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-joint robots including actuator dynamics. This design includes two interior loops. The inner loop controls the motor position using the proposed approach, while the outer one controls the joint angle of robots using a proportional-integralderivative (PID) control law. One novelty of this paper is the use of a particle swarm optimization (PSO) algorithm for optimizing the control design parameters in order to achieve the desired performance. It is worthy of note that to form the control law by considering practical considerations, just the available feedbacks are used. It is beneficial for industrial applications, where the 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 the structured and unstructured uncertainties. As a result, all the system states remain bounded. The results of the simulation conducted on a two-link flexible-joint robot show the efficiency of the proposed scheme.