Introduction to Multivariable Feedback Control

Abstract

Multivariable control design becomes sensible when there are more than one input and output that exist in a dynamic system and when there is relativity a strong coupling between these inputs and outputs. The multivariable or MIMO feedback control design includes a vast area of many different techniques. In this chapter, the authors start by discussing nonoptimal and optimal control strategies, such as Linear Quadratic Regulator and Linear Quadratic Gaussian, and robust control. They also start with reviewing deriving the SISO transfer function from its state-space matrices. The authors introduce the Schur complement and Rosenbrock system matrix and their application in deriving transfer functions and transfer function matrices from state-space matrices. Then they provide an interpretation of poles, zeros, and transmission blocking zeros of transfer functions. The authors end by introducing transfer function matrices including some of its basic aspects.