Fuzzy Neural Model with Global Convergence for Batch Process

To overcome the difficulty that an accurate mathematic model is hard to obtain,a batch process model based on fuzzy neural network with nonlinear fuzzy rule consequence is proposed.Then a parameters learning algorithm based on Lyapunov method with global convergence is also presented with rigorous proof.The proposed algorithm possesses the high approximation and better self-learning ability,thus it provides a new way for the modeling of batch processes.Lastly,to verify the efficiency of the proposed algorithm,it is applied to a benchmark batch process.The simulation results show the efficiency and potential practical value of the proposed model.