Machine learning control -- taming nonlinear dynamics and turbulence. ([2016])

• Record Type: Book
• Further Information: Note: Thomas Duriez, Steven L. Brunton, Bernd R. Noack.
• Authors: Duriez, Thomas; Brunton, Steven L (Steven Lee), 1984-; Noack, Bernd R
• Contents: Preface.- 1 Introduction.- 1.1 Feedback in engineering and living systems.- 1.2 Benefits of feedback control.- 1.3 Challenges of feedback control.- 1.4 Feedback turbulence control is a grand challenge problem.- 1.5 Nature teaches us the control design.- 1.6 Outline of the book.- 1.7 Exercises.- 2 Machine learning control (MLC).- 2.1 Methods of machine learning.- 2.2 MLC with genetic programming.- 2.3 Examples.- 2.4 Exercises.- 2.5 Suggested reading.- 2.6 Interview with Professor Marc Schoenauer.- 3 Methods of linear control theory.- 3.1 Linear systems.- 3.2 Full-state feedback.- Linear quadratic regulator (LQR).- 3.3 Sensor-based state estimation.- Kalman filtering.- 3.4 Sensor-based feedback.- Linear quadratic Gaussian (LQG).- 3.5 System Identification and Model Reduction.- 3.6 Exercises.- 3.7 Suggested reading.- 4 Benchmarking MLC against linear control.- 4.1 Comparison of MLC with LQR on a linear oscillator.- 4.2 Comparison of MLC with Kalman filter on a noisy linear oscillator.- 4.3 Comparison of MLC with LQG for sensor-based feedback.- 4.4 Modifications for small nonlinearity.- 4.5 Exercises.- 4.6 Interview with Professor Shervin Bagheri.- 5 Taming nonlinear dynamics with MLC.- 5.1 Generalized mean-field system.- 5.2 Machine learning control.- 5.3 Derivation outline for the generalized mean-field model.- 5.4 Alternative control approaches.- 5.5 Exercises.- 5.6 Suggested reading.- 5.7 Interview with Professor Mark N. Glauser.- 6 Taming real world flow control experiments with MLC.- 6.1 Separation control over a backward-facing step.- 6.2 Separation control of turbulent boundary layers.- 6.3 Control of mixing layer growth.- 6.4 Alternative model-based control approaches.- 6.5 Implementation of MLC in experiments.- 6.6 Suggested reading.- 6.7 Interview with Professor David Williams.- 7 MLC tactics and strategy.- 7.1 The ideal flow control experiment.- 7.2 Desiderata of the control problem — from the definition to hardware choices.- 7.3 Time scales of MLC.- 7.4 MLC parameters and convergence.- 7.5 The imperfect experiment.- 8 Future developments.- 8.1 Methodological advances of MLC.- 8.2 System-reduction techniques for MLC — Coping with high-dimensional input and output.- 8.3 Future applications of MLC.- 8.4 Exercises.- 8.5 Interview with Professor Belinda Batten.- Glossary.- Symbols.- Abbreviations.- Matlab® Code: OpenMLC.- Bibliography.- Index.
• Publisher Details: Switzerland : Springer
• Publication Date: 2016
• Copyright Date: 2017
• Extent: 1 online resource (xx, 211 pages), illustrations (some color)
• Subjects: 629.8/3; Engineering; Feedback control systems; Adaptive control systems; Machine learning; Hydraulic engineering; Microprogramming; Artificial intelligence; Adaptive control systems; Feedback control systems; Machine learning; Science -- Mechanics -- Dynamics -- Fluid Dynamics; Technology & Engineering -- Automation; Computers -- Systems Architecture -- General; Computers -- Intelligence (AI) & Semantics; Science -- Chaotic Behavior in Systems; Fluid mechanics; Automatic control engineering; Algorithms & data structures; Artificial intelligence; Nonlinear science; Technology & Engineering -- Mechanical; Mechanics of fluids; Electronic books
• Languages: English
• ISBNs: 9783319406244; 3319406248
• Related ISBNs: 9783319406237; 331940623X
• Notes: Note: Includes bibliographical references and index.; Note: Online resource; title from PDF title page (SpringerLink, viewed November 15, 2016).
• 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.