Fault-tolerant control of UAV anti-skid braking system with input and output constraints
-
摘要:
针对无人机防滑刹车系统工作过程中同时出现系统输出滑移率稳定区域受限、控制输入饱和与刹车执行机构故障的多重约束问题,提出了一种基于障碍Lyapunov形式的自适应神经网络反演容错控制器的设计方法。当刹车执行机构发生故障时,通过自适应神经网络补偿刹车系统中的非线性及不确定项。根据反演设计原理,应用神经网络输出设计相应的容错控制律,同时,在控制器的设计中引入鲁棒切换控制项,优化系统快速容错的暂态性能。首先本文设计的容错控制器无需精确获取执行机构在线故障的重构信息,也能使刹车闭环系统能够快速稳定,然后基于Lyapunov方法分析了系统的稳定性,最后通过数值仿真结果表明,所提出的容错控制算法能够有效地保证刹车执行机构故障时控制系统的稳定性和有效性。
Abstract:In this paper, a method of adaptive neural network backstepping fault-tolerant control, based on barrier Lyapunov function, is proposed for anti-skid braking system in the presence of slip-ratio constraint, control input saturation and partial loss of actuator effectiveness. The neural network can more accurately approximate the unknown nonlinearity in order to compensate the effect of actuator fault, and the great robustness to actuator fault is guaranteed. In this approach, the output of neural network is used to design the backstepping controller to achieve fault-tolerant control and uncertainty compensation, and a robust term is employed to optimize the transient performance of braking system. Firstly, the closed-loop fault-tolerant control system could be stable without the reconfiguration value of actuator fault in real time. Then, the stability of the system is analyzed based on the Lyapunov method. Finally, the numerical simulation results show that the proposed fault-tolerant control scheme can effectively guarantee the stability and effectiveness of the control system when the actuator happens faulty.
-
Key words:
- anti-skid braking /
- Lyapunov /
- fault-tolerant control /
- actuator fault /
- input and output constraints
-
表 1 μ-δ关系参数示意
Table 1. Relationship of μ-δ parametric representation
飞机跑道状态 D C B 干柏油跑道 0.8 1.534 4 14.032 6 湿柏油跑道 0.4 2.019 2 8.209 8 结冰跑道 0.2 2.087 5 7.201 8 -
[1] 胡庆雷, 肖冰, 马广富.输入受限的航天器姿态调节小波滑模反步控制[J].哈尔滨工业大学学报, 2010, 42(5):678-682. doi: 10.11918/j.issn.0367-6234.2010.05.002HU Q L, XIAO B, MA G F.Wavelet based backstepping sliding mode control for spacecraft attitude requlation under control input contraint[J].Journal of Harbin Institute of Technology, 2010, 42(5):678-682(in Chinese). doi: 10.11918/j.issn.0367-6234.2010.05.002 [2] HU Q L, HUO X, XIAO B.Reaction wheel fault tolerant control for spacecraft attitude stabilization with finite-time convergence[J].International Journal of Robust and Nonlinear Control, 2013, 23(15):1737-1752. doi: 10.1002/rnc.2924/citedby [3] HU Q L, FRISWELL M I, WAGG D J, et al.Adaptive backstepping fault-tolerant control for flexible spacecraft with bounded unknown disturbances[C]//Proceedings of the IEEE on the 28th Chinese Control Conference.Piscataway, NJ:IEEE Press, 2009:788-793. [4] CHEN X, DAI Z, LIN H, et al.Asymmetric barrier Lyapunov function-based wheel slip control for antilock braking system[J].International Journal of Aerospace Engineering, 2015, 2015:1-10. https://www.researchgate.net/publication/283955065_Asymmetric_Barrier_Lyapunov_Function-Based_Wheel_Slip_Control_for_Antilock_Braking_System [5] 李建成, 席涛.基于滑模迭代学习律的航天器姿态控制[J].系统工程与电子技术, 2012, 34(9):1895-1899. http://www.cnki.com.cn/Article/CJFDTOTAL-XTYD201209027.htmLI J C, XI T.Spacecraft attitude control scheme based on sliding mode controller with iterative learning law[J].System Engineering and Electronics, 2012, 34(9):1895-1899(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-XTYD201209027.htm [6] YANG H, WANG H.Robust adaptive fault-tolerant control for uncertain nonlinear system with unmodeled dynamics based on fuzzy approximation[J].Neurocomputing, 2016, 173(3):1660-1670. http://www.sciencedirect.com/science/article/pii/S0925231215013478 [7] WANG H, LIU X, LIU P X, et al.Robust adaptive fuzzy fault-tolerant control for a class of non-lower-triangular nonlinear systems with actuator failures[J].Information Sciences, 2016, 336:60-74. doi: 10.1016/j.ins.2015.12.008 [8] HUO B, TONG S, LI Y.Observer-based adaptive fuzzy fault-tolerant output feedback control of uncertain nonlinear systems with actuator faults[J].International Journal of Control, Automation and Systems, 2012, 10(6):1119-1128. doi: 10.1007/s12555-012-0606-z [9] POLYCARPOU M M.Stable adaptive neural control scheme for nonlinear systems[J].IEEE Transactions on Automatic Control, 1996, 41(3):447-451. doi: 10.1109/9.486648 [10] BECHLIOULIS C P, ROVITHAKIS G A.Adaptive control with guaranteed transient and steady state tracking error bounds for strict feedback systems[J].Automatica, 2009, 45(2):532-538. doi: 10.1016/j.automatica.2008.08.012 [11] WANG Y, ZHANG M, WILSON P A, et al.Adaptive neural network-based backstepping fault tolerant control for underwater vehicles with thruster fault[J].Ocean Engineering, 2015, 110:15-24. doi: 10.1016/j.oceaneng.2015.09.035 [12] POURSAMAD A.Adaptive feedback linearization control of antilock braking systems using neural networks[J].Mechatronics, 2009, 19(5):767-773. doi: 10.1016/j.mechatronics.2009.03.003 [13] TANG Y, ZHANG X, ZHANG D, et al.Fractional order sliding mode controller design for antilock braking systems[J].Neurocomputing, 2013, 111:122-130. doi: 10.1016/j.neucom.2012.12.019 [14] TAEHYUN S, SEHYUN C, SEOK L.Investigation of sliding-surface design on the performance of sliding mode controller in antilock braking systems[J].IEEE Transactions on Vehicular Technology, 2008, 57(2):747-759. doi: 10.1109/TVT.2007.905391 [15] TANELLI M, ASTOLFI A, SAVARESI S M.Robust nonlinear output feedback control for brake by wire control systems[J].Automatica, 2008, 44(4):1078-1087. doi: 10.1016/j.automatica.2007.08.020 [16] TEE K P, REN B, GE S S.Control of nonlinear systems with time-varying output constraints[J].Automatica, 2011, 47(11):2511-2516. doi: 10.1016/j.automatica.2011.08.044 [17] TEE K P, GE S S, TAY E H.Barrier Lyapunov functions for the control of output-constrained nonlinear systems[J].Automatica, 2009, 45(4):918-927. doi: 10.1016/j.automatica.2008.11.017 [18] QIU Y, LIANG X, DAI Z.Backstepping dynamic surface control for an anti-skid braking system[J].Control Engineering Practice, 2015, 42:140-152. doi: 10.1016/j.conengprac.2015.05.013 [19] ZHAO Z, HE W, GE S S.Adaptive neural network control of a fully actuated marine surface vessel with multiple output constraints[J].IEEE Transactions on Control Systems Technology, 2014, 22(4):1536-1543. doi: 10.1109/TCST.2013.2281211 [20] LI Y, TONG S, LI T.Adaptive fuzzy output-feedback control for output constrained nonlinear systems in the presence of input saturation[J].Fuzzy Sets and Systems, 2014, 248:138-155. doi: 10.1016/j.fss.2013.11.006 [21] CHEN M, MEI R.Actuator fault tolerant control for a class of nonlinear systems using neural networks[C]//Proceedings of the 11th IEEE International Conference on Control & Automation (ICCA).Piscataway, NJ:IEEE Press, 2014:101-106. [22] HUANG J T.Global tracking control of strict-feedback systems using neural networks[J].IEEE Transactions on Neural Networks and Learning Systems, 2012, 23(11):1714-1725. doi: 10.1109/TNNLS.2012.2213305 [23] 李玉忍, 张智慧, 徐健龙.飞机防滑刹车模糊滑模变结构控制研究[J].西北工业大学学报, 2015, 33 (1):45-49. http://www.cnki.com.cn/Article/CJFDTOTAL-XBGD201501009.htmLI Y R, ZHANG Z H, XU J L.Study on fuzzy sliding-mode variable structure control for aircraft anti-skid braking[J].Journal of Northwestern Polytechnical University, 2015, 33(1):45-49(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-XBGD201501009.htm [24] CHEN W, GE S S, WU J, et al.Globally stable adaptive backstepping neural network control for uncertain strict-feedback systems with tracking accuracy known a priori[J].IEEE Transactions on Neural Networks and Learning Systems, 2015, 26(9):1842-1854. doi: 10.1109/TNNLS.2014.2357451 [25] REN B, GE S S, TEE K P, et al.Adaptive neural control for output feedback nonlinear systems using a barrier Lyapunov function[J].IEEE Transactions on Neural Networks, 2010, 21(8):1339-1345. doi: 10.1109/TNN.2010.2047115 [26] 李兵强, 陈晓雷, 林辉, 等.飞机全电防滑刹车系统稳定动态面控制[J].系统工程与电子技术, 2016, 38(5):1139-1145. doi: 10.3969/j.issn.1001-506X.2016.05.26LI B Q, CHEN X L, LI H, et al.Enhanced stability dynamic surface control for aircraft antiskid braking system using electromechanical atuator[J].System Engineering and Electronics, 2016, 38(5):1139-1145(in Chinese). doi: 10.3969/j.issn.1001-506X.2016.05.26