Wang Anning, Feng Xianying, Liu Haiyang, Yao Ming
School of Software, Shandong University, Jinan, 250061, China.
Key Laboratory of High Efficiency and Clean Mechanical Manufacture of Ministry of Education, Shandong University, Jinan, 250061, China.
Sci Rep. 2024 Oct 23;14(1):24976. doi: 10.1038/s41598-024-75598-5.
Nonlinear friction, system uncertainty, and external disturbances have a significant impact on the performance of high-precision servo feed systems. In order to achieve higher tracking accuracy, a sliding mode controller based on a generalized extended state observer with the double critic deep deterministic policy gradient algorithm is designed. Firstly, a flexible two mass drive model (FTMDM) is established for the two-axis differential micro-feed system (TDMS). Next, a generalized extended state observer (GESO) is designed to estimate matched interference and mismatched interference. And it is proved that the observation error of GESO is bounded. A sliding mode controller based on GESO is further proposed. The stability of the controller has been proven through Lyapunov theory, and the error is bounded and converges to zero in finite time. The tuning process of controller parameters is simplified by using quadratic optimal control principle. Furthermore, a double critic deep deterministic policy gradient algorithm (DCDDPG) is proposed to achieve dynamic optimization of parameters about GESO. The simulation results show that GESO with DCDDPG can reduce the observation error of step signal and sinusoidal signal, and improve the observation accuracy of nonlinear friction significantly. Finally, experimental results show that the proposed control method achieves more accurate position tracking performance on TDMS.
非线性摩擦、系统不确定性和外部干扰对高精度伺服进给系统的性能有显著影响。为了实现更高的跟踪精度，设计了一种基于广义扩展状态观测器和双评论家深度确定性策略梯度算法的滑模控制器。首先，为两轴差分微进给系统（TDMS）建立了柔性双质量驱动模型（FTMDM）。其次，设计了广义扩展状态观测器（GESO）来估计匹配干扰和不匹配干扰，并证明了GESO的观测误差是有界的。进一步提出了一种基于GESO的滑模控制器，通过李雅普诺夫理论证明了该控制器的稳定性，且误差有界并在有限时间内收敛到零，利用二次最优控制原理简化了控制器参数的整定过程。此外，提出了双评论家深度确定性策略梯度算法（DCDDPG）来实现GESO参数的动态优化。仿真结果表明，采用DCDDPG的GESO能够减小阶跃信号和正弦信号的观测误差，显著提高非线性摩擦的观测精度。最后，实验结果表明，所提出的控制方法在TDMS上实现了更精确的位置跟踪性能。
