Least square estimation and optimal control of linear distributed-parameter systems

This paper presents computational algorithms for weighting function estimation and optimal control synthesis in one-dimensional, linear distributed-parameter systems. Using the least square approach, functional gradient procedures are developed for estimating system weighting functions associated with either boundary or distributed control. Same functional gradient procedures are also used to generate the optimal control function when a final state quadratic error criterion is chosen. These algorithms should be suitable for on-line adaptive control since optimal control function itself can be used as input for estimation. Finally, results from computer simulation study of a heat diffusion system are presented. They clearly demonstrate the convergence of these algorithms.