Single Neuron Adaptive PID Control of Seeker Stabilized Platform Speed Loop

摘要：

　　In order to effectively improve the dynamic performance of the seeker stable platform speed loop control system,a single neuron adaptive PID control method is proposed.Because the single neuron network has the characteristics of simple structure and self-learning,it can be combined with classic PID control to achieve adaptive parameter tuning.At the same time,this paper introduces the idea of quadratic performance index in the optimal control theory,and designs an improved single neuron adaptive PID control algorithm.Classical PID control,single neuron adaptive PID control and improved single neuron adaptive PID control method were used to simulate the speed loop control system of seeker stable platform.The results show that the improved single neuron adaptive PID control algorithm can not only adjust the adaptive parameters,but also has strong robustness and anti-jamming performance.

关键词： Seeker stable platform single neuron network PID controller adaptive parameter tuning quadratic performance index

作者: Bin Pu Jing Wang Huhai Jiang

作者单位: South-west institute of technical physics,Chengdu,610041,China

会议类型: 国际会议

会议名称: 2020 5th International Workshop on Materials Engineering and Computer Sciences 2020年第五届材料工程和计算机科学国际研讨会(IWMECS 2020)

会议地点: 重庆

会议语种:英文

页码: 12-19

在线出版日期: 2020-05-30（万方平台首次上网日期，不代表论文的发表时间）