Preface Author Biographies List of Figures List of Tables Nomenclature 1 Introduction 1.1 Overview of Motion Control Systems 1.2 Optimization Methods 1.3 Model-based Optimization for Motion Control Systems 1.4 Data-based Optimization for Motion Control Systems I Model-based Optimization for Motion Control Systems 2 Constrained Linear Quadratic Optimization 2.1 Background 2.2 Constrained Linear Quadratic Optimization Algorithm 2.3 Case Study 2.4 Conclusion 3 Constrained H2 Optimization 3.1 Background 3.2 Constrained H2 Optimization Algorithm 3.3 Case Study 3.4 Conclusion 4 Constrained H2 Guaranteed Cost Optimization 4.1 Background 4.2 Parameter Space Optimization with Structural Constraints 4.3 Constrained H2 Guaranteed Cost Optimization Algorithm 4.4 Case Study 4.5 Conclusion II Data-based Optimization for Motion Control Systems 5 Reduced-order Inverse Model Optimization 5.1 Background 5.2 Overview of the 3-DOF Control Structure 5.3 Reduced-order Inverse Model Optimization Algorithm 5.4 Simulation Analysis 5.5 Experimental Validation 5.6 Conclusion 6 Reference Profile Alteration and Optimization 6.1 Background 6.2 Problem Formulation 6.3 Predictive Feedforward Scheme with O setting Mechanism 6.4 Optimization Algorithm for Reference Profile Alteration 6.5 Simulation Analysis 6.6 Experimental Validation 6.7 Conclusion 7 Disturbance Observer Sensitivity Shaping Optimization 7.1 Background 7.2 Overview of Disturbance Observer based Control Systems 7.3 Sensitivity Shaping Optimization Procedures 7.4 Simulation Analysis 7.5 Experimental Validation 7.6 Conclusion Bibliography
Jun Ma is currently a Visiting Scholar with the Department of Mechanical Engineering, University of California, Berkeley, Berkeley, CA, USA. His research interests include control and optimization, precision mechatronics, robotics, and medical technology. He was a recipient of the Singapore Commonwealth Fellowship in Innovation. Xiaocong Li is currently a Research Scientist with the Mechatronics Group, Singapore Institute of Manufacturing Technology, Agency for Science, Technology and Research, Singapore. His research interests include precision motion control, data-driven intelligent control, and industrial automation. Kok Kiong Tan is currently a Professor with the Department of Electrical and Computer Engineering, National University of Singapore, Singapore. His current research interests include precision motion control and instrumentation, advanced process control and auto-tuning, and general industrial automation.