College of Electro-Mechanical Engineering, Changchun University of Science and Technology, Changchun 130022, China.
Key Laboratory of Airborne Optical Imaging and Measurement, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.
Rev Sci Instrum. 2022 Dec 1;93(12):125003. doi: 10.1063/5.0124203.
Fast steering mirror (FSM) is an efficient and reliable mechanical device in aerial optical image systems for controlling the beam direction with high precision. With the advantages of compact size, high speed, simple structure, and long linear stroke, voice coil motors are ideal actuators for FSM systems. However, model uncertainty can lead to poor performance or even system divergence, especially in environments with temperature variations, electromagnetic environment changes, etc. This paper proposes a novel finite-time adaptive control (FAC) algorithm for an FSM system to obtain high performance, i.e., positioning accuracy, dynamic performance, and robustness. In addition, the finite-time convergence of the controller is analyzed. In the experiments, the controller is implemented in a DSP-based microprocessor. The step response results show that the proposed algorithm has a shorter setting time, smaller overshoot, and smaller steady-state error compared to classical sliding mode control (SMC). The sinusoidal signal tracking accuracy of FAC + SMC has been improved by 19.8%. In addition, as the model uncertainty increases 10%, the root mean square errors (RMSEs) are 1.73″ and 1.18″ for SMC and FAC + SMC, respectively. With 20% model uncertainty, the RMSEs increase to 2.56″ and 1.85″, respectively. Extensive experiments demonstrate the general effectiveness of the proposed algorithm.
快速转向镜（FSM）是航空光学成像系统中一种高效、可靠的机械装置，可用于高精度控制光束方向。音圈电机具有体积小、速度快、结构简单、线性行程长等优点，是 FSM 系统的理想执行器。然而，模型不确定性可能导致性能不佳甚至系统发散，尤其是在温度变化、电磁环境变化等环境中。本文提出了一种用于 FSM 系统的新型有限时间自适应控制（FAC）算法，以获得高性能，即定位精度、动态性能和鲁棒性。此外，还分析了控制器的有限时间收敛性。在实验中，该控制器在基于 DSP 的微处理器上实现。阶跃响应结果表明，与经典滑模控制（SMC）相比，该算法具有较短的设定时间、较小的超调量和较小的稳态误差。FAC+SMC 对正弦信号的跟踪精度提高了 19.8%。此外，当模型不确定性增加 10%时，SMC 和 FAC+SMC 的均方根误差（RMSE）分别为 1.73″和 1.18″。当模型不确定性增加 20%时，RMSE 分别增加到 2.56″和 1.85″。大量实验证明了所提出算法的有效性。
