Annals of Computer Science and Information Systems, Volume 18

DOI: http://dx.doi.org/10.15439/2019F60

Citation: Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 18, pages 359–362 (2019)

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Abstract. The main objective of this paper is focused on the real time implementation in a MATLAB/SIMULINK environment of a closed-loop hybrid control strategy structure consisting of a combination of Fuzzy Logic control approach and a standard PID control strategy. This strategy is applied to control the speed of a 2 HP 1750 rpm permanent magnet DC motor used in a wide range of HVAC applications. The novelty of the paper is the new modeling approach by using SIMULINK SIMSCAPE library blocks, more practical due to its simplicity, easier and faster to implement and, in particular, very easy to practice for MATLAB users compared to a traditional modelling approach. The DC motor can be powered by a unidirectional DC voltage converter connected to a 10 kW-Microgrid PV array or directly from a Li-Ion battery or a Supercapacitor, both connected via two bidirectional DC boost-buck converters to the same Microgrid. The Microgrid energy storage system is suitable for renewable energy applications that are connected to a local grid, thus releasing the overloaded national grid, saving a considerable amount of energy and drastically reducing the energy costs.

References

1. Shweta Dikshit, “Solar Photovoltaic generator with MPPT and battery Storage”, International Journal of Electrical Engineering and Technology, vol.8 (3), 2017, pp. 42-49, ISSN Print: 0976-6545, ISSN online: 0976-6553.
2. R-E Tudoroiu, W. Kecs, M. Dobritoiu, N. Ilias, S-V Casavela, N. Tudoroiu,” Real-Time Implementation of DC Servomotor Actuator with Unknown Uncertainty using a Sliding Mode Observer”, ACSIS, vol.8, pp.841-848, http://dx.doi.org/10.15439/2016F95, Poland, 2016.
3. E-R. Tudoroiu, M. Zaheeruddin, N. Tudoroiu, D.D. Burdescu, “MATLAB Implementation of an Adaptive Neuro-Fuzzy Modeling Approach applied on Nonlinear Dynamic Systems – a Case Study”, Proceedings of the Federated Conference on Computer Science and Information Systems, pp. 577–583, September 2018, ISSN: 2300-5963, ACSIS, vol.15, http://dx.doi.org/10.15439/2018F38.
4. K. F. Hussein, “Hybrid Fuzzy-PID controller for Buck-Boost Converter in solar energy-Battery systems”, Master’s Thesis, Western Michigan University, May 2015.
5. Huang Jiang, Wang Jie, Fang Hui, “An anti-windup self-tuning fuzzy PID controller for speed control of brushless DC motor”, Automatika, 2017, vol. 58 (3), pp. 321-335, http://dx.doi.org/10.1080/00051144.2018.1423724.
6. Chuen Chien Lee, “Fuzzy Logic in control systems: Fuzzy Logic Controller-Part 1”, IEEE Transactions on Systems, Man. and Cybernetics, vol.20 (2), March/April 1990, pp. 404-418.
7. Md. Akram Ahmad, Pankaj Rai, Anita Mahato, Megha Mahapatra, “Speed control of a DC Motor using Fuzzy Logic application”, International Journal of Research in Engineering, Technology and Science, vol.7, Feb. 2017, ISSN 2454-1915, pp.1-12.
8. Umesh Kumar Bansal, Rakesh Narvey, “Speed Control of DC Motor Using Fuzzy PID Controller”, Advance in Electronic and Electric Engineering, ISSN 2231-1297, vol. 3(9), 2013, pp. 1209-1220.
9. MathWorks Documentation, MATLAB R2019a, Fuzzy Logic Toolbox Examples/Implement Fuzzy PID Controller in Simulink Using Lookup Table - SIMULINK Library MATLAB R2019a.