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CLC number: TP18; V279

On-line Access: 2021-07-20

Received: 2020-04-04

Revision Accepted: 2020-06-09

Crosschecked: 2021-03-17

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714


Alisson V. Brito


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Frontiers of Information Technology & Electronic Engineering  2021 Vol.22 No.7 P.1002-1009


Motor speed estimation and failure detection of a small UAV using density of maxima

Author(s):  Jefferson S. Souza, Moises C. Bezerril, Mateus A. Silva, Frank C. Veras, Abel Lima-Filho, Jorge Gabriel Ramos, Alisson V. Brito

Affiliation(s):  Laboratory of System Engineering and Robotics, Federal University of Paraiba, Joao Pessoa, Brazil; more

Corresponding email(s):   alissonbrito@ci.ufpb.br

Key Words:  Unmanned aerial vehicle (UAV), Speed identification, Failure detection, Chaos

Jefferson S. Souza, Moises C. Bezerril, Mateus A. Silva, Frank C. Veras, Abel Lima-Filho, Jorge Gabriel Ramos, Alisson V. Brito. Motor speed estimation and failure detection of a small UAV using density of maxima[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(7): 1002-1009.

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journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

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A1 - Mateus A. Silva
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This work presents the application of the technique named signal analysis based on chaos using density of maxima to analyze brushless direct current motors. It uses a correlation coefficient estimated from the density of maxima of the current signal. This study demonstrates in experiments the speed estimation of a brushless motor on a testbench and failure detection in a small flying drone. The experimental results demonstrate that it is possible to estimate the speed in 97.8% of the cases and to detect failure in 82.75% of the analyzed cases.


Jefferson S. SOUZA1,Moises C. BEZERRIL1,Mateus A. SILVA1,Frank C. VERAS2
Abel LIMA-FILHO3,Jorge Gabriel RAMOS4,Alisson V. BRITO1


Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]Baek G, Kim Y, Kim S, 2008. Fault diagnosis of identical brushless DC motors under patterns of state change. Proc IEEE Int Conf on Fuzzy Systems (IEEE World Congress on Computational Intelligence), p.2083-2088.

[2]Bazeia D, Pereira MBPN, Brito AV, et al., 2017. A novel procedure for the identification of chaos in complex biological systems. Sci Rep, 7:44900.

[3]Dietz B, Richter A, Samajdar R, 2015. Cross-section fluctuations in open microwave billiards and quantum graphs: the counting-of-maxima method revisited. Phys Rev E, 92(2):022904.

[4]Gosak M, Marhl M, Perc M, 2008. Chaos between stochasticity and periodicity in the prisoner’s dilemma game. Int J Bifurc Chaos, 18(3):869-875.

[5]Hou WQ, Zhang YX, Sun JP, 2015. A fault detection method for motors based on local polynomial Fourier transform. Prognostics and System Health Management Conf, p.1-5.

[6]Károlyi G, Neufeld Z, Scheuring I, 2005. Rock-scissors-paper game in a chaotic flow: the effect of dispersion on the cyclic competition of microorganisms. J Theory Biol, 236(1):12-20.

[7]Koteich M, Le Moing T, Janot A, et al., 2013. A real-time observer for UAV’s brushless motors. IEEE 11th Int Workshop of Electronics, Control, Measurement, Signals and Their Application to Mechatronics, p.1-5.

[8]Kuzma J, O’Sullivan S, Philippe T, et al., 2017. Commercialization strategy in managing online presence in the unamanned aerial vehicle industry. Int J Bus Strat, 17(1):59-68.

[9]Lei Y, Wang JL, 2019. Aerodynamic performance of quadrotor UAV with non-planar rotors. Appl Sci, 9(14):2779.

[10]Li YM, Du WB, Yang P, et al., 2019. A satisficing conflict resolution approach for multiple UAVs. IEEE Intern Things J, 6(2):1866-1878.

[11]Medeiros RLV, Ramos JGGS, Nascimento TP, et al., 2018. A novel approach for brushless DC motors characterization in drones based on chaos. Drones, 2(2):14.

[12]Medeiros RLV, Filho ACL, Ramos JGGS, et al., 2019. A novel approach for speed and failure detection in brushless DC motors based on chaos. IEEE Trans Ind Electron, 66(11):8751-8759.

[13]Mills MP, 2017. Drone disruption: the stakes, the players, and the opportunities. https://www.forbes.com/sites/markpmills/2016/03/23/drone-disruption-the-stakes-the-players-and-the-opportunities/#58333ffe7d0b

[14]Mitchell M, Hraber P, Crutchfield JP, 1993. Revisiting the edge of chaos: evolving cellular automata to perform computations. https://arxiv.org/abs/adap-org/9303003

[15]Nguyen NP, Hong SK, 2019. Active fault-tolerant control of a quadcopter against time-varying actuator faults and saturations using sliding mode backstepping approach. Appl Sci, 9(19):4010.

[16]Nowak MA, May RM, 1992. Evolutionary games and spatial chaos. Nature, 359(6398):826-829.

[17]Park BG, Lee KJ, Kim RY, et al., 2011. Simple fault diagnosis based on operating characteristic of brushless direct-current motor drives. IEEE Trans Ind Electron, 58(5):1586-1593.

[18]Ramos JGGS, Bazeia D, Hussein MS, et al., 2011. Conductance peaks in open quantum dots. Phys Rev Lett, 107(17):176807.

[19]Solomon O, 2007. Model reference adaptive control of a permanent magnet brushless DC motor for UAV electric propulsion system. Proc 33rd Annual Conf of the IEEE Industrial Electronics Society, p.1186-1191.

[20]Stéphane M, 2009. A Wavelet Tour of Signal Processing (3rd Ed.). Academic Press, Amsterdam, Boston, USA.

[21]Stöcker C, Bennett R, Nex F, et al., 2017. Review of the current state of UAV regulations. Remot Sens, 9(5):459.

[22]Straub J, Huber J, 2013. Validating a UAV artificial intelligence control system using an autonomous test case generator. Airborne Intelligence, Surveillance, Reconnaissance Systems and Applications X, Article 87130I.

[23]Tefay B, Eizad B, Crosthwaite P, et al., 2011. Design of an integrated electronic speed controller for compact robotic vehicles. Proc Australasian Conf on Robotics and Automation, p.2083-2088.

[24]Veras FC, Lima TLV, Souza JS, et al., 2019. Eccentricity failure detection of brushless DC motors from sound signals based on density of maxima. IEEE Access, 7:150318-150326.

[25]Wang W, Wang JW, 2019. Dynamic response enhancement and fault protection of boost converter-fed brushless DC motor in aerospace applications. Appl Sci, 9(10):2113.

[26]Xiao B, Yin S, 2017. A new disturbance attenuation control scheme for quadrotor unmanned aerial vehicles. IEEE Trans Ind Inform, 13(6):2922-2932.

[27]Yang HY, Yin S, 2019a. Descriptor observers design for Markov jump systems with simultaneous sensor and actuator faults. IEEE Trans Autom Contr, 64(8):3370-3377.

[28]Yang HY, Yin S, 2019b. Reduced-order sliding-mode-observer-based fault estimation for Markov jump systems. IEEE Trans Autom Contr, 64(11):4733-4740.

[29]Yang HY, Jiang YC, Yin S, 2020. Adaptive fuzzy fault tolerant control for Markov jump systems with additive and multiplicative actuator faults. IEEE Trans Fuzzy Syst, online.

[30]Yuan Y, Yuan HH, Guo L, et al., 2016. Resilient control of networked control system under DoS attacks: a unified game approach. IEEE Trans Ind Inform, 12(5):1786-1794.

[31]Zhang Q, Chen X, Xu DZ, 2020. Adaptive neural fault-tolerant control for the yaw control of UAV helicopters with input saturation and full-state constraints. Appl Sci, 10(4):1404.

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