基于KFESO的多艇分布式协同路径跟踪复合抗扰控制

KFESO based composite anti-disturbance control for distributed coordinated path following of unmanned surface vehicles

  • 摘要: 摘 要:【目的】针对高低频混合多源干扰导致的无人艇(USV)无法准确获取状态信息且跟踪精度低的问题,提出一种基于Kalman滤波联合扩张状态观测器(KFESO)的多艇分布式协同路径跟踪复合抗扰控制方法。【方法】首先,为估计出无人艇各阶状态量以及集总扰动,联合Kalman滤波器构造KFESO。其次,设计分布式状态观测器观测虚拟领航艇速度信息,并根据参考速度估计值以及KFESO输出的位置和速度估计值,基于一致性理论与视线引导律设计运动学协同控制器。在此基础上,利用反步法与动态面控制技术设计动力学抗扰控制器。然后,使用李雅普诺夫稳定性理论证明控制系统下所有误差信号一致最终有界。【结果】仿真结果表明所设计控制方法能够准确获取USV各阶状态,且在高低频混合多源干扰下依然具有良好的跟踪精度与抗干扰能力。【结论】该方法能够缓解ESO在估计速度与精度之间的矛盾,提高多艇协同路径跟踪精度。

     

    Abstract: Abstract:Objectives Aiming at the problem that the USV cannot get the state information accurately and the path tracking precision is low because of the high and low frequency mixed multi-source disturbance, a composite disturbance rejection control method based on extended state observer combined with Kalman filter for multiple USVs distributed formation path following is proposed. Methods Firstly, KFESO is constructed by combining Kalman filter to estimate USV states and lumped disturbances. Secondly, a distributed state observer was designed to observe the speed information of the virtual leader, and a kinematic cooperative controller is designed based on the consistency theory and line-of-sight guiding law according to the estimated reference speed and the position and speed of the KFESO output. On this basis, a dynamic disturbance rejection controller is designed by using backstepping method and dynamic surface control technique. Then, Lyapunov stability theory is used to prove that all error signals in the control system are uniformly ultimately bounded. Results Simulation results show that the proposed control method can accurately obtain states of USV, and still has good tracking accuracy and anti-disturbance ability under the mixed multi-source disturbance of high and low frequency. Conclusions The method can alleviate the contradiction between estimation speed and accuracy in ESO, and improve the accuracy of coordinated path following.

     

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