Development of Accommodation System for Faults in Thrusters of Underwater Robots
https://doi.org/10.17587/mau.22.262-271
Abstract
The article discusses a solution to the problem of increasing the reliability of operation of underwater robots through the use of accommodation systems that compensate for the consequences of faults that appear in the thrusters. The following types of faults were considered: 1) a fault in the rotation speed sensor of thruster, causing error in its readings; 2) overheating of the motor or short-circuiting of several turns of the winding of its armature circuit, causing a change in the value of electrical resistance; 3) the appearance of an unknown external torque effect on the engine shaft, including when winding plants on the propeller. A new method for constructing accommodation systems is proposed, which contains three stages. At the first, the detection of emerging faults is carried out using the bank of diagnostic observers. Each observer is synthesized according to a special procedure in such a way that the residual formed by it is sensitive to the appearance of various combinations of possible faults. This allows to detect each specific fault. At the second stage, the values of sensor errors and deviations of the parameters of the thruster from their nominal values are estimated by additional variable structure observers. At the third stage, additional control signals for robot’s thrusters are formed. They ensure the stabilization of dynamic properties and quality indicators of thrusters in the event of faults. The results of mathematical modeling are presented, which have confirmed the operability and high efficiency of the synthesized accommodation system.
Keywords
About the Authors
V. F. FilaretovRussian Federation
Vladivostok, 690041
Vladivostok, 690950
A. V. Zuev
Russian Federation
Vladivostok, 690091
A. N. Zhirabok
Russian Federation
Vladivostok, 690950
Vladivostok, 690091
A. A. Protsenko
Russian Federation
Junior Researcher
Vladivostok, 690091
References
1. Inzartsev A. V., Kiselev L. V., Kostenko V. V., Matvienko Yu. V., Pavin A. M., Shcherbatyuk A. F. Underwater robotic systems: systems, technologies, applications, Vladivostok, Publishing house of IPMT DVO RAN, 2018, 368 p. (in Russian).
2. Inzartsev A. V., Gribova V. V., Kleshchyov A. S. Intelligent system for the formation of behavior of an autonomous underwater robot in emergency situations, Podvodnye issledovaniya i robototekhnika, 2015, no. 2 (20), pp. 4—11 (in Russian).
3. Chirikjian G. S. Robotic Self-replication, Self-diagnosis, and Self-repair: Probabilistic Considerations, Distributed Autonomous Robotic Systems, 2009, no. 8, pp. 273—281.
4. Filaretov V. F., Zuev A. V., Zhirabok A. N., Protsenko A. A., Subudhi B. Method of synthesis of continuous systems of accommodation to the faults in navigation sensors of autonomous underwater robots, Mekhatronika, Avtomatizatsiya, Upravlenie, 2015, vol. 16, no 4, pp. 282—288 (in Russian).
5. Filaretov V. F., Lebedev A. V., Yuhimets D. A. Devices and control systems of underwater robots, Moscow, Nauka, 2005, 270 p. (in Russian).
6. Zhu D., Sun B. Information fusion fault diagnosis method for unmanned underwater vehicle thrusters, IET Electrical Systems in Transportation, 2013, vol. 3, no. 4, pp. 102—111.
7. Wang J. Fault Diagnosis of Underwater Vehicle with FNN, Proc. of the 10th World Congress on Intelligent Control and Automation, 2012, pp. 2931—2934.
8. Zhao B., Skjetne R., Blanke M., Dukan F. Particle Filter for Fault Diagnosis and Robust Navigation of Underwater Robot, IEEE Transactions on Control Systems Technology, 2014, vol. 22, no. 6, pp. 2399—2407.
9. Wang J. G. Fault Diagnosis of Underwater Vehicle with Neural Network, Proc. of the 24th Chinese Control and Decision Conference (CCDC), 2012, pp. 1613—1617.
10. Xiao Liang, Wei Li, Linfang Su, Han Yin, Jun Zhao. Thruster Fault Diagnosis of Autonomous Underwater Vehicles Based on Least Disturbance Wavelet Neural Network, Proc. of the Second International Conference on Computer Modeling and Simulation, Sanya, Hainan, China, 2010, pp. 78—82.
11. Nilanjan Sarkar. Fault-Accommodating Thruster Force Allocation of an AUV Considering Thruster Redundancy and Saturation, IEEE Transactions on Robotics and Automation, 2002, pp. 223—233.
12. Ageev M. D. Simplified methodology for calculating UR propulsion devices, Podvodnye roboty i ih sistemy, Vladivostok, Dal’nauka, 1995, pp. 33—49 (in Russian).
13. Zhirabok A. N., Zuev A. V., Shumskij A. E. Methods for diagnosing linear systems based on sliding observers, Izvestiya RAN. Teoriya i Sistemy Upravleniya, 2019, no. 6, pp. 73—89 (in Russian).
14. Zhirabok A. N., Zuev A. V., Shumskij A. E. Diagnosing Linear Dynamical Systems: A Sliding Observer Approach, Avtomatika i telemekhanika, 2020, no. 2, pp. 18—35 (in Russian).
15. Zhirabok A. N., Zuev A. V., Shumskij A. E. Identification of faults in sensors of technical systems using sliding observers, Izmeritel’naya Tekhnika, 2019, no. 10, pp. 21—28 (in Russian).
16. Edwards C., Spurgeon S., Patton R. Sliding Mode Observers for Fault Detection and Isolation, Automatica, 2000, vol. 36, p. 541—553.
17. He J., Zhang C. Fault reconstruction based on sliding mode observer for nonlinear systems, Mathematical Problems in Engineering, 2012, vol. 2012, pp. 1—22.
18. Alwi H., Edwards C. Fault Tolerant Control Using Sliding Modes with On-line Control Allocation, Automatica, 2008, vol. 44, p. 1859—1866.
19. Shumskij A. E., Zhirabok A. N. Methods and algorithms for diagnosing and fault-tolerant control of dynamic systems, Vladivostok, DVGTU, 2009, 196 p. (in Russian).
20. Utkin V. I. Sliding Modes and Their Application in Variable Structure Systems, Moscow, Nauka, 1974, 272 p. (in Russian).
21. Filaretov V. F., Yuhimets D. A. Features of the synthesis of high-precision control systems for high-speed movement and stabilization of underwater vehicles in space, Vladivostok, Dal’nauka, 2016, 400 p. (in Russian).
Review
For citations:
Filaretov V.F., Zuev A.V., Zhirabok A.N., Protsenko A.A. Development of Accommodation System for Faults in Thrusters of Underwater Robots. Mekhatronika, Avtomatizatsiya, Upravlenie. 2021;22(5):262-271. (In Russ.) https://doi.org/10.17587/mau.22.262-271