Adaptive Forgetting through Multiple Models and Adaptive Control of Car Dynamics

Abstract: A new recursive identif ication method, Adaptive Forgetting through Multiple Models - AFMM, is presented and evaluated using computer simulations. AFMM is specif ically suited for identification of systems with jumping or rapidly changing parameters. It can be viewed as a particular way of implementing adaptive gains or adaptive forgetting factors for recursive identif ication. The new method essentiallyconsists of multiple Recursive Least Squares (RLS) algorithms running in parallel, each with a corresponding weighting factor. The simulations indicate that AFMM is able to track rapidly changing parameters well, and that the method is robust in several respects.