液压四足机器人足端的力预测控制与运动平稳性  

Predictive Control of Plantar Force and Motion Stability of Hydraulic Quadruped Robot

作　　者：李冰 张永德[1] 袁立鹏[2] 朱光强 代雪松 苏文海[3] LI Bing;ZHANG Yongde;YUAN Lipeng;ZHU Guangqiang;DAI Xuesong;SU Wenhai(School of Mechanical and Power Engineering,Harbin University of Science and Technology,Harbin,150080;School of Mechatronics Engineering,Harbin Institute of Technology,Harbin,150001;College of Engineering,Northeast Agricultural University,Harbin,150030)

机构地区：[1]哈尔滨理工大学机械动力工程学院,哈尔滨150080 [2]哈尔滨工业大学机电工程学院,哈尔滨150001 [3]东北农业大学工程学院,哈尔滨150030

出　　处：《中国机械工程》2021年第5期523-532,共10页China Mechanical Engineering

基　　金：国家自然科学基金(51675142);国家科技支撑计划(2013BAH57F01);黑龙江省自然科学基金(ZD2018013)。

摘　　要：针对液压四足机器人在坚硬路面行走时,足端位置易受刚性冲击,导致运动姿态平稳性差的问题,提出一种液压四足机器人足端力预测控制方法。在分析液压四足机器人结构的基础上,根据运动学与力学模型构建了液压伺服系统的力控制模型;采用改进自适应布谷鸟优化BP神经网络算法建立足端力预测控制模型,通过仿真对比分析验证了该算法的可行性。最后通过液压四足机器人KL样机进行足端力及刚性地面行走测试,结果表明该方法能有效增强液压四足机器人腿部的力柔顺性,提高运动姿态平稳性。Aiming at the problem that plantar position of hydraulic quadruped robot is susceptible to rigid impacts when walking on hard roads,which is resulted in poor motion posture stability,a method for predicting plantar force of the hydraulic quadruped robot was proposed.On the basis of analyzing structure of the hydraulic quadruped robot,a force control model of hydraulic servo system according to kinematics and mechanics model was constructed.Then,an improved adaptive cuckoo optimized BP neural network algorithm was used to establish plantar force predictive control model,feasibility of the algorithm was verified with simulation and comparative analysis.Finally,a KL prototype of the hydraulic quadruped robot was used to test for the plantar force of rigid ground walking.The results show that the method may effectively enhance leg flexibility of the hydraulic quadruped robot and improve stability of motion posture.

关 键 词：液压四足机器人 预测控制 布谷鸟算法 BP神经网络 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]