航空发动机多模态切换控制方法研究
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摘要
随着航空发动机控制系统的发展，智能发动机技术已经成为其重要的发展方向。智能发动机通过“健康”管理，实时监视性能和环境的变化，根据状态的变化切换到相应的控制模式，从而大大提高发动机性能、可靠性、备战性，并延长发动机的寿命。航空发动机多模态切换控制技术作为智能发动机的关键技术，正受到越来越多的关注，已成为研究的热点。本文围绕航空发动机多模态切换控制这一主题，研究了航空发动机建模、模态切换方法、故障诊断以及基于模态切换的容错控制方法。论文的主要工作和贡献如下：
（1）建立了某型涡扇发动机非线性部件级模型和状态变量线性模型。提出了基于变尺度法的混合求解方法来建立状态变量线性模型，该方法避免了小扰动方法精度不高、稳态终值响应法动态过程不一致以及传统拟合法的随着维数增加精度下降和拟合时间长等缺点。仿真结果表明利用该方法建立的线性模型与非线性部件级模型在动态过程响应中吻合良好，具有较高的稳态精度。
（2）针对航空发动机不同控制通路切换过程中参数跳变甚至系统不稳定问题，提出了模糊切换控制方法，设计了不同结构控制通路的模糊切换控制器，基于无源性理论对航空发动机多路模糊切换控制系统进行了稳定性分析，给出了多路模糊切换控制系统稳定的充分条件。仿真结果表明了该方法不仅能够在全包线内使切换过程稳定过渡，保证系统的稳定性，而且还具有良好的动静态性能。
（3）研究了航空发动机分段加速优化和加速过程的切换控制问题。将航空发动机加速过程分为三个阶段，在不同阶段引入不同的目标函数以及采用不同的约束条件，采用SQP算法分段优化加速过程，得到了加速控制规律。提出了基于云模糊切换的分段最优加速控制方法，解决航空发动机加速过程中各阶段切换瞬间出现的参数跳变以及超限的问题。仿真结果表明，该方法不仅能够提高发动机加速性能，而且能保证航空发动机分段加速过程平滑过渡。
（4）分别运用基于数据和基于模型的方法来设计航空发动机部件故障和传感器故障的诊断和隔离系统。结合云理论和关联度分析方法，提出了基于知识的云关联度方法，并在分析航空发动机传感器故障和部件故障特点的基础上，利用云关联度方法，设计了航空发动机部件、传感器故障的识别系统，该系统不仅能够区分发动机部件、传感器故障，还能诊断发生故障的传感器或部件位置。设计了基于卡尔曼滤波器的发动机部件故障与传感器故障诊断方法。针对传感器故障诊断过程中诊断阈值的选择问题，提出了双层阈值机制，提高了传感器故障诊断系统的准确性和鲁棒性。建立了航空发动机部件与传感器故障诊断与隔离系统，该系统不仅能够对发动机传感器故障、部件故障以及部件与传感器同时故障进行区分，而且对于部件与传感器同时故障情况，能够隔离出传感器故障的位置以及部件故障的类型，提高了航空发动机复合故障诊断的精度。
（5）综合发动机控制和故障诊断方法，设计基于控制模式切换的发动机容错控制系统，包括任务级模式和发动机级模式。任务级模式主要针对发动机部件故障情况，设计了航空发动机性能恢复控制系统，系统根据发动机的工作状态以及健康状态在常规转速控制模式、稳态性能恢复控制模式和加速性能恢复控制模式之间切换，从而保证故障发动机的性能得以恢复；发动机级模式主要针对发动机在慢车状态、节流状态以及中间状态下的控制计划，在控制回路失效时，根据故障情况改变控制策略，切换到其它控制回路，从而保证发动机继续正常工作，将传感器的容错控制从硬件和软件冗余提升到发动机控制与健康管理综合的层次上。
With the development of aircraft engine control systems, intelligent engine technology hasbecome an important direction. Through the "health" management, intelligent engine real-timemonitors the changes of performance and environmenting, switches to the corresponding controlmode. Therefore, it would greatly improve engine performance, reliability and preparation, andextend the life of engine. Multi-mode switching control technology, as one of key technologies ofintelligent engine, gets increasing attention and become a research hotspot. Focusing on the subject ofmulti-mode switching control of aircraft engine, dynamic modeling, multi-mode switching algoritm,fault diagnosis and fault-tolerant control are studied in the thesis. The main work and contributionsare as follows:
（1）Nonlinear component level model and state variables linear model are established of aturbofan engine. A mixture solution method based on variable scale method is proposed to establishstate variables linear model. This proposed method avoids the disadvantages such as less annuracy ofsmall perturbation method, inconsistent of dynamic process of steady-state value of response, and lessaccuracy and longer time of traditional fitting method with the increase of the matrix dimensions. Thelinear model is in good agreement in the dynamic response, and steady accuracy with componentlevel model.
（2）For the jump of parameters and the unstable problem of the system during the shift betweendifferent control modes, a fuzzy switching control scheme is proposed for aircraft engine controlsystem. Fuzzy switching controllers for different structures of control modes are designed. Thestability of the multi-mode switching control system for aircraft engines is analyzed based on thepassivity theorem. Sufficient stable condition of multi-mode switching system is given. Simulationresults show that the proposed method can not only ensure the system stable but also have favorableperformance in the flight envelop.
（3）The problem of multi-section optimization and switch control in acceleration process ofaircraft engine are researched. The acceleration process is divided into three phases. The objectiveindexes and constraints are different in each phase. The optimal acceleration control law is obtainedusing the SQP algorithm to optimize each acceleration phase. For the significant jump and theexceeding of parameter limits during the shift of different phases on the acceleration process, a fuzzyswitching controller based on the cloud model is derived. Simulation results show that the proposedmethod can not only enhance acceleration performance but also guarantee the smooth transition of acceleration response.
（4）The knowledge-based and model-based methods are used respectively to design aircraftengine components fault and sensors fault diagnosis and isolation system. The knowledge-based cloudrelational analysis is proposed which integrates the cloud theory and the relational analysis. A faultdiagnosis system utilizing the cloud relational analysis is designed based on the analysis to the faultcharacteristics of the sensors and the engine components. The proposed method can not only isolatesensor fault and engine component fault, but also locate the fault position of the sensors or thecomponents. Kalman filter based fault diagnoses system designed for aircraft engine component andsensor faults. A double-threshold mechanism is proposed to select the threshold in senor faultdiagnosis. This greatly improves the accuracy and robustness of sensor fault diagnosis system. Theaircraft engine component and sensor fault detection and isolation system is established. The approachcan not only distinguish among sensor fault, component fault but also isolate and locate sensor faultand engine component fault when the two kinds of faults occur simultaneously. The fault diagnosisaccurency is effectively improved for the component-sensor simultaneous fault.
（5）Integrated engine control and fault diagnoses method, engine fault-tolerant control schemebased control mode switch is designed, including task-level mode and engine-level mode. Aimed atengine components fault, the performance recovery control system of task-level mode had beendesigned. The system switched among the conventional speed control mode, steady state performancerecovery control mode and acceleration performance recovery control modes, based on the engineoperation condition and healthy condition. Aimed at engine control project in the idle state, throttlestate and intermediate state, when a control loop failure occurs, the control strategies switch to othercontrol loop according to fault conditions, to ensure the engine control system performance upgradingsensor fault-tolerant control from hardware and software redundancy to the integrated engine controland fault diagnoses level.
（1）建立了某型涡扇发动机非线性部件级模型和状态变量线性模型。提出了基于变尺度法的混合求解方法来建立状态变量线性模型，该方法避免了小扰动方法精度不高、稳态终值响应法动态过程不一致以及传统拟合法的随着维数增加精度下降和拟合时间长等缺点。仿真结果表明利用该方法建立的线性模型与非线性部件级模型在动态过程响应中吻合良好，具有较高的稳态精度。
（2）针对航空发动机不同控制通路切换过程中参数跳变甚至系统不稳定问题，提出了模糊切换控制方法，设计了不同结构控制通路的模糊切换控制器，基于无源性理论对航空发动机多路模糊切换控制系统进行了稳定性分析，给出了多路模糊切换控制系统稳定的充分条件。仿真结果表明了该方法不仅能够在全包线内使切换过程稳定过渡，保证系统的稳定性，而且还具有良好的动静态性能。
（3）研究了航空发动机分段加速优化和加速过程的切换控制问题。将航空发动机加速过程分为三个阶段，在不同阶段引入不同的目标函数以及采用不同的约束条件，采用SQP算法分段优化加速过程，得到了加速控制规律。提出了基于云模糊切换的分段最优加速控制方法，解决航空发动机加速过程中各阶段切换瞬间出现的参数跳变以及超限的问题。仿真结果表明，该方法不仅能够提高发动机加速性能，而且能保证航空发动机分段加速过程平滑过渡。
（4）分别运用基于数据和基于模型的方法来设计航空发动机部件故障和传感器故障的诊断和隔离系统。结合云理论和关联度分析方法，提出了基于知识的云关联度方法，并在分析航空发动机传感器故障和部件故障特点的基础上，利用云关联度方法，设计了航空发动机部件、传感器故障的识别系统，该系统不仅能够区分发动机部件、传感器故障，还能诊断发生故障的传感器或部件位置。设计了基于卡尔曼滤波器的发动机部件故障与传感器故障诊断方法。针对传感器故障诊断过程中诊断阈值的选择问题，提出了双层阈值机制，提高了传感器故障诊断系统的准确性和鲁棒性。建立了航空发动机部件与传感器故障诊断与隔离系统，该系统不仅能够对发动机传感器故障、部件故障以及部件与传感器同时故障进行区分，而且对于部件与传感器同时故障情况，能够隔离出传感器故障的位置以及部件故障的类型，提高了航空发动机复合故障诊断的精度。
（5）综合发动机控制和故障诊断方法，设计基于控制模式切换的发动机容错控制系统，包括任务级模式和发动机级模式。任务级模式主要针对发动机部件故障情况，设计了航空发动机性能恢复控制系统，系统根据发动机的工作状态以及健康状态在常规转速控制模式、稳态性能恢复控制模式和加速性能恢复控制模式之间切换，从而保证故障发动机的性能得以恢复；发动机级模式主要针对发动机在慢车状态、节流状态以及中间状态下的控制计划，在控制回路失效时，根据故障情况改变控制策略，切换到其它控制回路，从而保证发动机继续正常工作，将传感器的容错控制从硬件和软件冗余提升到发动机控制与健康管理综合的层次上。
With the development of aircraft engine control systems, intelligent engine technology hasbecome an important direction. Through the "health" management, intelligent engine real-timemonitors the changes of performance and environmenting, switches to the corresponding controlmode. Therefore, it would greatly improve engine performance, reliability and preparation, andextend the life of engine. Multi-mode switching control technology, as one of key technologies ofintelligent engine, gets increasing attention and become a research hotspot. Focusing on the subject ofmulti-mode switching control of aircraft engine, dynamic modeling, multi-mode switching algoritm,fault diagnosis and fault-tolerant control are studied in the thesis. The main work and contributionsare as follows:
（1）Nonlinear component level model and state variables linear model are established of aturbofan engine. A mixture solution method based on variable scale method is proposed to establishstate variables linear model. This proposed method avoids the disadvantages such as less annuracy ofsmall perturbation method, inconsistent of dynamic process of steady-state value of response, and lessaccuracy and longer time of traditional fitting method with the increase of the matrix dimensions. Thelinear model is in good agreement in the dynamic response, and steady accuracy with componentlevel model.
（2）For the jump of parameters and the unstable problem of the system during the shift betweendifferent control modes, a fuzzy switching control scheme is proposed for aircraft engine controlsystem. Fuzzy switching controllers for different structures of control modes are designed. Thestability of the multi-mode switching control system for aircraft engines is analyzed based on thepassivity theorem. Sufficient stable condition of multi-mode switching system is given. Simulationresults show that the proposed method can not only ensure the system stable but also have favorableperformance in the flight envelop.
（3）The problem of multi-section optimization and switch control in acceleration process ofaircraft engine are researched. The acceleration process is divided into three phases. The objectiveindexes and constraints are different in each phase. The optimal acceleration control law is obtainedusing the SQP algorithm to optimize each acceleration phase. For the significant jump and theexceeding of parameter limits during the shift of different phases on the acceleration process, a fuzzyswitching controller based on the cloud model is derived. Simulation results show that the proposedmethod can not only enhance acceleration performance but also guarantee the smooth transition of acceleration response.
（4）The knowledge-based and model-based methods are used respectively to design aircraftengine components fault and sensors fault diagnosis and isolation system. The knowledge-based cloudrelational analysis is proposed which integrates the cloud theory and the relational analysis. A faultdiagnosis system utilizing the cloud relational analysis is designed based on the analysis to the faultcharacteristics of the sensors and the engine components. The proposed method can not only isolatesensor fault and engine component fault, but also locate the fault position of the sensors or thecomponents. Kalman filter based fault diagnoses system designed for aircraft engine component andsensor faults. A double-threshold mechanism is proposed to select the threshold in senor faultdiagnosis. This greatly improves the accuracy and robustness of sensor fault diagnosis system. Theaircraft engine component and sensor fault detection and isolation system is established. The approachcan not only distinguish among sensor fault, component fault but also isolate and locate sensor faultand engine component fault when the two kinds of faults occur simultaneously. The fault diagnosisaccurency is effectively improved for the component-sensor simultaneous fault.
（5）Integrated engine control and fault diagnoses method, engine fault-tolerant control schemebased control mode switch is designed, including task-level mode and engine-level mode. Aimed atengine components fault, the performance recovery control system of task-level mode had beendesigned. The system switched among the conventional speed control mode, steady state performancerecovery control mode and acceleration performance recovery control modes, based on the engineoperation condition and healthy condition. Aimed at engine control project in the idle state, throttlestate and intermediate state, when a control loop failure occurs, the control strategies switch to othercontrol loop according to fault conditions, to ensure the engine control system performance upgradingsensor fault-tolerant control from hardware and software redundancy to the integrated engine controland fault diagnoses level.
引文
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