本文選題：容錯(cuò)飛行控制 + 多模型自適應(yīng)切換　； 參考：《南京航空航天大學(xué)》2017年碩士論文

【摘要】：飛行失控嚴(yán)重威脅飛行品質(zhì)與安全,民機(jī)飛行若產(chǎn)生失控且未被及時(shí)改出,易造成重大飛行事故。其中,飛行故障是飛行失控主要誘因之一。因而,對(duì)飛行故障預(yù)測(cè)及失控后的特情改出保護(hù)研究可提高民機(jī)飛行可靠性。針對(duì)上述研究意義,論文主要開(kāi)展具體工作如下:(1)民機(jī)復(fù)雜動(dòng)力學(xué)模型線化方法。采用線性變參數(shù)(Linear Parameter Varying,LPV)建模理論對(duì)復(fù)雜強(qiáng)耦合非線性系統(tǒng)線性化�？紤]復(fù)雜系統(tǒng)凸胞型變參數(shù)實(shí)現(xiàn)過(guò)程困難,采用依賴網(wǎng)格劃分LPV理論中函數(shù)替換方法,并采用啟發(fā)式搜索算法中的遺傳算法對(duì)LPV建模優(yōu)化問(wèn)題求解,對(duì)民機(jī)正常飛行狀態(tài)、單發(fā)停車以及風(fēng)場(chǎng)LPV模型進(jìn)行設(shè)計(jì)。通過(guò)時(shí)域響應(yīng)、可達(dá)集分析、周期模態(tài)分析等仿真分析驗(yàn)證遺傳算法求解的LPV模型對(duì)原模型具有更高逼真度;通過(guò)對(duì)飛機(jī)著陸過(guò)程穿越風(fēng)場(chǎng)仿真實(shí)驗(yàn),驗(yàn)證含擾動(dòng)風(fēng)LPV模型有效性;另外,采用全發(fā)失效仿真驗(yàn)證發(fā)動(dòng)機(jī)失效LPV模型可逼近原非線性模型。(2)多模型自適應(yīng)預(yù)測(cè)(Multi Model Adaptive Estimator,MMAE)方法下飛行故障診斷與隔離(Fault Detection and Isolation,FDI)系統(tǒng)搭建。研究包括有色噪聲卡爾曼濾波器設(shè)計(jì)、FDI殘差信號(hào)獲取以及故障概率計(jì)算。通過(guò)增加主動(dòng)監(jiān)督機(jī)制和流程標(biāo)識(shí)位方法對(duì)原FDI改進(jìn)。實(shí)驗(yàn)結(jié)果表明改進(jìn)后FDI系統(tǒng)可一定程度提高系統(tǒng)故障檢測(cè)性能以及系統(tǒng)穩(wěn)定性。(3)特情控制改出問(wèn)題研究。考慮主動(dòng)FDI、被動(dòng)FDI特性以及FDI系統(tǒng)模型表現(xiàn)形式,選用兩類改出控制器進(jìn)行研究仿真,即基于r性能的魯棒綜合控制器及帶控制約束、狀態(tài)約束、控制增量約束的模型預(yù)測(cè)控制器(Model Predictive Control,MPC)仿真。與線性二次型最優(yōu)調(diào)節(jié)器(Linear Quadratic Regular,LQR)信號(hào)跟蹤結(jié)果對(duì)比驗(yàn)證兩類控制器改出結(jié)果有效。(4)容錯(cuò)飛行控制(Fault Tolerant Control,FTC)系統(tǒng)綜合及擾動(dòng)風(fēng)場(chǎng)參數(shù)辨識(shí)。以魯棒綜合控制器作為被動(dòng)FTC控制,以MPC作為主動(dòng)FTC控制,構(gòu)建針對(duì)風(fēng)場(chǎng)擾動(dòng)下的單發(fā)停車和升降舵卡阻兩類常用故障模式的FTC系統(tǒng)。與基于LQR的FTC系統(tǒng)改出結(jié)果證明:魯棒綜合控制可抑制擾動(dòng)風(fēng)場(chǎng)影響;升降舵卡阻改出策略選擇水平安定面為控制舵面,采用魯棒綜合控制器的FTC可實(shí)現(xiàn)升降舵卡阻改出控制目標(biāo);針對(duì)單發(fā)停車故障改出,采用MPC對(duì)剩余發(fā)動(dòng)機(jī)控制分配問(wèn)題求解,MPC的FTC系統(tǒng)同樣可保證飛機(jī)平穩(wěn)飛行。
[Abstract]:Flight runaway is a serious threat to flight quality and safety. If civil aircraft flight is out of control and is not corrected in time, it is easy to cause serious flight accidents. Among them, the flight failure is one of the main causes of flight out of control. Therefore, the prediction of flight failure and the study of special protection after runaway can improve the flight reliability of civil aircraft. In view of the above research significance, the main work of this paper is as follows: 1) linearization of complex dynamic model of civil aircraft. Linear variable Parameter Linear Parameter (LPV) modeling theory is used to linearize complex strongly coupled nonlinear systems. Considering the difficulty of realizing the variable parameters of convex cell type of complex system, the function replacement method in LPV theory is adopted, and the genetic algorithm in heuristic search algorithm is used to solve the optimization problem of LPV modeling, and the normal flight state of civil aircraft is obtained. Single stop and wind field LPV model are designed. The simulation results of time domain response, reachable set analysis and periodic modal analysis show that the LPV model solved by genetic algorithm has a higher fidelity to the original model. The validity of the LPV model with disturbance wind is verified, in addition, the engine failure LPV model can approach the original nonlinear model by full failure simulation, and the flight fault diagnosis and isolation fault detection and isolation (FDI) system is built under the method of Multi Model Adaptive Estimator (MMAE). The research includes the design of colored noise Kalman filter and the acquisition of FDI residual signal and the calculation of fault probability. The original FDI is improved by adding active supervision mechanism and process marking bit method. The experimental results show that the improved FDI system can improve the system fault detection performance and system stability to some extent. Considering the characteristics of active FDI, passive FDI and FDI system model, two kinds of modified output-out controllers are selected for simulation, that is, robust synthesis controller based on r performance, robust synthesis controller with control constraints and state constraints. Model Predictive Control (MPC) Simulation of Model Predictive Controller for controlling incremental constraints. Compared with linear quadratic optimal regulator linear Quadric regular LQR signal tracking results, it is proved that the two kinds of controllers are effective. 4) Fault tolerant flight control fault Tolerant control FTC) system synthesis and disturbance wind field parameter identification. Taking robust integrated controller as passive FTC control and MPC as active FTC control, the FTC system with two common fault modes of single stop and hoist resistance under wind field disturbance is constructed. The results show that robust integrated control can restrain the influence of disturbance wind field, and the horizontal stabilizer surface is chosen as the control rudder surface. The FTC with robust integrated controller can realize the control target of hoist stop and change out, and the FTC system using MPC to solve the residual engine control assignment problem can also ensure the smooth flight of the aircraft.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：V328;V249.1

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