ITERATIVE WEIGHTED LEAST-SQUARES IDENTIFICATION AND WEIGHTED LQG CONTROL DESIGN

Many practical applications of control system design based on input-ou tput measurements permit the repeated application of a system identifi cation procedure operating on closed-loop data together with successiv e refinements of the designed controller. Here we develop a paradigm f or such an iterative design. The key to the procedure is to account fo r evaluated modelling error in the control design and, equally, to let the closed-loop controller requirements determine the identification criterion. With an H-2 control problem, this is achieved by frequency weighting the linear-quadratic Gaussian (LQG) control criterion with f ilters that reflect the closed-loop plant/model mismatch, and by filte ring the identifier signals used in a least-squares identification sch eme in a logical and mutually supportive fashion.