The course is aimed at providing the principles for designing linear multivariable control systems to meet a range of practical applications.

At the end of the course, students should be familiar with transfer matrix and state variable models for linear multivariable systems, including the concepts of poles, zeros, controllability, observability, detectability, stabilizability and minimality. They should be able to specify design objectives as optimisation procedures in terms of norm-based objective functions and be able to understand and use the corresponding controller synthesis techniques.

Analysis: system representations, return difference matrix, stability theory, including internal stability, multivariable poles and zeros.
Design: design criteria, LQG design methods (including the optimal linear quadratic regulator and the Kalman filter), singular value and norm-based methods, robust stability and performance. H-infinity design techniques, including the generalised regulator problem. Model reduction, including modal and balanced truncation.
Design examples: use of CAD techniques in the design of controllers for industrial processes.