Abstract
This paper presents a novel feedback control method for networked control systems by combining the P-type iterative learning control (ILC) idea with minimum tracking error entropy control strategy. In specific, the time-delayed control system of robotic manipulator is considered, where the convergence of the proposed control law is proved. The stochastic characteristics of the tracking error are analyzed. Moreover, the procedure to solve the optimal iterative operator is given by using particle swarm optimization (PSO) techniques. Simulation results are provided to show the effectiveness of the proposed approach.
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