Electro-Pneumatic Drive Control Based on the Fuzzy Logic

Authors: Sheykin M.O., Cherkasskikh S.N., Shilin D.V., Fedenkov V.V. Published: 18.04.2024
Published in issue: #1(148)/2024  


Category: Mechanical Engineering and Machine Science | Chapter: Hydraulic Machines, Vacuum, Compressor Technology, Hydraulic and Pneumatic Systems  
Keywords: pneumatic drive, gutter--ball mechanical system, mathematical model, pneumatic distributor with proportional control, pneumatic cylinder, fuzzy logic


The paper considers an electro-pneumatic drive to control the gutter--ball mechanical system. A nonlinear mathematical model was compiled for both the control object including a gutter and a ball freely rolling along it, and the pneumatic drive with the proportional control. Several approaches were used to determine the initial differential equations. The resulting model was presented in the MATLAB Simulink in the function blocks form. The system control algorithm was synthesized and described forming the basis to present the fuzzy rules that determined the system inputs and outputs. Besides, a fuzzy logic controller was designed. Issues of forming linguistic variables and the knowledge base for the fuzzy logic controller were considered. Graphs of the transient processes in both the ball and the pneumatic cylinder rod positions were presented, and quality indicators of the ball transient process were determined. It was noted that when using a fuzzy controller, the control was smooth and without overshoot. To create a fuzzy controller, it becomes also necessary to understand the system control principle forming the knowledge base

Please cite this article in English as:

Sheykin M.O., Cherkasskikh S.N., Shilin D.V., et al. Electro-pneumatic drive control based on the fuzzy logic. Herald of the Bauman Moscow State Technical University, Series Mechanical Engineering, 2024, no. 1 (148), pp. 110--127 (in Russ.). EDN: GSCWVO


[1] Saravanakumar D., Mohan B., Muthuramalingam T. A review on recent research trends in servo pneumatic positioning systems. Precis. Eng., 2017, vol. 49, pp. 481--492. DOI: https://doi.org/10.1016/j.precisioneng.2017.01.014

[2] Ding M., Liu B., Lichao W. Position control for ball and beam system based on active disturbance rejection control. Syst. Sc. Control Eng., 2019, vol. 7, no. 1, pp. 97--108. DOI: https://doi.org/10.1080/21642583.2019.1575297

[3] Amiruddin B.P., Kadir R.E. Ball and beam control using adaptive PID based on Q-learning. EECSI, 2020, pp. 203--208. DOI: https://doi.org/10.23919/EECSI50503.2020.9251898

[4] Keshmiri M., Jahromi A.F., Mohebbi A., et al. Modeling and control of ball and beam system using model based and non-model based control approaches. Int. J. Smart Sens. Intell. Syst., 2012, vol. 5, no. 1, pp. 14--35. DOI: https://doi.org/10.21307/ijssis-2017-468

[5] Amjad M., Kashif M.I., Abdullah S.S., et al. Fuzzy logic control of ball and beam system. Int. Conf. on Education Technology & Computer, 2010, vol. 3, pp. 489--493. DOI: https://doi.org/10.1109/ICETC.2010.5529494

[6] Valdiero A.C., Ritter C.S., Rios C.F., et al. Nonlinear mathematical modeling in pneumatic servo position applications. Math. Probl. Eng., 2011, vol. 2011, art. 472903. DOI: https://doi.org/10.1155/2011/472903

[7] Gerts E.V., Kreynin G.V. Raschet pnevmoprivodov [Calculation of pneumatic drives]. Moscow, Mashinostroenie Publ., 1975.

[8] Faudzi A.A.M., Osman K., Rahmat M.F., et al. Nonlinear mathematical model of an intelligent pneumatic actuator (IPA) systems: position and force controls. IEEE/ASME Int. Conf. "Advanced Intelligent Mechatronics", 2012, pp. 1105--1110. DOI: https://doi.org/10.1109/AIM.2012.6266014

[9] Tsirelman N.M. Tekhnicheskaya termodinamika [Technical thermodynamics]. St. Petersburg, Lan Publ., 2018.

[10] Kazmirenko V.F. Elektrogidravlicheskie mekhatronnye moduli dvizheniya [Electrohydraulic mechatronic motion modules]. Moscow, Radio i svyaz Publ., 2001.

[11] Lee L., Chiang H., Li I. Development and control of a pneumatic-actuator 3-DOF translational parallel manipulator with robot vision. Sensors, 2019, vol. 19, no. 6, art. 1459. DOI: https://doi.org/10.3390/s19061459

[12] Nguyen A., Taniguchi T., Eciolaza L., et al. Fuzzy control systems: past, present and future. IEEE Comput. Intell. Mag., 2019, vol. 14, no. 1, pp. 56--68. DOI: https://doi.org/10.1109/MCI.2018.2881644

[13] Lee C.C. Fuzzy logic in control systems: fuzzy logic controller. Part I. IEEE Trans. Syst. Man Cybern. Syst., 1990, vol. 20, no. 2, pp. 404--418. DOI: https://doi.org/10.1109/21.52551

[14] Novakovic B.M. Adaptive fuzzy logic control synthesis without a fuzzy rule base. In: Fuzzy theory systems. New York, Academic Press, 1999, pp. 781--808.

[15] Takosoglu J., Dindorf R., Wos P. Design rules for fuzzy logic controllers for pneumatic systems. In: Advances in hydraulic and pneumatic drives and control. Cham, Springer Nature, 2021, pp. 192--204. DOI: https://doi.org/10.1007/978-3-030-59509-8_17

[16] Schulte H., Hahn H. Fuzzy state feedback gain scheduling control of servo-pneumatic actuators. Control Eng. Pract., 2004, vol. 12, no. 5, pp. 639--650. DOI: https://doi.org/10.1016/S0967-0661(03)00148-5

[17] Zhang D., Zhou Z., Jia X. Networked fuzzy output feedback control for discrete-time Takagi --- Sugeno fuzzy systems with sensor saturation and measurement noise. Inf. Sc., 2018, vol. 457-458, pp. 182--194. DOI: https://doi.org/10.1016/j.ins.2018.02.026

[18] Rohillaa P.K., Kumar V., Al-Hakkak F. Fuzzy gain scheduling of PID controller for stiction compensation in pneumatic control valve. JCARME, 2019, vol. 8, no. 2, pp. 165--174. DOI: https://doi.org/10.22061/jcarme.2018.2689.1270

[19] Echalih S., Abouloifa A., Lachkar I., et al. Hybrid automaton-fuzzy control of single phase dual buck half bridge shunt active power filter for shoot through elimination and power quality improvement. Int. J. Electr. Power Energy Syst., 2021, vol. 131, art. 106986. DOI: https://doi.org/10.1016/j.ijepes.2021.106986