Temperature Control of a Regasification System for LNG-fuelled Marine Engines Using Nonlinear Control Techniques
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This paper presents two nonlinear PID (NPID) controllers which control the glycol temperature of a regasification system for LNG-fuelled engines. The NPID controllers have a parallel structure of the three nonlinear P, I, D actions or the linear P, D actions and nonlinear I action. A nonlinear function is employed to scale the error as input of the integral and implemented as a Takagi-Sugeno (T-S) fuzzy model. The controller parameters are optimally tuned by using a genetic algorithm. Furthermore, the stability problem of the overall system is verified based on the circle criterion. A set of simulation works is carried out to validate the efficiency of the two proposed controllers.
KeywordsCircle criterion nonlinear PID controller temperature control T-S fuzzy model
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- IMO, Green House Gas Emissions from Ships, Phase 1 Report, 2008.Google Scholar
- MAN Diesel & Turbo, ME-GI Duel Fuel MAN B&W engines: A Technical, Operational and Cost-effective Solution for Ships Fuelled by Gas, 2012.Google Scholar
- V. Vinaya Krishna, K. Ramkumar, and V. Alagesan, “Control of heat exchangers using model predictive controller,” Proc. of IEEE Int. Conf. on Advances In Engineering, Science And Management, pp. 242–246, March 2012.Google Scholar
- M. Pandey, K. Ramkumar, and V. Alagesan, “Design of fuzzy logic controller for a cross flow shell and tube heatexchanger,” Proc. of IEEE Int. Conf. on Advances In Engineering, Science And Management, pp. 150–154, March 2012.Google Scholar
- P. Sivakumar, D. Prabhakaran, and T. Kannadasan, “Temperature control of shell and tube heat exchanger by using intelligent controllers-case study,” Int. J. of Computational Engineering Research, vol. 2, no. 8, pp. 285–291, December 2012.Google Scholar
- G. M. Sarabeevi and M. L. Beebi, “Temperature control of shell and tube heat exchanger system using internal model controllers,” Proc. of Int. Conf. on Next Generation Intelligent Systems (ICNGIS), February 2016.Google Scholar
- M. Korkmaz, O. Aydogdu, and H. Dogan, “Design and performance comparison of variable parameter nonlinear PID controller and genetic algorithm based PID controller,” Proc. of 2012 IEEE Int. Symp. on Innovations in Intelligent Systems and Applications, pp. 1–5, July 2012.Google Scholar
- B. M. Isayed and M. A. Hawwa, “A nonlinear PID control scheme for hard disk drive servo systems,” Proc. of Mediterranean Conf. on Control & Automation, pp. 1–6, June 2007.Google Scholar
- H. Seraji, “A new class of nonlinear PID controllers,” Proc. of 5th IFAC Robot Control, pp. 65–71, September 1997.Google Scholar
- G. Zaidner, S. Korotkin, E. Shteimberg, A. Ellenbogen, M. Arad, and Y. Cohen, “Nonlinear PID and its application in process control,” Proc. of IEEE 26th Convention of Electrical and Electronics Engineers, pp. 574–577, November 2010.Google Scholar