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2 2009

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Dynamic external force feedback loop control of a robot manipulator using a neural compensator - Application to the trajectory following in an unknown environment

100%

Ferguene F. , Toumi R.

tom Vol. 19, no 1

113-126

Force/position control strategies provide an effective framework to deal with tasks involving interaction with the environment. One of these strategies proposed in the literature is external force feedback loop control. It fully employs the available sensor measurements by operating the control action in a full dimensional space without using selection matrices. The performance of this control strategy is affected by uncertainties in both the robot dynamic model and environment stiffness. The purpose of this paper is to improve controller robustness by applying a neural network technique in order to compensate the effect of uncertainties in the robot model. We show that this control strategy is robust with respect to payload uncertainties, position and environment stiffness, and dry and viscous friction. Simulation results for a three degrees-of-freedom manipulator and various types of environments and trajectories show the effectiveness of the suggested approach compared with classical external force feedback loop structures.

Neural network parallel force/position control of robot manipulators under environment and robot dynamics uncertainties

80%

Ferguene F. , Achour N. , Toumi R.

tom Vol. 19, no. 1

93-121

The performance of a parallel force/position controller for robot force tracking is affected by the uncertainties in both the robot dynamics and the environment stiffness. This paper aims to improve the controller's robustness by applying the neural network (NN) technique to compensate for the robot dynamics at the input trajectory level and adaptive feed-forward compensation to cope with variations in the contact environment. A NN control technique is applied to a conventional PID force/position parallel control scheme which is composed of a PD action on position loop and a proposed adaptive I (integral) action on the force loop, which allows a complete use of available sensor measurements by operating the control action in a full dimensional space without using selection matrices. Simulation results for a three degrees-of-freedom robot show that highly robust position/force tracking can be achieved in the presence of a full dynamic robot and large environment stiffness uncertainties.