涡轴发动机/旋翼综合建模、控制及优化研究
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摘要
随着新一代直升机的各种性能不断提高,对直升机火控系统,操纵品质,生存性,敏捷性和机动性的要求越来越高,直升机各子系统的复杂程度大大增加,子系统间的耦合作用也大大加强,传统的将各子系统分割独立设计的方法已不能满足要求,只有采用综合设计和综合控制技术。发动机从功率涡轮输出经过主减速器带动旋翼,旋翼既是发动机的负载,又是使直升机产生升力、控制飞行速度以至飞行姿态的重要部件,可见发动机/旋翼系统对整个直升机性能影响至关重要。本文以直升机为对象,建立了直升机/发动机一体化综合仿真平台,并在此平台上进行涡轴发动机/旋翼控制及优化研究。
本文第一章首先介绍了直升机综合飞行/发动机控制研究,模型预测控制研究及最优化问题研究现状。第二章以黑鹰直升机数据为基础建立了直升机/发动机综合仿真平台,此平台可以在飞行包线内任意点开始仿真计算,并解决了发动机/旋翼扭振问题,为后续章节的展开提供了仿真平台。第三章采用统一建模语言(UML)建立了基于C++的优化算法库,包括单纯形算法求解线性规划(LP)问题、有效集算法求解二次规划问题(QP)及序列二次规划算法(SQP)求解一般非线性优化问题,为后续章节的研究提供了实时优化算法的保证。第四章进行了基于SQP的涡轴发动机非线性模型预测控制研究,采用神经元网络进行预测模型的计算,采用SQP算法进行在线滚动优化计算,并讨论了此控制器的实时性问题。第五章针对全局优化问题进行了填充函数方法(FFM)研究,提出了一种新的单参数填充函数算法,并利用此算法进一步进行非线性模型预测控制研究,设计了基于FFM的涡轴发动机非线性模型预测控制器。第六章分别采用LP和SQP算法对涡轴发动机进行了在线导叶角优化控制研究,讨论了在发动机性能寻优过程中的LP算法和SQP算法在实时性方面的差别,论述了SQP算法在实时性方面应优于LP算法。第七章针对发动机/旋翼系统进行了变旋翼转速综合优化控制研究,打破了传统的恒定旋翼及功率涡轮转速限制。第八章进行了全文总结,并对后续工作提出了展望。
With the performance improvement of new generation of helicopters, the demands of helicopter’s fire control system, maneuver quality, survivability, agility and maneuverability become higher and higher, and the complexity and the coupling dynamic effects of helicopter’s subsystems also increase. The traditional design methods of individual subsystems have been unable to meet the demand, and the only solution is the integrated design and control methods. The rotor is driven by a shaft projecting from main gear box which connects to the turboshaft engine’s power turbine, and the rotor is not only the load of the turboshaft engine, but also the important component of generating the lift of the helicopter and controlling the flight velocity and attitude, so the turboshaft engine/rotor system has the important influence on the whole helicopter performance. In this dissertation, the integrated helicopter/engine simulation platform is built, and the control and optimization of the turboshaft engine/rotor are researched based on the platform.
In the first Chapter, a general introduction of the helicopter integrated flight/engine control, the model predictive control and the optimization program is presented with a brief description. The helicopter/engine integrated simulation platform is built based on the Black-Hawk helicopter’s experimental data in Chapter 2. In Chapter 3, the optimization library based on C++ is built with Unified Modeling Language (UML), which includes the Simplex algorithm to Linear Programming(LP), the Active Set algorithm to Quadratic Programming(QP) and the Sequential Quadratic Programming(SQP) to the general nonlinear optimization problem. In Chapter 4, the nonlinear model predictive controller based on SQP is designed, in which the neural network model is used to get the predictive model; the SQP optimization algorithm is used to optimize the fuel flow of the turboshaft engine online. Finally, the real-time problem of the controller is discussed in detail. In Chapter 5, the Filled Function Method(FFM) for the global optimization is researched, and a new FFM with one parameter is proposed. The nonlinear model predictive controller based on the new FFM is designed. In Chapter 6, the online optimization for turboshaft engines based on variable inlet guide vane with LP and SQP methods is studied. The difference on real-time problem between the LP and SQP for aero-engine performance seeking control is discussed, and it states that the SQP is better than LP in real-time aspect. In Chapter 7, the optimization for turboshaft engines based on variable rotor speed is researched. The last Chapter is the conclusion of this dissertation.
本文第一章首先介绍了直升机综合飞行/发动机控制研究,模型预测控制研究及最优化问题研究现状。第二章以黑鹰直升机数据为基础建立了直升机/发动机综合仿真平台,此平台可以在飞行包线内任意点开始仿真计算,并解决了发动机/旋翼扭振问题,为后续章节的展开提供了仿真平台。第三章采用统一建模语言(UML)建立了基于C++的优化算法库,包括单纯形算法求解线性规划(LP)问题、有效集算法求解二次规划问题(QP)及序列二次规划算法(SQP)求解一般非线性优化问题,为后续章节的研究提供了实时优化算法的保证。第四章进行了基于SQP的涡轴发动机非线性模型预测控制研究,采用神经元网络进行预测模型的计算,采用SQP算法进行在线滚动优化计算,并讨论了此控制器的实时性问题。第五章针对全局优化问题进行了填充函数方法(FFM)研究,提出了一种新的单参数填充函数算法,并利用此算法进一步进行非线性模型预测控制研究,设计了基于FFM的涡轴发动机非线性模型预测控制器。第六章分别采用LP和SQP算法对涡轴发动机进行了在线导叶角优化控制研究,讨论了在发动机性能寻优过程中的LP算法和SQP算法在实时性方面的差别,论述了SQP算法在实时性方面应优于LP算法。第七章针对发动机/旋翼系统进行了变旋翼转速综合优化控制研究,打破了传统的恒定旋翼及功率涡轮转速限制。第八章进行了全文总结,并对后续工作提出了展望。
With the performance improvement of new generation of helicopters, the demands of helicopter’s fire control system, maneuver quality, survivability, agility and maneuverability become higher and higher, and the complexity and the coupling dynamic effects of helicopter’s subsystems also increase. The traditional design methods of individual subsystems have been unable to meet the demand, and the only solution is the integrated design and control methods. The rotor is driven by a shaft projecting from main gear box which connects to the turboshaft engine’s power turbine, and the rotor is not only the load of the turboshaft engine, but also the important component of generating the lift of the helicopter and controlling the flight velocity and attitude, so the turboshaft engine/rotor system has the important influence on the whole helicopter performance. In this dissertation, the integrated helicopter/engine simulation platform is built, and the control and optimization of the turboshaft engine/rotor are researched based on the platform.
In the first Chapter, a general introduction of the helicopter integrated flight/engine control, the model predictive control and the optimization program is presented with a brief description. The helicopter/engine integrated simulation platform is built based on the Black-Hawk helicopter’s experimental data in Chapter 2. In Chapter 3, the optimization library based on C++ is built with Unified Modeling Language (UML), which includes the Simplex algorithm to Linear Programming(LP), the Active Set algorithm to Quadratic Programming(QP) and the Sequential Quadratic Programming(SQP) to the general nonlinear optimization problem. In Chapter 4, the nonlinear model predictive controller based on SQP is designed, in which the neural network model is used to get the predictive model; the SQP optimization algorithm is used to optimize the fuel flow of the turboshaft engine online. Finally, the real-time problem of the controller is discussed in detail. In Chapter 5, the Filled Function Method(FFM) for the global optimization is researched, and a new FFM with one parameter is proposed. The nonlinear model predictive controller based on the new FFM is designed. In Chapter 6, the online optimization for turboshaft engines based on variable inlet guide vane with LP and SQP methods is studied. The difference on real-time problem between the LP and SQP for aero-engine performance seeking control is discussed, and it states that the SQP is better than LP in real-time aspect. In Chapter 7, the optimization for turboshaft engines based on variable rotor speed is researched. The last Chapter is the conclusion of this dissertation.
引文
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