Fault-Tolerant Time-Varying Elliptical Formation Control of Multiple Fixed-Wing UAVs for Cooperative Forest Fire Monitoring

Abstract

This paper investigates the cooperative forest fire monitoring problem of multiple fixed-wing unmanned aerial vehicles (UAVs) in the presence of actuator faults during the fire monitoring mission. By using the fractional-order sliding-mode control strategy, a fault-tolerant time-varying elliptical formation control scheme is developed for multiple UAVs to monitor the elliptical spread of forest fire. To estimate the lumped disturbances induced by the external disturbances and actuator faults, sliding-mode disturbance observers are developed by introducing reference systems and sliding-mode differentiators. It is proved that all fixed-wing UAVs can be steered to elliptically monitor the forest fire and the cooperative tracking errors are uniformly ultimately bounded. Simulation results have demonstrated the effectiveness of the proposed control scheme.

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All simulation data in this study are included in this article.

References

  1. 1.

    Mysorewala, M.F., Popa, D.O., Lewis, F.L.: Multi-scale adaptive sampling with mobile agents for mapping of forest fires. J. Intell. Robot. Syst. 54(4), 535 (2009)

    Article  Google Scholar 

  2. 2.

    Merino, L., Caballero, F., Martínez-De-Dios, J.R., Maza, I., Ollero, A.: An unmanned aircraft system for automatic forest fire monitoring and measurement. J. Intell. Robot. Syst. 65(1-4), 533–548 (2012)

    Article  Google Scholar 

  3. 3.

    Yuan, C., Zhang, Y.M., Liu, Z.X.: A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques. Can. J. For. Res. 45(7), 783–792 (2015)

    Article  Google Scholar 

  4. 4.

    Hossain, F.M.A., Zhang, Y.M., Tonima, M.A.: Forest fire flame and smoke detection from UAV-captured images using fire-specific color features and multi-color space local binary pattern. J. of Unmanned Vehicle Syst. 8(4), 285–309 (2020)

    Article  Google Scholar 

  5. 5.

    Huang, Z., Hou, L.: Highest alert follows deadly fire. https://www.chinadaily.com.cn/a/201904/03/WS5ca3eeb3a3104842260b40d3.html. Accessed 3 Jan 2020

  6. 6.

    Huang, Z.: One of 3 weekend fires extinguished. https://global.chinadaily.com.cn/a/201904/09/WS5cabf430a3104842260b514d.html. Accessed 3 Jan 2020

  7. 7.

    Merino, L., Caballero, F., de Dios, J.R.M., Maza, I., Ollero, A.: Automatic forest fire monitoring and measurement using unmanned aerial vehicles. In: International Congress on Forest Fire Research. Coimbra, Portugal (2010)

  8. 8.

    Skorput, P., Mandzuka, S., Vojvodic, H.: The use of unmanned aerial vehicles for forest fire monitoring. In: International Symposium on Electronics in Marine. Zadar, Croatia (2016)

  9. 9.

    Sudhakar, S., Vijayakumar, V., Kumar, C.S., Priya, V., Ravi, L., Subramaniyaswamy, V.: Unmanned aerial vehicle (UAV) based forest fire detection and monitoring for reducing false alarms in forest-fires. Comput. Commun. 149, 1–16 (2020)

    Article  Google Scholar 

  10. 10.

    Wardihani, E., Ramdhani, M., Suharjono, A., Setyawan, T.A., Hidayat, S.S., Helmy, S.W., Triyono, E., Saifullah, F.: Real-time forest fire monitoring system using unmanned aerial vehicle. J. Eng. Sci. Technol. 13(6), 1587–1594 (2018)

    Google Scholar 

  11. 11.

    Yuan, C., Liu, Z.X., Zhang, Y.M.: Aerial images-based forest fire detection for firefighting using optical remote sensing techniques and unmanned aerial vehicles. J. Intell. Robot. Syst. 88(2-4), 635–654 (2017)

    Article  Google Scholar 

  12. 12.

    Casbeer, D.W., Kingston, D., Beard, R.W., Mclain, T.W.: Cooperative forest fire surveillance using a team of small unmanned air vehicles. Int. J. Syst. Sci. 37(6), 351–360 (2006)

    Article  Google Scholar 

  13. 13.

    Merino, L., Caballero, F., Martinez-de Dios, J., Ollero, A.: Cooperative fire detection using unmanned aerial vehicles. In: International Conference on Robotics and Automation. Barcelona, Spain (2005)

  14. 14.

    Merino, L., Caballero, F., Ferruz, J., Ollero, A.: A cooperative perception system for multiple UAVs: Application to automatic detection of forest fires. J. Field Robot. 23(3-4), 165–184 (2006)

    Article  Google Scholar 

  15. 15.

    Sujit, P., Kingston, D., Beard, R.: Cooperative forest fire monitoring using multiple UAVs. In: IEEE Conference on Decision and Control. New Orleans, LA, USA (2007)

  16. 16.

    Kingston, D., Beard, R.W., Holt, R.S.: Decentralized perimeter surveillance using a team of UAVs. IEEE Trans. Robot. 24(6), 1394–1404 (2008)

    Article  Google Scholar 

  17. 17.

    Sherstjuk, V., Zharikova, M., Sokol, I.: Forest fire-fighting monitoring system based on UAV team and remote sensing. In: International Conference on Electronics and Nanotechnology. Kiev, Ukraine (2018)

  18. 18.

    Xu, Q., Yang, H., Jiang, B., Zhou, D.H., Zhang, Y.M.: Fault tolerant formations control of UAVs subject to permanent and intermittent faults. J. Intell. Robot. Syst. 73(1-4), 589–602 (2014)

    Article  Google Scholar 

  19. 19.

    Yu, X., Liu, Z.X., Zhang, Y.M.: Fault-tolerant formation control of multiple UAVs in the presence of actuator faults. Int. J. Robust Nonlinear Control 26(12), 2668–2685 (2016)

    MathSciNet  Article  Google Scholar 

  20. 20.

    Yu, Z.Q., Qu, Y.H., Zhang, Y.M.: Distributed fault-tolerant cooperative control for multi-UAVs under actuator fault and input saturation. IEEE Trans. Control Syst. Technol. 27(6), 2417–2429 (2018)

    Article  Google Scholar 

  21. 21.

    Yu, Z.Q., Qu, Y.H., Zhang, Y.M.: Fault-tolerant containment control of multiple unmanned aerial vehicles based on distributed sliding-mode observer. J. Intell. Robot. Syst. 93(1-2), 163–177 (2019)

    Article  Google Scholar 

  22. 22.

    Yu, Z.Q., Liu, Z.X., Zhang, Y.M., Qu, Y.H., Su, C.Y.: Distributed finite-time fault-tolerant containment control for multiple unmanned aerial vehicles. IEEE Trans. Neural Netw. Learn. Syst. 31 (6), 2077–2091 (2020)

    MathSciNet  Article  Google Scholar 

  23. 23.

    Yu, Z.Q., Qu, Y.H., Zhang, Y.M.: Safe control of trailing UAV in close formation flight against actuator fault and wake vortex effect. Aerosp. Sci. Technol. 77, 189–205 (2018)

    Article  Google Scholar 

  24. 24.

    Yu, Z.Q., Zhang, Y.M., Jiang, B., Yu, X., Fu, J., Jin, Y., Chai, T.Y.: Distributed adaptive fault-tolerant close formation flight control of multiple trailing fixed-wing UAVs. ISA Trans. 106, 181–199 (2020)

    Article  Google Scholar 

  25. 25.

    Li, Z., Liu, L., Dehghan, S., Chen, Y.Q., Xue, D.: A review and evaluation of numerical tools for fractional calculus and fractional order controls. Int. J. Control 90(6), 1165–1181 (2017)

    MathSciNet  Article  Google Scholar 

  26. 26.

    Han, J., Di, L., Coopmans, C., Chen, Y.: Pitch loop control of a VTOL UAV using fractional order controller. J. Intell. Robot. Syst. 73(1-4), 187–195 (2014)

    Article  Google Scholar 

  27. 27.

    Yu, Z.Q., Zhang, Y.M., Jiang, B., Fu, J., Jin, Y., Chai, T.Y.: Composite adaptive disturbance observer-based decentralized fractional-order fault-tolerant control of networked UAVs. IEEE Trans. Syst. Man Cybern. -Syst. https://doi.org/10.1109/TSMC.2020.3010678 (2020)

  28. 28.

    Yu, Z.Q., Zhang, Y.M., Jiang, B., Su, C.Y., Fu, J., Jin, Y., Chai, T. Y.: Decentralized fractional-order backstepping fault-tolerant control of multi-uavs against actuator faults and wind effects. Aerosp. Sci Technol. https://doi.org/10.1016/j.ast.2020.105939 (2020)

  29. 29.

    Yang, Q., Chen, D., Zhao, T., Chen, Y.Q.: Fractional calculus in image processing: A review. Fract. Calc. Appl. Anal. 19(5), 1222–1249 (2016)

    MathSciNet  Article  Google Scholar 

  30. 30.

    Li, B., Xie, W.: Adaptive fractional differential approach and its application to medical image enhancement. Comput. Electr. Eng. 45, 324–335 (2015)

    Article  Google Scholar 

  31. 31.

    Magin, R.L.: Fractional calculus in bioengineering. Begell House Redding (2006)

  32. 32.

    Li, H.S., Luo, Y., Chen, Y.Q.: A fractional order proportional and derivative (FOPD) motion controller: tuning rule and experiments. IEEE Trans. Control Syst. Technol. 18(2), 516–520 (2009)

    Article  Google Scholar 

  33. 33.

    Yin, C., Chen, Y.Q., Zhong, S.M.: Fractional-order sliding mode based extremum seeking control of a class of nonlinear systems. Automatica 50(12), 3173–3181 (2014)

    MathSciNet  Article  Google Scholar 

  34. 34.

    Wang, Y.Y., Gu, L., Xu, Y., Cao, X.: Practical tracking control of robot manipulators with continuous fractional-order nonsingular terminal sliding mode. IEEE Trans. Ind. Electron. 63(10), 6194–6204 (2016)

    Article  Google Scholar 

  35. 35.

    Nikdel, N., Badamchizadeh, M., Azimirad, V., Nazari, M.A.: Fractional-order adaptive backstepping control of robotic manipulators in the presence of model uncertainties and external disturbances. IEEE Trans. Ind. Electron. 63(10), 6249–6256 (2016)

    Article  Google Scholar 

  36. 36.

    Sun, G., Wu, L., Kuang, Z., Ma, Z., Liu, J.: Practical tracking control of linear motor via fractional-order sliding mode. Automatica 94, 221–235 (2018)

    MathSciNet  Article  Google Scholar 

  37. 37.

    Hua, C.C., Chen, J.N., Guan, X.P.: Fractional-order sliding mode control of uncertain QUAVs with time-varying state constraints. Nonlinear Dyn. 95(2), 1347–1360 (2019)

    Article  Google Scholar 

  38. 38.

    Yuan, C., Liu, Z.X., Zhang, Y.M.: UAV-based forest fire detection and tracking using image processing techniques. In: International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, Denver, CO, USA (2015)

  39. 39.

    Casbeer, D.W., Beard, R.W., McLain, T.W., Li, S.M., Mehra, R.K.: Forest fire monitoring with multiple small UAVs. In: American Control Conference. Portland, OR, USA (2005)

  40. 40.

    Yu, Z.Q., Zhang, Y.M., Liu, Z.X., Qu, Y.H., Su, C.Y., Jiang, B.: Decentralized finite-time adaptive fault-tolerant synchronization tracking control for multiple UAVs with prescribed performance. J. Frankl. Inst. 357(16), 11,830–11, 862 (2020)

    MathSciNet  Article  Google Scholar 

  41. 41.

    Menon, P.K., Sweriduk, G.D., Sridhar, B.: Optimal strategies for free-flight air traffic conflict resolution. J. Guidance Control Dyn. 22(2), 202–211 (1999)

    Article  Google Scholar 

  42. 42.

    Lin, W.: Distributed UAV formation control using differential game approach. Aerosp. Sci. Technol. 35, 54–62 (2014)

    Article  Google Scholar 

  43. 43.

    Perry, G.L.W.: Current approaches to modelling the spread of wildland fire: A review. Prog. Phys. Geogr. 22(2), 222–245 (1998)

    Article  Google Scholar 

  44. 44.

    Xiang, X., Liu, C., Su, H.S., Zhang, Q.: On decentralized adaptive full-order sliding mode control of multiple UAVs. ISA Trans. 71, 196–205 (2017)

    Article  Google Scholar 

  45. 45.

    Qu, Z.H.: Matrix theory for cooperative systems. In: Cooperative Control of Dynamical Systems: Applications to Autonomous Vehicles, pp 153–193. Springer (2009)

  46. 46.

    Podlubny, I.: Fractional Differential Equations, vol. 198. Academic Press, Cambridge (1999)

    Google Scholar 

  47. 47.

    Nojavanzadeh, D., Badamchizadeh, M.: Adaptive fractional-order non-singular fast terminal sliding mode control for robot manipulators. IET Contr. Theory Appl. 10(13), 1565–1572 (2016)

    MathSciNet  Article  Google Scholar 

  48. 48.

    Basin, M., Yu, P., Shtessel, Y.: Finite-and fixed-time differentiators utilising HOSM techniques. IET Contr. Theory Appl. 11(8), 1144–1152 (2016)

    MathSciNet  Article  Google Scholar 

  49. 49.

    Zhang, F., Li, C.: Stability analysis of fractional differential systems with order lying in (1, 2). Adv. Diff. Eq. 2011(1), 213485 (2011)

    MathSciNet  MATH  Google Scholar 

  50. 50.

    Xu, Y.J.: Nonlinear robust stochastic control for unmanned aerial vehicles. J. Guidance Control Dyn. 32(4), 1308–1319 (2009)

    Article  Google Scholar 

  51. 51.

    Sun, K.K., Liu, L., Qiu, J., Feng, G.: Fuzzy adaptive finite-time fault-tolerant control for strict-feedback nonlinear systems. IEEE Trans. Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2020.2965890 (2020)

  52. 52.

    Sun, K.K., Qiu, J., Karimi, H.R., Fu, Y.: Event-triggered robust fuzzy adaptive finite-time control of nonlinear systems with prescribed performance. IEEE Trans. Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2020.2979129(2020)

  53. 53.

    Sun, K.K., Qiu, J., Karimi, H.R., Gao, H.: A novel finite-time control for nonstrict feedback saturated nonlinear systems with tracking error constraint. IEEE Trans. Syst. Man Cybern -Syst. https://doi.org/10.1109/TSMC.2019.2958072 (2019)

  54. 54.

    Yoo, S.J., Park, B.S.: Connectivity preservation and collision avoidance in networked nonholonomic multi-robot formation systems: Unified error transformation strategy. Automatica 103, 274–281 (2019)

    MathSciNet  Article  Google Scholar 

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Funding

This work was supported in part by National Natural Science Foundation of China (No. 61833013, 62003162, and 62020106003), Natural Science Foundation of Jiangsu Province of China (No. BK20200416), China Postdoctoral Science Foundation (No. 2020TQ0151, 2020M681590), State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China (No. 2019-KF-23-05), 111 Project (No. B20007), and Natural Sciences and Engineering Research Council of Canada. These funds are related with the flight control or cooperative control of multiple unmanned aerial vehicles, which support this study.

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Ziquan Yu: Conceptualization, Methodology, Validation, Writing - original draft Youmin Zhang: Supervision, Discussion, Resources, Writing - review & editing Bin Jiang: Supervision, Resources Xiang Yu: Discussion, Resources

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Correspondence to Youmin Zhang.

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Yu, Z., Zhang, Y., Jiang, B. et al. Fault-Tolerant Time-Varying Elliptical Formation Control of Multiple Fixed-Wing UAVs for Cooperative Forest Fire Monitoring. J Intell Robot Syst 101, 48 (2021). https://doi.org/10.1007/s10846-021-01320-6

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Keywords

  • Unmanned aerial vehicle
  • Cooperative forest fire monitoring
  • Fault-tolerant control
  • Time-varying formation control
  • Fractional-order control