A learning control algorithm is proposed for hybrid force/position tracking of a manipulator in contact with a hard surface. The algorithm utilizes acceleration errors and force errors for learning the inputs required to perform repetitive tasks. We prove the convergence of both force and position tracking errors theoretically. The speed of convergence of the tracking errors is shown to be improved by proper choice of learning gains. The method is compared with PI and PID learning, and similarities with the free-space case are outlined. The robustness of the new scheme to uncertainties in surface geometry and link parameters is discussed. Results of simulation studies and experimental implementation on 3-link robot manipulators are presented to illustrate the effectiveness of the proposed learning controller.

Force/position control is a relatively young and rapidly developing branch of robotics. Its practical implementation faces many difficulties due to inherent process complexity. Despite this, the majority of contributions in this field use the classic approach to force control, i.e. single-loop PID control. In this paper, two model-based control structures are proposed, yielding much better results of force control as compared to the classic approach, to be achieved. These are two-loop model-following control (MFC) structures that guarantee interesting disturbance suppression behaviour by an additional degree of freedom. Tests carried out with a Manutec r2 manipulator with six degrees of freedom have shown clear advantages of the control structures under study.

In this paper, a mathematical representation of constrained robot systems in the form of a differential-algebraic equation model is first considered. This model in modified further to include the joint flexibility between the linkages of the robot, and the actuator dynamics. The objective is to design a feedback control law for the system so that the position output variables (typically the end-effector position) and the force output variables (typically the contact force between the robot's end-effector and the contact surface) of the robot follows the desired position and the desired force trajectories, respectively, despite the presence of joint flexibility and actuator dynamics. A systematic procedure is developed for designing a feedback control law which ensures that the position variables track the desired position trajectories exponentially, and the force variables track the desired force trajectories exponentially. Since the development of the control law is based on the model of a constrained robot system which includes the effects of actuator dynamics and joint flexibility, it is possible to achieve better tracking performance using the force/position control law developed in this paper in cases where such effects are significant.