Multi-Innovation Gradient Parameter Estimation Based Adaptive Control for Discrete-Time Systems

This paper uses the multi-innovation stochastic gradient (MISG) algorithm to estimate the parameters of discrete- time systems and presents an MISG based adaptive control scheme. Further, we prove that the parameter estimation error converges to zero under the persistent excitation, and the parameter estimation based control algorithm can achieve virtually asymptotically optimal control and ensure that the closed-loop systems are stable and globally convergent. The simulation results are included.