This paper proposed a control method for the single manipulator of control based on RBF neural network model.RBF neural network,the radial basis function,is a threelayer feedforward network with single hidden layer.Its mapping is nonlinear from input space to the output space,but from the hidden layer to the output space,its mapping presents linear space,and because it used Gaussian basis function as role function of the RBF network,its output is associated with some adjustable parameters,and it is not zero in the limited range of input space,so it is a kind of local approximation of the neural network method,it can quickly learn and avoid local minimum problem in the RBF network,and it satisfies the requirement of the control in the realtime.It is found that the RBF neural network model can improve the control accuracy,robustness and adaptability significantly through the establishment of Simulink control system simulation of the relevant models and the discrete digital simulation of M language. Its Control effect is good.
豆勤勤.基于RBF神经网络模型的单力臂机器人控制[J].重庆工商大学学报(自然科学版),2021,38(2):23-27 DOU Qin-qin. Control of Onearm Robot Based on RBF Neural Network Model[J]. Journal of Chongqing Technology and Business University(Natural Science Edition),2021,38(2):23-27