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

Abstract

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.

Keywords

Spacecraft control / Robust control / Adaptive control / Optimal control

References

[1] Adachi, S., Yamaguchi, I., Kida, T., , 1999. On-orbit system identification experiments on Engineering Test Satellite-VI. Contr. Eng. Pract., 7(7):831–841. http://dx.doi.org/10.1016/S0967-0661(99)00032-5

[2] Anderson, B.D.O., Moore, J.B., 1990. Optimal Control: Linear Quadratic Methods. Prentice Hall, USA.

[3] Anthony, T., Andersen, G., 1995. On-orbit modal identification of the Hubble Space Telescope. Proc. American Control Conf., p.402–406. http://dx.doi.org/10.1109/ACC.1995.529278

[4] Antsaklis, P.J., Michel, A.N., 2007. A Linear Systems Primer. Birkhäuser, Boston.

[5] Åström, K.J., Wittenmark, B., 2008. Adaptive Control (2nd Ed.). Dover Publications Inc., USA.

[6] Bedrossian, N., Bhatt, S., 2008. Space station zero-propellant maneuver guidance trajectories compared to eigenaxis. Proc. American Control Conf., p.4833–4838. http://dx.doi.org/10.1109/ACC.2008.4587259

[7] Bedrossian, N., Bhatt, S., Lammers, M., , 2007. First ever flight demonstration of zero propellant maneuverTM attitude control concept. Proc. AIAA Guidance, Navigation and Control Conf. and Exhibit, p.1–12. http://dx.doi.org/10.2514/6.2007-6734

[8] Betts, J.T., Kolmanovsky, I., 2002. Practical methods for optimal control using nonlinear programming. Appl. Mech. Rev., 55(4):B68. http://dx.doi.org/10.1115/1.1483351

[9] Bharadwaj, S., Osipchuk, M., Mease, K.D., , 1998. Geometry and inverse optimality in global attitude stabilization. J. Guid. Contr. Dyn., 21(6):930–939. http://dx.doi.org/10.2514/2.4327

[10] Bukley, A.P., 1995. Hubble Space Telescope pointing control system design improvement study results. J. Guid. Contr. Dyn., 18(2):194–199. http://dx.doi.org/10.2514/3.21369

[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. http://dx.doi.org/10.2514/6.2010-3364

[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. http://dx.doi.org/10.1109/TAC.2007.914282

[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. http://dx.doi.org/10.2514/6.2010-7907

[14] Corraro, F., Cuciniello, G., Morani, G., , 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.

[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.

[16] DeKock, B., Sanders, D., Vanzwieten, T., , 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.

[17] Doyle, J., 1984. Lecture Notes in Advanced Multivariable Control. Lecture Note, ONR/Honeywell Workshop, Minneapolis, USA.

[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. http://dx.doi.org/10.1109/9.467672

[19] Francis, B.A., 1987. A Course in H∞ Control Theory. Springer-Verlag, New York.

[20] Freeman, R.A., Kokotovic, P.V., 1995. Optimal nonlinear controllers for feedback linearizable systems. Proc. American Control Conf., p.2722–2726. http://dx.doi.org/10.1109/ACC.1995.532343

[21] Freeman, R.A., Kokotovic, P.V., 1996. Inverse optimality in robust stabilization. SIAM J. Contr. Optim., 34(4):1365–1391. http://dx.doi.org/10.1137/S0363012993258732

[22] Fujiwara, Y., Nagano, H., Yonechi, H., , 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. http://dx.doi.org/10.2514/6.2003-2365

[23] Glover, K., 1984. All optimal Hankel-norm approximations of linear multivariable systems and their L∞ error bounds. Int. J. Contr., 39(6):1115–1193. http://dx.doi.org/10.1080/00207178408933239

[24] Gong, Q., Ross, I.M., Kang, W., , 2008. Connections between the covector mapping theorem and convergence of pseudospectral methods for optimal control. Comput. Optim. Appl., 41(3):307–335. http://dx.doi.org/10.1007/s10589-007-9102-4

[25] Grocott, S., How, J., Miller, D., , 1994. Robust control design and implementation on the middeck active control experiment. J. Guid. Contr. Dyn., 17(6):1163–1170. http://dx.doi.org/10.2514/3.21328

[26] Hamada, Y., Ohtani, T., Kida, T., , 2011. Synthesis of a linearly interpolated gain scheduling controller for large flexible spacecraft ETS-VIII. Contr. Eng. Pract., 19(6):611–625. http://dx.doi.org/10.1016/j.conengprac.2011.02.005

[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. http://dx.doi.org/10.2514/6.2002-4557

[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. http://dx.doi.org/10.1016/j.actaastro.2011.07.010

[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. http://dx.doi.org/10.1109/87.294331

[30] How, J., Glaese, R., Grocott, S., , 1996. Finite element model-based robust controllers for the middeck active control experiment (MACE). IEEE Trans. Contr. Syst. Technol., 5(1):110–118. http://dx.doi.org/10.1109/87.553669

[31] Hu, J., 1998. All coefficients adaptive reentry lifting control of manned spacecraft. J. Astron., 19(1):8–12 (in Chinese).

[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).

[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.

[34] Hu, J., Xie, Y.C., Zhang, H., , 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).

[35] Huang, H., 2015. Multiple characteristic model-based goldensection adaptive control: stability and optimization. Int. J. Adapt. Contr. Signal Process., 29(7):877–904. http://dx.doi.org/10.1002/acs.2510

[36] Karpenko, M., Bhatt, S., Bedrossian, N., , 2012. First flight results on time-optimal spacecraft slews. J. Guid. Contr. Dyn., 35(2):367–376. http://dx.doi.org/10.2514/1.54937

[37] Kharisov, E., Gregory, I., Cao, C., , 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. http://dx.doi.org/10.2514/6.2008-7128

[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. http://dx.doi.org/10.2514/2.4159

[39] Moylan, P., Anderson, B., 1973. Nonlinear regulator theory and an inverse optimal control problem. IEEE Trans. Autom. Contr., 18(5):460–465. http://dx.doi.org/10.1109/TAC.1973.1100365

[40] Nagashio, T., Kida, T., Hamada, Y., , 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. http://dx.doi.org/10.1109/TCST.2013.2248009

[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. http://dx.doi.org/10.1016/j.arcontrol.2011.03.010

[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. http://dx.doi.org/10.1109/MED.2013.6608701

[43] Nurre, G.S., Sharkey, J.P., Nelson, J.D., , 1995. Preservicing mission, on-orbit modifications to Hubble Space Telescope pointing control system. J. Guid. Contr. Dyn., 18(2):222–229.http://dx.doi.org/10.2514/3.21373

[44] Ohtani, T., Hamada, Y., Nagashio, T., , 2009. Robust attitude control using μ-synthesis for the large flexible satellite ETS-VIII. J. Space Technol. Sci., 25(1):27–40. http://dx.doi.org/10.11230/jsts.25.1_27

[45] Orr, J., VanZwieten, T.S., 2012. Robust, practical adaptive control for launch vehicles. Proc. AIAA Guidance, Navigation, and Control Conf., p.1–20. http://dx.doi.org/10.2514/6.2012-4549

[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. http://dx.doi.org/10.2514/6.2006-6309

[47] Proulx, R., Ross, I.M., 2001. Time-optimal reorientation of asymmetric rigid bodies. Adv. Astronaut. Sci., 109:1207–1227.

[48] Psiaki, M.L., 2001. Magnetic torquer attitude control via asymptotic periodic linear quadratic regulation. J. Guid. Contr. Dyn., 24(2):386–394. http://dx.doi.org/10.2514/2.4723

[49] Ross, I.M., 2005a. A historical introduction to the covector mapping principle. Proc. AAS/AIAA Astrodynamics Specialist Conf., p.1–21.

[50] Ross, I.M., 2005b. A roadmap for optimal control: the right way to commute. Proc. Annual Princeton Conf., p.210–231. http://dx.doi.org/10.1196/annals.1370.015

[51] Ross, I.M., 2007. A Beginner’s Guide to DIDO: a MATLAB Application Package for Solving Optimal Control Problems. Available from http://www.elissarglobal.com/ industry/products/.

[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.http://dx.doi.org/10.1109/TAC.2004.832972

[53] Ross, I.M., Gong, Q., 2010. Emerging Principles in Fast Trajectory Optimization. Course, Naval Postgraduate School, Monterey, CA, USA.

[54] Ross, I.M., Karpenko, M., 2012. A review of pseudospectral optimal control: from theory to flight. Ann. Rev. Contr., 36(2):182–197. http://dx.doi.org/10.1016/j.arcontrol.2012.09.002

[55] Rudin, W., 1975. Functional Analysis. McGraw-Hill, New York, USA.

[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. http://dx.doi.org/10.2514/6.2008-7165

[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.

[58] Wall, J.H., Miller, C.J., Hanson, C.E., , 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.

[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.

[60] Wu, H.X., 1990. All Coefficient Adaptive Control Theory and Applications. National Defense Industry Press, Beijing (in Chinese).

[61] Wu, H.X., Liu, Y.W., Liu, Z., ., 2001. Characteristic modeling and the control of flexible structure. Sci. China Inform. Sci., 44(4):278–291.

[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. http://dx.doi.org/10.1109/TSMCC.2006.887004

[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).

[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).

[65] Xie, Y.C., Hu, J., Wang, M., , 2013. Accurate and stable control of Shenzhou spacecraft in rendezvous and docking. Proc. 19th IFAC Symp. on Automatic Control in Aerospace, p.524–528. http://dx.doi.org/10.3182/20130902-5-DE-2040.00063

[66] Yamada, K., Yonechi, H., Wakao, M., , 2003. Adaptive attitude control of the data relay test satellite. Proc. 21st Int. Communications Satellite Systems Conf. and Exhibit, p.1–7.

[67] Yu, L., 2002. Robust Control—LMI Method. Tsinghua University, China (in Chinese).

[68] Zhou, K.M., Doyle, J.C., 1999. Essentials of Robust Control. Prentice Hall, New Jersey, USA.

[69] Zhou, K.M., Doyle, J.C., Glover, K., 1996. Robust and Optimal Control. Prentice Hall, Upper Saddle River, New Jersey, USA.

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