Optimal Adaptive Controllers Based on Least Squares Algorithms
基于最小二乘算法的最优适应控制器

Optimal adaptive controllers based on input matching for the stochastic systems are studied by using least squares algorithms in this paper. The one- step-ahead least squares method is established and the convergence rate of the parameter estimation is obtained. Without any excited condition it is shown that the closed-loop system is globally stable and adaptive control converges to the one-step-ahead optimal control.