The path following control of quad-rotors transporting uncertain payloads, whose control system is featured with time-variation, high nonlinearity and strong couplings among state variables and inputs, is investigated. Targeting this, an internal model frame-based disturbance attenuation control scheme that requires only rough model information is proposed. Firstly, a novel disturbance estimator (DE) for general single-input-single-output (SISO) system is proposed. Secondly, the DE proposed is applied in transporting unknown payloads by quad-rotors, to estimate the disturbances caused by the payloads for feedback compensation. Lastly, the control scheme based on internal model frame is designed to further reduce the remaining disturbances from disturbance estimation error.
AdachiSSanoH (1997) Two-degree-of-freedom active noise control based on internal model control. In: 1997 European Control Conference (ECC), IEEE, Brussels, Belgium, July, pp. 1634–1639.
2.
Cavalcante SaRDe AraujoALCVarelaATGuilhermeDAB (2013) Construction and PID control for stability of an unmanned aerial vehicle of the type quadrotor. In: 2013 Latin American Robotics Symposium and Competition, IEEE, Arequipa, Peru, October, pp. 21–27.
3.
ChenJHeZFQiX (2011) A new control method for mimo first order time delay non-square systems. Journal of Process Control21(4): 538–546.
4.
ChoiIHBangHC (2013) Quadrotor-tracking controller design using adaptive dynamic feedback-linearization method. Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering228(12): 2329–2342.
5.
DouJXKongXXWenBC (2016) Altitude and attitude active disturbance rejection controller design of a quadrotor unmanned aerial vehicle. Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering231(9): 1732–1745.
6.
GarciaCEMorariM (1982) Internal model control. A unifying review and some new results. Industrial & Engineering Chemistry Process Design and Development21(2): 308–323.
7.
HanYKarimiHRZhuXM (2014) Research of smart car’s speed control based on the internal model control. Abstract & Applied Analysis2014: 1–5. DOI: 10.1155/2014/274293
8.
HeZFZhaoL (2015) Quadrotor trajectory tracking based on quasi-LPV system and internal model control. Mathematical Problems in Engineering2015: 1–13. DOI: 10.1155/2015/857291
9.
HernandezACopotCKeyserRD, et al. (2013) Identification and path following control of an AR.Dronequadrotor. In: 2013 17th International Conference on System Theory, Control and Computing (ICSTCC), IEEE, Sinaia, Romania, October, pp. 583–588.
10.
HouZSJinST (2016) Model Free Adaptive Control: Theory and Applications. Taylor & Francis Group.
11.
HudsonRA (1978) Model predictive heuristic control: Applications to industrial processes. Automatica14(5): 413–428.
12.
ItoDGeorgieJValasekJWardDT (2002) Reentry vehicle flight controls design guidelines: dynamic inversion. GN&C Design and Analysis Branch, NASA Johnson Space Center, Report No.: NAG9-1085.
13.
LiMZuoZYLiuH, et al. (2018) Adaptive fault tolerant control for trajectory tracking of a quadrotor helicopter. Transactions of the Institute of Measurement and Control40(12): 3560–3569.
14.
LiXRChenM (2016) Extended state observer–based nonlinear cascade proportional–integral–derivative control of the nano quadrotor. Advances in Mechanical Engineering8(12): 1–15.
15.
LiaoTLChanWSYanJJ (2018) Distributed adaptive dynamic surface formation control for uncertain multiple quadrotor systems with interval type-2 fuzzy neural networks. Transactions of the Institute of Measurement and Control41(7): 1861–1879.
16.
ModirroustaAKhodabandehM (2017) Adaptive non-singular terminal sliding mode controller: new design for full control of the quadrotor with external disturbances. Transactions of the Institute of Measurement and Control39(3): 371–383.
17.
MurrayCCChuAG (2015) The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery. Transportation Research Part C54: 86–109.
18.
PratamaGNPMasngutICahyadiAIHerdjunantoS (2017) Robustness of PD control for transporting quadrotor with payload uncertainties. In: 2017 3rd International Conference on Science and Technology-Computer (ICST), IEEE, Yogyakarta, Indonesia, July.
SadeghzadehIAbdolhosseiniMZhangYM (2012) Payload drop application of unmanned quadrotor helicopter using gain-scheduled PID and model predictive control techniques. In: Proceedings of the 5th International Conference on Intelligent Robotics and Applications, Montreal, QC, Canada, October, pp. 386–395.
21.
ShastryAKBhargavapuriMTKothariMRanjanS (2018) Quaternion based adaptive control for package delivery using variable-pitch quadrotors. In: IEEE Indian Control Conference, Kanpur, India, January.
22.
TranTTGeSSHeW (2017) Adaptive control of a quadrotor aerial vehicle with input constraints and uncertain parameters. International Journal of Control91(5): 1140–1160.
23.
WangBMuLZhangY (2017) Adaptive robust control of quadrotor helicopter towards payload transportation applications. In: Proceedings of the 36th Chinese Control Conference, IEEE, Dalian, China, July, pp. 4774–4779.
24.
WutthithanyawatCSrisiriwatN (2014) Internal model control design for autothermal reforming system. Applied Mechanics & Materials627: 236–240.
25.
YangYYanY (2016) Attitude regulation for unmanned quadrotors using adaptive fuzzy gain-scheduling sliding mode control. Aerospace Science & Technology54: 208–217.
26.
ZuoZYDingXFLiuH (2016) Almost global trajectory tracking control of quadrotors with constrained control inputs. Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering230(5): 856–869.
