Robust LPV modeling and control of aircraft flying through wind disturbance
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摘要
This article deals with the disturbance attenuation control of aircraft flying through wind shear via Linear Parameter Varying(LPV) modeling and control method. A Flight Dynamics Model(FDM) with wind shear effects considered was established in wind coordinate system. An LPV FDM was built up based on function substitution whose decomposing function was optimized by Genetic Algorithm(GA). The wind disturbance was explicitly included in the system matrix of LPV FDM. Taking wind disturbance as external uncertainties, robust LPV control method with the LPV FDM was put forward. Based on ride quality and flight safety requirements in wind disturbance, longitudinal and lateral output feedback robust LPV controllers were designed respectively,in which the scheduling flight states in LPV model were actually dependent parameters in LPV control. The results indicate that LPV FDM can reflect the instantaneous dynamics of nonlinear system especially at the boundary of aerodynamic envelope. Furthermore, the LPV FDM also can approach nonlinear FDM's response in wind disturbance special flight. Compared with a parameter-invariant LQR controller designed with a small-disturbance FDM, the LPV controllers show preferable robustness and stability for disturbance attenuation.
This article deals with the disturbance attenuation control of aircraft flying through wind shear via Linear Parameter Varying(LPV) modeling and control method. A Flight Dynamics Model(FDM) with wind shear effects considered was established in wind coordinate system. An LPV FDM was built up based on function substitution whose decomposing function was optimized by Genetic Algorithm(GA). The wind disturbance was explicitly included in the system matrix of LPV FDM. Taking wind disturbance as external uncertainties, robust LPV control method with the LPV FDM was put forward. Based on ride quality and flight safety requirements in wind disturbance, longitudinal and lateral output feedback robust LPV controllers were designed respectively,in which the scheduling flight states in LPV model were actually dependent parameters in LPV control. The results indicate that LPV FDM can reflect the instantaneous dynamics of nonlinear system especially at the boundary of aerodynamic envelope. Furthermore, the LPV FDM also can approach nonlinear FDM's response in wind disturbance special flight. Compared with a parameter-invariant LQR controller designed with a small-disturbance FDM, the LPV controllers show preferable robustness and stability for disturbance attenuation.
This article deals with the disturbance attenuation control of aircraft flying through wind shear via Linear Parameter Varying(LPV) modeling and control method. A Flight Dynamics Model(FDM) with wind shear effects considered was established in wind coordinate system. An LPV FDM was built up based on function substitution whose decomposing function was optimized by Genetic Algorithm(GA). The wind disturbance was explicitly included in the system matrix of LPV FDM. Taking wind disturbance as external uncertainties, robust LPV control method with the LPV FDM was put forward. Based on ride quality and flight safety requirements in wind disturbance, longitudinal and lateral output feedback robust LPV controllers were designed respectively,in which the scheduling flight states in LPV model were actually dependent parameters in LPV control. The results indicate that LPV FDM can reflect the instantaneous dynamics of nonlinear system especially at the boundary of aerodynamic envelope. Furthermore, the LPV FDM also can approach nonlinear FDM's response in wind disturbance special flight. Compared with a parameter-invariant LQR controller designed with a small-disturbance FDM, the LPV controllers show preferable robustness and stability for disturbance attenuation.
引文
1.Aviation Safety.Statistical summary of commercial jet airplane accidents[Internet].Seattle:Boeing Commercial Airplanes[updated 2017 July;cited 2018 April].Available from:http://www.boeing.com/resources/boeingdotcom/company/about_bca/pdf/statsum.pdf.
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3.Dogan A.Guidance strategies for microburst escape[dissertation].Michigan:University of Michigan;2000.
4.Richadson JR,Atkins EM,Kabamba PT.Envelopes for flight through stochastic gusts.J Guid Control Dyn 2013;36(5):1464-76.
5.Jordan T,Langford W,Belcastro C.Development of a dynamically scaled generic transport model testbed for flight research experiments.Washington,D.C.:NASA Langley Research Center;2004.Report No.:20040085988.
6.Frost W,Bowles RL.Wind shear terms in the equations of aircraft motion.J Aircr 1984;21(11):866-72.
7.Bouadi H,Mora-Camino F,Choukroun D.Space-indexed control for aircraft vertical guidance with time constraint.J Guid Control Dyn 2014;37(4):1103-13.
8.Luo QN,Duan HB.Symbolic control approach to aircraft taking off in wind shear.Aircr Eng Aerosp Technol 2015;87(1):45-51.
9.Pourtakdoust SH,Kiani M,Hassanpour A.Optimal trajectory planning for flight through microburst wind shears.Aerosp Sci Technol 2011;15:567-76.
10.Othman N,Kanazaki M.Development of multi-objective trajectory-optimization method and its application to improve aircraft landing.Aerosp Sci Technol 2016;58:166-77.
11.Fu P,Zhou X,Yuan SZ.NDI-PID based control law design for aircraft approaching in low-altitude windshear.Electron Opt Control 2015;23(11):33-9[Chinese].
12.Guo Q,Yu T,Jiang D.Robust H1positional control of 2-DOFrobotic arm driven by electro-hydraulic servo system.ISA Trans2015;59:55-64.
13.Guo Q,Wang Q,Liu YL.Antiwindup control of an electrohydraulic system with load disturbance and model uncertainty.IEEETrans Ind Inf 2018;14(7):3097-108.
14.Hess RA,Peng C.Design for robust aircraft flight control.J Aircr2018;55(2):875-86.
15.Liao F,Wang JL,Poh EK.Fault-tolerant robust automatic landing control design.J Guid Control Dyn 2005;28(5):854-71.
16.Jafar Z,Allahyar M,Mohmmad RJM.Design and comparison of LQG/LTR and H1controllers for a VSTOL flight control system.J Franklin Inst 2007;344:577-94.
17.Stevens BL.Aircraft control and simulation.3rd ed.New York:John Wiley and Sons;2003.
18.Hou YZ,Wang Q,Dong CY.Gain scheduled control:switched polytopic system approach.J Guid Control Dyn 2011;34(2):623-8.
19.Sun B,Yang LY,Zhang J.Robust LPV control design based on HOSVD.J Beijing Univ Aeronaut Astronaut 2016;42(7):1536-42[Chinese].
20.Yue T,Wang LX,Ai JQ.Gain self-scheduled H1control for morphing aircraft in the wing transition process based on an LPVmodel.Chin J Aeronaut 2013;26(4):909-17.
21.Marcos A,Balas GJ.Development of linear-parameter-varying models for aircraft.J Guid Control Dyn 2004;27(2):218-28.
22.Yue T,Wang LX.Longitudinal linear parameter varying modeling and simulation of morphing aircraft.J Aircr 2013;50(6):1673-81.
23.Al-Jiboory AK,Zhu GM,Swei SSM.LPV modeling of a flexible wing aircraft using modal alignment and adaptive gridding methods.Aerosp Sci Technol 2017;66:92-102.
24.Jens DR,Neville KW,Draxler JG.Aerodynamic data and flight control system description for the 737-600/-700/-800/-900 training simulator.Seattle:The Boeing Company;2003.Report No.:D611A001-VOL1.
25.Shikany DA,Neville KW,Harrington TA.Aerodynamic data for the 737-800 training simulator.Seattle:The Boeing Company;2003.Report No.:D611A001-VOL3.
26.Lim SY.Analysis and control of linear parameter varying systems[dissertation].California:Stanford University;1999.
27.Giovanni M,Andrea P.Ride quality of civil aircraft from a probabilistic viewpoint.J Aircr 2000;23(2):319-24.
28.Gao ZX,Gu HB,Liu H.Real-time simulation of large aircraft flying through microburst wind field.Chin J Aeronaut 2009;22(5):459-66.
29.Stefan S,Thomas L,Diana A.Autonomous flight envelope estimation for loss-of-control prevention.J Guid Control Dyn2017;40(4):847-62.
2.Gawron VJ.Airplane upset recovery training evaluation report.Washington,D.C.:NASA Ames Research Center;2002.Report No.:2002211405.
3.Dogan A.Guidance strategies for microburst escape[dissertation].Michigan:University of Michigan;2000.
4.Richadson JR,Atkins EM,Kabamba PT.Envelopes for flight through stochastic gusts.J Guid Control Dyn 2013;36(5):1464-76.
5.Jordan T,Langford W,Belcastro C.Development of a dynamically scaled generic transport model testbed for flight research experiments.Washington,D.C.:NASA Langley Research Center;2004.Report No.:20040085988.
6.Frost W,Bowles RL.Wind shear terms in the equations of aircraft motion.J Aircr 1984;21(11):866-72.
7.Bouadi H,Mora-Camino F,Choukroun D.Space-indexed control for aircraft vertical guidance with time constraint.J Guid Control Dyn 2014;37(4):1103-13.
8.Luo QN,Duan HB.Symbolic control approach to aircraft taking off in wind shear.Aircr Eng Aerosp Technol 2015;87(1):45-51.
9.Pourtakdoust SH,Kiani M,Hassanpour A.Optimal trajectory planning for flight through microburst wind shears.Aerosp Sci Technol 2011;15:567-76.
10.Othman N,Kanazaki M.Development of multi-objective trajectory-optimization method and its application to improve aircraft landing.Aerosp Sci Technol 2016;58:166-77.
11.Fu P,Zhou X,Yuan SZ.NDI-PID based control law design for aircraft approaching in low-altitude windshear.Electron Opt Control 2015;23(11):33-9[Chinese].
12.Guo Q,Yu T,Jiang D.Robust H1positional control of 2-DOFrobotic arm driven by electro-hydraulic servo system.ISA Trans2015;59:55-64.
13.Guo Q,Wang Q,Liu YL.Antiwindup control of an electrohydraulic system with load disturbance and model uncertainty.IEEETrans Ind Inf 2018;14(7):3097-108.
14.Hess RA,Peng C.Design for robust aircraft flight control.J Aircr2018;55(2):875-86.
15.Liao F,Wang JL,Poh EK.Fault-tolerant robust automatic landing control design.J Guid Control Dyn 2005;28(5):854-71.
16.Jafar Z,Allahyar M,Mohmmad RJM.Design and comparison of LQG/LTR and H1controllers for a VSTOL flight control system.J Franklin Inst 2007;344:577-94.
17.Stevens BL.Aircraft control and simulation.3rd ed.New York:John Wiley and Sons;2003.
18.Hou YZ,Wang Q,Dong CY.Gain scheduled control:switched polytopic system approach.J Guid Control Dyn 2011;34(2):623-8.
19.Sun B,Yang LY,Zhang J.Robust LPV control design based on HOSVD.J Beijing Univ Aeronaut Astronaut 2016;42(7):1536-42[Chinese].
20.Yue T,Wang LX,Ai JQ.Gain self-scheduled H1control for morphing aircraft in the wing transition process based on an LPVmodel.Chin J Aeronaut 2013;26(4):909-17.
21.Marcos A,Balas GJ.Development of linear-parameter-varying models for aircraft.J Guid Control Dyn 2004;27(2):218-28.
22.Yue T,Wang LX.Longitudinal linear parameter varying modeling and simulation of morphing aircraft.J Aircr 2013;50(6):1673-81.
23.Al-Jiboory AK,Zhu GM,Swei SSM.LPV modeling of a flexible wing aircraft using modal alignment and adaptive gridding methods.Aerosp Sci Technol 2017;66:92-102.
24.Jens DR,Neville KW,Draxler JG.Aerodynamic data and flight control system description for the 737-600/-700/-800/-900 training simulator.Seattle:The Boeing Company;2003.Report No.:D611A001-VOL1.
25.Shikany DA,Neville KW,Harrington TA.Aerodynamic data for the 737-800 training simulator.Seattle:The Boeing Company;2003.Report No.:D611A001-VOL3.
26.Lim SY.Analysis and control of linear parameter varying systems[dissertation].California:Stanford University;1999.
27.Giovanni M,Andrea P.Ride quality of civil aircraft from a probabilistic viewpoint.J Aircr 2000;23(2):319-24.
28.Gao ZX,Gu HB,Liu H.Real-time simulation of large aircraft flying through microburst wind field.Chin J Aeronaut 2009;22(5):459-66.
29.Stefan S,Thomas L,Diana A.Autonomous flight envelope estimation for loss-of-control prevention.J Guid Control Dyn2017;40(4):847-62.