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• W2979179297 abstract "Abstract A Min-Max structure combined with several linear limit controllers are utilized for conventional aero-engines safety control, which is complex and conservative, therefore a new nonlinear model predictive control strategy is proposed that owns the ability to manage time-varying input/output limits during acceleration/deceleration transient states of aero-engines. Penalty function items are constructed according to the characteristics of input/output limits, and are incorporated in the cost function of online receding horizon optimization for limit management of aero-engines. Considering the large computational burden of nonlinear component-level aero-engine model directly used as prediction model, a piecewise linear model is built to describe the steady-state and dynamic properties of aero-engines and its design process is explained in detail. Further, computational efforts are investigated as control horizon, prediction horizon are varied in the improved nonlinear predictive controller. Particularly, when penalty function items are activated, control performance and computational burden are examined, thus providing guidelines for key parameters tuning. Simulations show two clear results. One is that computational efforts become larger for bigger control horizon or prediction horizon, but it depends more on control horizon than prediction horizon. The other is that the proposed method can handle time-varying input/output limits effectively without resulting in a great increase of computational burden." @default.
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• W2979179297 date "2019-03-22" @default.
• W2979179297 modified "2023-10-18" @default.
• W2979179297 title "Nonlinear Model Predictive Control Strategy for Limit Management of Aero-Engines" @default.
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• W2979179297 doi "https://doi.org/10.1515/tjj-2019-0004" @default.
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