Multivariable Adaptive Control Method for Turbofan Engine With Dynamic and Input Uncertainties

Author:

Liu Jiashuai1,Wang Xi1,Zhu Meiyin1,Miao Keqiang1

Affiliation:

1. School of Energy and Power Engineering, Beihang University, Beijing 100191, China

Abstract

Abstract The dynamic characteristics of the turbofan engine vary greatly in the full flight envelope, which makes the problem of dynamic uncertainty and input uncertainty very prominent. This brings different degrees of performance impact to the engine control system and even makes it lose stability. This paper proposes a multivariable adaptive control method for dealing with multivariable dynamic uncertainty and input uncertainty. First, for the case where the number of state variables is less than or equal to the number of input variables and the input matrix satisfies the full-rank condition of the row, the existence of the right pseudo-inverse matrix of the input matrix can be guaranteed. Then, the dynamic uncertainty and input uncertainty can be mathematically converted into standard matched uncertainty. Second, the Lyapunov quadratic function is constructed by the closed-loop tracking error vector and the adaptively adjustable control parameter estimation errors, and the Lyapunov stability constraint is considered. Then, under the premise of considering the dynamic characteristics of the actuator, an adaptive control algorithm for multivariable uncertainty model of turbofan engine is derived. Finally, ground and high-altitude simulations are carried out on the dual-loop control system based on the nonlinear dynamic model of the turbofan engine. The results show that the control system has robust stability and anti-interference performance for dynamic uncertainty and input uncertainty of turbofan engine in the full flight envelope. By introducing stronger parameter change rate information to the controller, its performance can be further improved, and the transient state control is more stable.

Publisher

ASME International

Subject

Mechanical Engineering,Energy Engineering and Power Technology,Aerospace Engineering,Fuel Technology,Nuclear Energy and Engineering

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3. Nian, F. Q., 2014, “ Model Reference Adaptive Control for Aeroengine,” Master's thesis, Northeastern University, Liaoning, China.

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