河南工程学院学报（自然科学版）

通过对仿生机器人机电控制设计的优化提高仿生机器人电动机运行的稳定性和可靠性,提出了一种基于变结构PID模糊神经网络的仿生机器人机电控制算法.仿生机器人机电控制单元模型主要由DC/AC逆变器模型、微型同步电动机、内环控制器模型和电压外环控制器模型组成.采用变结构的前向三层自适应PID神经网络模型为学习器,实现了机器人机电控制算法的优化设计.仿真结果表明,采用该方法进行仿生机器人的机电控制,输出状态响应的稳健性较好、适应度较高,有较好的控制品质.

The mechanical and electrical control design of the bionic robot is researched,the stability and reliability of the operation of the motor is improved. An electromechanical control algorithm based on variable structure PID fuzzy neural network is proposed.The electromechanical control unit model of the bionic robot is mainly composed of the DC / AC inverter model,the miniature synchronous motor,the inner loop controller model and the voltage outer loop controller. An adaptive PID neural network model with variable structure is adopted as a learning device to realize the optimal design of the robot mechanical and electrical control algorithm. The simulation results show that the method is used to control the mechanical and electrical control of the bionic robot,the output of the output of the state response is better,the degree of adaptability is higher,and the control quality is satisfied.