Multi-Parameter Fuzzy Optimization Design in Robust Control of Aero-engine Based on Cooperative Game Theory

In the paper, we propose a novel robust control with two tunable design parameters for aero-engines. Engines are modeled as fuzzy dynamical systems with (possibly fast) time-varying but bounded uncertainties. Rather than probability theory, the uncertainties are described by the fuzzy set theory. A robust control was designed on this basis, and two adjustable design parameters must be determined. To deal with the multiple-parameter multi-objective optimization problem, the cooperative game theory is skillfully applied to render the best control performance. Unlike other multi-objective optimization approaches, cooperative game theory can determine the existence of solutions and obtain Pareto optimality through rigorous mathematical analysis and proof. The proposed control is applied to a turbofan engine, and compared with the Sliding Mode Control (SMC), the simulation results demonstrate the superiority of the proposed control method.