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基于改进遗传算法的电液伺服系统轨迹控制
引用本文:宋倩玉,冯浩,刘慧勤,周世萱,朱雅利,张亦心,殷晨波. 基于改进遗传算法的电液伺服系统轨迹控制[J]. 液压与气动, 2022, 0(4): 44-50. DOI: 10.11832/j.issn.1000-4858.2022.04.006
作者姓名:宋倩玉  冯浩  刘慧勤  周世萱  朱雅利  张亦心  殷晨波
作者单位:1.南京信息工程大学人工智能学院, 江苏南京 210044;2.南京工业大学挖掘机关键技术联合研究所, 江苏南京 211816;3.三一重机有限公司, 江苏昆山 215300
基金项目:国家自然科学基金(52105064);南京信息工程大学科研启动经费(2021R042);南京信息工程大学大学生创新创业训练计划项目(XJDC202110300350);江苏省科技成果转化资金项目(SBA2020030413)
摘    要:为了提高挖掘机器人电液伺服系统的轨迹精度,首先,建立挖掘机器人电液伺服系统模型;其次,对遗传算法的种群、适应度函数、交叉概率和变异概率进行改进,设计改进遗传算法的PID控制器,在联合仿真平台上进行了仿真研究,用阶跃和斜坡信号评估控制器性能;最后,搭建挖掘机器人轨迹控制实验平台,采用对挖掘机器人精度要求较高的斜坡作业验证控制器性能。结果表明:相比较于传统的PID控制器和经典遗传算法优化的PID控制器,改进遗传算法优化的PID控制器调整时间短,响应快速,实际动作控制时轨迹跟踪误差最小,可用在挖掘机器人实际轨迹控制中。

关 键 词:挖掘机器人  电液伺服系统  轨迹控制  遗传算法  
收稿时间:2021-08-02

Trajectory Control of Electro-hydraulic Servo Systems Based on an Improved Genetic Algorithm
SONG Qian-yu,FENG Hao,LIU Hui-qin,ZHOU Shi-xuan,ZHU Ya-li,ZHANG Yi-xin,YIN Chen-bo. Trajectory Control of Electro-hydraulic Servo Systems Based on an Improved Genetic Algorithm[J]. Chinese Hydraulics & Pneumatics, 2022, 0(4): 44-50. DOI: 10.11832/j.issn.1000-4858.2022.04.006
Authors:SONG Qian-yu  FENG Hao  LIU Hui-qin  ZHOU Shi-xuan  ZHU Ya-li  ZHANG Yi-xin  YIN Chen-bo
Affiliation:1. School of Artificial Intelligence, Nanjing University of Information Science & Technology, Nanjing, Jiangsu210044;2. United Institute of Excavator Key Technology, Nanjing Tech University, Nanjing, Jiangsu211816;3. SANY Group Co., Ltd., Kunshan, Jiangsu215300
Abstract:In order to improve the trajectory accuracy of the robotic excavator electro-hydraulic servo systems, firstly, the mechanism models of the electro-hydraulic servo systems are established. Secondly, the population, fitness function, crossover and mutation probabilities of the genetic algorithm are improved. Simulations are carried out on a co-simulation platform, and the performances of the proposed controller are evaluated with step and ramp signals. Finally, an experimental platform for the trajectory control of the robotic excavator is built, and the performances of the proposed controller is verified by ramp operations with high accuracy. The results show that: compared with the traditional PID and the PID optimized by the classical genetic algorithm, the PID controller optimized by the improved genetic algorithm has shorter adjustment time, fast response, and the smallest trajectory tracking error, which can be used in actual conditions.
Keywords:robotic excavator  electro hydraulic servo system  trajectory control  genetic algorithm  
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