A disturbance observer–based multi-model soft switching tracking control design is proposed for the near-space interceptor. Initially, based on the Takagi–Sugeno modeling approach, a slow–fast loop soft switching model is employed to approximately describe the nonlinear dynamics of the near-space interceptor. Subsequently, a disturbance observer is constructed to estimate the unknown disturbance. Based on the disturbance observer, a descriptor system approach is proposed to solve the multi-model soft switching tracking control design problem. The suggested controller can not only ensure the stability of the closed-loop near-space interceptor system but also provide an upper bound of the cost function. Moreover, a robust least-squares weighted control allocation algorithm is employed to distribute the virtual control command among the redundant actuators (the aerodynamic fins and reaction jets). Finally, simulation results demonstrate the effectiveness of the proposed control scheme.
RodriguezADickesonJCifdalozO. Modeling and control of scramjet-powered hypersonic vehicles: challenges, trends, & tradeoffs. In: AIAA guidance, navigation and control conference and exhibit, Honolulu, HI, 18–21 August 2008, AIAA paper no. 2008-6793. Reston, VA: AIAA.
2.
DavisMCWhiteJT. X-43A flight-test-determined aerodynamic force and moment characteristics at Mach 7.0. J Spacecraft Rockets2008; 45(3): 472–484.
3.
HankJMMurphyJSMutzmanRC. The X-51A scramjet engine flight demonstration program. In: Proceeding of 15th AIAA international space planes and hypersonic systems and technologies conference, Dayton, OH, 28 April–1 May 2008, AIAA paper no. 2008-2540. Reston, VA: AIAA.
4.
ThukralAInnocentiM. A sliding mode missile pitch autopilot synthesis for high angle of attack maneuvering. IEEE T Contr Syst T1998; 6(3): 359–371.
5.
ShtesselYBShkolnikovIALevantA. Guidance and control of missile interceptor using second-order sliding modes. IEEE T Aero Elec Sys2009; 45(1): 110–124.
6.
KorenAIdanMGolanOM. Integrated sliding mode guidance and control for missile with on-off actuators. J Guid Control Dynam2008; 31(1): 204–214.
XingLDZhangKNChenWC. Optimal control and output feedback considerations for missile with blended aero-fin and lateral impulsive thrust. Chinese J Aeronaut2010; 23(4): 401–408.
9.
ZhouDShaoCT. Dynamics and autopilot design for endoatmospheric interceptors with dual control systems. Aerosp Sci Technol2009; 13(6): 291–300.
10.
ZhaoMYWeiMYHeQR. Research on method of lateral jet and aerodynamic fins compound control based on finite time stability and backstepping approach. J Astronaut2010; 31(9): 2157–2164 (in Chinese).
11.
GuoCLiangXGWangJ-W. Nonlinear disturbance observer-based dynamic inverse control for near space interceptor. J Syst Eng Electron2014; 36(11): 2259–2265 (in Chinese).
12.
GuoCLiangXGWangJ-W. Blended control of near space interceptor by using reaction-jet and aerodynamics. Flight Dyn2014; 32(3): 243–247 (in Chinese).
13.
LiZWeiMYZhouD. Technology of lateral thrust and aerodynamics blended control for anti-air missile. Beijing, China: China Astronautic Publishing House, 2012 (in Chinese).
14.
HeFTongWMZhaoSH. The smooth switching of double modes fuzzy control. Soft Comput2011; 15(5): 889–896.
15.
WangYFJiangCSWuQX. Multi-model soft-switching cost-guaranteed non-fragile control for near-space vehicle. Control Theory Appl2012; 29(4): 440–446 (in Chinese).
16.
WangYFJiangCS. Multi-model robust guaranteed cost soft switching control for near space vehicle. Control Decis2012; 27(5): 658–664 (in Chinese).
17.
Van Der SchaftAJ. L2-gain analysis of nonlinear systems and nonlinear state-feedback H∞ control. IEEE T Automat Contr1992; 37(6): 770–784.
YuSHYuXHShirinzadehB. Continuous finite-time control for robotic manipulators with terminal sliding mode. Automatica2005; 41(11): 1957–1964.
20.
YangJLiSHSuJY. Continuous nonsingular terminal sliding mode control for systems with mismatched disturbances. Automatica2013; 49(7): 2287–2291.
21.
XiaYQFuMX. Compound control methodology for flight vehicles. Berlin: Springer Science Business Media, 2013.
22.
ChenWH. Disturbance observer based control for nonlinear systems. IEEE/ASME T Mech2004; 9(4): 706–710.
23.
LevantA. High-order sliding models, differentiation and output-feedback control. Int J Control2003; 76(9–10): 924–941.
24.
GuoLChenWH. Disturbance attenuation and rejection for systems with nonlinearity via DOBC approach. Int J Robust Nonlin2005; 15(3): 109–125.
25.
WeiXJGuoL. Composite disturbance-observer-based control and H∞ control for complex continuous models. Int J Robust Nonlin2010; 20(1): 106–118.
26.
YangJChenWHLiSH. Non-linear disturbance observer-based robust control for systems with mismatched disturbances/uncertainties. IET Control Theory A2011; 5(18): 2053–2062.
27.
ChenWH. Nonlinear disturbance observer-enhanced dynamic inversion control of missiles. J Guid Control Dynam2003; 26(1): 161–166.
28.
YangJChenWHLiSH. Robust autopilot design of uncertain bank-to-turn missiles using state-space disturbance observers. Proc IMechE, Part G: J Aerospace Engineering2012; 226(1): 97–107.
29.
LiSHYangJ. Robust autopilot design for bank-to-turn missiles using disturbance observers. IEEE T Aero Elec Sys2013; 49(1): 558–579.
30.
ChenXSYangJLiSH. Disturbance observer based multi-variable control of ball mill grinding circuits. J Process Contr2009; 19(7): 1205–1213.
31.
LiuHGuoLZhangY. Composite attitude control for flexible spacecraft with simultaneous disturbance attenuation and rejection performance. Proc IMechE, Part I: J Systems and Control Engineering2012; 226(2): 154–161.
32.
LuKFXiaYQZhuZ. Sliding mode attitude tracking of rigid spacecraft with disturbances. J Franklin I2012; 349(2): 413–440.
33.
XiaYQZhuZFuMY. Attitude tracking of rigid spacecraft with bounded disturbances. IEEE T Ind Electron2011; 58(2): 647–659.
34.
JohansenTAFossenTI. Control allocation—a survey. Automatica2013; 49(5): 1087–1103.
35.
BuffingtonJMEnnsDF. Lyapunov stability analysis of daisy chain control allocation. J Guid Control Dynam1996; 19(6): 1226–1230.
36.
DurhamWC. Constrained control allocation: three moment problem. J Guid Control Dynam1994; 17(2): 330–336.
37.
TjønnasJJohansenTA. Adaptive control allocation. Automatica2008; 44(11): 2754–2765.
38.
HärkegårdO. Dynamic control allocation using constrained quadratic programming. J Guid Control Dynam2004; 27(6): 1028–1034.
39.
HuQLLiBHuoX. Spacecraft attitude tracking control under actuator magnitude deviation and misalignment. Aerosp Sci Technol2013; 28(1): 266–280.
40.
GhaouiLLebretH. Robust solutions to least squares problems with uncertain data. SIAM J Matrix Anal A1997; 18(4): 1035–1064.
41.
CuiLYangY. Disturbance rejection and robust least-squares control allocation in flight control system. J Guid Control Dynam2011; 34(6): 1632–1643.
42.
TanakaKOhtakeHWangHO. A descriptor system approach to fuzzy control system design via fuzzy Lyapunov functions. IEEE T Fuzzy Syst2007; 15(3): 333–341.
43.
BoydSGhaouiLEFeronE. Linear matrix inequalities in system and control theory. Philadelphia, PA: SIAM, 1994.
44.
GahinetPNemirovskiiALaubAJ. LMI control toolbox for use with MATLAB. Natick, MA: The MathWorks Inc., 1995.
45.
TeixeiraMZakS. Stabilizing controller design for uncertain nonlinear systems using fuzzy models. IEEE T Fuzzy Syst1999; 7(2): 133–142.
46.
PetersonIR. A stabilization algorithm for a class of uncertain linear systems. Syst Control Lett1987; 8(4): 351–357.
