Course Objectives

The course aims to introduce students to the main methods of synthesis of controllers for multivariable linear continuous-time and discrete-time dynamical systems. The definitions of sensitivity, complementary sensitivity and control sensitivity function are extended and their characteristics are analyzed using appropriately defined performance indices. State estimation for deterministic and stochastic systems are presented with particular emphasis on the Kalman filtering.

Course Programme

Multivariable systems

Sensitivity, complementary sensitivity and control sensitivity function. Representations of uncertainty. Analysis of robustness and performance.

Linear Quadratic Control

Problem formulation, solution algorithms, properties of robustness.

State estimator

Estimators for deterministic systems. Kalman filter and predictor. Linearized and extended predictor. Applications to the estimation of uncertain parameters and diagnostics industry. H2 control.

Model Predictive Control

Problem definition. Open and clsed-loop solution. Stability.