Title :
Stochastic adaptive one-step-ahead optimal controllers based on input matching
Author :
Lo, Kueiming ; Zhang, Dachun
Author_Institution :
Dept. of Math. Sci., Tsinghua Univ., Beijing, China
fDate :
5/1/2000 12:00:00 AM
Abstract :
Optimal adaptive controller based on the ELS algorithm is established using the input matching technique. The control signal is reduced to a constant weighted sum of the measurable information-state vector components using a one-step-ahead quadratic cost function to govern the behavior of the stochastic linear systems. The control effort can be estimated globally. The algorithm also predicts the convergence rate. With no excitation condition, the closed-loop system is globally stable and the input converges to the one-step-ahead optimal input
Keywords :
adaptive control; closed loop systems; convergence; least squares approximations; optimal control; stability; stochastic systems; ELS algorithm; LS algorithm; closed-loop system; convergence rate; global stability; input matching; least squares algorithm; measurable information-state vector components sum; one-step-ahead quadratic cost function; stochastic adaptive one-step-ahead optimal controllers; stochastic linear systems; Adaptive control; Control systems; Cost function; Impedance matching; Linear systems; Optimal control; Programmable control; Stochastic processes; Stochastic systems; Vectors;
Journal_Title :
Automatic Control, IEEE Transactions on
