Event-triggered model predictive tracking control of aero-engine with varying prediction horizon

Yu Peng, Ning Xu, Peng Li, Shuoshuo Liu, Xudong Zhao
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Abstract

Aero-engine is a complex thermal-mechanical system with strong nonlinearity, uncertainty, and time variation. Thus, it is crucial to design an effective controller for such a complex system to obtain the desired performances of the aero-engine. In recent years, model predictive control (MPC) has shown great potential in dealing with control problems with complex constraints of multi-variable systems, which has been applied to aero-engine control, achieving good results. Furthermore, the MPC strategy using an event-driven mechanism is good at balancing system resources and ensuring system control performances. In this paper, the problem of event-triggered MPC for aero-engine systems with bounded disturbances is studied. Firstly, an event-triggered strategy with a dynamic forced-trigger mechanism is proposed. Then, an MPC algorithm based on an event-triggered mechanism is designed. Finally, an application to the JT9D aero-engine model provided by T-MATS verifies the effectiveness of the designed algorithm. It is shown that the calculation load is significantly reduced, which proves the superiority of this method.
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变预测视界航空发动机事件触发模型预测跟踪控制
航空发动机是一个复杂的热力系统,具有很强的非线性、不确定性和时变特性。因此,设计一种有效的控制器以获得航空发动机期望的性能是至关重要的。近年来,模型预测控制(MPC)在处理具有复杂约束的多变量系统控制问题方面显示出巨大的潜力,并已应用于航空发动机控制中,取得了良好的效果。此外,采用事件驱动机制的MPC策略能够很好地平衡系统资源,保证系统控制性能。研究了具有有界扰动的航空发动机系统的事件触发MPC问题。首先,提出了一种带有动态强制触发机制的事件触发策略。然后,设计了一种基于事件触发机制的MPC算法。最后,以T-MATS提供的JT9D航空发动机模型为例,验证了所设计算法的有效性。计算结果表明,计算量明显减少,证明了该方法的优越性。
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