Journal of Drive and Control (드라이브 ㆍ 컨트롤)

The Korean Society for Fluid Power and Construction Equipment (유공압건설기계학회)
권호 표지
DOI QR코드

DOI QR Code

The Numerical Modeling and Sliding Mode Control of A New Submersible Fish Cage

  • Lee, Hyunsu (School of Mechanical and Automotive Engineering, University of Ulsan) ;
  • Won, Sung Jae (R&D center, BMInternational) ;
  • Ahn, Kyoung Kwan (School of Mechanical and Automotive Engineering, University of Ulsan)
  • Received : 2017.05.16
  • Accepted : 2017.07.24
  • Published : 2017.09.01
Download PDF
⟨ Previous Next ⟩

Abstract

The purpose of this paper is to develop a new submersible fish cage operated by a pneumatic system for offshore aquaculture. Although some researchers have investigated modeling and control of fish cages, such cages consist of variable ballast tanks that with closed cylinders and thus present a maintenance issue. In solving the issue the new submersible fish cage investigated consists of bottom-opening cylinders. Accordingly, we designed a mathematical model of the concept and applied Sliding Mode Control for nonlinear angle control. Some experiments conducted under assumed conditions indicate that the angle of the system converges to zero under all conditions and the control has the stability to balance the fish cage.

Keywords

References

  1. Blackburn, J.F., Reethof, G., Shearer, J., 1960. Fluid Power Control. MIT Press.
  2. Fullerton, B., Swift, M.R., Boduch, S., Eroshkin, O., Rice, G., 2004. Design and analysis of an automated feed-buoy for submerged cages. Aquacult. Eng. 32, 95-111. https://doi.org/10.1016/j.aquaeng.2004.03.008
  3. Huang, C., Tang, H., Liu, J., 2006. Dynamical analysis of net cage structures for marine aquaculture: Numerical simulation and model testing. Aquacult. Eng. 35, 258-270. https://doi.org/10.1016/j.aquaeng.2006.03.003
  4. Kim, T., Hur, J., Yang, K., 2010. Submerging performances of automatic submersible buoy operated by air control. Journal of the Korean Society of Marine Engineering 34, 743-749. https://doi.org/10.5916/jkosme.2010.34.5.743
  5. Kim, T.H., Yang, K.U., Hwang, K.S., Jang, D.J., Hur, J.G., 2011. Automatic submerging and surfacing performances of model submersible fish cage system operated by air control. Aquacult. Eng. 45, 74-86. https://doi.org/10.1016/j.aquaeng.2011.07.003
  6. Lee, P.G., 2000. Process control and artificial intelligence software for aquaculture. Aquacult. Eng. 23, 13-36. https://doi.org/10.1016/S0144-8609(00)00044-3
  7. Messina, A., Giannoccaro, N.I., Gentile, A., 2005. Experimenting and modelling the dynamics of pneumatic actuators controlled by the pulse width modulation (PWM) technique. Mechatronics 15, 859-881. https://doi.org/10.1016/j.mechatronics.2005.01.003
  8. Molnar, L., Toal, D., 2007. A control system development for submersible sea cage system., 1-11.
  9. Richer, E., Hurmuzlu, Y., 2000a. A high performance pneumatic force actuator system: Part II-Nonlinear controller design. TRANSACTIONSAMERICAN SOCIETY OF MECHANICAL ENGINEERS JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL 122, 426-434. https://doi.org/10.1115/1.1286366
  10. Richer, E., Hurmuzlu, Y., 2000b. A high performance pneumatic force actuator system: Part I-Nonlinear mathematical model. Transactions- American Society of Mechanical Engineers Journal of Dynamic Systems Measurement and Control 122, 416-425. https://doi.org/10.1115/1.1286336
  11. Ryan, J., 2004. Farming the Deep Blue. Marine Institute.
  12. Scott, D., Muir, J., 2000. Offshore cage systems: A practical overview. Option Mediterraneennes-International Centre for Advanced Mediterranean Agronomic Studies, 79-89.
  13. Young, D.F., Munson, B.R., Okiishi, T.H., Huebsch, W.W., 2010. A Brief Introduction to Fluid Mechanics. John Wiley & Sons.
  14. Zhan, J., Jia, X., Li, Y., Sun, M., Guo, G., Hu, Y., 2006. Analytical and experimental investigation of drag on nets of fish cages. Aquacult. Eng. 35, 91-101. https://doi.org/10.1016/j.aquaeng.2005.08.013
  15. Ba, D.X., Ahn, K.K., 2015. Indirect sliding mode control based on gray-box identification method for pneumatic artificial muscle. Mechatronics 32, 1-11. https://doi.org/10.1016/j.mechatronics.2015.09.005
  16. J. H. Yoon, K. K. Ahn, 2016.6. Optimizations of Design Parameters of a EPPR Valve Solenoid using Artificial Neural Network. Journal of Drive and Control. 13, 34-41.
  17. H. G. Park, S. A. Nahian, K. K. Ahn, 2016.12. A Study on Energy Saving of IMV Circuit using Pressure Feedback. Journal of Drive and Control. 13, 31-44. https://doi.org/10.7839/ksfc.2016.13.4.031

Cited by

  1. A Neural Network Based Sliding Mode Control for Tracking Performance with Parameters Variation of a 3-DOF Manipulator vol.9, pp.10, 2019, https://doi.org/10.3390/app9102023
  2. Adaptive Fuzzy Backstepping Sliding Mode Control for a 3-DOF Hydraulic Manipulator with Nonlinear Disturbance Observer for Large Payload Variation vol.9, pp.16, 2019, https://doi.org/10.3390/app9163290