Title :
A parameter estimation algorithm for continuous time stochastic adaptive control
Author :
Gevers, M. ; Wertz, V. ; Goodwin, G.C.
Author_Institution :
Louvain Univ., Belgium
Abstract :
An adaptive parameter estimator for continuous-time stochastic systems which results in globally stable adaptive control algorithms is presented. The analysis method is inspired by G.C. Goodwin and D.Q. Mayne (1987) in that properties of the parameter estimator are established that hold irrespective of the control law. Compared with comparable discrete-time schemes, the success of the algorithm hinges crucially on a modification of the parameter update law which ensures that the normalized regression vector remains uniformly bounded
Keywords :
adaptive control; parameter estimation; stability; stochastic systems; continuous-time systems; globally stable adaptive control algorithms; normalized regression vector; parameter estimation; parameter update law; stochastic systems; uniformly bounded regression vector; Adaptive control; Integral equations; Parameter estimation; Programmable control; Stability; State-space methods; Stochastic processes; Stochastic resonance; Stochastic systems; White noise;
Conference_Titel :
Decision and Control, 1988., Proceedings of the 27th IEEE Conference on
Conference_Location :
Austin, TX
DOI :
10.1109/CDC.1988.194663
