RBFNN based direct adaptive control of MIMO Nonlinear system and its application to a Distillation column

In this paper, a RBFNN ( Radial basis function neural network) based direct adaptive controller for MIMO nonlinear system is designed. The tuning law of weights of neural network is derived from a selected Lyapunov function. So the stability of the closed loop and convergence of weights are guaranteed. The design method is applied to the quality control of a distillation column. The dual-point control strategy is adopted instead of single-point control. Some simulation is illustrated to show the validity of the designed controller.