Internal Model Control Based on Dynamic Fuzzy Neural Network

A novel internal model control (IMC) approaches is proposed to control for process with large time delays. A dynamic fuzzy neural network (DFNN) was applied to model the process and its mathematical inverse to control the process. The presented strategy can overcome the unstable problem caused by time delays and the problem of time consuming and complex and incapable obtaining mathematical inverse of model using the classical internal model control. The automatic configuration and learning of the networks is carried out by using new adding techniques and on-line learning algorithm. The effectiveness of the proposed control scheme is verified by simulated results.