采用混沌粒子群优化算法(CPSO)对网络初始值进行迭代寻优,加快系统的收敛速度.为了实现PID神经网络的硬件平台搭建,新型纳米器件——自旋忆阻器,由于其独特的记忆特性和纳米级尺寸,被用来模拟电子突触,以实现神经元之间的相互连接.最后,通过对强耦合系统进行解耦控制验证了该方案的有效性. The chaotic particle swarm optimization (CPSO) algorithm is used to optimize the initial value of the network to speed up the convergence of the system.In order to realize the hardware platform construction of PID neural network, a new type of nano-device, spin-memorizer, Properties and nano-scale size are used to simulate electronic synapses to achieve the interconnection between neurons.Finally, the effectiveness of this scheme is verified by decoupling the strongly coupled system.