Fuzzy predictive control of Tape Rectification

Tape Rectification is a highly nonlinear process. Conventional Model Predictive Control (MPC) may not be able to cope with such process. The Fuzzy Neural Network (FNN) methodology is proposed to realize the model of the nonlinear process. The measured data serve as samples to train the neural network. The prediction accuracy is guaranteed due to the interpolation ability of the feedforward network. Multidimensional searching technique is used to solve the nonlinear optimization problem. The optimization results are embedded into a BP neural network predictive controller. On-line computation of BP neural network can satisfy the real-time control demand. The experimental results have shown the effectiveness of the FNN predictive control.