Optimal Quantitative Controller Design for Twin Rotor MIMO System

Khreabet, Mustafa K.; Ali, Hazem I.

doi:10.30684/etj.v38i12A.1618

	Optimal Quantitative Controller Design for Twin Rotor MIMO System
Engineering and Technology Journal
Article 15, Volume 38, 12A, 2020, Pages 1880-1894 PDF (1.31 M)
Document Type: Research Paper
DOI: 10.30684/etj.v38i12A.1618
Authors
Mustafa K. Khreabet^* ¹; Hazem I. Ali²
¹Control and Systems Engineering Department, University of Technology , Baghdad, Iraq,
²Control and Systems Engineering Department, University of Technology , Baghdad, Iraq
Abstract
In this paper, the control approach is used for achieving the desired performance and stability of the twin-rotor MIMO system. This system is considered one of the complex multiple inputs of multiple-output systems. The complexity because of the high nonlinearity, significant cross-coupling and parameter uncertainty makes the control of such systems is a very challenging task. The dynamic of the Twin Rotor MIMO System (TRMS) is the same as that in helicopters in many aspects. The Quantitative Feedback Theory (QFT) controller is added to the control to enhance the control algorithm and to satisfy a more desirable performance. QFT is one of the frequency domain techniques that is used to achieve a desirable robust control in presence of system parameters variation. Therefore, a combination between control and QFT is presented in this paper to give a new efficient control algorithm. On the other hand, to obtain the optimal values of the controller parameters, Particle Swarm Optimization (PSO) which is one of the powerful optimization methods is used. The results show that the proposed quantitative control can achieve more desirable performance in comparison to control especially in attenuating the cross-coupling and eliminating the steady-state error.
Keywords
Twin Rotor MIMO System (TRMS); Robust control; control; QFT; Optimal control; PSO

References
[1] C. W. Tao, J. S. Taur and Y. C. Chen, "Design of a Parallel Distributed Fuzzy LQR Controller for the Twin Rotor Multi-Input Multi-Output System", Fuzzy Sets and Systems, Vol. 161, No. 15, pp. 2081-2103, 2010. [2] U. Ahmed, W. Anjum and S. M. A. Bukhari, " and Controller Design of Twin Rotor System (TRS)" Proc. Scientific Research. Intelligent Control and Automation, Vol. 4, pp. 55-62, 2013. [3] J. K. Pradhan and A. Ghosh, "Design and Implementation of Decoupled Compensation for a Twin Rotor Multiple-Input and Multiple-Output System", IET Control Theory & Applications, Vol. 7, No. 2, pp. 282-289, 2013. [4] Q. N. Van and C. H. Hyun, "Multiple Sliding Surface Control Approach to Twin Rotor MIMO Systems", International Journal of Fuzzy Logic and Intelligent Systems, Vol. 14, No. 3, pp. 171-180, 2014. [5] M. Taimoor, S. Iqbal and A. Waheed, "Sliding and Integral Sliding Mode Control Design for Twin Rotor System", Journal of Space Technology, Vol. 5, No. 1, 2015. [6] S. K. Pandey and V. Laxmi, "Optimal Control of Twin Rotor MIMO System using LQR Technique", Computational Intelligence in Data Mining, Springer, New Delhi, Vol. 1, pp. 11-21, 2015. [7] R. Chithra and K. Thomas, "Robust Optimal Sliding Mode Control of Twin Rotor MIMO System", International Journal of Engineering Research and Technology, Vol. 5, pp. 111-115, 2016. [8] H. I. Ali, "Swarm Intelligence to Robust control Design", United scholars publications, USA, 2018. [9] H. I. Ali, S. B. B. M. Noor, S. M. Bashi and M. H. Marhaban, "Quantitative Feedback Theory Control Design using Particle swarm optimization method", Transactions of the institute of measurement and control, Vol. 34, No. 4, pp. 463-476, 2012. [10] S. Mondal and C. Mahanta, "Adaptive Second-Order Sliding Mode Controller for a Twin Rotor Multi-Input-Multi-Output System", IET Control Theory Appl., Vol. 6, No. 14, pp. 2157-2167, 2012. [11] P. Wen and T. W. Lu, "Decoupling Control of a Twin Rotor MIMO System using Robust Deadbeat Control Technique", IET Control Theory Appl., Vol. 2, No. 11, pp. 999-1007, 2008. [12] Singh and S. Purwar, "Two Term Control Strategy for Position Control of Twin Rotor System.", International Conference on Control, Decision and Information Technologies (CoDIT), IEEE, 2017. [13] S. K. Pandey, J. Dey, and S. Banerjee, "Design of Controller for Twin Rotor MIMO System (TRMS) Based on Linear Matrix Inequalities", Advanced Computational and Communication Paradigms. Springer, Singapore, pp. 465-473, 2018. [14] A. K. Agrawal and S. Ghosh, "Optimal Controller Design for Twin Rotor MIMO System", National Institute of Technology, PhD Thesis, India, 2013. [15] S. M. Ahmad and A. J. Chipperfield and O. Tokhi, "Dynamic Modeling and Optimal Control of a Twin Rotor MIMO System", IEEE Conference, pp.391-398, 2000. [16] Twin Rotor MIMO System", Advanced Teaching Manual 1, Feedback Instruments Ltd, Feedback Part No. 1160–330074M5. [17] Y. S. Ban, R. Varatharajoo and M. Ovchinnikov, " Optimal Control Solution for a Combined Energy and Attitude Control System”, Acta Astronautica, Vol. 76, pp. 79-83, 2012. [18] ] C. Fauvel, F. Claveau and P. Chevrel, "A Generically Well-Posed Control Problem for a One Shot Feedforward and Feedback Synthesis", 17th International Conference System Theory, Control and Computing (ICSTCC), IEEE, France, 2013. [19] A. Sinha, "Linear Systems Optimal and Robust Control", Taylor & Francis Group, New York, 2007. [20] M. S. Ramli, M. F. Rahmat and M. S. Najib, "Design and Modeling of Integral Control State-feedback Controller for Implementation on Servomotor Control", International Conference on Circuits, Systems, Electronics, Control & Signal Processing, Cairo, Egypt, 2007. [21] K. Zhang, L. Peng, Y. Kang, J. Xiong and J. Chen, "State-Feedback-with-Integral Control plus Repetitive Control for UPS Inverters", Twentieth Annual IEEE Applied Power Electronics Conference and Exposition, Vol. 1. IEEE, 2005. [22] I. Horowitz, "Survey of Quantitative Feedback Theory (QFT)", International Journal of Robust and Nonlinear Control: IFAC‐Affiliated Journal, Vol. 11, No. 10, pp. 887-921, 2001. [23] ] M. D. Patil and K. R. Kothawale, "Design of Robust PID Controller for Flexible Transmission System Using Quantitative Feedback Theory (QFT)", Springer-Verlag Berlin Heidelberg, pp. 479–485, 2011. [24] H. I. Ali, "Design of PSO Based Robust Blood Glucose Control in Diabetic Patients", IJCCCE, Vol. 14, No. 1, 2014. [25] A. A. El-Saleh, M. Ismail, R. Viknesh, C. C. Mark and M. L. Chen, "Particle swarm optimization for mobile network design", IEICE Electronics Express, Vol.6, No. 17, pp. 1219-1225, 2009.
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