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The controller design is one of the major difficulties in realizing robot-aided rehabilitation program. The purpose of our study is to develop an adaptive impedance force control strategy based on dynamic recurrent fuzzy neural network to maintain the stability of the rehabilitation robot system in the case when the patient's physical condition makes a change. An on-line identification method was...
Aiming at the difficulty of force control in impedance control lies in the unknown parameters of the environment, a reference trajectory generation approach for impedance control is presented, which uses neural networks to estimate the environment parameters. In this method, the environment parameters are estimated by a neural network (NN1), which constructs the relationship between the environment...
This paper describes the use of evolutionary algorithms to find an optimal solution for the parameters of an impedance controller represented as an artificial neural network (ANN). An impedance controller with force tracking capabilities has been evolved using evolutionary strategies which control the forces between a robotic manipulator and the environment. Simulation results show the controllerpsilas...
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