Applications of advanced control methods in spacecrafts: progress, challenges, and future prospects



We aim at examining the current status of advanced control methods in spacecrafts from an engineer’s perspective. Instead of reviewing all the fancy theoretical results in advanced control for aerospace vehicles, the focus is on the advanced control methods that have been practically applied to spacecrafts during flight tests, or have been tested in real time on ground facilities and general testbeds/simulators built with actual flight data. The aim is to provide engineers with all the possible control laws that are readily available rather than those that are tested only in the laboratory at the moment. It turns out that despite the blooming developments of modern control theories, most of them have various limitations, which stop them from being practically applied to spacecrafts. There are a limited number of spacecrafts that are controlled by advanced control methods, among which H2/H robust control is the most popular method to deal with flexible structures, adaptive control is commonly used to deal with model/parameter uncertainty, and the linear quadratic regulator (LQR) is the most frequently used method in case of optimal control. It is hoped that this review paper will enlighten aerospace engineers who hold an open mind about advanced control methods, as well as scholars who are enthusiastic about engineering-oriented problems.


Spacecraft control Robust control Adaptive control Optimal control 

CLC number

V448.22 TP273 


  1. Adachi, S., Yamaguchi, I., Kida, T., et al., 1999. On-orbit system identification experiments on Engineering Test Satellite-VI. Contr. Eng. Pract., 7(7): 831–841. Scholar
  2. Anderson, B.D.O., Moore, J.B., 1990). Optimal Control: Linear Quadratic Methods. Prentice Hall, USA.MATHGoogle Scholar
  3. Anthony, T., Andersen, G., 1995). On-orbit modal identification of the Hubble Space Telescope. Proc. American Control Conf., p.402–406. Scholar
  4. Antsaklis, P.J., Michel, A.N., 2007. A Linear Systems Primer. Birkhäuser, Boston.MATHGoogle Scholar
  5. Åström, K.J., Wittenmark, B., 2008. Adaptive Control (2nd Ed.). Dover Publications Inc., USA.Google Scholar
  6. Bedrossian, N., Bhatt, S., 2008. Space station zero-propellant maneuver guidance trajectories compared to eigenaxis. Proc. American Control Conf., p.4833–4838. Scholar
  7. Bedrossian, N., Bhatt, S., Lammers, M., et al., 2007). First ever flight demonstration of zero propellant maneuverTM attitude control concept. Proc. AIAA Guidance, Navigation and Control Conf. and Exhibit, p.1–12. Scholar
  8. Betts, J.T., Kolmanovsky, I., 2002. Practical methods for optimal control using nonlinear programming. Appl. Mech. Rev., 55(4):B68. Scholar
  9. Bharadwaj, S., Osipchuk, M., Mease, K.D., et al., 1998. Geometry and inverse optimality in global attitude stabilization. J. Guid. Contr. Dyn., 21(6): 930–939. Scholar
  10. Bukley, A.P., 1995. Hubble Space Telescope pointing control system design improvement study results. J. Guid. Contr. Dyn., 18(2): 194–199. Scholar
  11. Burken, J., Nguyen, N., Griffin, B., 2010. Adaptive flight control design with optimal control modification on an F-18 aircraft model. Proc. AIAA Infotech@Aerospace, p.1–17. Scholar
  12. Cao, C.Y., Hovakimyan, N., 2008. Design and analysis of a novel L1 adaptive control architecture with guaranteed transient performance. IEEE Trans. Autom. Contr., 53(2): 586–591. Scholar
  13. Charbonnel, C., 2010. H controller design and µ-analysis: powerful tools for flexible satellite attitude control. Proc. AIAA Guidance, Navigation, and Control Conf., p.1–14. Scholar
  14. Corraro, F., Cuciniello, G., Morani, G., et al., 2011a). Advanced GN&C technologies for TAEM: flight test results of the Italian Unmanned Space Vehicle. Proc. AIAA Guidance, Navigation, and Control Conf, p.2345–2362.Google Scholar
  15. Corraro, F., Cuciniello, G., Morani, G., 2011b). Flight control strategies for transonic phase of high lift reentry vehicles: comparison and flight testing. Proc. 8th Int. ESA Conf. on Guidance and Navigation Control Systems.Google Scholar
  16. DeKock, B., Sanders, D., Vanzwieten, T., et al., 2011. Design and integration of an all-magnetic attitude control system for FASTSAT-HSV01’s multiple pointing objectives. Proc. 34th Annual Guidance and Control Conf, p.1–19.Google Scholar
  17. Doyle, J., 1984. Lecture Notes in Advanced Multivariable Control. Lecture Note, ONR/Honeywell Workshop, Minneapolis, USA.Google Scholar
  18. Elnagar, G., Kazemi, M.A., Razzaghi, M., 1995. The pseudospectral legendre method for discretizing optimal control problem. IEEE Trans. Autom. Contr., 40(10): 1793–1796. Scholar
  19. Francis, B.A., 1987. A Course in H Control Theory. Springer-Verlag, New York.CrossRefGoogle Scholar
  20. Freeman, R.A., Kokotovic, P.V., 1995. Optimal nonlinear controllers for feedback linearizable systems. Proc. American Control Conf., p.2722–2726. Scholar
  21. Freeman, R.A., Kokotovic, P.V., 1996. Inverse optimality in robust stabilization. SIAM J. Contr. Optim., 34(4): 1365–1391. Scholar
  22. Fujiwara, Y., Nagano, H., Yonechi, H., et al., 2003. The performance of attitude control system on orbit of Data Relay Test Satellite (DRTS). Proc. 21st Int. Communications Satellite Systems Conf. and Exhibit, p.1–8. Scholar
  23. Glover, K., 1984. All optimal Hankel-norm approximations of linear multivariable systems and their L8 error bounds. Int. J. Contr., 39(6): 1115–1193. Scholar
  24. Gong, Q., Ross, I.M., Kang, W., et al., 2008. Connections between the covector mapping theorem and convergence of pseudospectral methods for optimal control. Comput. Optim. Appl., 41(3): 307–335. Scholar
  25. Grocott, S., How, J., Miller, D., et al., 1994. Robust control design and implementation on the middeck active control experiment. J. Guid. Contr. Dyn., 17(6): 1163–1170. Scholar
  26. Hamada, Y., Ohtani, T., Kida, T., et al., 2011. Synthesis of a linearly interpolated gain scheduling controller for large flexible spacecraft ETS-VIII. Contr. Eng. Pract., 19(6): 611–625. Scholar
  27. Hanson, J., 2002. A plan for advanced guidance and control technology for 2nd generation reusable launch vehicles. Proc. AIAA Guidance, Navigation, and Control Conf. and Exhibit, p.1–9. Scholar
  28. Horri, N.M., Palmer, P., Roberts, M., 2011. Design and validation of inverse optimisation software for the attitude control of microsatellites. Acta Astron., 69(11–12):997–1006. Scholar
  29. How, J., Hall, S.R., Haddad, W.M., 1994. Robust controllers for the middeck active control experiment using Popov controller synthesis. IEEE Trans. Contr. Syst. Technol., 2(2): 73–87. Scholar
  30. How, J., Glaese, R., Grocott, S., et al., 1996. Finite element model-based robust controllers for the middeck active control experiment (MACE). IEEE Trans. Contr. Syst. Technol., 5(1): 110–118. Scholar
  31. Hu, J., 1998. All coefficients adaptive reentry lifting control of manned spacecraft. J. Astron., 19(1): 8–12 (in Chinese).Google Scholar
  32. Hu, J., 2014. Demonstration and Proof of a First-Order Characteristic Model Applied to Prediction-Based All-Coefficient Self-Adaptive Corrector. Technical Report CEK-5T1.LB4, Beijing Institute of Control Engineering (in Chinese).Google Scholar
  33. Hu, J., Zhang, Z., 2014. A study on the reentry guidance for a manned lunar return vehicle. Contr. Theory Appl., 31(12): 1678–1685.Google Scholar
  34. Hu, J., Xie, Y.C., Zhang, H., et al., 2011. Shenzhou-8 spacecraft guidance navigation and control system and flight result evaluation for rendezvous and docking. Aerosp. Contr. Appl., 37(6): 1–5 (in Chinese).Google Scholar
  35. Huang, H., 2015. Multiple characteristic model-based goldensection adaptive control: stability and optimization. Int. J. Adapt. Contr. Signal Process., 29(7): 877–904. Scholar
  36. Karpenko, M., Bhatt, S., Bedrossian, N., et al., 2012. First flight results on time-optimal spacecraft slews. J. Guid. Contr. Dyn., 35(2): 367–376. Scholar
  37. Kharisov, E., Gregory, I., Cao, C., et al., 2008. L1 adaptive control law for flexible space launch vehicle and proposed plan for flight validation. Proc. AIAA Guidance, Navigation and Control Conf. and Exhibit, p.1–20. Scholar
  38. Kida, T., Yamaguchi, I., Sekiguchi, T., 1997. On-orbit robust control experiment of flexible spacecraft ETSVI. J. Guid. Contr. Dyn., 20(5): 865–872. Scholar
  39. Moylan, P., Anderson, B., 1973. Nonlinear regulator theory and an inverse optimal control problem. IEEE Trans. Autom. Contr., 18(5): 460–465. Scholar
  40. Nagashio, T., Kida, T., Hamada, Y., et al., 2014. Robust two-degrees-of-freedom attitude controller design and flight test result for Engineering Test Satellite-VIII spacecraft. IEEE Trans. Contr. Syst. Technol., 22(1): 157–168. Scholar
  41. Narendra, K.S., Han, Z., 2011. The changing face of adaptive control: the use of multiple models. Ann. Rev. Contr., 335(1): 1–12. Scholar
  42. Nebula, F., Ariola, M., 2013. Italian Unmanned Space Vehicle mission: flight results of the virtual air data algorithm. Proc. 21st Mediterranean Conf. on Control and Automation, p.73–81. Scholar
  43. Nurre, G.S., Sharkey, J.P., Nelson, J.D., et al., 1995. Preservicing mission, on-orbit modifications to Hubble Space Telescope pointing control system. J. Guid. Contr. Dyn., 18(2): 222–229. Scholar
  44. Ohtani, T., Hamada, Y., Nagashio, T., et al., 2009. Robust attitude control using µ-synthesis for the large flexible satellite ETS-VIII. J. Space Technol. Sci., 25(1): 27–40. Scholar
  45. Orr, J., VanZwieten, T.S., 2012. Robust, practical adaptive control for launch vehicles. Proc. AIAA Guidance, Navigation, and Control Conf., p.1–20. Scholar
  46. Paris, S., Riehl, J., Sjauw, W., 2006. Enhanced procedures for direct trajectory optimization using nonlinear programming and implicit integration. Proc. AIAA/AAS Astrodynamics Specialist Conf. and Exhibit, p.1–19. Scholar
  47. Proulx, R., Ross, I.M., 2001. Time-optimal reorientation of asymmetric rigid bodies. Adv. Astronaut. Sci., 109: 1207–1227.Google Scholar
  48. Psiaki, M.L., 2001. Magnetic torquer attitude control via asymptotic periodic linear quadratic regulation. J. Guid. Contr. Dyn., 24(2): 386–394. Scholar
  49. Ross, I.M., 2005a). A historical introduction to the covector mapping principle. Proc. AAS/AIAA Astrodynamics Specialist Conf., p.1–21.Google Scholar
  50. Ross, I.M., 2005b). A roadmap for optimal control: the right way to commute. Proc. Annual Princeton Conf., p.210–231. Scholar
  51. Ross, I.M., 2007. A Beginner’s Guide to DIDO: a MATLAB Application Package for Solving Optimal Control Problems. Available from Scholar
  52. Ross, I.M., Fahroo, F., 2004. Pseudospectral methods for optimal motion planning of differentially flat systems. IEEE Trans. Autom. Contr., 49(8): 1410–1413. Scholar
  53. Ross, I.M., Gong, Q., 2010. Emerging Principles in Fast Trajectory Optimization. Course, Naval Postgraduate School, Monterey, CA, USA.Google Scholar
  54. Ross, I.M., Karpenko, M., 2012. A review of pseudospectral optimal control: from theory to flight. Ann. Rev. Contr., 36(2): 182–197. Scholar
  55. Rudin, W., 1975. Functional Analysis. McGraw-Hill, New York, USA.MATHGoogle Scholar
  56. Scarritt, S., 2008. Nonlinear model reference adaptive control for satellite attitude tracking. Proc. AIAA Guidance, Navigation and Control Conf. and Exhibit, p.1–10. Scholar
  57. Thompson, M.O., Hunley, J.D., 2000. Flight Research: Problems Encountered and What They Should Teach Us. Technical Report NASA/SP-2000-4522, NASA.Google Scholar
  58. Wall, J.H., Miller, C.J., Hanson, C.E., et al., 2015. Inflight suppression of a destabilized F/A-18 structural mode using the space launch system adaptive augmenting control system. Proc. AIAA Guidance, Navigation, and Control Conf., p.1–22.Google Scholar
  59. Woods-Vedeler, J.A., Horta, L.G., 1996. On-Orbit Application of H to the Middeck Active Controls Experiment: Overview of Results. NASA Technical Memorandum 110239.Google Scholar
  60. Wu, H.X., 1990. All Coefficient Adaptive Control Theory and Applications. National Defense Industry Press, Beijing (in Chinese).Google Scholar
  61. Wu, H.X., Liu, Y.W., Liu, Z., et al., 2001. Characteristic modeling and the control of flexible structure. Sci. China Inform. Sci., 44(4): 278–291.MATHGoogle Scholar
  62. Wu, H.X., Hu, J., Xie, Y.C., 2007. Characteristic modelbased all-coefficient adaptive control method and its applications. IEEE Trans. Syst. Man Cybern. Part C, 37(2): 213–221. Scholar
  63. Wu, H.X., Hu, J., Xie, Y.C., 2009. Characteristic Model Based Intelligent and Adaptive Control. China Science and Technology Press, Beijing (in Chinese).Google Scholar
  64. Xie, Y.C., Wu, H.X., 1992. The application of the golden section in adaptive robust controller design. Acta Autom. Sin., 18(2): 177–185 (in Chinese).Google Scholar
  65. Xie, Y.C., Hu, J., Wang, M., et al., 2013. Accurate and stable control of Shenzhou spacecraft in rendezvous and docking. Proc. 19th IFAC Symp. on Automatic Control in Aerospace, p.524–528. Scholar
  66. Yamada, K., Yonechi, H., Wakao, M., et al., 2003. Adaptive attitude control of the data relay test satellite. Proc. 21st Int. Communications Satellite Systems Conf. and Exhibit, p.1–7.Google Scholar
  67. Yu, L., 2002. Robust Control—LMI Method. Tsinghua University, China (in Chinese).Google Scholar
  68. Zhou, K.M., Doyle, J.C., 1999. Essentials of Robust Control. Prentice Hall, New Jersey, USA.MATHGoogle Scholar
  69. Zhou, K.M., Doyle, J.C., Glover, K., 1996. Robust and Optimal Control. Prentice Hall, Upper Saddle River, New Jersey, USA.MATHGoogle Scholar

Copyright information

© Journal of Zhejiang University Science Editorial Office and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Yong-chun Xie
    • 1
    • 2
  • Huang Huang
    • 1
    • 2
  • Yong Hu
    • 1
    • 2
  • Guo-qi Zhang
    • 1
    • 2
  1. 1.Science and Technology on Space Intelligent Control LaboratoryBeijingChina
  2. 2.Beijing Institute of Control EngineeringBeijingChina

Personalised recommendations