全向移动机器人的神经滑模自适应PD跟踪控制  

Neural Sliding Mode Adaptive PD Tracking Control of Omnidirectional Mobile Robots

作　　者：张凯文 李国丽[1,2] 许家紫 王群京[1,2] 文彦[1,2] Zhang Kaiwen;Li Guoli;Xu Jiazi;Wang Qunjing;Wen Yan(School of Electrical Engineering and Automation,Anhui University,Hefei 230601,China;National Engineering Laboratory of Energy-saving Motor&Control Technique,Anhui University,Hefei 230601,China)

机构地区：[1]安徽大学电气工程与自动化学院,安徽合肥230601 [2]安徽大学高节能电机及控制技术国家地方联合实验室,安徽合肥230601

出　　处：《机械传动》2023年第11期9-13,21,共6页Journal of Mechanical Transmission

基　　金：国家自然科学基金重点项目(51637001)。

摘　　要：针对四轮全向机器人数学模型中未知因数的干扰,提出了一种基于神经滑模的比例微分(Proportional plus Derivative,PD)自适应跟踪控制策略。首先,对机器人的动力学模型进行分析;其次,利用反步轨迹跟踪控制器得到虚拟速度,基于虚拟输入与实际输入的误差设计PD控制器;接着,采用神经网络来逼近动力学模型中的不确定性,并利用Lyapunov定理证明了系统的稳定性。仿真和实验结果表明,该控制策略具有有效性。A proportional plus derivative(PD)adaptive tracking control strategy based on neural sliding mode is proposed for the interference of unknown factors in the mathematical model of four-wheel omnidirectional robots.Firstly,the dynamics model of the robot is analyzed.Secondly,the backstepping trajectory tracking controller is used to obtain the virtual velocity,and the PD controller is designed based on the error between the virtual input and the actual input.Then,the neural network is used to approximate the uncertainty in the dynamics model,and the stability of the system is proved by the Lyapunov theorem.Simulation and experimental results show that the control strategy is effective.

关 键 词：轨迹跟踪 全向移动机器人 神经网络自适应控制 PD控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] TP242[自动化与计算机技术—控制科学与工程]