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access icon openaccess Development of underground coal mine drainage monitoring system based on DSP

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 21/04/2020, Accepted 08/09/2020, Revised 30/08/2020, Published 26/10/2020

Aiming at solving problems such as non-linear, time-varying parameters, and weak digital computing capability in the underground drainage system, the monitoring system is built based on a digital signal processor (DSP). Adopting DSP28335 as its control core, the hardware circuit and software program are designed in this monitoring system. The single-neuron fuzzy proportional, integration, and differential (PID) control algorithm with feedforward proportional and differential compensation is proposed in this study. The simulation results are compared and analysed with a traditional PID algorithm, fuzzy PID algorithm, and single-neuron fuzzy PID algorithm with feedforward in Matlab/Simulink, and the experimental platform is built to verify the application effect of three control algorithms. The simulation and experiment results show that the single-neuron fuzzy PID algorithm with feedforward has significant advantages such as shorter adjustment time, good adaptivity, and strong anti-interference ability, which could effectively improve the work efficiency of an underground mine drainage monitoring system.

Inspec keywords: mining industry; compensation; fuzzy control; digital signal processing chips; three-term control; feedforward

Other keywords: control core; nonlinear parameters; Matlab-Simulink; single-neuron fuzzy PID algorithm; digital signal processor; time-varying parameters; weak digital computing capability; DSP28335; feedforward proportional compensation; differential compensation; underground coal mine drainage monitoring system; single-neuron fuzzy proportional, integration, and differential control algorithm; hardware circuit; software program

Subjects: Fuzzy control; Mining, oil drilling and natural gas industries; Control applications in mining, oil and natural gas technology; Digital signal processing chips

References

    1. 1)
      • 18. Jegatheesh, A., Agees Kumar, C.: ‘Novel fuzzy fractional order PID controller for non linear interacting coupled spherical tank system for level process’, Microprocess. Microsyst., 2020, 72, pp. 1–13.
    2. 2)
      • 14. Chang, X., Xiong, J., Park, J.H.: ‘Fuzzy robust dynamic output feedback control of nonlinear systems with linear fractional parametric uncertainties’, Appl. Math. Comput., 2016, 291, pp. 213–225.
    3. 3)
      • 26. Li, H.J.: ‘Research on the underground drainage monitoring and control system of coal mine’. Master thesis, Shaanxi University of Science and Technology, 2014.
    4. 4)
      • 3. Fan, Z.R.: ‘Design of the mine drainage automatic control system’, Ind. Saf. Environ. Prot., 2017, 43, (7), pp. 38–40.
    5. 5)
      • 5. Zhao, L.N.: ‘Design of mine drainage automatic monitoring system based on S7–300 PLC’, Electron. Technol., 2018, 47, (10), pp. 92–94.
    6. 6)
      • 16. Zheng, Y.H., Dai, R.S., Zhou, Z.J.: ‘Design of torque system for electric bicycle based on fuzzy PID’, J. Eng., 2019, 2019, (23), pp. 8710–8714.
    7. 7)
      • 11. Chang, Y., Wang, Y.Q., Alsaadi, F.E., et al: ‘Adaptive fuzzy output-feedback tracking control for switched stochastic pure-feedback nonlinear systems’, Int. J. Adapt. Control Signal Process., 2019, 33, (10), pp. 1567–1582.
    8. 8)
      • 17. Priyanka, E.B., Maheswari, C., Thangavel, S.: ‘Online monitoring and control of flow rate in oil pipelines transportation system by using PLC based fuzzy-PID controller’, Flow Meas. Instrum., 2018, 62, pp. 144–151.
    9. 9)
      • 23. He, L., Cheng, F.Q., Wang, D.Q., et al: ‘Adaptive control of steam generator feed-water system based on improved single neuron self-adaptive control’. Proc. Int. Conf. on Robotics and Control (CRC), Hong Kong, China, April 2016, pp. 18–21.
    10. 10)
      • 9. Yin, X.W., Song, X.N., Wang, M.: ‘Passive fuzzy control design for a class of nonlinear distributed parameter systems with time-varying delay’, Int. J. Control Autom. Syst., 2020, 18, pp. 911–921.
    11. 11)
      • 12. Zhao, X., Wang, X., Ma, L., et al: ‘Fuzzy-approximation-based asymptotic tracking control for a class of uncertain switched nonlinear systems’, IEEE Trans. Fuzzy Syst., 2020, 28, (4), pp. 632–644.
    12. 12)
      • 4. Li, C., Liu, X.M.: ‘Nonlinear system control strategies’, Adv. Mater. Res., 2013, 694–697, pp. 2157–2161.
    13. 13)
      • 24. Yao, J., Zhang, W., Cao, X.M., et al: ‘Pressure control strategy for pump motor energy transfer unit’, High Technol. Lett., 2019, 25, (3), pp. 286–293.
    14. 14)
      • 13. Ma, L., Huo, X., Zhao, X.D., et al: ‘Adaptive fuzzy tracking control for a class of uncertain switched nonlinear systems with multiple constraints: a small-gain approach’, Int. J. Fuzzy Syst., 2019, 21, (8), pp. 2609–2624.
    15. 15)
      • 25. Sousa, F.M.M., Amarante, V.M.B., Fonseca, R.R.: ‘Adaptive fuzzy feedforward-feedback controller applied to level control in an experimental prototype’, IFAC-PapersOnLine, 2019, 52, (1), pp. 219–224.
    16. 16)
      • 2. Liu, B.: ‘Research on the factors influencing the efficiency of mine drainage equipment and improvement measures’, Shanxi Coal, 2018, 37, (5), pp. 89–91.
    17. 17)
      • 1. Donovan, J.J., Perry, E.F.: ‘Mine flooding history of a regional below-drainage coalfield dominated by barrier leakage’, Geofluids, 2019, 2019, pp. 1–16.
    18. 18)
      • 20. Krzysztof, P., Maciej, P., Damian, K.: ‘Neural networks in design of iterative learning control for nonlinear systems’, IFAC-PapersOnLine, 2017, 50, (1), pp. 13402–13407.
    19. 19)
      • 22. Zhao, Y.: ‘Software upgrading technology for coal mine monitoring substation based on ethernet’, Coal Mine Saf., 2018, 49, (3), pp. 95–97.
    20. 20)
      • 15. Liu, S.Q.: ‘Application of fuzzy PID in water pump control in mines’, Shanxi Coal, 2015, 35, (5), pp. 72–74.
    21. 21)
      • 21. Zhang, C.S., Mao, Y.: ‘Study on mine communication network based on ethernet and WSN’. Proc. Int. Conf. on Computational Intelligence and Communication Networks, Jabalpur India, December 2015, pp. 183–187.
    22. 22)
      • 6. Chouzal, M.F., Restivo, M.T., Silva, F.G., et al: ‘Remote level monitoring and control solution’, IFAC-PapersOnLine, 2016, 49, (6).
    23. 23)
      • 8. Yang, J.: ‘Application of PLC technology and fuzzy control in coal mine automatic drainage system’, China Mine Eng., 2018, 47, (3), pp. 19–21.
    24. 24)
      • 7. Ren, L.Z., Zhang, X., Zhang, Y., et al: ‘Research of mine drainage automatic control system based on PLC’, Adv. Mater. Res., 2013, 619, pp. 131–134.
    25. 25)
      • 19. Zhang, L., Wang, J.H., Zhu, H.Y.: ‘The research and design of liquid level control system based on computer nerve network’, Adv. Mater. Res., 2012, 591–593, pp. 1629–1632.
    26. 26)
      • 10. Errouha, M., Derouich, A., Motahhir, S, et al: ‘Optimization and control of water pumping PV systems using fuzzy logic controller’, Energy Rep., 2019, 5, pp. 853–865.
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