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An Electro-Pneumatic Force Tracking System using Fuzzy Logic Based Volume Flow Control

Author

Listed:
  • Zhonglin Lin

    (Jiangsu Province Key Laboratory of Aerospace Power System, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Qingyan Wei

    (Jiangsu Province Key Laboratory of Aerospace Power System, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Runmin Ji

    (Jiangsu Province Key Laboratory of Aerospace Power System, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Xianghua Huang

    (Jiangsu Province Key Laboratory of Aerospace Power System, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Yuan Yuan

    (Jiangsu Province Key Laboratory of Aerospace Power System, College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Zhiwen Zhao

    (Centre for Propulsion Engineering, School of Aerospace, Transport, and Manufacturing, Cranfield University, Central Bedfordshire MK43 0AL, UK)

Abstract

In this paper, a fuzzy logic based volume flow control method is proposed to precisely control the force of a pneumatic actuator in an electro-pneumatic system including four on-off valves. The volume flow feature, which is the relationship between the duty cycle of the pulse width modulation (PWM) period, pressure difference, and volume flow of an on-off valve, is based on the experimental data measured by a high-precision volume flow meter. Through experimental data analysis, the maximum and minimum duty cycles are acquired. A new volume flow control method is introduced for the pneumatic system. In this method, the raw measured data are innovatively processed by a segmented, polynomial fitting method, and a newly designed procedure for calculating the duty cycle is adopted. This procedure makes it possible to combine the original data with fuzzy logic control (FLC). Additionally, the method allows us to accurately control the minimum and maximum opening pulse width of the valve. Several experiments are performed based on the experimental data, instead of the traditional theoretical models. Only 0.141 N (1.41%) overshoot and 0.03 N (0.03%) steady-state error are observed in the step response experiment, and 0.123 N average error is found while tracking the sine wave reference.

Suggested Citation

  • Zhonglin Lin & Qingyan Wei & Runmin Ji & Xianghua Huang & Yuan Yuan & Zhiwen Zhao, 2019. "An Electro-Pneumatic Force Tracking System using Fuzzy Logic Based Volume Flow Control," Energies, MDPI, vol. 12(20), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:4011-:d:279046
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    References listed on IDEAS

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    1. Yang Li & Binyu Xiong & Yixin Su & Jinrui Tang & Zhiwen Leng, 2019. "Particle Swarm Optimization-Based Power and Temperature Control Scheme for Grid-Connected DFIG-Based Dish-Stirling Solar-Thermal System," Energies, MDPI, vol. 12(7), pages 1-23, April.
    2. Yeming Zhang & Ke Li & Geng Wang & Jingcheng Liu & Maolin Cai, 2019. "Nonlinear Model Establishment and Experimental Verification of a Pneumatic Rotary Actuator Position Servo System," Energies, MDPI, vol. 12(6), pages 1-24, March.
    3. Youjie Ma & Long Tao & Xuesong Zhou & Wei Li & Xueqi Shi, 2019. "Analysis and Control of Wind Power Grid Integration Based on a Permanent Magnet Synchronous Generator Using a Fuzzy Logic System with Linear Extended State Observer," Energies, MDPI, vol. 12(15), pages 1-19, July.
    4. Hao Fu & Tong Jiang & Yan Cui & Bin Li, 2018. "Adaptive Hydraulic Potential Energy Transfer Technology and Its Application to Compressed Air Energy Storage," Energies, MDPI, vol. 11(7), pages 1-13, July.
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    Cited by:

    1. Grzegorz Filo, 2023. "A Review of Fuzzy Logic Method Development in Hydraulic and Pneumatic Systems," Energies, MDPI, vol. 16(22), pages 1-19, November.
    2. Lyubov Kotkas & Anatolij Donskoy & Aleksandr Zharkovskii & Nikita Zhurkin, 2024. "The Distributed Parameter Model of an Electro-Pneumatic System Actuated by Pneumatic Artificial Muscles with PWM-Based Position Control," Energies, MDPI, vol. 17(14), pages 1-20, July.
    3. Michał Bartyś, 2020. "Heterogenic Autotuner for Electro-Pneumatic Single-Action Actuators," Energies, MDPI, vol. 13(18), pages 1-22, September.
    4. Marcin Drzewiecki & Jarosław Guziński, 2020. "Fuzzy Control of Waves Generation in a Towing Tank," Energies, MDPI, vol. 13(8), pages 1-17, April.

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