二轮平衡车的神经元控制算法及仿真

通过在MATLAB-Simulink-Simscape中搭建二轮平衡车的仿真物理模型和控制系统，直观、快速地验证控制算法的效果。使用神经元PID控制算法替代传统PID控制算法设计神经元PD平衡控制器、神经元PI速度控制器，并在此基础上组合成二轮平衡车的神经元PID控制系统。通过实验对比神经元PID控制算法与传统的PID控制算法的控制效果，验证了神经元PID控制算法具有更高的控制精度、更强的抗干扰能力、更快的响应速度，能及时适应模型的非线性变化。

Neural Control Algorithm and Simulation of Two-Wheel Balancing Vehicle

Through building the simulation physical model and control system of the two-wheel balancing vehicle in MATLAB-Simulink-Simscape, the effect of the control algorithm was verified intuitively and quickly. Neuronal PD balance controller and neuronal PI speed controller were designed by using neuronal PID control algorithm instead of traditional PID control algorithm, the neuronal PID control system of two-wheel balancing vehicle was combined on this basis. The control effect of neuronal PID control algorithm was compared with the traditional PID control algorithm through experiment. It is verified that the neuronal PID control algorithm has higher control accuracy, stronger anti-interference ability, faster response speed, and can adapt to the nonlinear changes of the model in time.