@article { author = {Moradizirkohi, M. and Izadpanah, S.}, title = {Direct adaptive fuzzy control of flexible-joint robots including actuator dynamics using particle swarm optimization}, journal = {Journal of AI and Data Mining}, volume = {5}, number = {1}, pages = {137-147}, year = {2017}, publisher = {Shahrood University of Technology}, issn = {2322-5211}, eissn = {2322-4444}, doi = {10.22044/jadm.2016.739}, abstract = {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.}, keywords = {Fuzzy System,Particle Swarm Optimization,flexible-joints robot,Actuator Dynamics}, url = {https://jad.shahroodut.ac.ir/article_739.html}, eprint = {https://jad.shahroodut.ac.ir/article_739_f5ed9069b61ee046d9bf176b039d0680.pdf} }