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Leg compliance control of hexapod robot based on adaptive-fuzzy control |
ZHU Ya-guang, JIN Bo, LI Wei |
The State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, China |
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Abstract Considering the compliance control problem of hexapod robot under different environment, a control strategy based on the adaptive-fuzzy control algorithm was raised. Based on the model of robot structure and impedance control, the indirect adaptive control algorithm was derived. And through the analysis of its parameters, it could be noticed that the algorithm does not meet the requirements of the robot compliance control in a complex environment. According to this situation, the fuzzy control algorithm was used to modify the parameters of adaptive control and satisfied system response could be obtained based on the adjustment in real time according to the difference between input and output. The comparative analysis of traditional indirect adaptive control and the improved adaptive-fuzzy control algorithm was presented. It can be verified that not only desired contact force can be tracked when the environmental parameters are changing, but also small contact impact and high steady-state accuracy can be guaranteed under the fluctuations in the body height. The control strategy has great significance to enhance the adaptability of the hexapod robot.
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Published: 01 August 2014
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基于自适应-模糊控制的六足机器人单腿柔顺控制
针对六足机器人在不同环境下进行柔顺控制的问题,提出一种基于自适应-模糊控制算法的腿部柔顺控制策略.在建立六足机器人结构模型和阻抗控制模型的基础上,推导间接自适应控制算法,并通过对该算法参数进行分析,得知该算法并不能满足在复杂环境下机器人脚力控制的要求.根据这一情况提出自适应-模糊控制算法,运用模糊控制算法对自适应控制参数进行修正,根据输入与输出的差异关系实时调整参数以得到满意的系统响应.通过对传统的间接自适应控制和改进后自适应-模糊控制算法的比较分析,结果表明,改进后的算法不仅在环境参数发生变化时能够很好跟随期望接触力,而且在躯体高度波动的情况下依然能够保证较小的接触冲击力和较高的稳态精度.这对于提高六足机器人的适应性有着重要意义.
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