This paper presents an adaptive partial state feedback controller for rigid-link flexible-joint (RLFJ) robots. The controller compensates for parametric uncertainty throughout the entire mechanical system while only requiring measurement of link position and actuator position. To eliminate the need for measuring link velocity and actuator velocity a set of filters is utilized as a surrogate for the unmeasurable quantities. Based on this set of filters, an adaptive integrator backstepping procedure is used to develop a torque input controller which guarantees semiglobal asymptotic link position tracking while also ensuring that all signals remain bounded during closed-loop operation. Simulation results for a two-link RLFJ robot are utilized to validate the performance of the proposed controller.

In this paper, we design an adaptive position/force controller for robot manipulators during constrained motion. The proposed controller can compensate for parametric uncertainty while only requiring measurements of link position and end-effector force. A filtering technique is utilized to produce a pseudo-velocity error signal and thus, eliminate the need for link velocity measurements. The control strategy provides semiglobal asymptotic tracking performance for the end-effector position and the interaction force between the constraint and the end-effector. An experimental implementation of the proposed controller on a two-link planar robot is also presented.

In this paper, we propose a robust output feedback link position tracking controller for the full-order model used to describe rigid-link flexible-joint (RLFJ) robot manipulators. The method uses a bank of dynamic filters, with the link position tracking error as the input, to generate surrogates for the immeasurable system states. One of these generated filter states is then used in the feedback control strategy. The method is distinguished from previous results by the limited amount of modeling information required, the utilization of only link position measurements, and the overall simplicity of the controller. Even though the approach only requires link position measurements, the controller exhibits good robustness properties while ensuring semi-global uniformly ultimately bounded link position tracking.

In this paper, we present a voltage input controller for robot manipulators actuated by induction motors. The control is designed to compensate for the nonlinear dynamics associated with the mechanical subsystem and the electrical subsystems while only requiring measurements of link position, link velocity, stator winding currents, and exact model knowledge. Specifically, through the use of nonlinear observers for rotor flux and an observed integrator backstepping approach, we obtain semiglobal uniform ultimately bounded link position tracking. The result is semiglobal in the sense that a control parameter must be made sufficiently large relative to the electromechanical initial conditions in order to guarantee that control singularities are avoided. To provide insight into the design procedure, the controller is first presented for a one-link robot manipulator system. We then extend the controller from the one-degree of freedom system to the multidegree of freedom system. Experimental results are then presented to illustrate the performance of the proposed approach applied to a one-link robot. Finally, simulation results are presented to illustrate the tracking performance for the proposed controller applied to a two-link robot manipulator system.

In this paper an adaptive partial state feedback controller is designed for rigid-link electrically-driven (RLED) robot manipulators actuated by multi-phase motors. The controller is based on structural knowledge of the electromechanical dynamics of the RLED robot and measurements of link position and electrical winding current in each of the link actuators. The proposed controller is designed to adapt for parametric uncertainty in the electromechanical dynamics while utilizing a dynamic filter to generate link velocity tracking error information. The controller, adaptation laws, and the pseudo-velocity filter are designed via a Lyapunov-like approach, the benefit of which is that at the end of the design procedure, the controller can be mathematically shown to produce semiglobal asymptotic link position tracking.

In this paper, we present an adaptive partial state feedback position/force controller for rigid-link robot manipulators under constrained motion. The proposed controller can compensate for parametric uncertainty while only requiring measurements of link position and end-effector force. The control strategy provides semi-global asymptotic tracking performance for the position of the end-effector and the interaction force between the constraint and the end-effector.