Fuzzy model-based predictive control by instantaneous linearization

This paper investigates the application of the product-sum crisp type fuzzy model linearization technique and the multistep predictive control strategy for the construction of a model-based predictive fuzzy controller. A model-based predictive controller is based on a local linear approximate model generated by using the proposed linearization technique that linearizes the product-sum crisp type fuzzy process model around the current operating point. The control of pH in a continuous stirred tank reactor is chosen as a realistic nonlinear case study for the demonstration of the proposed control algorithm. The controller is shown to be capable controlling the nonlinear processes that operate over a wide range, and providing better overall system performance than the optimal PI controller.