光电跟踪系统伺服控制算法研究

摘要

Servo control,which plays decisive role in electro-optical tracking system,directly determines the system performance,this essay focus on design a fuzzy neural network algorithm with parameters self-learning and structures self-learning,which have been proved that it has the advantages over traditional PID and fuzzy logic in dynamic and static performances as well as in system robustness by using the insertion SIMULINK in MATLAB,this algorithm improved performances in accuracy and rapidity,and also provide a feasible technical solution for servo control.%伺服控制直接决定了光电跟踪系统的性能,文章采用模糊神经网络控制算法,具有参数学习和结构学习功能,通过Matlab仿真对比发现无论是动态、静态性能还是鲁棒性方面都要优于传统的PID控制以及模糊控制,表现出很好的准确性和快速性,为光电跟踪系统伺服控制设计提供了一种可行的技术方案.