Course ObjectivesThe 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.
Multivariable systemsSensitivity, complementary sensitivity and control sensitivity function. Representations of uncertainty. Analysis of robustness and performance.
Linear Quadratic ControlProblem formulation, solution algorithms, properties of robustness.
State estimatorEstimators 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 ControlProblem definition. Open and clsed-loop solution. Stability.
- Docente: CHIARA TOFFANIN