Uncertainty Nonlinear Systems Control with Fuzzy Equations

Many uncertain nonlinear systems can be modeled by the linear-in-parameter model, and the parameters are uncertain in the sense of fuzzy numbers. Dual fuzzy equations are alternative models for these nonlinear systems identification, while the solutions of the fuzzy equations are the controllers. In this paper, we propose a novel fuzzy controller via dual fuzzy equations. Two types of neural networks are applied to approximate the solutions of the fuzzy equations. These solutions are then transformed into the fuzzy controllers. The novel methods are validated with two benchmark examples.