四川轻化工大学学报（自然科学版）2024，Vol.37Issue(1)：51-60,10.DOI:10.11863/j.suse.2024.01.07
基于LESO的轮式移动机器人滑模轨迹跟踪控制
Sliding Mode Trajectory Tracking Control of Wheeled Mobile Robot Based on LESO
摘要
Abstract
Aiming at the trajectory tracking control problem of wheeled mobile robots under the condition of wheel slipping,a control scheme consisting of linear extended state observer(LESO)and integral sliding mode surface has been proposed.First of all,the kinematics model of the wheeled mobile robot is established according to the nonholonomic constraints under the condition of wheel slipping.And the dynamic model of the wheeled mobile robot is established according to the kinetic energy function and Lagrange equation.A mathematical model for wheel torque and speed can be derived by combining these two models.Secondly,the mathematical model is expanded by using LESO,and the total disturbance is estimated.The sliding mode surface with an integral term is designed from the difference between the actual speed and the virtual speed.The dynamic controller is designed by combining the disturbance estimation feedforward with the sliding mode surface and the convergence of velocity tracking error in finite time is proved.Finally,the proposed scheme is compared with the simulation of the control scheme based on the super-twisting disturbance observer.The simulation results show that the angular velocity tracking error of the proposed scheme tends to zero curve when it is about 1 s.The wheel torques are stable at about 3 N·m,and the waveforms have no sawtooth jitter.The disturbance error fluctuates less within 1～5 s,and there is no jitter in the waveform within 5～20 s.The simulation results show that the proposed scheme has better tracking effect,stronger anti-interference ability and higher observation accuracy.关键词
轮式移动机器人/轨迹跟踪/车轮打滑/线性扩张状态观测器/滑模控制Key words
wheeled mobile robot/trajectory tracking/wheel slipping/linear extended state observer/sliding mode control分类
信息技术与安全科学引用本文复制引用
罗淇,陈昌忠,刘鑫..基于LESO的轮式移动机器人滑模轨迹跟踪控制[J].四川轻化工大学学报（自然科学版）,2024,37(1):51-60,10.基金项目
国家自然科学基金项目(61902268) （61902268）
人工智能四川省重点实验室开放基金项目(2020RYJ05) （2020RYJ05）
