首页> 外文期刊>Smart Materials & Structures >Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control
【24h】

Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control

机译:使用优化的模糊逻辑控制的三层导电聚合物致动器的力控制

获取原文
获取原文并翻译 | 示例
       

摘要

Conducting polymers actuators (CPAs) are potential candidates for replacing conventional actuators in various fields, such as robotics and biomedical engineering, due to their advantageous properties, which includes their low cost, light weight, low actuation voltage and biocompatibility. As these actuators are very suitable for use in micro-nano manipulation and in injection devices in which the magnitude of the force applied to the target is of crucial importance, the force generated by CPAs needs to be accurately controlled. In this paper, a fuzzy logic (FL) controller with a Mamdani inference system is designed to control the blocking force of a trilayer CPA with polypyrrole electrodes, which operates in air. The particle swarm optimization (PSO) method is employed to optimize the controller's membership function parameters and therefore enhance the performance of the FL controller. An adaptive neuro-fuzzy inference system model, which can capture the nonlinear dynamics of the actuator, is utilized in the optimization process. The optimized Mamdani FL controller is then implemented on the CPA experimentally, and its performance is compared with a non-optimized fuzzy controller as well as with those obtained from a conventional PID controller. The results presented indicate that the blocking force at the tip of the CPA can be effectively controlled by the optimized FL controller, which shows excellent transient and steady state characteristics but increases the control voltage compared to the non-optimized fuzzy controllers.
机译:导电聚合物致动器(CPA)由于其优越的性能,包括低成本,轻巧,低致动电压和生物相容性等优点,成为了在各个领域(例如机器人技术和生物医学工程)中替代常规致动器的潜在候选者。由于这些致动器非常适合用于微纳操纵和注射装置,在这些装置中,施加到目标的力的大小至关重要,因此需要精确控制CPA产生的力。本文设计了带有Mamdani推理系统的模糊逻辑(FL)控制器,以控制在空气中工作的带有聚吡咯电极的三层CPA的阻塞力。粒子群优化(PSO)方法用于优化控制器的隶属函数参数,从而提高FL控制器的性能。在优化过程中采用了自适应神经模糊推理系统模型,该模型可以捕获执行器的非线性动力学。然后,将优化的Mamdani FL控制器通过实验在CPA上实现,并将其性能与未优化的模糊控制器以及从常规PID控制器获得的性能进行比较。给出的结果表明,通过优化的FL控制器可以有效地控制CPA尖端的闭锁力,与非优化的模糊控制器相比,该控制器具有出色的瞬态和稳态特性,但增加了控制电压。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号