This course aims at giving complete overview of modern synthesis techniques of robust controllers for dynamical systems. By this, we mean the design of controllers with the property that their sensitivity to ever present disturbances, noise, model uncertainties, unmodeled dynamics, actuator saturation etc., have been eliminated (or reduced) as much as possible. Furthermore, students are introduced to advanced linear parameter-varying (LPV) modelling and control synthesis methods, providing controllers that schedule their behaviour with changing operating conditions or time-variation of the plant.
After completing the course successfully, the student should:
1) Have a good understanding of the concepts (theories, definitions, notation) of modern, robust, linear time-invariant and linear parameter-varying control synthesis.
2) Define, model, analyze and quantify modeling errors and disturbances as uncertainties. Capable to define linear parameter-varying models of nonlinear/time-varying systems.
3) Interpret robust performance specifications as control design objectives and be able to describe and accomplish robust performance and stability analysis of a given system.
4) Describe and apply robust and LPV H_inf-controller synthesis procedure based on linear matrix inequalities for MIMO plants and accomplish performance shaping in the process.
5) Carry out robust and LPV control design and analysis in Matlab (Robust Control Toolbox, LPVTools).