Iterative learning control with passive incomplete information : algorithms design and convergence analysis /: algorithms design and convergence analysis. (2018)

• Record Type: Book
• Further Information: Note: Dong Shen.
• Authors: Shen, Dong, 1982-
• Contents: Intro; Preface; Contents; 1 Introduction; 1.1 Iterative Learning Control-Why and How; 1.2 Basic Formulation of ILC; 1.2.1 Discrete-Time Case; 1.2.2 Continuous-Time Case; 1.3 ILC with Random Data Dropouts; 1.3.1 Data Dropout Models; 1.3.2 Data Dropout Positions; 1.3.3 Convergence Meanings; 1.4 ILC with Other Incomplete Information; 1.4.1 Communication Delay and Asynchronism; 1.4.2 Iteration-Varying Lengths; 1.5 Structure of This Monograph; 1.6 Summary; References; Part I One-Side Data Dropout; 2 Random Sequence Model for Linear Systems; 2.1 Problem Formulation. 2.2 Intermittent Update Scheme and Its Almost Sure Convergence2.3 Extension to Arbitrary Relative Degree Case with Mean Square Convergence; 2.3.1 Noise-Free System Case; 2.3.2 Stochastic System Case; 2.4 Illustrative Simulations; 2.5 Summary; References; 3 Random Sequence Model for Nonlinear Systems; 3.1 Problem Formulation; 3.2 Intermittent Update Scheme and Its Convergence; 3.3 Successive Update Scheme and Its Convergence; 3.4 Illustrative Simulations; 3.5 Summary; References; 4 Random Sequence Model for Nonlinear Systems with Unknown Control Direction; 4.1 Problem Formulation. 4.2 Intermittent Update Scheme and Its Almost Sure Convergence4.3 Proofs of Lemmas; 4.4 Illustrative Simulations; 4.5 Summary; References; 5 Bernoulli Variable Model for Linear Systems; 5.1 Problem Formulation; 5.2 Intermittent Update Scheme and Its Almost Sure Convergence; 5.3 Successive Update Scheme and Its Almost Sure Convergence; 5.4 Mean Square Convergence of Intermittent Update Scheme; 5.4.1 Noise-Free System Case; 5.4.2 Stochastic System Case; 5.5 Illustrative Simulations; 5.5.1 System Description; 5.5.2 Tracking Performance of both Schemes. 5.5.3 Comparison of Different Data Dropout Rates5.5.4 Comparison of Different Learning Gains; 5.5.5 Comparison with Conventional P-Type Algorithm; 5.6 Summary; References; 6 Bernoulli Variable Model for Nonlinear Systems; 6.1 Problem Formulation; 6.2 Intermittent Update Scheme and Its Almost Sure Convergence; 6.3 Successive Update Scheme and Its Almost Sure Convergence; 6.4 Illustrative Simulations; 6.5 Summary; References; 7 Markov Chain Model for Linear Systems; 7.1 Problem Formulation; 7.2 ILC Algorithms; 7.3 ILC for Classical Markov Chain Model Case. 7.4 ILC for General Markov Data Dropout Model Case7.5 Illustrative Simulations; 7.6 Summary; References; Part II Two-Side Data Dropout; 8 Two-Side Data Dropout for Linear Deterministic Systems; 8.1 Problem Formulation; 8.2 ILC Algorithms; 8.3 Markov Chain Model of Input Evolution; 8.4 Convergence Analysis; 8.5 Illustrative Simulations; 8.6 Summary; References; 9 Two-Side Data Dropout for Linear Stochastic Systems; 9.1 Problem Formulation; 9.2 Markov Chain of Input Evolution; 9.3 Convergence Analysis; 9.4 Discussions on Convergence Speed; 9.5 Illustrative Simulations; 9.6 Summary; References.
• Publisher Details: Singapore : Springer
• Publication Date: 2018
• Extent: 1 online resource
• Subjects: 629.8/312; Intelligent control systems; Iterative methods (Mathematics); TECHNOLOGY & ENGINEERING -- Engineering (General); Intelligent control systems; Iterative methods (Mathematics); Electronic books; Electronic book
• Languages: English
• ISBNs: 9789811082672; 9811082677
• Related ISBNs: 9789811082665; 9811082669
• Notes: Note: Includes bibliographical references and index.; Note: Online resource; title from PDF title page (SpringerLink, viewed April 24, 2018).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.