1 Introduction 2 Deterministic Dynamic Programming and Viscosity Solutions 3 Stochastic Control 3.1 Some Probability Theory 3.2 Controlled State Space Models 3.3 Filtering 3.4 Dynamic Programming - Case I : Complete State Information 3.5 Dynamic Programming - Case II : Partial State Information 3.6 Two Continuous Time Problems 4 Robust Control 4.1 Introduction and Background 4.2 The Standard Problem of H∞ Control 4.3 The Solution for Linear Systems 4.4 Risk-Sensitive Stochastic Control and Robustness 5 Optimal Feedback Control of Quantum Systems 5.1 Preliminaries 5.2 The Feedback Control Problem 5.3 Conditional Dynamics 5.4 Optimal Control 5.5 Appendix: Formulas for the Two-State System with Feedback Example 6 Optimal Risk-Sensitive Feedback Control of Quantum Systems 6.1 System Model 6.2 Risk-Neutral Optimal Control 6.3 Risk-Sensitive Optimal Control 6.4 Control of a Two Level Atom 6.5 Control of a Trapped Atom
System compensation is the process of designing a controller that will produce an acceptable transient response while maintaining a desired steady-state accuracy .These two design objectives are conflicting in most systems ,since small errors imply high gains reduce system stability and may even drive the system unstable .Compensation may be thought of as the process of increasing the stability of a system without reducing its accuracy below minimum acceptable standards
