direct adaptive fuzzy control of flexible-joint robots including actuator dynamics using particle swarm optimization

in this paper a novel direct adaptive fuzzy system is proposed to control flexible-joints robot including actuator dynamics. the design includes two interior loops: the inner loop controls the motor position using proposed approach while the outer loop controls the joint angle of the robot using a pid control law. one novelty of this paper is the use of a pso algorithm for optimizing the control design parameters to achieve a desired performance. it is worthy of note that to form control law by considering practical considerations just the available feedbacks are used. it is beneficial for industrial applications wherethe real-time computation is costly. the proposed control approach has a fast response with a good tracking performance under the well-behaved control efforts. the stability is guaranteed in the presence of both structured and unstructured uncertainties. as a result, all system states are remained bounded. simulation results on a two-link flexible-joint robot show the efficiency of the proposed scheme.