This course will introduce students to the basic results of stochastic systems for estimation, identification, stochastic control and adaptive control.
Innhold
The course will present the following topics in stochastic processes, with additional topics and examples presented at the lecturer's discretion.
Stochastic processes and their descriptions
Mathematical description of stochastic systems
Analysis of linear systems with random inputs
Prediction and filtering theory
Prediction for ARMAX systems
The Kalman filter and the Riccati equation
Parameter estimation theory for parametric models
Least squares and maximum likelihood estimators
Stochastic control methods based on dynamic programmeming
The LQG problem and the separation theorem
Minimum variance control
Adaptive control of stochastic systems
Self-tuning regulators
Direct adaptive control schemes
Stability and convergence analysis
Selected advanced topics
Undervisnings- og læringsformer
Lectures and examples classes
Eksamen
Oral or Written Examination at the lecturer's discretion. Pass/Fail.