基于自抗扰理论的欠驱动AUV无模型自适应路径跟踪控制

Model-Free Adaptive Path Tracking Control Based on Active Disturbance Rejection Control for AUVs

面向自主水下航行器(AUV)精准回收的任务需求,针对AUV运动中模型不确定性、易受环境干扰导致的路径跟踪精度不足的问题,从无模型控制的角度出发,提出了一种适用于AUV的基于自抗扰控制理论的无模型自适应控制(ADRC-MFAC)算法。该算法针对2阶系统模型特性,结合视线角制导重新设计控制输入准则函数对无模型自适应控制(MFAC)进行了改进,解决了MFAC只适用于自衡系统的问题。引入跟踪微分器对期望信号进行指令平滑,考虑未知复合干扰的影响设计了线性扩张状态观测器,在控制器中对估计扰动进行补偿,并证明了所提控制器的稳定性,提升了系统鲁棒性。在同样的干扰情况下,文中控制方案相比传统比例-积分-微分控制器抗干扰能力提升了42.37%,控制精度提高了45%,表明ADRC-MFAC能够明显改善AUV的抗干扰性能,提高路径跟踪精度。

In view of the task requirements of accurate recovery of autonomous undersea vehicles(AUVs),a model-free adaptive control based on the active disturbance rejection control(ADRC-MFAC)algorithm was proposed from the perspective of model-free control,so as to improve the insufficient path tracking accuracy caused by model uncertainty and vulnerability to environmental interference in AUV motion.According to the characteristics of the second-order model system and line-of-sight guidance,the MFAC was improved by redesigning the control input criterion function,solving the problem that MFAC was only applicable to the self-balancing system.A tracking differentiator was introduced to smooth the desired signal,and a linear extended state observer was designed by considering the influence of unknown compound interference.The estimated disturbance was compensated for in the controller.The stability of the controller was verified,and system robustness was improved.Under the same interference,the proposed control scheme could improve the anti-interference ability and control precision by 42.37%and 45%,compared with the traditional proportional-integral-differential controller.The result shows that ADRC-MFAC can significantly improve the anti-interference performance of AUVs and enhance path tracking accuracy.