Single Neuron Adaptive PID Control of Seeker Stabilized Platform Speed Loop
Download as PDF
Bin Pu, Jing Wang and Huhai Jiang
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.
Seeker stable platform, single neuron network, PID controller, adaptive parameter tuning, quadratic performance index