The course is aimed at providing the principles for designing linear multivariable control systems to meet a range of practical applications. You will derive models of linear multivariable control systems and analyse the structural properties of these models. You will also design control laws to achieve the desired objectives and performance.

On successfully completing this module you will be able to (1) Derive models of linear multivariable control systems using tranfer matrix and state variable methods, (2) Compute the poles and zeros, including the type of zeros, for such systems and (3) Analyse the controllability, observability, detectability, stabilizability and minimality properties for such systems. You should also be able to (4) Synthesize design objectives as optimisation procedures in terms of norm-based objective functions and (5) Devise the most appropriate 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.