Multivariable Generalized Predictive Control Method for Aero-Engine

Yuzhu Zhang, Yong-Liang Zhang, Lingcong Nie, Jin-Quan Huang, F. Lu
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Abstract

The current aero-engine control algorithm application is mainly Proportional Integral Derivative (PID) control, and it is simple and easy to implement. However, it is difficult to meet the growing requirements of high-performance intelligent engine control based on the PID algorithm. In this paper, a novel multivariable control algorithm, called Multivariable Generalized Predictive Control (MGPC), is studied based on the Generalized Predictive Control (GPC) combined with the intelligent optimization-seeking for aero-engine speed and pressure ratio control. The engine control quality is influenced by some control parameters, including prediction time domain and control time domain. The simulation results show that the designed engine MGPC controller can provide better dynamic and steady control performance than the traditional PID one.
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航空发动机多变量广义预测控制方法
目前应用的航空发动机控制算法主要是比例积分导数(PID)控制,且算法简单,易于实现。然而,基于PID算法的高性能智能发动机控制难以满足日益增长的需求。本文在广义预测控制与智能寻优相结合的基础上,研究了一种新的多变量控制算法——多变量广义预测控制(MGPC)。发动机的控制质量受预测时域和控制时域等控制参数的影响。仿真结果表明,所设计的发动机MGPC控制器比传统的PID控制器具有更好的动态和稳态控制性能。
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