Browse > Article
http://dx.doi.org/10.3796/KSFOT.2022.58.4.359

Genetic algorithm-based design of a nonlinear PID controller for the temperature control of load-following coolant systems  

Yu-Soo, LEE (Global Customer Operation Experts, Winterthur Gas & Diesel Korea)
Soon-Kyu, HWANG (Energy System R&D Department, DSME)
Jong-Kap, AHN (Training Ship Operation Center, Gyeongsang National University)
Publication Information
Journal of the Korean Society of Fisheries and Ocean Technology / v.58, no.4, 2022 , pp. 359-366 More about this Journal
Abstract
In this study, the load fluctuation of the main engine is considered to be a disturbance for the jacket coolant temperature control system of the low-speed two-stroke main diesel engine on the ships. A nonlinear PID temperature control system with satisfactory disturbance rejection performance was designed by rapidly transmitting the load change value to the controller for following the reference set value. The feed-forwarded load fluctuation is considered the set points of the dual loop control system to be changed. Real-coded genetic algorithms were used as an optimization tool to tune the gains for the nonlinear PID controller. ITAE was used as an evaluation function for optimization. For the evaluation function, the engine jacket coolant outlet temperature was considered. As a result of simulating the proposed cascade nonlinear PID control system, it was confirmed that the disturbance caused by the load fluctuation was eliminated with satisfactory performance and that the changed set value was followed.
Keywords
Low-speed two-stroke main diesel engine; Jacket cooling water system; Nonliner PID controller; Cascade controller; Genetic algorithm;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Choi SM. 2008. Configuration and analysis of a feed-forward control system for jacket cooling water temperature of marine prime diesel engine. Journal of Advanced Marine Engineering and Technology 32, 1303-1308.
2 De Jong KA. 1975. An analysis of the behavior of a class of genetic adaptation systems. Ph.D. Dissertation, The University of Michigan, Ann Arbor Michigan, 96-160.
3 Grefenstette JJ. 1986. Optimization of control parameters for genetic algorithms. IEEE Transactions on Systems Man and Cybernetics 16, 122-128. https://doi.org/10.1109/TSMC.1986.289288.   DOI
4 Jacobsen SB. 2014. Cold corrosion control. MAN Diesel Course 2014 Busan, November 7, 6-7.
5 Janikow CZ and Michalewicz Z. 1991. An experimental comparison of binary and floating point representations in genetic algorithms. Proceedings of the 4th ICGA, San Diego, CA, USA, 31-36.
6 Jin GG and Ha JS. 1997. Genetic algorithms as optimisation tools and their applications. Journal of Advanced Marine Engineering and Technology 21, 108-116.
7 Jin GG and Joo SR. 2000. A study on a real-coded genetic algorithm. Journal of Institute of Control. Robotics and Systems 6, 268-275.
8 Jin GG. 2004. Genetic algorithms and their applications. KyoWooSa, Seoul Korea, 149-261.
9 Kim DH. 2014. Prevention of the cold corrosion. MAN Diesel & Turbo Korea, 1-17.
10 Kim DK, Lee JH and Cho KH. 2017. A study on performance comparison of jacket cooling fresh water system for marine diesel engine. Journal of the Korean Society of Marine Engineering 41, 8-14. https://doi.org/10.5916/jkosme.2017.41.1.8.   DOI
11 MAN Diesel & Turbo. 2012. Design update note - jacket cooling water system S/G50ME-B9.2 & 9.3 and all engines from 60 bore and above. Copenhagen, Denmark: MAN, 17 October, 1-2.
12 MAN Diesel & Turbo. 2012. Jacket cooling water temperature control. Copenhagen, Denmark: MAN, 05 October, Info. No.: 375633, Item Id.:5323487-4, 1-3.
13 Najm AA and Ibraheem IK. 2019. Nonlinear PID controller design for a 6-DOF UAV quadrotor system. Engineering Science and Technology, an International Journal 22, 1087-1097. https://doi.org/10.1016/j.jestch.2019.02.005.   DOI
14 Korkmaz M, Aydogdu O and Dogan H. 2012. Design and performance comparison of variable parameter nonlinear PID controller and genetic algorithm based PID controller. 2012 International Symposium on Innovations in Intelligent Systems and Applications, 1-5. https://doi.org/10.1109/INISTA.2012.6246935.   DOI
15 Lee YH., So MO, Jung BG, Jin GG and Jin SH. 2005. RCGA-based tuning of the PID controller for marine gas turbine engines. Journal of Advanced Marine Engineering and Technology 29, 116-123.
16 WINGD. 2022. Continuous low load operation (slow steaming). Winterthur, Switzerland, Service Letter SL-0009-3, 04 March, 1-4.
17 So GB. 2014. RCGA-based design of a nonlinear PID controller. Master thesis, Korea Maritime & Ocean University, 24-29.
18 So GB. and Jin GG. 2018. Fuzzy-based nonlinear PID controller and its application to CSTR. Korean J Chem Eng 35, 819-825. https://doi.org/10.1007/s11814-017-0329-1.   DOI
19 Wartsila. 2014. Ancillary system of W-X engine. WARTSILA, 12-24.
20 WINGD. 2022. Central cooling water system. Winterthur, Switzerland, Item ID PTAA036137, 1-3.
21 Zhang H and Hu B. 2012. The application of nonlinear PID controller in generator excitation system. Energy Procedia, 17(Part A), 202-207. https://doi.org/10.1016/j.egypro.2012.02.084.   DOI
22 Ahn JK, So GB, Lee JY, Lee YH, So MO and Jin GG. 2014. PID control of a shell and tube heat exchanger system incorporating with feedforward control and anti-windup techniques. Journal of Institute of Control, Robotics and Systems 20, 543-550. https://doi.org/10.5302/J.ICROS.2014.14.0009.   DOI
23 Aidan O. 2009. Handbook of PI and PID controller tuning rules (3rd Edition). Imperial College Press, 1-2.
24 Astrom KJ and Hagglund T. 1995. PID controllers: theory, design and tuning (2nd Edition). ISA Press, 1-4.
25 Chen JP, Lu BC, Fan F, Zhu SC and Wu JX. 2011. A nonlinear PID controller for electro-hydraulic servo system based on PSO algorithm. Applied Mechanics and Materials 141, 157-161. https://doi.org/10.4028/www.scientific.net/AMM.141.157.   DOI