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A novel robust control design is proposed for aircraft engines. The engine is modeled as an uncertain dynamic system, whose uncertainty may be (possibly fast) time-varying. The possible value of the uncertainty is prescribed to be within fuzzy sets. This distinguishes our modeling from the Takagi&#x2013;Sugeno inference system. The uncertainty is divided into matched and mismatched portions. While the matched uncertainty lies within the range space of the input matrix, the mismatched uncertainty falls outside, which poses a significant challenge for the control design. The objective is to propose a new robust control design for aircraft engines, which are subject to mismatched uncertainty. A robust control, which is deterministic and is not IF&#x2013;THEN fuzzy rule-based, is designed. The control design parameter needs to be feasible, i.e., within a prescribed range. Some prescribed deterministic performances of the system are guaranteed. By taking the control cost and the performance threshold into consideration, which is under the influence of both matched and mismatched uncertainty, the unique optimal choice of the design parameter is proposed. As a result, this control design delicately blends optimality with mismatched uncertainty. This design is applied to a turbofan engine. Hardware-in-the-loop laboratory testing in the flight envelope demonstrates the superiority of the control design.

Fuzzy-Set Theoretic Control Design for Aircraft Engine Hardware-in-the-Loop Testing: Mismatched Uncertainty and Optimality