针对传统PID控制器由于参数固定而难以满足火箭炮发射架对跟踪精度和抗负载变化能力要求的缺点,文中设计了基于RBF神经网络的PID控制器,首先通过改进的动态资源分配网络算法完成了神经网络结构的设计,然后对神经网络进行简化将其成功应用于DSP处理器中以实时调节PID控制参数。实验结果表明,此控制策略可以有效的提高系统的跟踪精度与抗负载能力。

Traditional PID controller parameters are fixed and difficult to meet the shortcomings of the rockets launchers on the requirements of the tracking accuracy and resistance to load capacity, a PID controller based on RBF neural network was designed. Firstly, by improving the network of dynamic resource allocation algorithm, neural network structure was completed, and then the neural network was simplified to be successfully applied to real-time adjustment of the PID control parameters in the DSP processor. The experimental results show that this control strategy can effectively improve the tracking precision and resistance to load capacity.