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

• Published in: Journal of AI and data mining Vol. 5; no. 1; pp. 137 - 147
• Main Authors: M. Moradizirkohi, S. Izadpanah
• Format: Journal Article
• Language: English
• Published: Shahrood University of Technology 01.03.2017
• Subjects: Actuator Dynamics; flexible-joints robot; Fuzzy System; Particle Swarm Optimization
• ISSN: 2322-5211; 2322-4444
• DOI: 10.22044/jadm.2016.739

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.