传统的光电跟踪伺服系统滑模控制中,对目标位移信号微分以求取速度、加速度等运动状态的方法会影响控制的精度和稳定性。针对这一缺点,提出了基于改进容积卡尔曼滤波(CKF)的二阶滑模控制算法。基于系统原理,建立了系统模型;应用限定下界法改进了CKF算法以提高目标状态估计的准确度;应用超螺旋算法设计了二阶滑模控制器,并将滤波预测的目标状态作为系统输入进行仿真实验。结果表明,相对于传统的二阶滑模控制,所设计的控制方法提高了控制精度,减小了抖振,且具有更好的稳定性。

In the process of conventional second-order sliding mode control of electro-optical tracking servo system, the target moving state, such as velocity and acceleration of the target, are obtained from the differentiation of target displacement. It would depress the precision and stability of control system. In response to this defect, a second-order sliding mode control based on improved cubature Kalman filter (CKF) of electro-optical tracking servo system is proposed. The system principle is analyzed, and the system model is set up. To increase estimation accuracy of target state, the CKF algorithm is improved with the method of limiting lower bound. The super-twisting algorithm is used to design the second-order sliding mode controller, and a simulation experiment is finished with the input of predicted target state. The simulation results show that, compared with conventional second-order sliding mode controller, the controller proposed improves the tracking accuracy. It relieves the chattering problem substantially, and enhances the robustness of system.