摘要
针对移动机器人反演轨迹跟踪控制中的速度跳变与速度跟踪问题,提出一种采用生物膜电压模型和反演滑模方法的移动机器人生物启发式变结构轨迹跟踪控制系统。首先基于移动机器人的运动学模型建立位姿跟踪回路,即利用生物启发式膜电压模型获取虚拟的位姿误差信号,并结合Lyapunov函数设计反演控制器来解决速度跳变;然后考虑移动机器人的动力学模型设计速度跟踪回路,构造基于组合趋近律的滑模变结构力矩控制器来保证速度跟踪;接下来,根据Lyapunov理论对所提系统的稳定性进行证明;最后,以iRobot Create移动机器人为控制对象进行直线、圆和折线轨迹跟踪控制的仿真研究。通过分析比较初始阶段和拐点处的跟踪误差、速度和力矩,验证了所提系统的有效性。
To address both velocity-jump and velocity-tracking problems in back-stepping trajectory tracking control for mobile robots,a biologically inspired variable structure trajectory tracking control system based on biological membrane voltage model and back-stepping sliding mode methods is proposed.By constructing posture tracking loop based on kinematics,virtual posture errors were firstly obtained by using the bio-inspired membrane voltage model and the back-stepping controller was designed by choosing a Lyapunov function to solve the velocity-jump problem.Secondly,designing velocity-tracking loop based on dynamic model,a combined asymptotic law was utilized to construct a sliding mode variable structure torque controller,which guarantees the velocity-tracking.The stability of the hybrid control system was proved by Lyapunov functions.Finally,straight line,circular path and polyline were used as the desired paths in the simulation experiments which were carried out on iRobot Create to verify the performance of the proposed control system.Through comparing tracking errors,velocities and torques at the initial stage and turning points,the effectiveness of the proposed system is demonstrated.
作者
马晓敏
刘丁
辛菁
张友民
MA Xiao-min1,2 , LIU Ding1 , XIN Jing1 , ZHANG You-min2(1. Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi'an University of Technology, Xi'an 710048, China; 2. Department of Mechanical,Industrial and AerosjDace Engineering, Concordia University,Montreal H3G1M82,Canad)
出处
《电机与控制学报》
EI
CSCD
北大核心
2018年第7期97-106,共10页
Electric Machines and Control
基金
国家自然科学基金(61573282)
陕西省自然科学基金(2016JM6006)
国家留学基金委资助(201508610098)
关键词
移动机器人
生物膜电压模型
轨迹跟踪
反演控制
滑模变结构
mobile robot
biological membrane voltage model
trajectory tracking
back-stepping
sliding mode variable structure