algorithms for the incomplete data, namely, the intermittent update algorithm and successive update algorithm. Incomplete information environments include random data dropout, random communication delay, random iteration-varying lengths, and other communication constraints. With numerous intuitive figures to make the content more accessible, the book explores several potential solutions to this topic, ensuring that readers are not only introduced to the latest advances in ILC for systems with random factors, but also gain an in-depth understanding of the intrinsic relationship between incomplete information environments and essential tracking performance. It is a valuable resource for academics and engineers, as well as graduate students who are interested in learning about control, data-driven control, networked control systems, and related fields. Front Matter ....Pages i-xiv Introduction (Dong Shen)....Pages 1-20 Front Matter ....Pages 21-21 Random Sequence Model for Linear Systems (Dong Shen)....Pages 23-50 Random Sequence Model for Nonlinear Systems (Dong Shen)....Pages 51-64 Random Sequence Model for Nonlinear Systems with Unknown Control Direction (Dong Shen)....Pages 65-82 Bernoulli Variable Model for Linear Systems (Dong Shen)....Pages 83-114 Bernoulli Variable Model for Nonlinear Systems (Dong Shen)....Pages 115-131 Markov Chain Model for Linear Systems (Dong Shen)....Pages 133-160 Front Matter ....Pages 161-161 Two-Side Data Dropout for Linear Deterministic Systems (Dong Shen)....Pages 163-178 Two-Side Data Dropout for Linear Stochastic Systems (Dong Shen)....Pages 179-195 Two-Side Data Dropout for Nonlinear Systems (Dong Shen)....Pages 197-214 Front Matter ....Pages 215-215 Multiple Communication Conditions and Finite Memory (Dong Shen)....Pages 217-240 Random Iteration-Varying Lengths for Linear Systems (Dong Shen)....Pages 241-253 Random Iteration-Varying Lengths for Nonlinear Systems (Dong Shen)....Pages 255-269 Iterative Learning Control for Large-Scale Systems (Dong Shen)....Pages 271-285 Back Matter ....Pages 287-294