WIENER-FILTER-BASED MINIMUM-VARIANCE SELF-TUNING REGULATION

This paper presents a new direct discrete-time self-tuning minimum var iance control scheme for not necessarily minimum-phase SISO systems th at are operating in a stochastic environment. It is assumed that the o pen-loop system is asymptotically stable, or can be stabilized by a fi xed controller, and that the noise model satisfies the standard SPR pr operties. No assumptions are made regarding the zero polynomial of the controlled plant. The proposed direct self-tuning scheme consists of two-parameter adaptation algorithms (PAA) running simultaneously. The first PAA is an adaptive whitening filter. The adaptive whitening filt er error residual is fed into an adaptive finite impulse response (FIR ) filter, which generates the control signal. The second PAA estimates the parameters of the optimal Wiener FIR filter which minimizes the v ariance of the system output. A complete stability analysis and a disc ussion of the convergence and self-tuning properties of the proposed s elf-tuning scheme is included. (C) 1998 Elsevier Science Ltd. All righ ts reserved.