未知环境下水下机械手智能抓取的自适应阻抗控制
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摘要
为了满足水下机械手在未知环境下对目标抓取的多样性,保证抓住、抓牢并最大限度地避免目标损伤,提出了自适应阻抗控制方法.构建了基于位置的阻抗模型的力跟踪控制系统,采用递推最小二乘法辨识目标的阻抗参数,根据阻抗参数与机械手的运动特征,利用模糊推理方法在线调整抓取力的期望值,并根据期望抓取力与实际抓取力的误差设计自适应比例-积分-微分(PID)控制器来调整期望位置,以实现在跟踪目标位置的同时对期望抓取力信号的跟踪,并利用MATLAB/Simulink软件平台进行仿真实验.结果表明:自适应阻抗控制方法在自由空间和约束空间均具有良好的力、位移的跟踪性能;对期望抓取力的实时调整满足抓取目标的多样性,期望位置的自适应调整能够实现对期望抓取力的跟踪.
In order to realize the diversity of the unknown environment target capture of underwater manipulator, the adaptive impedance control method is proposed to ensure grasping, holding and minimizing the damage of the target. A force tracking control system based on position impedance model is established, and the target impedance parameter is identified by recursive least square method, and the expected value of grasping force is adjusted online according to the impedance parameter and the manipulator motion characteristic with fuzzy inference. According to the expectation force and grasping force error, the adaptive PID controller adjusts the desired position, realizes the tracking of different expected force signals while tracking the target position, and realizes the simulation verification on the MATLAB/Simulink platform. The results show that the adaptive impedance control has good force and displacement tracking performance in free space and constrained space. The realtime expectation force adjustment satisfies the diversity of grasping target, and the adaptive adjustment of the desired position realizes the tracking of the desired force.
In order to realize the diversity of the unknown environment target capture of underwater manipulator, the adaptive impedance control method is proposed to ensure grasping, holding and minimizing the damage of the target. A force tracking control system based on position impedance model is established, and the target impedance parameter is identified by recursive least square method, and the expected value of grasping force is adjusted online according to the impedance parameter and the manipulator motion characteristic with fuzzy inference. According to the expectation force and grasping force error, the adaptive PID controller adjusts the desired position, realizes the tracking of different expected force signals while tracking the target position, and realizes the simulation verification on the MATLAB/Simulink platform. The results show that the adaptive impedance control has good force and displacement tracking performance in free space and constrained space. The realtime expectation force adjustment satisfies the diversity of grasping target, and the adaptive adjustment of the desired position realizes the tracking of the desired force.
引文
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[10] 朱雅光, 金波, 李伟. 基于自适应-模糊控制的六足机器人单腿柔顺控制[J]. 浙江大学学报(工学版), 2014, 48(8): 1419-1426. ZHU Yaguang, JIN Bo, LI Wei. Leg compliance control of hexapod robot based on adaptive-fuzzy control[J]. Journal of Zhejiang University (Engineering Science), 2014, 48(8): 1419-1426.
[11] 张永昌, 蔡倩, 彭玉宾, 等. 带参数辨识功能的三电平变换器高效模型预测控制方法[J]. 电气工程学报, 2018, 13(4): 1-10. ZHANG Yongchang, CAI Qian, PENG Yubin, et al. An efficient model predictive control for three-level converters with the function of parameter identification[J]. Journal of Electrical Engineering, 2018, 13(4): 1-10.
[12] 徐国政, 宋爱国, 李会军. 基于模糊推理的上肢康复机器人自适应阻抗控制[J]. 东南大学学报(自然科学版), 2009, 39(1): 156-160. XU Guozheng, SONG Aiguo, LI Huijun. Fuzzy-based adaptive impedance control for upper-limb rehabilitation robot[J]. Journal of Southeast University (Natural Science Edition), 2009, 39(1): 156-160.
[13] SERAJI H. Adaptive admittance control: An approach to explicit force control in compliant motion[C]//IEEE International Conference on Robotics and Automation. San Diego, USA: IEEE, 2002: 2705-2712.
[2] 姬伟, 罗大伟, 李俊乐, 等. 果蔬采摘机器人末端执行器的柔顺抓取力控制[J]. 农业工程学报, 2014, 30(9): 19-26. JI Wei, LUO Dawei, LI Junle, et al. Compliance grasp force control for end-effector of fruit-vegetable picking robot[J]. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(9): 19-26.
[3] 文忠, 钱晋武, 沈林勇, 等. 基于阻抗控制的步行康复训练机器人的轨迹自适应[J]. 机器人, 2011, 33(2): 142-149. WEN Zhong, QIAN Jinwu, SHEN Linyong, et al. Trajectory adaptation for impedance control based walking rehabilitation training robot [J]. Robot, 2011, 33(2): 142-149.
[4] ROVEDA L, IANNACCI N, VICENTINI F, et al. Optimal impedance force-tracking control design with impact formulation for interaction tasks[J]. IEEE Robotics and Automation Letters, 2016, 1(1): 130-136.
[5] HOGAN N. Impedance control: An approach to manipulation[C]//American Control Conference. San Diego, USA: IEEE, 1984: 304-313.
[6] JUNG S, HSIA T C, BONITZ R G. Force tracking impedance control for robot manipulators with an unknown environment: Theory, simulation, and experiment[J]. The International Journal of Robotics Research, 2001, 20(9): 765-774.
[7] 王学林, 肖永飞, 毕淑慧, 等. 机器人柔性抓取试验平台的设计与抓持力跟踪阻抗控制[J]. 农业工程学报, 2015, 31(1): 58-63. WANG Xuelin, XIAO Yongfei, BI Shuhui, et al. Design of test platform for robot flexible grasping and grasping force tracking impedance control[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(1): 58-63.
[8] DONG J H, SANG O S, LEE J, et al. High speed trot-running: Implementation of a hierarchical controller using proprioceptive impedance control on the MIT cheetah[J]. International Journal of Robotics Research, 2014, 33(11): 1417-1445.
[9] 李杰, 韦庆, 常文森, 等. 基于阻抗控制的自适应力跟踪方法[J]. 机器人, 1999, 21(1): 23-29. LI Jie, WEI Qing, CHANG Wensen, et al. Adaptive force tracking in impedance control[J]. Robot, 1999, 21(1): 23-29.
[10] 朱雅光, 金波, 李伟. 基于自适应-模糊控制的六足机器人单腿柔顺控制[J]. 浙江大学学报(工学版), 2014, 48(8): 1419-1426. ZHU Yaguang, JIN Bo, LI Wei. Leg compliance control of hexapod robot based on adaptive-fuzzy control[J]. Journal of Zhejiang University (Engineering Science), 2014, 48(8): 1419-1426.
[11] 张永昌, 蔡倩, 彭玉宾, 等. 带参数辨识功能的三电平变换器高效模型预测控制方法[J]. 电气工程学报, 2018, 13(4): 1-10. ZHANG Yongchang, CAI Qian, PENG Yubin, et al. An efficient model predictive control for three-level converters with the function of parameter identification[J]. Journal of Electrical Engineering, 2018, 13(4): 1-10.
[12] 徐国政, 宋爱国, 李会军. 基于模糊推理的上肢康复机器人自适应阻抗控制[J]. 东南大学学报(自然科学版), 2009, 39(1): 156-160. XU Guozheng, SONG Aiguo, LI Huijun. Fuzzy-based adaptive impedance control for upper-limb rehabilitation robot[J]. Journal of Southeast University (Natural Science Edition), 2009, 39(1): 156-160.
[13] SERAJI H. Adaptive admittance control: An approach to explicit force control in compliant motion[C]//IEEE International Conference on Robotics and Automation. San Diego, USA: IEEE, 2002: 2705-2712.