Locomotion Control of a Hydraulically Actuated Hexapod Robot by Robust Adaptive Fuzzy Control with Self-Tuned Adaptation Gain and Dead Zone Fuzzy Pre-compensation |
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Authors: | Ranjit Kumar Barai Kenzo Nonami |
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Affiliation: | (1) Graduate School of Science and Technology, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 2638522, Japan;(2) Department of Mechanical and Electronics Engineering, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 2638522, Japan |
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Abstract: | Hydraulically actuated robotic mechanisms are becoming popular for field robotic applications for their compact design and
large output power. However, they exhibit nonlinearity, parameter variation and flattery delay in the response. This flattery
delay, which often causes poor trajectory tracking performance of the robot, is possibly caused by the dead zone of the proportional
electromagnetic control valves and the delay associated with oil flow. In this investigation, we have proposed a trajectory
tracking control system for hydraulically actuated robotic mechanism that diminishes the flattery delay in the output response.
The proposed controller consists of a robust adaptive fuzzy controller with self-tuned adaptation gain in the feedback loop
to cope with the parameter variation and disturbances and a one-step-ahead fuzzy controller in the feed-forward loop for hydraulic
dead zone pre-compensation. The adaptation law of the feedback controller has been designed by Lyapunov synthesis method and
its adaptation rate is varied by fuzzy self-tuning. The variable adaptation rate helps to improve the tracking performance
without sacrificing the stability. The proposed control technique has been applied for locomotion control of a hydraulically
actuated hexapod robot under independent joint control framework. For tracking performance of the proposed controller has
also been compared with classical PID controller, LQG state feedback controller and static fuzzy controller. The experimental
results exhibit a very accurate foot trajectory tracking with very small tracking error with the proposed controller. |
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Keywords: | Robust adaptive fuzzy control Self-tuned adaptive gain Dead zone pre-compensation One-step-ahead control |
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