Title :
Parameter convergence in the stochastic gradient adaptive control law
Author :
Lin, Sheng-Fuu ; Kumar, P.R.
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA
Abstract :
The authors exhibit self-tuning results for the adaptive control law proposed by G.C. Godwin, P.J. Ramadge and P.E. Caines (SIAM J. Control Optim., vol.19, no.6, p.829-53, 1981). They also show how the dimension of the adaptive control law can be reduced in situations where the reference trajectory has a low order of excitation. The results are compared with an adaptive control law proposed by P.R. Kumar and L. Praly (SIAM J. Control Optim., vol.25, no.4, p.1053-71, 1987)
Keywords :
adaptive control; convergence; self-adjusting systems; stochastic systems; parameter convergence; self adjusting systems; self-tuning; stochastic gradient adaptive control law; stochastic systems; Adaptive control; Contracts; Control engineering; Convergence; Error correction; Stochastic processes; Stochastic resonance; Stochastic systems; Trajectory; White noise;
Conference_Titel :
Decision and Control, 1988., Proceedings of the 27th IEEE Conference on
Conference_Location :
Austin, TX
DOI :
10.1109/CDC.1988.194513
