An optimal control strategy for hybrid actuator systems: Application to an artificial muscle with electric motor assist
An optimal control strategy for hybrid actuator systems: Application to an artificial muscle with electric motor assist
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DOI：
10.1016/j.neunet.2017.12.010
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发表时间：
2018-03-01
期刊：
影响因子：
7.8
通讯作者：
Morimoto, Jun
中科院分区：
文献类型：
--
作者：
Ishihara, Koji;Morimoto, Jun
人类使用多块肌肉来产生肘部运动等关节运动。使用多个轻便、柔顺的执行器，还可以有效地产生关节运动。类似地，机器人可以使用多个致动器来有效地产生一个自由度的运动。对于这种运动，所需的关节扭矩必须适当地分配给每个执行器。解决这种扭矩分配问题的一种方法是最优控制方法。然而，求解每个控制时间步长的最优控制问题，由于其计算量大，一直被认为不是一种实用的方法。本文提出了一种计算高效的方法来推导由多个执行器组成的混合执行器系统的最优控制策略，其中每个执行器具有不同的动力学特性。我们研究了一个混合执行器模型的奇异摄动系统，它将原始的大规模控制问题细分为较小的子问题，以便在每个控制时间步长得到每个执行器的最优控制输出，并将我们提出的方法应用到我们的气电混合执行器系统中。该方法通过解决实时最优控制问题的困难，推导出了混合执行器的力矩分配策略。(三)2017年提交人(S)。爱思唯尔有限公司出版。
Humans use multiple muscles to generate such joint movements as an elbow motion. With multiple lightweight and compliant actuators, joint movements can also be efficiently generated. Similarly, robots can use multiple actuators to efficiently generate a one degree of freedom movement. For this movement, the desired joint torque must be properly distributed to each actuator. One approach to cope with this torque distribution problem is an optimal control method. However, solving the optimal control problem at each control time step has not been deemed a practical approach due to its large computational burden. In this paper, we propose a computationally efficient method to derive an optimal control strategy for a hybrid actuation system composed of multiple actuators, where each actuator has different dynamical properties. We investigated a singularly perturbed system of the hybrid actuator model that subdivided the original large-scale control problem into smaller subproblems so that the optimal control outputs for each actuator can be derived at each control time step and applied our proposed method to our pneumatic-electric hybrid actuator system. Our method derived a torque distribution strategy for the hybrid actuator by dealing with the difficulty of solving real-time optimal control problems. (c) 2017 The Author(s). Published by Elsevier Ltd.