Discrete Linear Control Systems

Inhaltsverzeichnis

• 1 Basic concepts and statement of problems in control theory.
• 1.1 Initial Premises.
• 1.2 Basic concepts of control theory.
• 1.3 Modelling of control objects and their general characteristics.
• 1.4 Precising the statement of the control problem.
• 2 Finite time period control.
• 2.1 Dynamic programming.
• 2.2 Stochastic control systems.
• 2.3 Stochastic dynamic programming.
• 2.4 Bayesian control strategy.
• 2.5 Linear quadratic Gaussian Problem.
• 2. A Appendix.
• 2. P Proofs of lemmas and theorems.
• 3 Infinite time period control.
• 3.1 Stabilitzation of dynamic systems using Liapunov’s method.
• 3.2 Discrete form for analytical design of regulators.
• 3.3 Transfer function method in linear optimization problem.
• 3.4 Limiting optimal control of stochastic processes.
• 3.5 Minimax control.
• 3. A Appendix.
• 3. P Proofs of the lemmas and theorems.
• 4 Adaptive linear control systems with bounded noise.
• 4.1 Fundamentals of adaptive control.
• 4.2 Existence of adaptive control strategy in a minimax control problem.
• 4.3 Self-tuning systems.
• 4. P Proofs of the lemmas and theorems.
• 5 The problem of dynamic system identification.
• 5.1 Optimal recursive estimation.
• 5.2 The Kalman-Bucy filter for tracking the parameter drift in dynamic systems.
• 5.3 Recursive estimation.
• 5.4 Identification of a linear control object in the presence of correlated noise.
• 5.5 Identification of control objects using test signals.
• 5. P Proofs of lemmas and theorems.
• 6 Adaptive control of stochastic systems.
• 6.1 Dual control.
• 6.2 Initial synthesis of adaptive control strategy in presence of the correlated noise.
• 6.3 Design of the adaptive minimax control.
• 6. P Proofs of the lemmas and the theorems.
• Comments.
• References.
• Operators and Notational Conventions.