多神经元神经网络算法的DSP无人侦察车伺服控制系统

提出一种改进型多神经元神经网络算法的DSP无人侦察车伺服控制系统，对多神经元PID控制器进行交叉并联构建并在DSP中运行，解决国内无人侦察车单片机伺服控制系统数据处理速度慢、设计不灵活、智能算法应用受限问题.结果表明该方法收敛速度快、无需人工干预实现自主调节系统被控量，仿真及试验验证了算法的有效性，为无人侦察车应用于战场侦察、突发灾害紧急救援等提供理论基础和借鉴. 

A Multi-Neuron Neural Network Algorithm for DSP Servo Control System of Unmanned Reconnaissance Vehicle

To solve the problem of slow data processing speed, inflexible design and application restriction of intelligent algorithm in domestic single-chip servo control system, a new method was proposed based on an improved multi-neuron neural network algorithm for DSP servo control system of the unmanned reconnaissance vehicle. The multi-neuron PID controller was constructed in a parallel connection and intercross form, and operated in DSP. Experiment and simulation results show that the method can converge quickly and can realize self-adjusting of the system controlled quantity without human intervention, validating the validity of the algorithm. The basic research provides a theoretical basis and a reference for further application of the unmanned reconnaissance vehicle in battlefield reconnaissance and emergency rescue of unexpected disasters.