基于自适应反演滑模的全向AGV运动控制

Motion Control for Omnidirectional AGV Based on Adaptive Backstepping Sliding Mode Control

为了提高全向自动导引车(Automatic Guide Vehicle,AGV)的运动控制精度,提出了一种基于自适应反演滑模的全向AGV运动控制算法。首先建立了基于麦克纳姆轮的全向AGV运动学及动力学模型;然后设计了反演滑模全向AGV控制律;接着在此基础上引入了自适应控制律,设计出基于自适应反演滑模的全向AGV控制律,并证明了其稳定性。在施加复杂干扰的情况下,多种路径下的轨迹跟踪仿真表明,与PID算法、反演滑模算法和模糊自适应滑模算法相比,文中运动控制算法的轨迹跟踪误差最小,验证了算法的有效性和优越性。而圆形轨迹跟踪性能分析表明,文中运动控制算法的跟踪误差不仅小而且输出抖动大幅减弱,从而进一步验证了文中控制律的有效性。

In order to improve the motion control accuracy of omnidirectional AGV, an adaptive backstepping sliding mode control algorithm is proposed in this paper. First, the kinematics and dynamics models of an omnidirectional AGV with Mecanum wheels was established. Second, a backstepping sliding mode control law of the omnidirectional AGV was designed. Then an adaptive control law was introduced to design an adaptive backstepping sliding mode control algorithm of the omnidirectional AGV, and its stability was proved. The simulation experiments for trajectory tracking of various paths under complex disturbance show that compared with PID algorithm, backstepping sliding mode algorithm and fuzzy adaptive sliding mode algorithm, the tracing errors of the proposed control algorithm are the smallest, which verifies its validity and superiority. The performance analysis of circle trajectory tracking shows that the position error of the omnidirectional AGV based on the proposed algorithm is small, and also the output jitter is greatly weakened, which further verifies the effectiveness of the proposed control law.