Abstract
This study was conducted to develop a novel tracking control strategy for aeroengines with strong nonlinearity and uncertainty. Compared to existing robust gain-scheduling control strategies, the proposed control strategy has relatively low conservatism and can markedly improve engine performance. An improved on-board adaptive aeroengine model was established to estimate engine performance degradation and eliminate the degradation term contained in the perturbation block of the engine uncertain model in the design process. Robust controllers under engine normal and performance degradation states were designed at a set of operating points and scheduled according to relevant scheduling and health parameters. A desired robust gain-scheduling controller, which works based on performance degradation, can be precisely constructed via this approach. Simulation results are given to demonstrate the effectiveness of the proposed method, where the response speed of engine is improved by 38%.
Highlights
The modern aeroengine is a complex nonlinear dynamic system with a wide range of functions and parameters
We developed an improved on-board adaptive model (IOBAM) by updating the nonlinear on-board engine model (NOBEM) using the health parameter vector estimated by the piecewise linearized Kalman filters (PLKF)
A robust gain-scheduling control technique based on performance degradation for aeroengines was developed in this study
Summary
The modern aeroengine is a complex nonlinear dynamic system with a wide range of functions and parameters. We built an accurate gain-scheduling robust controller based on the estimation of performance degradation for a turbofan engine, with special focus on the problems discussed above. A gain-scheduling method which works based on scheduling parameters and engine performance degradation information is used to effectively control the engine in the full flight envelope. B. AUGMENTED STATE VARIABLE AEROENGINE MODEL Considering the health parameter vector h as the control input of the engine, the small-perturbation method or the fitting method [42] can be used to linearize the engine nonlinear model at a healthy steady-state reference point as follows:.
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