Model and Sensor Based Nonlinear Adaptive Flight Control with Online System Identification PDF
Preview Model and Sensor Based Nonlinear Adaptive Flight Control with Online System Identification
Invitation FF MM ll MMooddeell aanndd SSeennssoorr BBaasseedd ISBN: 978-94-6186-350-8 ii oo gg dd turbulence hh ee t t ll NNoonnlliinneeaarr AAddaappttiivvee FFlliigghhtt CCoonnttrrooll On thursday CC aa October 30, 2014 oo nn wwiitthh OOnnlliinnee SSyysstteemm IIddeennttiiffiiccaattiioonn nn dd at 12.30 tt rr SS oo VTP ll ee ON Li Guo SUN nn R ww E ss L I itit oo A will defend his thesis hh rr ENGINE_1 O O B B titled: aa nn LEFT HTP ss ll Model and Sensor ii ee nn dd R ee Based R VATO S S N N Nonlinear Adaptive ED LE yy oo D E U ss nn Flight Control R tt ll ee inin with Online mm ee aa System II rr dd Identification E L E V A T O R enen AdAd tt aa ii ff pp ii The defense will cc tt ii aa vv take place in the tt ee RIGHT HTP ii Senaatszaal at the Aula oo nn of TU Delft ENGINE_2 Mekelweg 5, Delft At 12.00, prior to the defense, N there will be a short O R E A I L RIGHT WING L Li Guo Sun presentation about the i thesis work G u o S u n MODEL AND SENSOR BASED NONLINEAR ADAPTIVE FLIGHT CONTROL WITH ONLINE SYSTEM IDENTIFICATION LiGuo SUN (cid:3632)(cid:1220)(cid:3422)(cid:13557)(cid:17886)(cid:16892)(cid:8279)(cid:3521)(cid:2754)(cid:1366)(cid:5973)(cid:3230)(cid:11450)(cid:19860)(cid:13557)(cid:5725)(cid:3) (cid:14368)(cid:17976)(cid:5322)(cid:20244)(cid:16002)(cid:6621)(cid:2156)(cid:3) (cid:3) (cid:4495)(cid:12545)(cid:3379)(cid:3) MODEL AND SENSOR BASED NONLINEAR ADAPTIVE FLIGHT CONTROL WITH ONLINE SYSTEM IDENTIFICATION Proefschrift terverkrijgingvandegraadvandoctor aandeTechnischeUniversiteitDelft, opgezagvandeRectorMagnificusprof.ir.K.C.A.M.Luyben, voorzittervanhetCollegevoorPromoties, inhetopenbaarteverdedigenopdonderdag30oktober2014om12.30uur door LiGuo SUN MasterofScience,NanjingUniversityofAeronauticsandAstronautics geborenteTangshan,HebeiProvince,China Ditproefschriftisgoedgekeurddoordepromotor: Prof.dr.ir.M.Mulder Copromotor:Dr.Q.P.Chu Samenstellingpromotiecommissie: RectorMagnificus, voorzitter Prof.dr.ir.M.Mulder, TechnischeUniversiteitDelft,promotor Dr.Q.P.Chu, TechnischeUniversiteitDelft,copromotor Prof.dr.ir.M. Verhaegen, TechnischeUniversiteitDelft Prof.dr.-lngF.Holzapfel, TechnischeUniversitätMünchen Dr.ir.G.H.N.Looye, DeutschesZentrumfürLuftandRaumfahrt(DLR) Prof.dr.A. Zolghadri, UniversityofBordeaux Dr.ir.C.C.deVisser, TechnischeUniversiteitDelft Prof.dr.ir.J.A.Mulder, TechnischeUniversiteitDelft,reservelid Keywords: Fly-by-wire, Aerodynamic model, Adaptive control, Fault tolerant, Reconfiguration,Flightenvelopeprotection,Simplexsplinetheory Printedby: IpskampDrukkers,Enschede,TheNetherlands. Coverphotocopyright©BenUllings,AviationPhotosInternational. CoverdesignbyYazdiIbrahimJenie. ISBN978-94-6186-350-8 PublishedanddistributedbyL.G. Sun. Email: [email protected] Anelectronicversionofthisdissertationisavailableat http://repository.tudelft.nl/. Copyright©2014byL.G. Sun. Allrightsreserved. Nopartofthematerialprotected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storageandretrievalsystem,withoutpriorpermissionoftheauthor. Tomyparentsandmywife S UMMARY Model and Sensor Based Nonlinear Adaptive Flight Control with Online System Identification Li Guo Sun Consensusexiststhatmanyloss-of-control(LOC)inflightaccidentscausedbysevere aircraft damage or system failure could be prevented if flight performance could be recoveredusingthevalidandremainingcontrolauthorities. However,thesafemaneu- verability of a post-failure aircraft will inevitably be reduced due to the malfunction. Non-conventional control strategies which rely on modern control techniques and computationalpowerareessentialtocontrolsystemsinpost-failureflightconditionsto extractthemostfromthereduced,remainingaircraftcontrolauthoritiesandrestorethe flightperformanceofanaircraftorachieveasafelanding. Onesuchnon-conventional controlstrategyiscalledactivefaulttolerantflightcontrol(FTFC),whichisdesignedto detectchangesinanaircraft’sdynamicscausedbystructural,actuator,orsensorfailure andaccommodatethedamageorfailureusinganadaptivereconfigurationmechanism. TheactiveFTFCtechniqueisabletodealwithunanticipatedandmultiplesimultaneous failures. The overall architecture of an active FTFC system ideally should consist of a fault detection and diagnosis (FDD) module, a state reconstruction unit, a reconfigurable control component, a control allocation unit and a flight envelope protection (FEP) unit. Generally speaking, FTFC systems can be classified into two types: model- based FTFC systems and model-free FTFC systems, according to whether any of the system’s components require an aerodynamic model at their core or not. A model- basedFTFCsystemcontainsanaerodynamicmodelidentification(AMI)module,which suppliesanaccurateaircraftmodeltoanindirectadaptivenonlinearcontrollerinthe reconfigurablecontrolblock,toadynamicflightenvelopedeterminationalgorithmin anFEPunit,ortoanFDDunit. Anaerodynamicmodelidentificationapproachusing a physical, interpretable modeling structure can detect and even quantify structural failuresoccurringintheaircraftstructureoroneofthecontrolsurfacesbymonitoring changesinstabilityderivativesandcontrolderivatives. There are many candidate control approaches which can achieve reconfiguration whendesigningareconfigurableflightcontroller.Thesereconfigurablecontrolmethods mayrelyonmanydifferentreconfigurationmechanismsrangingfromswitching,model following,matchingtoadaptivecompensation.Thesemethodsincludenonlinearadap- tive control which achieves reconfiguration through compensation, and this method is receiving increasing attention in the flight control aerospace research community. Nonlinearadaptivecontrolisdividedintodirectadaptivecontrolandindirectadaptive vii viii control, the difference is that the latter requires an online system model. Indirect adaptive control is also called model-based or modular adaptive control, which has someadvantagesoverthedirectadaptivecontrolandothermodel-freecontrolmethods. One advantage is that a modular control approach has the potential to yield a more efficient controller which requires less control effort. Such an efficient controller can beachievedbymaintainingusefuldampingtermsofanidentifiedsystemmodelinthe closed-loop system. This is attributed to the good properties of many control design techniques such as backstepping such that the dynamics of an original system can be chosen to be canceled or maintained during a controller design process. Modular adaptive control also has an inherited shortcoming, it can only guarantee input-to- state stability, i.e. modular adaptive control cannot guarantee the stability of the overallclosed-loopsystembecauseitsstabilityproofreliesonthecertaintyequivalence principle.Theweaknessofthecertaintyequivalenceprinciple,i.e.convergenceproblem ofthemodelparameters,canbeimprovedbyenhancingmodelaccuracyorreliability, to do this, it becomes critical to develop advanced, powerful aerodynamic model identificationapproachescapableofcapturingchangesinflightdynamicseitherduring ahighmaneuveringflightmissionorapost-failurecondition. Flight envelope protection is a necessary technique that should be applied by controllerdesignerstopreventLOCincidents,takingintoaccounthighlymaneuvering flighttasksand/orhighlyperturbedflightconditionsduetotheongoingfailure.AnFEP componentshouldprovideapilotwithasafeflightenvelopeandposeconstraintsonthe referencecommandsfedtoaninternalcontrollertomakethecommandsachievable. Anaerodynamicmodelthatisvalidoveranentireflightenvelopeplaysacrucialrole in full-envelope modular adaptive control and flight envelope protection. A globally validmodelisrequiredformodularadaptivecontroltoenablethedesignedcontroller to work properly in a large operating range. Once estimated, the global model in a model-based adaptive control method can be stored for later re-use when the same flight condition is revisited. Except being needed by a model-based controller, an accurateaerodynamicmodelisalsorequiredforflightenvelopeprotection. Naturally, theestimatedaerodynamicmodelhastobevalidforthecurrentaircraftconfiguration overtheentireflightenvelopetoenableanevolutionalgorithmtoestimatetheboundary of the safe flight envelope for the current flight condition. However, only a limited number of model identification approaches are suited for estimating a globally valid aerodynamic model, and each existing possible candidate has variant shortcomings or limitations which make it hard to apply directly to identify an aircraft model. For example,neuralnetworksusuallyyieldanontransparentmodelstructurewhichishard to interpret using physical knowledge of the system, and they commonly encounter a convergence problem. Most kernel methods fall into the nonparametric type of methods,whichbynatureneedasmanykernelsasthedatapointsunderevaluation. It shouldbekeptinmindthatonlyequation-errortypemodelidentificationmethodswere investigated in the work reported here. The assumption was made that a sufficiently accurateestimationofaircraftstateswasavailable. Analternatemethodtothemodularadaptivereconfigurablecontrolapproachisthe accelerationmeasurements-basedincrementalnonlinearcontrol(AMINC)method.An accurateestimationofanaircraftishardtoachieveduringahighmaneuveringmoment ix oratatransientperiodwhentheflightperformanceishighlyperturbedduetoaircraft failure. Incrementalnonlinearcontrollerssuchasincrementalnonlineardynamicin- version(INDI),incrementalbackstepping(IBKS)andsensor-basedbackstepping(SBB) aresuitedforreconfigurableflightcontroldesignsinthesensethattheydonotrequire completeaircraftmodelknowledge. The main research question for the research presented here was: How can an advanced fault-tolerant flight control system be designed to increase the survivability ofanaircraft?Thisledtotwosubsidiaryquestions: • Howcanthecandidatefunctionapproximationmethods,i.e.multivariatesimplex B-splinesandkernelmethods,beimprovedintermsofapproximationaccuracy andcomputationalefficiency,tomeettheneedofmodel-basedadaptivecontrol andonlineflightenvelopeprotection? • Whatarethebenefitsofusinganaccelerationmeasurements-basedcontrolap- proach, i.e. the sensor based backstepping, as an alternative to a model-based adaptive control approach, when designing a reconfigurable flight controller to dealwithaircraftfailuresinagenericfault-tolerantflightcontrol(FTFC)system? Withregardtoreconfigurablecontrol,theidentifiedmodelshouldenablethecontroller to achieve active reconfiguration and restore the control performance. To answer thesequestions,fourdifferentglobalmodelidentificationmethodsandtwononlinear incrementaladaptivecontrollersweredeveloped. Twomodelidentificationmethodsuseaparametricmodelstructurenamelystan- dard multivariate simplex B-splines. The focus was placed on how to achieve fast parameterestimationduringtheresearchprocessforthesetwomethods. Inthethird identificationmethod,anewmodelstructurecalledtensor-productsimplexB-splines was extended from a single dimension case to a multidimensional case, with a focus on demonstrating the advantage of this new compound model structure in terms of theflexibilityinmodelstructureselection,computationalefficiencyandapproximation power. Thefourthmethodusesakerneltypemodelstructurewhichisalsoparametric. The new recursive kernel approach was developed by combining a classical recursive kernelmethodwithanovelsupportvectorregressionapproach. A model identification method using standard multivariate simplex B-splines has manyadvantages,itcanavoidtheover-fittingproblemwhichoccurswithanordinary polynomial method using a triangulation technique. The approximation power of a simplexB-splinebasedmethodisdeterminedbytheper-simplexpolynomialorderand smoothnessorder,andcanbeincreasedbyincreasingthedensityofthesubdomainsina triangulation. ThissimplexB-splinebasedfunctionapproximationmethodguarantees thatitsoutputisboundedbythemaximumandminimumB-coefficients,thisfacilitates its certification for future real life applications. The linear regression formulation of the simplex B-spline based method allows for applying most of the constrained recursive parameter estimation methods. Furthermore, the simplex B-spline based method has a sparse property, which can lead to high computational efficiency by adopting distributed computation or other modern computing techniques. However, asimplexB-splinemethodcaneasilyyieldalargeamountofunknownparametersifthe functiondimensionexceeds4,whichresultsinahighcomputationalloadconsidering thesmoothnessmaintainingandcovariancematrixupdating.
Description:The list of books you might like
