A globally stable direct adaptive control algorithm for robotic manipulators is proposed. The algorithm is based on a desired compensation adaptation law and control law such that the measurement noise is no longer correlated with the regression vector. Therefore the parameter estimates are not susceptible to parameter drift. Lyapunov theory is used to design both the control law and the adaptation law. Based on stability theory we establish sufficient conditions for the choice of the controller gains. These sufficient conditions are formulated directly from the bounds on the inertial parameters. The performance of the proposed algorithm is demonstrated by computer simulation. The proposed method is also compared to the methods proposed by Slotine and Li (1987), and Sadegh and Horowitz (1990).
['H. Asmer', 'Howard M. Schwartz', 'Gabriel D. Warshaw']
A Direct Adaptive Control Method With Desired Compensation For Robotic Manipulators