惯性稳定平台单神经元/PID自适应复合控制与参数优化

Single neuron/PID adaptive compound control and parameter optimization for the inertially stabilized platform

针对成像载荷对惯性稳定平台高稳定精度控制的要求,提出一种基于改进型细菌觅食优化算法的单神经元/PID自适应复合控制方法。首先将单神经元与PID控制结合组成单神经元/PID自适应复合控制器,实现惯性稳定平台自适应控制,提高系统控制精度;其次,针对传统试凑法难以获得控制器最优控制参数的不足,采用改进型细菌觅食优化算法对复合控制器进行参数寻优,实现控制参数最优化;最后,对提出方法进行仿真分析和实验验证。实验结果表明:采用参数优化的单神经元/PID自适应复合控制后,稳定平台稳定精度和扰动抑制能力都得到明显提高,静基座和动基座条件下角位置误差分别为0.0038°和0.2904°,与传统PID控制相比分别提高19.1%和39.9%。

To meet the requirements of high stability precision control to an inertially stabilized platform(ISP),a single neuron/proportion integration differentiation(PID)adaptive compound control method based on the improved bacterial foraging optimization algorithm is proposed.Firstly,the single neuron and PID control are fused to formulate a single neuron/PID adaptive controller to realize the adaptive control of ISP.In this way,the control accuracy of the ISP is improved.Secondly,to solve the problem that the optimal parameters of the controller are hard to be achieved by the trial method,an improved bacterial foraging optimization algorithm is used to optimize the parameters of the compound controllers.Finally,simulations and experiments are carried out.Experimental results show that the proposed method can significantly improve the system performance such as stability accuracy and disturbance rejection ability.After utilizing the compound control with parameter optimization,the stabilization accuracy of the platform under the condition of static and dynamic base are 0.0038°and 0.2904°,which are 19.1%and 39.9%higher than the traditional PID control.