Fuzzy Control Algorithm of Intelligent Cantilever Based on Neural Network

Modern industry is developing towards scale and integration, and its manufacturing processes are becoming increasingly complex. Due to its high degree of nonlinearity, time-varying, uncertainty, and strong coupling between variables, many systems are difficult to accurately describe using traditional theoretical methods. Therefore, it is necessary to conduct in-depth research on new intelligent control methods. A neural network-based intelligent cantilever beam fuzzy controller is proposed. On this basis, a fuzzy control(FC) method based on neural networks is proposed. Each input of a neuron is the axon output of the relevant neuron, and the weight of the input is the connection strength between the neuron and the synapse of the relevant neuron, and the value of the weight can be positive or negative, positive indicates excitatory synapse, negative indicates inhibitory synapse. The fuzzy control system is mapped to a kind of neural network(NN) structure, so that the self-organization problem of fuzzy rules is transformed into the self-learning problem of neural network, and it is changed from a hierarchical discrete controller to a continuous controller, which improves the control accuracy and adaptive ability. After this study, the algorithm in this paper has remarkable effect and is suitable for wide application.