首页> 外文期刊>International Journal of Intelligent Systems Technologies and Applications >Tracking control of a 3-DOF rehabilitation robot actuated by pneumatic muscle actuators using adaptive self-organising fuzzy sliding mode control
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Tracking control of a 3-DOF rehabilitation robot actuated by pneumatic muscle actuators using adaptive self-organising fuzzy sliding mode control

机译:使用自适应自组织模糊滑模控制的气动肌肉执行器驱动的3自由度康复机器人的跟踪控制

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摘要

The action of a pneumatic muscle actuator (PMA) is very similar to that of animal skeletal muscle. It also has other advantages such as high power/weight ratio, high power/volume ratio, low price, little maintenance needed, great compliance and inherent safety. Therefore, it can be suitably applied to rehabilitation engineering for persons with neuromuscular or musculoskeletal pathologies affecting extremity functions. However, excellent control performance can hardly be achieved by classical control methods because gas compression and non-linear elasticity of bladder containers cause parameter variations. An adaptive self-organising fuzzy sliding mode control (ASOFSMC) is developed in this study to improve end-effector tracking performance. The use of a fuzzy sliding surface can reduce the number of fuzzy rules required. A self-organising learning mechanism is employed to modify online fuzzy rules. An adaptive law is adopted to adjust scaling factors, Finally, Lyapunov theorem is employed to prove the stability of the ASOFSMC. Experimental results show that this control strategy can achieve excellent tracking performance.
机译:气动肌肉促动器(PMA)的作用与动物骨骼肌非常相似。它还具有其他优势,例如高功率/重量比,高功率/体积比,低廉的价格,很少的维护需求,良好的兼容性和固有的安全性。因此,它可以适当地应用于患有神经肌肉或肌肉骨骼病变而影响四肢功能的人的康复工程。但是,经典的控制方法几乎无法获得出色的控制性能,因为气囊容器的气体压缩和非线性弹性会导致参数变化。本研究开发了一种自适应自组织模糊滑模控制(ASOFSMC),以提高末端执行器的跟踪性能。使用模糊的滑动表面可以减少所需的模糊规则的数量。自组织学习机制用于修改在线模糊规则。采用自适应律调整比例因子,最后利用李雅普诺夫定理证明了ASOFSMC的稳定性。实验结果表明,该控制策略可以获得很好的跟踪性能。

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