Application of discrete-time model reference adaptive control to industrial robots: A computer simulation

Abstract In this paper a direct approach to discrete-time model reference adaptive control (MRAC) based on hyperstability theory is proposed to control industrial robotic manipulators. For industrial robots and manipulators which usually have highly nonlinear and complex dynamic behaviors and often unknown inertia characteristics, it is very difficult to achieve high performance with conventional control strategies. This high performance in terms of speed and accuracy can be obtained by adaptive control techniques. Considering the effects of gravity, process noise, and payload uncertainty, this approach is investigated using simulation for a three degree of freedom industrial robot. These simulation results show that adaptive control techniques can provide robust properties in spite of poor a priori information regarding the robot dynamics and circumstances.