Design and Implementation of an Optimized Controller by TLBO Algorithm on a Twin-Rotor System
Subject Areas : electrical and computer engineering
Mostafa
Yazdani
1
(Electrical Engineering Dep., Arak University)
Khosro
Khandani
2
(Arak University)
Keywords: TLBO, Twin rotor system, PID,
Abstract :
In this research, a new intelligent control design using Teaching-Learning-Based-Optimization (TLBO) algorithm to optimize PID controller coefficients is presented. This method has been applied on the twin rotor system which has been constructed in Control Engineering Lab at Arak University. The purpose of controlling the twin rotor system is to stabilize the system in the zero degree horizontal position. After modeling and obtaining the state space description, the PID controller is designed and implemented on the system. In this study, by reviewing meta-heuristic optimization methods such as particle swarm optimization algorithm, genetic algorithm, colonial competition algorithm and differential evolution algorithm, the optimization results were compared with the above-mentioned meta-heuristic methods. With the optimization performed by the teaching and learning algorithm, the stability and faster performance of the system compared to other meta-heuristic methods can be seen. The merit of TLBO is that it does not have control parameters, which makes it convenient to employ. The simulation results of the PID controller for a twin rotor system show the effectiveness of the proposed methods.
[1] Y. Xin, Z. C. Qin, and J. Q. Sun, "Input-output tracking control of a 2-DOF laboratory helicopter with improved algebraic differential estimation," Mechanical Systems and Signal Processing, vol. 116, pp. 843-857, Feb. 2019.
[2] R. F. Faisal and O. W. Abdulwahhab, "Design of an adaptive linear quadratic regulator for a twin rotor aerodynamic system," J. of Control, Automation and Electrical Systems, vol. 32, no. 2, pp. 404-415, Jan. 2021.
[3] L. Dutta and D. K. Das, "A new adaptive explicit nonlinear model predictive control design for a nonlinear MIMO system: an application to twin rotor MIMO system," International J. of Control, Automation and Systems, vol. 19, no. 7, pp. 2406-2419, Mar. 2021.
[4] N. Almtireen, H. Elmoaqet, and M. Ryalat, "Linearized modelling and control for a twin rotor system," Automatic Control and Computer Sciences, vol. 52, no. 6, pp. 539-551, Jan. 2018.
[5] A. Tastemirov, A. Lecchini-Visintini, and R. M. Morales-Viviescas, "Complete dynamic model of the twin rotor MIMO System (TRMS) with experimental validation," Control Engineering Practice, vol. 66, pp. 89-98, Sept. 2017.
[6] M. Z. Ghellab, S. Zeghlache, A. Djerioui, and L. Benyettou, "Experimental validation of adaptive RBFNN global fast dynamic terminal sliding mode control for twin rotor MIMO system against wind effects," Measurement, vol. 168, Article ID:108472, Jan. 2021.
[7] W. Netto, R. Lakhani, and S. M. Sundaram, "Design and performance comparison of different adaptive control schemes for pitch angle control in a twin-rotor-MIMO-system," International J. of Electrical & Computer Engineering, vol. 9, pp. 2088-8708, Oct. 2019.
[8] B. Pratap and S. Purwar, "Real-time implementation of nonlinear state and disturbance observer-based controller for twin rotor control system," International J. of Automation and Control, vol. 13, no. 4, pp. 469-497, Mar. 2019.
[9] P. K. Paul and J. Jacob, "On the modeling of twin rotor MIMO system using chirp inputs as test signals," Asian J. of Control, vol. 19, no. 5, pp. 1731-1740, Apr. 2017.
[10] M. Parvizian, K. Khandani, and V. J. Majd, "A non-fragile observer-based adaptive sliding mode control for fractional-order Markovian jump systems with time delay and input nonlinearity," Trans. of the Institute of Measurement and Control, vol. 42, no. 8, pp. 1448-1460, May 2020.
[11] H. Zamani, K. Khandani, and V. J. Majd, "Fixed-time sliding-mode distributed consensus and formation control of disturbed fractional-order multi-agent systems," ISA Trans., vol. 138, pp. 37-48, Jul. 2023.
[12] M. Parvizian and K. Khandani, "Robust H∞ sliding mode control scheme for uncertain fractional stochastic systems: nonlinear analysis and design," Asian J. of Control, vol. 25, no. 5, pp. 4086-4095, Feb. 2023.
[13] K. Khandani, V. J. Majd, and M. Tahmasebi, "Robust stabilization of uncertain time-delay systems with fractional stochastic noise using the novel fractional stochastic sliding approach and its application to stream water quality regulation," IEEE Trans. on Automatic Control, vol. 62, no. 4, pp. 1742-1751, Apr. 2017.
[14] M. Parvizian and K. Khandani, "A diffusive representation approach toward H∞ sliding mode control design for fractional-order Markovian jump systems," in Proc. of the Institution of Mechanical Engineers, Part I: J. of Systems and Control Engineering, vol. 235, no. 7, pp. 1154-1163, Aug. 2021.
[15] A. N. Vargas, M. A. Montezuma, X. Liu, L. Xu, and X. Yu, "Sliding-mode control for stabilizing high-order stochastic systems: application to one-degree-of-freedom aerial device," IEEE Trans. on Systems, Man, and Cybernetics: Systems, vol. 50, no. 11, pp. 4318-4325, Nov. 2018.
[16] F. Faris, A. Moussaoui, B. Djamel, and T. Mohammed, "Design and real-time implementation of a decentralized sliding mode controller for twin rotor multi-input multi-output system," Proc. of the Institution of Mechanical Engineers, Part I: J. of Systems and Control Engineering, vol. 231, no. 1, pp. 3-13, Jan. 2017.
[17] S. K. Pandey, J. Dey, and S. Banerjee, "Design of robust proportional-integral-derivative controller for generalized decoupled twin rotor multi-input-multi-output system with actuator non-linearity," in Proc. of the Institution of Mechanical Engineers, Part I: J. of Systems and Control Engineering, vol. 232, no. 8, pp. 971-982, Aug. 2018.
[18] K. Khandani, A. A. Jalali, and M. Alipoor, "Particle swarm optimization based design of disturbance rejection PID controllers for time delay systems," in Proc. IEEE Int. Conf. on Intelligent Computing and Intelligent Systems, pp. 862-866, Shanghai, China, 20-22 Nov. 2009.
[19] K. Khandani and A. A. Jalali, "PSO based optimal fractional PID controller design for an active magnetic bearing system," in Proc. of 18th Annual Int.l Conf. on Mechanical Engineering, 6 pp., Tehran, Iran, 11-11 May 2010.
[20] K. Khandani and A. A. Jalali, "Robust fractional order control of a DC motor based on particle swarm optimization," Advanced Materials Research, vol. 403-408, Trans Tech Publications, Ltd., pp. 5030-5037, Nov. 2011
[21] J. G. Juang, M. T. Huang, and W. K. Liu, "PID control using presearched genetic algorithms for a MIMO system," IEEE Trans. on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 38, no. 5, pp. 716-727, Jan. 2008.
[22] 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 Proc. IEEE Int. Conf. on Power, Energy and Control, ICPEC'13, pp. 443-448, Dindigul, India, 6-8 Feb. 2013.
[23] R. Maiti, K. D. Sharma, and G. Sarkar, "PSO based parameter estimation and PID controller tuning for 2-DOF nonlinear twin rotor MIMO system," International J. of Automation and Control, vol. 12, no. 4, pp. 582-609, Oct. 2018.
[24] M. Kumar and Y. V. Hote, "Real-time performance analysis of PIDD2 controller for nonlinear twin rotor TITO aerodynamical system," J. of Intelligent & Robotic Systems, vol. 101, no. 3, pp. 1-16, Dec. 2021.
[25] R. Rao, V. J. Savsani, and D. P. Vakharia, "Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems," Information Sciences, vol. 183, no. 1, pp. 1-15, May 2012.
[26] R. Rao, "Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems," Decision Science Letters, vol. 5, no. 1, pp. 1-30, Feb. 2012.
[27] A. Abaeifar, H. Barati, and A. R. Tavakoli, "Inertia-weight local-search-based TLBO algorithm for energy management in isolated micro-grids with renewable resources," International J. of Electrical Power & Energy Systems, vol. 137, Article ID: 107877, Apr. 2022.
[28] S. Chafea, K. Kamel, and B. Mohamed, "Optimized FLPID using TLBO algorithm: applied to quadrotor (UAV) system," in Proc. Int. Conf. on Advances in Electronics, Control and Communication Systems, ICAECCS'23, 6 pp., BLIDA, Algeria, 6-7 Mar. 2023.
[29] N. Bouhabza and K. Kara, "Optimized sliding mode based PID controller for a quadrotor system, ICAEE'22, 5 pp., Constantine, Algeria, Sept. 2022.
[30] N. Karimi and K. Khandani, "Social optimization algorithm with application to economic dispatch problem," International Trans. on Electrical Energy Systems, vol. 30, Article ID: e12593, Jul. 2020.