REAL TIME CONTROL OF TWIN ROTOR MIMO SYSTEM WITH PID AND FRACTIONAL ORDER PID CONTROLLER

Year 2020, Special Issue 2020, 1 - 9, 20.07.2020

Tufan Doğruer , Nusret Tan

https://doi.org/10.22531/muglajsci.669738

Cited By: 1

Abstract

This paper presents real-time control applications for the TRMS system. The twin rotor helicopter model has some complex features which make it difficult to control and therefore it can be used an ideal test setup for control applications. In this study, firstly, twin rotor helicopter model is run in real time and mathematical models are determined. According to the mathematical models, fractional order PID controller designs are realized by using Genetic Algorithm and real time pitch and yaw position control of the twin rotor helicopter model is provided. In the optimization algorithm, fractional order PID controller parameters were determined according to four different integral performance criteria. In real-time control of TRMS, integral performance criteria are compared with each other and the results are presented in figures. The results show that the real-time control of the system has been successfully performed using fractional order PID controller.

Keywords

TRMS, PID, Fractional Order PID, Optimization

References

• [1] Bayrak, A., Dogan, F., Tatlicioglu, E., and Ozdemirel, B., "Design of an experimental twin‐rotor multi‐input multi‐output system," Computer Applications in Engineering Education, vol. 23, no. 4, pp. 578-586, 2015.
• [2] Kavuran, G., Ates, A., Alagoz, B. B., and Yeroglu, C., "An Experimental Study on Model Reference Adaptive Control of TRMS by Error-Modified Fractional Order MIT Rule," Control Enginnering and Applied Informatics, vol. 19, no. 4, pp. 101-111, 2017.
• [3] Juang, J.-G., Huang, M.-T., and Liu, W.-K., "PID control using presearched genetic algorithms for a MIMO system," IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 38, no. 5, pp. 716-727, 2008.
• [4] Rotondo, D., Nejjari, F., and Puig, V., "Quasi-LPV modeling, identification and control of a twin rotor MIMO system," Control Engineering Practice, vol. 21, no. 6, pp. 829-846, 2013.
• [5] Chalupa, P., Přikryl, J., and Novák, J., "Modelling of twin rotor MIMO system," Procedia Engineering, vol. 100, pp. 249-258, 2015.
• [6] Juang, J.-G., Lin, R.-W., and Liu, W.-K., "Comparison of classical control and intelligent control for a MIMO system," Applied Mathematics and Computation, vol. 205, no. 2, pp. 778-791, 2008.
• [7] Ahmad, S., Chipperfield, A., and Tokhi, M., "Dynamic modelling and open-loop control of a twin rotor multi-input multi-output system," Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, vol. 216, no. 6, pp. 477-496, 2002.
• [8] Ahmad, S., Chipperfield, A., and Tokhi, O., "Dynamic modeling and optimal control of a twin rotor MIMO system," presented at the Proceedings of the IEEE 2000 National Aerospace and Electronics Conference, 2000.
• [9] Ahmad, S., Shaheed, M., Chipperfield, A., and Tokhi, M., "Nonlinear modelling of a twin rotor MIMO system using radial basis function networks," presented at the Proceedings of the IEEE 2000 National Aerospace and Electronics Conference, 2000.
• [10] Juang, J.-G., Liu, W.-K., and Lin, R.-W., "A hybrid intelligent controller for a twin rotor MIMO system and its hardware implementation," ISA transactions, vol. 50, no. 4, pp. 609-619, 2011.
• [11] Rahideh, A., Bajodah, A. H., and Shaheed, M. H., "Real time adaptive nonlinear model inversion control of a twin rotor MIMO system using neural networks," Engineering Applications of Artificial Intelligence, vol. 25, no. 6, pp. 1289-1297, 2012.
• [12] Shih, C. L., Chen, M. L., and Wang, J. Y., "Mathematical model set‐point stabilizing controller design of a twin rotor MIMO system," Asian journal of control, vol. 10, no. 1, pp. 107-114, 2008.
• [13] Mirjalili, S. and Lewis, A., "The whale optimization algorithm," Advances in engineering software, vol. 95, pp. 51-67, 2016.
• [14] Åström, K. J. and Hägglund, T., PID controllers: theory, design, and tuning. Instrument society of America Research Triangle Park, NC, 1995.
• [15] Podlubny, I., "Fractional-order systems and PIλDµ-controllers," IEEE Transactions on automatic control, vol. 44, no. 1, pp. 208-214, 1999.
• [16] Shah, P. and Agashe, S., "Review of fractional PID controller," Mechatronics, vol. 38, pp. 29-41, 2016.
• [17] Graham, D. and Lathrop, R. C., "The synthesis of optimum transient response: criteria and standard forms," Transactions of the American Institute of Electrical Engineers, Part II: Applications and Industry, vol. 72, no. 5, pp. 273-288, 1953.
• [18] Atherton, D., Control engineering. Bookboon, 2009.
• [19] Holland, J. H., Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT press, 1992.
• [20] Goldberg, D. E. and Deb, K., "A comparative analysis of selection schemes used in genetic algorithms," in Foundations of genetic algorithms, vol. 1: Elsevier, 1991, pp. 69-93.
• [21] Jayachitra, A. and Vinodha, R., "Genetic algorithm based PID controller tuning approach for continuous stirred tank reactor," Advances in Artificial Intelligence, vol. 2014, p. 9, 2014.
• [22] Oustaloup, A., Levron, F., Mathieu, B., and Nanot, F. M., "Frequency-band complex noninteger differentiator: characterization and synthesis," IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 47, no. 1, pp. 25-39, 2000.
• [23] TRMS, Twin Rotor MIMO System Control Experiments Manuel, 33-949S: Feedback Instruments Ltd., Sussex, U.K., 2010. [Online]. Available.