惯性稳定平台单神经元/PID自适应复合控制与参数优化

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 0.003 8° and 0.290 4°, which are 19.1% and 39.9% higher than the traditional PID control.