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Optimal Tuning of Linear Quadratic Regulator Controller Using a Particle Swarm Optimization for Two-Rotor Aerodynamical System
Authors: Ayad Al-Mahturi, Herman Wahid
Abstract:
This paper presents an optimal state feedback controller based on Linear Quadratic Regulator (LQR) for a two-rotor aero-dynamical system (TRAS). TRAS is a highly nonlinear multi-input multi-output (MIMO) system with two degrees of freedom and cross coupling. There are two parameters that define the behavior of LQR controller: state weighting matrix and control weighting matrix. The two parameters influence the performance of LQR. Particle Swarm Optimization (PSO) is proposed to optimally tune weighting matrices of LQR. The major concern of using LQR controller is to stabilize the TRAS by making the beam move quickly and accurately for tracking a trajectory or to reach a desired altitude. The simulation results were carried out in MATLAB/Simulink. The system is decoupled into two single-input single-output (SISO) systems. Comparing the performance of the optimized proportional, integral and derivative (PID) controller provided by INTECO, results depict that LQR controller gives a better performance in terms of both transient and steady state responses when PSO is performed.Keywords: Linear quadratic regulator, LQR controller, optimal control, particle swarm optimization, PSO, two-rotor aero-dynamical system, TRAS.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1128899
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[1] J.G. Juang, R.W. Lin, and W.K. Liu, “Comparison of classical control and intelligent control for a MIMO system,” Applied Mathematics and Computation, vol. 205, no. 2, pp. 778-791, 2008.
[2] G.D. Prasad, P.S. Manoharan, and A.P.S. Ramalakshmi, “PID control scheme for twin rotor MIMO system using a real valued genetic algorithm with a predetermined search range,” in Power, Energy and Control (ICPEC), 2013.
[3] S.S. Butt, and H. Aschemann, “Multi-Variable Integral Sliding Mode Control of a Two Degrees of Freedom Helicopter,” IFAC-PapersOnLine, vol. 48, no. 1, pp. 802-807, 2015.
[4] J.G. Juang, M.T. Huang, and W.K. Liu, “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.
[5] A. Phillips, and F. Sahin, “Optimal control of a twin rotor MIMO system using LQR with integral action,” World Automation Congress (WAC), 2014.
[6] Rahideh and M.H. Shaheed, “Real time hybrid fuzzy-PID control of a twin rotor system,” IEEE International Conference, 2009.
[7] C.W. Tao, J.S. Taur, Y.H. Chang and C-W. Chang, “A Novel Fuzzy-Sliding and Fuzzy-Integral-Sliding Controller for the Twin-Rotor Multi-Input Multi-Output System,” IEEE Transactions on Fuzzy Systems, vol. 18, no. 5, pp. 893-905, 2010.
[8] P. Wen and T.W. Lu, “Decoupling control of a twin rotor MIMO system using robust deadbeat control technique,” IET Control Theory & Applications, vol. 2, no. 11, pp. 999-1007, 2008.
[9] A. Boulkroune, M. M’Saad, and H. Chekireb, “Design of a fuzzy adaptive controller for MIMO nonlinear time-delay systems with unknown actuator nonlinearities and unknown control direction,” Information Sciences, vol. 180, no. 24, pp. 5041-5059, 2010.
[10] J. Juang, W. Liu, and R. Lin, “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] A. Rahideh and M.H. Shaheed, “Hybrid Fuzzy-PID-based Control of a Twin Rotor MIMO System,” In IEEE Industrial Electronics, IECON, 32nd Annual Conference 2006.
[12] 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.
[13] J. Thomas, “Particle swarm optimization based model predictive control for constrained nonlinear systems,” in Informatics in Control, Automation and Robotics (ICINCO), 11th International Conference. 2014.
[14] L. Chrif and Z.M. Kadda, “Aircraft Control System Using LQG and LQR Controller with Optimal Estimation-Kalman Filter Design,” Procedia Engineering, vol. 80, pp. 245-257, 2014.
[15] S.K. Pandey and V. Laxmi, “Optimal Control of Twin Rotor MIMO System Using LQR Technique,” in Computational Intelligence in Data Mining - Volume 1: Proceedings of the International Conference on CIDM, pp. 11-21, Dec. 2014.
[16] “INTECO”, Two Rotor Aero-Dynamical System User’s Manual, 2013; Available: http://www.inteco.com.pl/products/two-rotor-aerodynamical-system/. Accessed: Oct, 15, 2016.
[17] R.S. Esfandiari and B. Lu, Modeling and Analysis of Dynamic Systems. Second Edition. CRC Press, 2014.
[18] Y. Han, Q. Li, H. Yang and W. Chen, Design optimal temperature control system based on effective informed adaptive particle swarm optimization for proton exchange membrane fuel cell, 35th Chinese Control Conference (CCC), 2016.
[19] S.K. Meena and S. Channa, Load Frequency Control of multi area system using Hybrid Particle Swarm Optimization. 2nd International Conference on Recent Advances in Engineering & Computational Sciences (RAECS), 2015.