Pseudo-linear indentification and its application to adaptive control

Abstract

The method of Pseudo-Linear Identification (PLID) is presented as an explicitly linear approach to the joint state and parameter estimation problem. The convergence properties of the algorithm in the stochastic case are investigated through simulation and comparisons with popular methods are made. The method is then extended to allow the tracking of time-varying system parameters.

An adaptive control structure based upon this Tracking–PLID algorithm is proposed which utilizes pole–placement state variable feedback via Ackermann's formula. The capabilities of this adaptive control scheme are demonstrated by application to a full-order nonlinear aircraft simulation model where significant improvement is shown over fixed-gain controllers in the face of rapid plant changes.