A new multi-model internal model control scheme based on neural network

Aiming at the practical plants with strong nonlinear characteristics, a new multi-model internal model control (MIMC) strategy based on Gaussian potential function networks (GPFN) is proposed in this paper. The internal model is represented by GPFN and the corresponding controller can be got directly, which simplifies the control law design and analyses greatly. Meanwhile, the way of model switch is developed based on fuzzy decision. This MIMC scheme avoids the complex calculation when adjusting the controller parameter and overcomes the switch vibration. Simulation results demonstrate that the strategy has advantage of internal model control (IMC) and multi-model control and could achieve better system performance than the conventional IMC (CIMC).