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 P...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Shahrood University of Technology
2017-03-01
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| Series: | Journal of Artificial Intelligence and Data Mining |
| Subjects: | |
| Online Access: | http://jad.shahroodut.ac.ir/article_739_f5ed9069b61ee046d9bf176b039d0680.pdf |
| Summary: | 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. |
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| ISSN: | 2322-5211 2322-4444 |