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Adaptive gain-scheduling control for hypersonic flight vehicles across wide envelopes based on Guardian map

Published online by Cambridge University Press:  02 April 2025

T.Y. Zhang
Affiliation:
College of Artificial Intelligence, Nankai University, Tianjin, China
M.W. Sun*
Affiliation:
College of Artificial Intelligence, Nankai University, Tianjin, China
Z.Q. Chen
Affiliation:
College of Artificial Intelligence, Nankai University, Tianjin, China
Y.S. Wang
Affiliation:
College of Artificial Intelligence, Tiangong University, Tianjin, China
*
Corresponding author: M.W. Sun; Email: [email protected]

Abstract

In this study, we developed an adaptive gain-scheduling algorithm for hypersonic flight vehicles operating across wide altitude-Mach number envelopes. First, we employed a gap metric-based nominal point selection algorithm to establish a linear parameter-varying (LPV) model more accurate than the traditional Jacobian linearisation method. Active disturbance rejection control (ADRC) was then applied to cope with disturbances and uncertainties, and control gains were scheduled using the Guardian maps (GM) method to adapt to the wide envelope of velocity and altitude. The simulation results demonstrate that under all operating conditions, the proposed algorithm can automatically iterate to obtain a gain-scheduling strategy that meets the flying qualities requirements. Notably, the proposed algorithm exhibited an integral of the time absolute error approximately half of that of the traditional ADRC and significantly lower than that of the GM-LQR method in the ascent phase, demonstrating its excellent control performance and robustness.

Type
Research Article
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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References

Shahzad, S.K. and Hu, W.D. Hypersonic reentry trajectory planning by using hybrid fractional-order particle swarm optimization and gravitational search algorithm, Chin J Aeronaut, 2021, 34, (1), pp 5067.Google Scholar
Mimouni, M.Z., Araar, O., Oudda, A. and Haddad, M. A new control scheme for an aerodynamic-surface-free tilt-rotor convertible UAV, Aeronaut J, 2024, 128, (1324), pp 11191144.Google Scholar
Wang, X. and Xu, B. Robust adaptive control of hypersonic flight vehicle with aero-servo-elastic effect, IEEE Trans Aerosp Electron Syst 2023, 59, (2), pp 19551964.Google Scholar
Suicmez, E.C. and Kutay, A.T. Full envelope nonlinear flight controller design for a novel electric VTOL (eVTOL), Aeronaut J, 2024, 128, (1323), pp 966993.Google Scholar
Feng, Y., Sun, Z.H., Wu, L.N., Wang, Y.S. and Xi, B. Nonlinear adaptive flight control system: performance enhancement and validation, Chin J Aeronaut, 2023, 36, (4), pp 354365.Google Scholar
Wang, G. and Xia, H.W. Fault-tolerant learning control of air-breathing hypersonic vehicles with uncertain parameters and actuator faults, Expert Syst Appl, 2024, 238, p 121874.CrossRefGoogle Scholar
Ni, Z. and Fang, S. Study of the spike-aerodisk-opposing jet on heat protection to both the spike-aerodisk and the blunt body and overall drag reduction in rarefied hypersonic flow in near space, Aerosp Sci Technol, 2024, 147, p109061.Google Scholar
Qu, F., Wang, T., Liu, C., Fu, J. and Bai, J. Aerodynamic shape optimization of the vortex-shock integrated waverider over a wide speed range, Aerosp Sci Technol, 2023, 143, p 108696.Google Scholar
Wu, X., Zhou, Z. and Wang, Z.P. Rapid dynamic aeroelastic response analysis of the highly flexible wing with distributed propellers influence, Aeronaut J, Published online 2024, pp 123.Google Scholar
Wang, F., Fan, P., Zhang, J., Fan, Y. and Yan, J. Preventing inlet unstart in air-breathing hypersonic vehicles using adaptive backstepping control with state constraints, Acta Astronaut, 2023, 211, pp 498509.Google Scholar
Guo, L., Pang, L., Yang, X, Zhao, J and Ma, D. A power and thermal management system for long endurance hypersonic vehicle, Chin J Aeronaut, 2023, 36, pp 2940.Google Scholar
Li, N, Liu, Y, Gong, G, Zhao, L, Yuan, H. A generative deep learning approach for real-time prediction of hypersonic vehicles in fluid-thermo-structural coupling fields, Aerosp Sci Technol, 2023, 139, p 108398.Google Scholar
Xu, B. and Shi, Z. An overview on flight dynamics and control approaches for hypersonic vehicles, Sci China Inf Sci, 2015, 58, (7), pp 119.Google Scholar
Xu, B., Shou, Y., Shi, Z. and Yan, T. Predefined-time hierarchical coordinated neural control for hypersonic reentry vehicle, IEEE Trans. Neural. Netw. Learning Syst., 2023, 34, pp 84568466.CrossRefGoogle ScholarPubMed
Han, J. Auto-disturbances-rejection controller and its applications. Control Decis, 1998, 13, (1), pp 1923.Google Scholar
Sun, M., Wang, Z. and Chen, Z. Practical solution to attitude control within wide envelope, Aircr Eng Aerosp Tech, 2014, 86, (2), pp 117–28.Google Scholar
Gao, Z. Scaling and bandwidth-parameterization based controller tuning, American Control Conference, 2003, vol. 4, pp 49894996.Google Scholar
Huang, Y. and Xue, W. Active disturbance rejection control: Methodology and theoretical analysis, ISA Trans, 2014, 53, (4), pp 963976.CrossRefGoogle ScholarPubMed
Xie, X., Wei, C., Gu, Z. and Shi, K. Relaxed resilient fuzzy stabilization of discrete-time Takagi–Sugeno systems via a higher order time-variant balanced matrix method, IEEE Trans Fuzzy Syst, 2022, 30, pp 50445050.Google Scholar
Ducard, G.J. and Allenspach, M. Review of designs and flight control techniques of hybrid and convertible VTOL UAVs, Aerosp Sci Technol, 2021, 118, p 107035.CrossRefGoogle Scholar
Caigny, D., Camino, J.F., Oliveira, R., Peres, P. and Swevers, J. Gain-scheduled dynamic output feedback control for discrete-time LPV systems, Intl J Robust & Nonlinear, 2012, 22, (5), pp 535558.Google Scholar
Kazemi, M.H. and Tarighi, R. PID-based attitude control of quadrotor using robust pole assignment and LPV modeling, Int. J. Dynam. Control, 2024, pp 113.Google Scholar
Souza, L., Peixoto, M. and Palhares, R.M. New gain-scheduling control conditions for time-varying delayed LPV systems, J Franklin Inst, 2022, 359, pp 719742.Google Scholar
Jiang, W., Zheng, C., Sun, X. and Wang, Y. Switching polytopic linear parameter-varying control for hypersonic vehicles in full envelope, Int. J. Control Autom. Syst., 2023, 22, pp 785796.CrossRefGoogle Scholar
Jiang, W., Wu, K., Wang, Z. and Wang, Y. Gain-scheduled control for morphing aircraft via switching polytopic linear parameter-varying systems, Aerosp Sci Technol, 2020, 107, p 106242.Google Scholar
Vinco, G.M., Sename, O., Strub, G. Linear parameter-varying polytopic modeling and control design for guided projectiles, J Guid Control Dynam, 2024, 47, (3), pp 433447.Google Scholar
Saydy, L., Tits, A. and Abed, E. Guardian maps and the generalized stability of parametrized families of matrices and polynomials, Math Control Sig Syst, 1990, 3, (4), pp 345371.CrossRefGoogle Scholar
Saussie, D., Ouassima, A. and Saydy, L. Aircraft pitch rate control design with guardian maps, 18th Mediterranean Conference on Control and Automation, MED’10; Marrakech, Morocco; 2010, pp 1473–1478.CrossRefGoogle Scholar
Xiao, D., Liu, M., Liu, Y. and Lu, Y. Switching control of a hypersonic vehicle based on guardian maps, Acta Astronaut, 2016, 122, pp 294306.Google Scholar
Liu, Y., Chen, B., Chen, J. and Liu, Y. Rapid parametric modeling and robust analysis for the hypersonic ascent based on gap metrics, Appl Sci, 2023, 13, p 5189.CrossRefGoogle Scholar
Chen, B., Chen, J. and Liu, Y. Guardian maps based robust stability analysis with applications in flight control of hypersonic vehicles, Aerosp Sci Technol, 2020, 106, p 106208.CrossRefGoogle Scholar
Cao, R., Wan, H.W., He, Z. and Lu, Y.P. Multiple model predictive control of perching maneuver based on guardian maps, Chin J Aeronaut, 2022, 35, (5), pp 347360.Google Scholar
French, M. Adaptive control and robustness in the gap metric, IEEE Trans Automat Contr, 2008, 53, pp 461478.Google Scholar
Shaughnessy, J.D., Pinckney, S.Z. and McMinn, J.D. Hypersonic vehicle simulation model: winged-cone configuration, NASA TM 102610, 1990.Google Scholar
Marrison, C. and Stengel, R. Design of robust control systems for a hypersonic aircraft, J Guid Control Dynam, 1998, 21, (1), pp 5863.CrossRefGoogle Scholar
Tao, X., Li, N. and Li, S. Multiple model predictive control for large envelope flight of hypersonic vehicle systems, Inform Sci, 2016, 328, pp 115126.Google Scholar
Cavanini, L., Ippoliti, G. and Camacho, E. Model predictive control for a linear parameter varying model of an UAV, J Intell Robot Syst, 2021, 101, pp 118.Google Scholar
Gao, H., Chen, Z., Sun, M., Huang, J, Wang, Z. and Chen, Z. An efficient fast altitude control for hypersonic vehicle, Control Eng Pract, 2020, 100, p 104426.Google Scholar
Saussié, D., Saydy, L., Akhrif, O. and Berard, C. Gain scheduling with guardian maps for longitudinal flight control, J Guid Control Dynam, 2011, 34, (4), pp 10451059.CrossRefGoogle Scholar
Drob, D.P., Emmert, J.T., Meriwether, J.W., Makela, J.J., Doornbos, E., Conde, M., and Klenzing, J.H. An update to the Horizontal Wind Model (HWM): The quiet time thermosphere, Earth Space Sci, 2015, 2, (7), pp 301319.CrossRefGoogle Scholar
Drob, D.P., Emmert, J.T., Crowley, G., Picone, J., Shepherd, G.G., Skinner, W., and Vincent, R.A. An empirical model of the Earth’s horizontal wind fields: HWM07. J Geophys Res Space Phys, 2008, 113, (A12).CrossRefGoogle Scholar
Madden, M.M. Verifying Implementation of the Dryden Turbulence Model and MIL-F-8785 Gust Gradient, 2018 Modeling and Simulation Technologies Conference, 2018, p 3580.CrossRefGoogle Scholar