A revised iterative learning control strategy for robotic manipulators

In this paper a modified learning control algorithm is studied as one kind of hybrid type learning control which possesses properties of both iterative and repetitive learning control. The proposed learning control system consists of two parts: the memory based control and current cycle feedback control. The global convergence condition is derived in time domain. The corresponding physical meaning of the convergence condition is discussed in frequency domain. Multiperiod learning strategy is also developed. The learning control method has been successfully applied to motion control systems of manipulators