Kemeng Ren, Daqi Zhu, Tianhong Zeng, and Simon X. Yang
[1] F.Q. Liu, H. Tang, Y. Qin, C.Q. Duan, J. Luo, and H.Y. Pu,Review on fault diagnosis of unmanned underwater vehicles,Ocean Engineering, 243, 2022, 1–9. [2] X. Wen, Y. Wang, Q. Zhu, J. Wu, R. Xiong, and A. Xie,Design of recognition algorithm for multiclass digital displayinstrument based on convolution neural network, BiomimeticIntelligence and Robotics, 3(3), 2023, 100118. [3] K. Low, Design, development and locomotion control of bio-fish robot with undulating anal fins, International Journal ofRobotics & Automation, 22(1), 2007, 88. [4] E.J. Park and J.K. Mills, Dynamic modelling of flexiblepayloads manipulated by a smart gripper in robotic assembly,International Journal of Robotics and Automation, 21(1), 2006,50–62. [5] Y.M. Zhang and J. Jiang, Bibliographical review onreconfigurable fault-tolerant control systems, Annual Reviewsin Control, 32(2), 2008, 229–252. [6] C. Liu, S. Li, H. Chen, X. Xiu, and C. Peng, Semi-supervisedjoint adaptation transfer network with conditional adversariallearning for rotary machine fault diagnosis, Intelligence &Robotics, 3(2), 2023, 131–144. [7] Y. Jiang, B. He, P. Lv, J. Guo, J.H. Wan, C. Feng, F Yu,Actuator fault diagnosis in autonomous underwater vehiclebased on principal component analysis, in Proceeding of theIEEE Underwater Technology (UT) Conference, Kaohsiung,2019, 1–5. [8] A. Alessandri, M. Caccia, and G. Veruggio, Fault detectionof actuator faults in unmanned underwater vehicles, ControlEngineering Practice, 7(3), 1999, 357–368. [9] Y.H. Wei, J. Liu, S.G. Hao, and J.X. Hu, Design of headingfault-tolerant system for underwater vehicles based on double-criterion fault detection method, Journal of Marine Scienceand Application, 18(4), 2019, 530–541. [10] L. Merckelbach, A. Berger, G. Krahmann, M. Dengler, andJ.R. Carpenter, A dynamic flight model for slocum glidersand implications for turbulence microstructure measurements,Journal of Atmospheric and Oceanic Technology, 36(2), 2019,281–296. [11] Z.F. Chen, Y.Y. An, H.M. Li, and C.Z. Sun, Parameterestimation of thruster motor for underwater robot throughweighted least square method, in Proceeding of the IEEEInternational Conference on Robotics, Intelligent Systems andSignal Processing, Changsha, 2003, 1007–1011. [12] M.W. Lin, C.J. Yang, and D.J. Li, Hybrid strategy based modelparameter estimation of irregular-shaped underwater vehiclesfor predicting velocity, Robotics and Autonomous Systems, 127,2020, 12. [13] G. Chen, Y. Xu, X. Yang, H. Hu, H. Cheng, L. Zhu, J.Zhang, J. Shi, and X. Chai, Target tracking control of abionic mantis shrimp robot with closed-loop central patterngenerators, Ocean Engineering, 297, 2024, 116963. [14] D.Q. Zhu, J. Bai, and S.X. Yang, A multi-fault diagnosismethod for sensor systems based on principle componentanalysis, Sensors, 10(1), 2010, 241–253. [15] W. Abed, S.K. Sharma, R. Sutton, and A. Khan, An unmannedmarine vehicle thruster fault diagnosis scheme based onOFNDA, Journal of Marine Engineering and Technology,16(1), 2017, 37–44. [16] G. Matteucci, R. Bellacosa Marotti, B. Zattera, and D.Zoccolan, Truly pattern: Nonlinear integration of motion signalsis required to account for the responses of pattern cells in ratvisual cortex, Science Advances, 9(45), 2023, 1–23. [17] S. Dong, P. Wang, and K. Abbas, A survey on deep learningand its applications, Computer Science Review, 40, 2021,100379. [18] D.X. Ji, X. Yao, S. Li, Y.G. Tang, and Y. Tian, Model-free faultdiagnosis for autonomous underwater vehicles using sequenceconvolutional neural network, Ocean Engineering, 232, 2021,1–11. [19] P. Wu, C.A. Harris, G. Salavasidis, A. Lorenzo-Lopez, I.Kamarudzaman, A.B. Phillips, G. Thomas, and E. Anderlini,Unsupervised anomaly detection for underwater gliders usinggenerative adversarial networks, Engineering Applications ofArtificial Intelligence, 104, 2021, 1–12. [20] L. Xun, Y. Song, J. Guo, C. Feng, G. Li, T. Yan, and B.He, Sensor fault diagnosis of autonomous underwater vehiclebased on extreme learning machine, in Proceeding of the IEEEUnderwater Technology (UT), Busan, 2017, 1–5. [21] Z.Z. Chu, Y.S. Chen, D.Q. Zhu, and M.J. Zhang, Observer-based fault detection for magnetic coupling underwaterthrusters with applications in jiaolong HOV, Ocean Engineer-ing, 210, 2020, 1–10. [22] S. Nascimento and M. Valdenegro-Toro, Modeling and soft-fault diagnosis of underwater thrusters with recurrent neuralnetworks, in Proceeding of the 11th IFAC Conference onControl Applications in Marine Systems, Robotics, and Vehicles(CAMS), Opatija, 2018, 462. [23] Q. Jiang, X. Peng, H. Chen, and Y. Guo, Facial expressionrecognition based on residual network, in Proceeding of the 41stChinese Control Conference (CCC), Hefei, 2022, 7000–7006. [24] J.Y. He, Y. Li, Y.M. Li, Y.Q. Jiang, and L. An, Fault diagnosisin autonomous underwater vehicle propeller in the transitionstage based on GP-RPF, International Journal of AdvancedRobotic Systems, 15(6), 2018, 1–9. [25] G.E. Hinton, S. Osindero, and Y.-W. the, A fast learningalgorithm for deep belief nets, Neural computation, 18(7),2006, 1527–1554. [26] G.E. Hinton and R.R. Salakhutdinov, Reducing the dimension-ality of data with neural networks, Science, 313(5786), 2006,504–507. [27] K. Cho, B. Van Merri¨enboer, D. Bahdanau, and Y. Bengio, Onthe properties of neural machine translation: Encoder-decoderapproaches, 2014, arXiv:1409.1259. [28] T. Tieleman, Training restricted Boltzmann machines usingapproximations to the likelihood gradient, in Proceedings of the25th International Conference on Machine Learning, Helsinki,2008, 1064–1071.
Important Links:
Go Back