Similar articles

Abstract: This paper presents a reliable active fault-tolerant tracking control system (AFTTCS) for actuator faults in a quadrotor unmanned aerial vehicle (QUAV). The proposed AFTTCS is designed based on a well-known model reference adaptive control (MRAC) framework that guarantees the global asymptotic stability of a QUAV system. To mitigate the negative impacts of model uncertainties and enhance system robustness, a radial basis function neural network is incorporated into the MRAC scheme for adaptively identifying the model uncertainties online and modifying the reference model. Meanwhile, actuator dynamics are considered to avoid undesirable performance degradation. Furthermore, a fault detection and diagnosis estimator is constructed to diagnose loss-of-control-effectiveness faults in actuators. Based on the fault information, a fault compensation term is added to the control law to compensate for the adverse effects of actuator faults. Simulation results show that the proposed AFTTCS enables the QUAV to track the desired reference commands in the absence/presence of actuator faults with satisfactory performance.

模型不确定性和执行器故障下的四旋翼飞行器主动容错控制方法

[1]Avram RC, Zhang XD, Muse J, 2018. Nonlinear adaptive fault-tolerant quadrotor altitude and attitude tracking with multiple actuator faults. Trans Contr Syst Technol, 26(2):701-707.

[2]Chen FY, Zhang KK, Wang Z, et al., 2015. Trajectory tracking of a quadrotor with unknown parameters and its fault-tolerant control via sliding mode fault observer. Proc Inst Mech Eng Part I J Syst Contr Eng, 229(4):279-292.

[3]Chen FY, Jiang RQ, Zhang KK, et al., 2016. Robust backstepping sliding-mode control and observer-based fault estimation for a quadrotor UAV. IEEE Trans Ind Electron, 63(8):5044-5056.

[4]Cheng E, 2015. Aerial photography and videography using drones. In: Johnson K (Ed.), Aerial Photograph Techniques. Peachpit Press, San Francisco.

[5]Dydek ZT, Annaswamy AM, Lavretsky E, 2013. Adaptive control of quadrotor UAVs: a design trade study with flight evaluations. IEEE Trans Contr Syst Technol, 21(4):1400-1406.

[6]Hao W, Xian B, 2017. Nonlinear adaptive fault-tolerant control for a quadrotor UAV based on immersion and invariance methodology. Nonl Dynam, 90(4):2813-2826.

[7]Ioannou PA, Sun J, 1996. Robust Adaptive Control. Prentice-Hall, Upper Saddle River, NJ, USA.

[8]Joshi SM, Patre P, Tao G, 2012. Adaptive control of systems with actuator failures using an adaptive reference model. J Guid Contr Dynam, 35(3):938-949.

[9]Kayacan E, Maslim R, 2017. Type-2 fuzzy logic trajectory tracking control of quadrotor VTOL aircraft with elliptic membership functions. IEEE/ASME Trans Mech, 22(1):339-348.

[10]Liu ZX, Yuan C, Zhang YM, et al., 2016. A learning-based fault tolerant tracking control of an unmanned quadrotor helicopter. J Intell Rob Syst, 84(1-4):145-162.

[11]Liu ZX, Yuan C, Yu X, et al., 2017. Retrofit fault-tolerant tracking control design of an unmanned quadrotor helicopter considering actuator dynamics. Int J Robust Nonl Contr, in press.

[12]Mallavalli S, Fekih A, 2018. A fault tolerant tracking control for a quadrotor UAV subject to simultaneous actuator faults and exogenous disturbances. Int J Contr, in press.

[13]Murray CC, Chu AG, 2015. The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery. Transp Res Part C Emerg Technol, 54:86-109.

[14]Park J, Sandberg IW, 1991. Universal approximation using radial-basis-function networks. Neur Comput, 3(2):246-257.

[15]Ríos H, Falc‘on R, González OA, et al., 2018. Continuous sliding-modes control strategies for quad-rotor robust tracking: real-time application. IEEE Trans Ind Electron, 66(2):1264-1272.

[16]Tao G, Chen SH, Tang XD, et al., 2004. State feedback designs for state tracking. In: Tao G, Chen SH, Tang XD, et al. (Eds.), Adaptive Control of Systems with Actuator Failures. Springer, London, p.15-54.

[17]Wang B, Ghamry KA, Zhang YM, 2016. Trajectory tracking and attitude control of an unmanned quadrotor helicopter considering actuator dynamics. 35^thChinese Control Conf, p.10795-10800.

[18]Wu EN, Zhang YM, Zhou KM, 2000. Detection, estimation, and accommodation of loss of control effectiveness. Int J Adapt Contr Signal Process, 14(7):775-795.

[19]Xiong JJ, Zhang GB, 2017. Global fast dynamic terminal sliding mode control for a quadrotor UAV. ISA Trans, 66:233-240.

[20]Xu R, Ozguner U, 2006. Sliding mode control of a quadrotor helicopter. 45^th IEEE Conf on Decision and Control, p.4957-4962.

[21]Xu ZW, Nian XH, Wang HB, et al., 2017. Robust guaranteed cost tracking control of quadrotor UAV with uncertainties. ISA Trans, 69:157-165.

[22]Yacef F, Bouhali O, Hamerlain M, et al., 2016. Observer-based adaptive fuzzy backstepping tracking control of quadrotor unmanned aerial vehicle powered by Li-ion batter. J Intell Robot Syst, 84(1-4):179-197.

[23]Yuan C, Liu ZX, Zhang YM, 2015. UAV-based forest fire detection and tracking using image processing technique. Int Conf on Unmanned Aircraft Systems p.639-643.

[24]Zhang CH, Kovacs JM, 2012. The application of small unmanned aerial systems for precision agriculture: a review. Prec Agric, 13(6):693-712.

[25]Zhang YM, Jiang J, 2002. Active fault-tolerant control system against partial actuator failures. IEE Proc Contr Theory Appl, 149(1):95-104.

[26]Zhang YM, Jiang J, 2008. Bibliographical review on reconfigurable fault-tolerant control systems. Ann Rev Contr, 32(2):229-252.

[27]Zhong YJ, Zhang W, Zhang YM, 2018a. Active fault-tolerant tracking control of a quadrotor UAV. Int Conf on Sensing, Diagnostics, Prognostics, and Control.

[28]Zhong YJ, Zhang YM, Zhang W, et al., 2018b. Robust actuator fault detection and diagnosis for a quadrotor UAV with external disturbances. IEEE Access, 6:48169-48180.

[29]Zou Y, Zhu B, 2017. Adaptive trajectory tracking controller for quadrotor systems subject to parametric uncertainties. J Frankl Inst, 354(15):6724-6746.