Ebook: Real-time Iterative Learning Control: Design and Applications

Iterative learning control (ILC) has been a major control design methodology for twenty years; numerous algorithms have been developed to solve real-time control problems, from MEMS to batch reactors, characterised by repetitive control operations.

Real-time Iterative Learning Control demonstrates how the latest advances in ILC can be applied to a number of plants widely encountered in practice. The authors provide a hitherto lacking systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in the linear and nonlinear plants that pervade mechatronics and batch processes are addressed. In particular, the book discusses:

• ILC design in the continuous- and discrete-time domains;

• design in the frequency and time domains;

• design with problem-specific performance objectives including robustness and optimality;

• design by means of classical tools based on Bode plots and state space; and

• iterative-learning-based parametric identification.

Real-time Iterative Learning Control will interest control engineers looking for examples of how this important control technique can be applied to a variety of real-life problems. With its systematic formulation and analysis of different system properties and performance and its exposition of open problems, academics and graduate students working in control will find it a useful reference to the current status of ILC.

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Iterative learning control (ILC) has been a major control design methodology for twenty years; numerous algorithms have been developed to solve real-time control problems, from MEMS to batch reactors, characterised by repetitive control operations.

Real-time Iterative Learning Control demonstrates how the latest advances in ILC can be applied to a number of plants widely encountered in practice. The authors provide a hitherto lacking systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in the linear and nonlinear plants that pervade mechatronics and batch processes are addressed. In particular, the book discusses:

• ILC design in the continuous- and discrete-time domains;

• design in the frequency and time domains;

• design with problem-specific performance objectives including robustness and optimality;

• design by means of classical tools based on Bode plots and state space; and

• iterative-learning-based parametric identification.

Real-time Iterative Learning Control will interest control engineers looking for examples of how this important control technique can be applied to a variety of real-life problems. With its systematic formulation and analysis of different system properties and performance and its exposition of open problems, academics and graduate students working in control will find it a useful reference to the current status of ILC.

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Iterative learning control (ILC) has been a major control design methodology for twenty years; numerous algorithms have been developed to solve real-time control problems, from MEMS to batch reactors, characterised by repetitive control operations.

Real-time Iterative Learning Control demonstrates how the latest advances in ILC can be applied to a number of plants widely encountered in practice. The authors provide a hitherto lacking systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in the linear and nonlinear plants that pervade mechatronics and batch processes are addressed. In particular, the book discusses:

• ILC design in the continuous- and discrete-time domains;

• design in the frequency and time domains;

• design with problem-specific performance objectives including robustness and optimality;

• design by means of classical tools based on Bode plots and state space; and

• iterative-learning-based parametric identification.

Real-time Iterative Learning Control will interest control engineers looking for examples of how this important control technique can be applied to a variety of real-life problems. With its systematic formulation and analysis of different system properties and performance and its exposition of open problems, academics and graduate students working in control will find it a useful reference to the current status of ILC.

Content:
Front Matter....Pages i-xvi
Introduction....Pages 1-5
Introduction to ILC: Concepts, Schematics, and Implementation....Pages 7-28
Robust Optimal ILC Design for Precision Servo: Application to an XY Table....Pages 29-45
ILC for Precision Servo with Input Non-linearities: Application to a Piezo Actuator....Pages 47-63
ILC for Process Temperature Control: Application to a Water-heating Plant....Pages 65-83
ILC with Robust Smith Compensator: Application to a Furnace Reactor....Pages 85-100
Plug-in ILC Design for Electrical Drives: Application to a PM Synchronous Motor....Pages 101-120
ILC for Electrical Drives: Application to a Switched Reluctance Motor....Pages 121-140
Optimal Tuning of PID Controllers Using Iterative Learning Approach....Pages 141-167
Calibration of Micro-robot Inverse Kinematics Using Iterative Learning Approach....Pages 169-180
Conclusion....Pages 181-182
Back Matter....Pages 183-194

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Iterative learning control (ILC) has been a major control design methodology for twenty years; numerous algorithms have been developed to solve real-time control problems, from MEMS to batch reactors, characterised by repetitive control operations.

Real-time Iterative Learning Control demonstrates how the latest advances in ILC can be applied to a number of plants widely encountered in practice. The authors provide a hitherto lacking systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in the linear and nonlinear plants that pervade mechatronics and batch processes are addressed. In particular, the book discusses:

• ILC design in the continuous- and discrete-time domains;

• design in the frequency and time domains;

• design with problem-specific performance objectives including robustness and optimality;

• design by means of classical tools based on Bode plots and state space; and

• iterative-learning-based parametric identification.

Real-time Iterative Learning Control will interest control engineers looking for examples of how this important control technique can be applied to a variety of real-life problems. With its systematic formulation and analysis of different system properties and performance and its exposition of open problems, academics and graduate students working in control will find it a useful reference to the current status of ILC.

Content:
Front Matter....Pages i-xvi
Introduction....Pages 1-5
Introduction to ILC: Concepts, Schematics, and Implementation....Pages 7-28
Robust Optimal ILC Design for Precision Servo: Application to an XY Table....Pages 29-45
ILC for Precision Servo with Input Non-linearities: Application to a Piezo Actuator....Pages 47-63
ILC for Process Temperature Control: Application to a Water-heating Plant....Pages 65-83
ILC with Robust Smith Compensator: Application to a Furnace Reactor....Pages 85-100
Plug-in ILC Design for Electrical Drives: Application to a PM Synchronous Motor....Pages 101-120
ILC for Electrical Drives: Application to a Switched Reluctance Motor....Pages 121-140
Optimal Tuning of PID Controllers Using Iterative Learning Approach....Pages 141-167
Calibration of Micro-robot Inverse Kinematics Using Iterative Learning Approach....Pages 169-180
Conclusion....Pages 181-182
Back Matter....Pages 183-194
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