Abstract
A neural adaptive compensation control scheme for a class of multi-input multi-ouput (MIMO) uncertain nonlinear systems with actuator failures is proposed based on prescribed performance bound (PPB) transient performance which characterizes the convergence rate and maximum overshoot of the tracking error. RBF neural networks are used to approximate the error of plant model, the control law proposed can guarantee the asymptotic output tracking and closed-loop signal bounds. The control scheme is applied to a twin otter aircraft longitudinal nonlinear dynamics model in the presence of unknown failures. Simulation results demonstrate the effectiveness of the proposed method.
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P.C. Bechlioulis, A.G. Rovithakis, Adaptive control with guaranteed transient and steady state tracking error bounds for strict feedback systems. Automatica 45(2), 532–538 (2009)
M. Bodson, J.E. Groszkiewicz, Multivariable adaptive algorithms for reconfigurable flight control. IEEE Trans. Control Syst. Technol. 5(2), 217–229 (1997)
J.D. Boskovic, J.A. Jackson, R.K. Mehra et al., Multiple-model adaptive fault-tolerant control of a planetary lander. J. Guid. Control Dyn. 32(6), 1812–1826 (2009)
M. Chen, C. Jiang, Q. Zong, Adaptive H ∞ control of a class of uncertain nonlinear systems based on RBF neural networks. J. Control Theory Appl. 20(1), 27–32 (2003)
M.L. Corradini, G. Orlando, Actuator failure identification and compensation through sliding modes. IEEE Trans. Control Syst. Technol. 15(1), 184–190 (2007)
J. Jiang, Design of reconfigurable control systems using eigenstructure assignments. International Journal of Control, 395–410 (1994)
P. Li, G. Yang, Adaptive fuzzy control of unknown nonlinear systems with actuator failures for robust output tracking, in Proceedings of the 2005 American Control Conference (IEEE, New York, 2005), pp. 4862–4867
D. Looze, J.L. Weiss, J. Eterno et al., An automatic redesign approach for restructurable control systems. IEEE Control Syst. Mag. 5(2), 16–22 (1985)
S. Mohammad-Hoseini, M. Farrokhi, A.J. Koshkouei, Robust adaptive control of uncertain non-linear systems using neural networks. Int. J. Control 81(8), 1319–1330 (2008)
X. Qiu, S. Zhang, C. Liu, Backstepping adaptive compensation control for a class of MIMO nonlinear systems with actuator failures, in Proceedings of the 32nd Chinese Control Conference, Xian, China (2013), pp. 6088–6093
W. Sun, H. Gao, Adaptive backstepping control for active suspension systems with hard constraints. IEEE/ASME Trans. Mechatron. 18(3), 3889–3895 (2013)
W. Sun, Z. Zhao, H. Gao, Saturated adaptive robust control for active suspension systems. IEEE Trans. Ind. Electron. 60(9), 1072–1079 (2013)
X. Tang, G. Tao, S.M. Joshi, Adaptive actuator failure compensation for parametric strict feedback systems and an aircraft application. Automatica 39(11), 1975–1982 (2003)
X. Tang, G. Tao, S.M. Joshi, Virtual grouping based adaptive actuator failure compensation for MIMO nonlinear systems. IEEE Trans. Autom. Control 50(11), 1775–1780 (2005)
X. Tang, G. Tao, S.M. Joshi, Adaptive actuator failure compensation for nonlinear MIMO systems with an aircraft control application. Automatica 43(11), 1869–1883 (2007)
G. Tao, Adaptive control of systems with actuator failures, in Control and Decision Conference, Yantai, China (2008), pp. 53–54
W. Wang, C. Wen, Adaptive actuator failure compensation control of uncertain nonlinear systems with guaranteed transient performance. Automatica 46 (12), 2082–2091 (2010)
J. Yao, Z. Jiao, B. Yao et al., Nonlinear adaptive robust force control of hydraulic load simulator. Chin. J. Aeronaut. 25(5), 766–775 (2012)
J. Yao, Z. Jiao, D. Ma, Adaptive robust control of DC motors with extended state observer. IEEE Trans. Ind. Electron. (2013) doi:10.1109/TIE.2013.2281165
J. Yao, Z. Jiao, D. Ma et al., High-accuracy tracking control of hydraulic rotary actuators with modeling uncertainties. IEEE/ASME Trans. Mechatron. (2013). doi:10.1109/TMECH.2013.2252360
Y. Zhang, J. Jiang, Bibliographical review on reconfigurable fault tolerant control systems. Annu. Rev. Control 32(2), 229–252 (2008)
S. Zhang, C. Liu, S. Hu, Robust adaptive control for a class of nonlinear systems using backstepping based on RBF neural network. J. Syst. Eng. Electron. 32(3), 635–637 (2010)
S. Zhang, C. Liu, S. Hu, Adaptive fault-tolerant control for multi-input-multi-output minimum-phase systems with actuator failures. Control Theory Appl. 27(9), 1190–1194 (2010)
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This work is supported by the National Nature Science Foundation of China under Grants 61074063 and National University Foundational Research Funds of NUAA under grants NZ2012007, NS2013032.
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Zhang, S., Qiu, X. & Liu, C. Neural Adaptive Compensation Control for a Class of MIMO Uncertain Nonlinear Systems with Actuator Failures. Circuits Syst Signal Process 33, 1971–1984 (2014). https://doi.org/10.1007/s00034-013-9716-y
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DOI: https://doi.org/10.1007/s00034-013-9716-y