Abstract
In this paper we present a centralised flight-by-wire system based on μ-synthesis approach to the longitudinal flight motion of our experimental flying wing unmanned aerial vehicle (UAV), P15035 series. The challenge associated with our UAV is related to the fact that all motions of our UAV are controlled by two independently-actuated-ailerons namely elevons, together with its throttle. The scope of this research, nonetheless, falls within the area of elevon control based on the trimmed linear longitudinal flight modes obtained experimentally while throttle was set constant. The reason for considering μ-synthesis autopilot is to minimise the effects of uncertainty in modelling by maximising the amount of tolerable uncertainty within our system’s bandwidth as we aim to minimise the structure singular value μ of the corresponding robust performance associated with the uncertain systems. Second, it also provides flexibility in tunning due to the absence of partitioning model of MIMO system. Hence the entire autopilot was designed by keeping the system model as a whole. We also perform a comparative study with respect to well-known \(\textbf {H}_{\infty }\) mixed sensitivity autopilot. Our study indicates that the μ synthesis autopilot designed possesses better performances both in time and frequency domain as indicated by reasonably quick settling time in the absence of overshoot while still maintaining better robust stability margin.
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Chao, H., Cao, Y., Chen Y.: Autopilots for small unmanned aerial vehicles: a survey. Int. J. Control. Autom. Syst. 8(1), 36–44 (2010)
Shabayek, A.R., Demonceaux, C., Morel, O., Fofi, D.: Vision based UAV attitude estimation: progress and insights. J. Intell. Robot. Syst. 65(1-4), 295–308 (2012)
Santoso, F.: Sub-optimal decentralised control algorithms for blanket and k-barrier coverage in autonomous robotic wireless sensor networks. IET Commun. 4(17), 2041–2057 (2010)
Goodrich, M., Morse, B.S., Gerhardt, D., Cooper, J.L., Quigley, M., Adams, J A., Humphrey, C.: Supporting wilderness search and rescue using a camera-equipped mini UAV. Field Robot. Spec. Issue Search Rescue Robots 25(1–2), 89–110 (2008) (2008)
A decentralised self-dispatch algorithm for square-grid blanket coverage intrusion detection systems in wireless sensor networks. IEEE Trans. Veh. Technol. Conf. (VTC Fall) 1(5), 5–8 (2011)
Santoso, F.: Range-only distributed navigation protocol for uniform coverage in wireless sensor networks. IET Wirel. Sens. Syst. 4 (2014), to appear
Balas, G.J., Packard, A.K., Harduvel, J.T.: Application of μ-synthesis techniques to momentum management and attitude control of the space station. AIAA Guidance, Navigation and Control Conference, New Orleans (1991)
Balas, G.J., Doyle, J.C.: Robust control of flexible modes in the controller crossover region. AIAA J. Guid. Dyn. Control. 17(2), 370–377 (1994)
Doyle, J.C., Glover, P., Francis, B.: State-space solutions to standard H2 and H\(_{\mathrm {\infty }}\) control problems,. IEEE Trans. Autom. Control 34(8), 831–847 (1989)
Doyle, J.C., Tannenbau, A., Francis, B.: Feedback Control Theory. Mac Milan Publishing Co. (1990)
Doyle, J.C., Lenz, K., Packard, A.: Design examples using μ-synthesis: space shuttle lateral axis FCS during re-entry. In: NATO ASI Series, Modelling, Robustness, and Sensitivity Reduction in Control Systems, vol. 34. Springer-Verlag Berlin, Heidelberg (1987
Packard, A., Doyle, J., Balas, G.: Linear, multivariable robust control with a μ perspective, ASME. J. Dyn. Syst. Meas. Control. 1115(2b), 310–319 (1993). 50th Anniversary Issue
Glover, K., Doyle, J.C.: State-space formulae for all stabilizing controllers that satisfy an H norm bound and relations to risk sensitivity. Syst. Control Lett. 11, 167–172 (1988)
Zhou, K., Doyle, J.: Essentials of Robust Control. Prentice Hall, Upper Saddle River
Stein, G., Doyle, J.: Beyond singular values and loop shapes. AIAA J. Guid. Control 14(1), 5–16 (1991)
Safonov, M.G., Laub, A.J., Hartmann, G.: Feedback properties of multivariable systems: the role and use of return difference matrix. IEEE Trans. Automat. Control, 26,47–65
Stevens, L.B., Lewis, F.: Aircraft Control and Simulation, 2nd edn. Wiley, New York (2003)
Pratt, R.: Flight Control Systems: Practical Issues in Design and Implementation. The Institution of Electrical Engineers, UK (2000)
Bryson, A.J.R.: Control of Spacecraft and Aircraft. Princeton University Press, Princeton, NJ
Melin, P., Castillo, O.: A new neuro-fuzzy-fractal approach for adaptive model-based control of non-linear dynamic systems: The case of controlling aircraft dynamics. In: Proceedings of IEEE international fuzzy systems conference, August 22-29, Seoul, Korea (1999)
Ye, Z., Bhattacharya, P., Mohamadian, H., Majlesein, H., Ye, Y.: Equational dynamic modeling and adaptive control of UAV. In: Proceedings of the 2006 IEEE/SMC International Conference on System of Systems Engineering, Los Angeles, CA (2006)
Escareño, J., Salazar, S., Lozano, R.: Modelling and control of a convertible VTOL aircraft. In: Proceedings of the 45th IEEE Conference on Decision & Control, December 13–15. Grand Hyatt Hotel, Manchester (2006)
Rimal, B.P., Shin, H., Choi, E.: Simulation of nonlinear identification and control of unmanned aerial vehicle: An artificial neural network approach. In: 9th International Symposium on Communications and Information Technology, (ISCIT-2009), 28–30 September, pp. 442, 447 (2009)
George, V.I., D’Souza, J., Kurian, C.P., Thirunavukkaras, I.: A simulink model for an aircraft landing system using energy functions. In: 7th IEEE Conference on Industrial Electronics and Applications (ICIEA), 18–20 July pp. 355–360 (2012)
Yuan, W., Katupitiya, J.: Design of a μ-synthesis controller to stabilise an unmanned helicopter. In: 28th International Congress of the Aeronautical Sciences (ICAS-2012), 23–28 September. Brisbane (2012)
Boulet, B., Francis, B.A., Hughes, P.C., Hong, T.: μ-synthesis for a large flexible space structure experimental testbed. J. Guid. Control Dyn. 24(5), 967–977 (2001)
Liu, M., Egan, G., Ge, Y.: Identification of attitude flight dynamics for an unconventional UAV. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 9–15 October. Beijing (2006)
Santoso, F., Liu, M., Egan, G.: H 2 and \(H_{\infty }\) Robust Autopilot Synthesis for longitudinal flight of a special unmanned aerial vehicle. A comparative Study. IET Control Theory Appl. 2(7), 583–594 (2008)
Santoso, F., Liu, M., Egan, G.: Optimal control linear quadratic synthesis for an unconventional aircraft. In: Proceedings of Twelfth Australian International Aerospace congress (AIAC-12), 19–22 March 2007, also as MECSE-5-2007. Department of Electrical & Computer Systems Engineering, Monash University, Melbourne (2006)
Balas, G.J., Packard, A.K., Safonov, M.G., Chiang, R.Y.: Next generation of tools for robust control. In: Proceedings of the American Control Conference, June 30–July 2, pp. 5612–5615. Boston (2004)
Eykhoff, P.: System Identification: Parameter and State Estimation. Wiley, New York
Goodwin, G.C., Payne, R.L.: Dynamic System Identification: Experiment Design and Data Analysis. Academic Press Inc. Ltd., London
Mehra, R.K., Lainiotis, D.G.: System Identification Advances and Case Studies. Academic Press Inc. Ltd., London
Sage, A.P., Melsa, J.L.: System Identification. Academic Press Inc. Ltd., London (1971)
Slotine, J.J.E., Li, W.: Applied Non-Linear Control. Prentice Hall, Upper Saddle River
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Santoso, F., Liu, M. & Egan, G.K. Robust μ-synthesis Loop Shaping for Altitude Flight Dynamics of a Flying-Wing Airframe. J Intell Robot Syst 79, 259–273 (2015). https://doi.org/10.1007/s10846-014-0059-0
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DOI: https://doi.org/10.1007/s10846-014-0059-0