Tremor suppression for 4-DOFs biodynamic hand model using genetic algorithm

A. As’arry, K. A. Rezali, N. A. A. Jalil, R. Samin, Z. A. Zulkefli, M. Zain
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Abstract

A person who has severe hand tremor will have difficulty in doing specific tasks such as eating, combing or holding any objects. Currently, there is no medication that can cure the tremor. Thus, this study proposes the active tremor control, in which an intelligent controller is applied to suppress the hand tremor. The main objective is to optimise the proportional-integral (PI) controller using genetic algorithm (GA). A linear voice coil actuator (LVCA) is applied onto a four degree of freedom (4-DOF) human hand model represented in state space. The findings of the study demonstrate that the PI controller optimised by GA gives excellent performance in reducing the tremor error. Based on the frequency evaluation, the PI controller performance was roughly around 84% in reducing the peak of simulated hand tremor. The outcomes provide an important contribution towards achieving novel methods in suppressing hand tremor model by means of intelligent control.
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基于遗传算法的四自由度生物动力学手部模型震颤抑制
患有严重手抖的人会很难完成特定的任务,比如吃饭、梳洗或拿东西。目前,还没有治疗震颤的药物。因此,本研究提出了主动震颤控制,其中应用智能控制器来抑制手部震颤。主要目标是使用遗传算法(GA)优化比例积分(PI)控制器。将线性音圈致动器(LVCA)应用于状态空间中表示的四自由度(4-DOF)人手模型。研究结果表明,通过遗传算法优化的PI控制器在降低抖动误差方面具有良好的性能。基于频率评估,PI控制器在降低模拟手抖峰值方面的性能约为84%。这些结果为实现通过智能控制抑制手抖模型的新方法做出了重要贡献。
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来源期刊
International Journal of Advanced Mechatronic Systems
International Journal of Advanced Mechatronic Systems Engineering-Mechanical Engineering
CiteScore
1.20
自引率
0.00%
发文量
5
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