微型涡喷发动机控制器设计

A. M. Shehata, M. Khalil, M. Ashry
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引用次数: 2

摘要

现代涡轮喷气发动机采用数字控制器控制。首先,对微型涡喷发动机离散模型进行了辨识。系统识别技术采用的是喷气机P200sx发动机运行实验的真实数据。数字PID控制器主要用于控制这些发动机。数字PID控制器参数的整定技术引起了人们极大的兴趣。本文采用两种整定技术对得到的离散模型的PID控制器参数进行整定。首先,采用基于模型的局部最优控制技术,沿整个范围沿某一工作点整定PID控制器参数;该技术首次应用于相关引擎。增益调度用于管理这些工作点周围的控制器参数。在第二种技术中,遗传算法在整个操作范围内的不同操作点上使用。此外,增益调度用于管理这些工作点周围的控制器参数。在Matlab仿真环境下对两种调优方法进行了比较。比较是基于每个控制器对噪声的鲁棒性和抗干扰性。仿真结果表明,采用基于模型的局部最优控制的数字PID控制器具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Controller Design for Micro Turbojet Engine
Modern turbojet engines are controlled using digital controllers. First of all, the micro turbojet engine discrete model is identified. System identification technique utilized real data obtained from jet cat P200sx engine running experiments. Digital PID controllers are mostly used for controlling these engines. The tuning techniques for digital PID controller parameters are of a great interest. Two tuning techniques are used in this paper to tune the PID controller parameters for the discrete model obtained. In the first, model based local optimal control technique is used to tune the PID controller parameters around certain operating points along the whole range. This technique is used for the first time with the concerned engine. The gain scheduling is used to manage the controller parameters around these operating points. In the second technique, genetic algorithms are used at different operating points along the whole range of operation. Also, the gain scheduling is used to manage the controller parameters around these operating points. The two tuning techniques are compared in Matlab simulation environment. The comparison is based on each controller robustness against noise effect and disturbance rejection. The simulated results are discussed and show better behavior for the digital PID controller tuned using model based local optimal control.
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