LS-SVM Based Modeling and Model Predictive Control for a Water-Hydraulic Artificial Muscle Actuator

被引：4
|
作者：
Kawahara Y. [1 ]
Kosaki T. [1 ]
Li S. [1 ]
机构：
[1] Department of Systems Engineering, Graduate School of Information Sciences, Hiroshima City University
来源：
SICE Journal of Control, Measurement, and System Integration | 2020年 / 13卷 / 03期
关键词：
artificial muscle actuator; hysteresis; least squares support vector machine; model predictive control; water-hydraulic system;
D O I：
10.9746/jcmsi.13.114
中图分类号：
学科分类号：
摘要：
Artificial muscle actuators (AMAs) driven by the pressure of tap water are flexible and lightweight and are therefore safe for humans and suitable for wearable power-assist devices. This paper proposes a modeling approach for a water-hydraulic AMA based on least squares support vector machines (LS-SVMs). Modeling tests are carried out on this LS-SVM approach with experimentally acquired data and show that the proposed model can capture the hysteretic characteristics of the water-hydraulic AMA. In addition, we constructed a state-space model of the water-hydraulic AMA into which the proposed LS-SVM-based model was incorporated and propose a model predictive control system based on the state-space model. An experimental comparison of the proposed control system and a control system with an inverse model of the water-hydraulic AMA, used in our previous study, demonstrated that the proposed one exceeds the previous one in control performance. © Taylor & Francis Group, LLC 2020.
引用
收藏
页码：114 / 121
页数：7
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