Open Access Open Access  Restricted Access Subscription or Fee Access

The Intelligent Adjustment of LQR Controller Using Ants System Metaheuristic

(*) Corresponding author

Authors' affiliations



Many approaches in automatic control are based on solving optimization problems. In the case of nonlinear systems, these optimization problems become difficult to solve in a reasonable computing time. Furthermore, most of the criteria are non-differentiable and even non analytical.  In this paper we exploit the ants system metaheuristic to adjust the parameters of the state feedback controller in order to achieve some compromise between the use of control effort, the magnitude, and the speed of response that will guarantee a stable system. Practically, the simulation results show that the proposed method is indeed adaptive, robust and the optimised control is provided in a reasonable computing time.
Copyright © 2016 Praise Worthy Prize - All rights reserved.


Non-Linear Systems; Ants System Metaheuristic; Controller Adjustment; LQR Controller

Full Text:



M.P. Hansen (1997). Tabu search for multiple objective com-binatorial optimization: MOTS. The 13th International Conference on Multiple Criteria Decision Making (MCDM), University of Cap Town.

E.L. Ulungu, J. Teghem, and Ph. Fortemps (1995). Heuristics for multiob-jective combinatorial optimisation by simulated annealing. Multiple Criteria Decision Making: Theory and applications, Proceedings of the Sixth International Conference on MCDM, Beijing, China.

Bh P. Czyzac and A. Jaszkiewicz (1998). "Pareto simulated an-nealing – a metaheuristic technique for multiple objective combinatorial optimization." Journal of Multicriteria Decision Analysis 7: 34-47.;2-6

N. Liouane, I. Saad and P. Borne (2007). Ant System and Fuzzy Controller for Multi-Objective Optimization of the Flexible Job Shop Scheduling Problems, Studies in Informatics in Control (SIC). Vol. 16, no. 2, pp. 217-226.

H. Liouane, A. Douik and H. Messaoud (2009) Hybrid approach for pole assignment using LQR technique and Ant System metaheuristic. International Journal of Artificial Intelligence and Soft Computing. Vol.1, pp. 213-222.

C. E. Mariano and E. M. Morales (1999a). MOAQ an Ant-Q Algorithm for Multiple Objective Optimization Problems. Genetic and Evolutionary Computing Conference (GECCO 99). Orlando. Florida, July 1999, Morgan Kaufmann.

C. E. Mariano and E. M. Morales (1999b). A Multiple Objective Ant-Q Algorithm for the Design of Water Distribution Irrigation Networks. Technical Report HC-9904, Instituto Mexicano de Tecnologia del Agua.

J. Horn and N. Nafpliotis (1993). Multiobjective optimization using the niched Pareto genetic algorithms, IlliGAL Report No. 93005.

C.M. Fonseca and P. J. Fleming (1995). Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization. Procedings of the of the Fifth International Conference on Genetic Algorithms, San Mateo, CA., Morgan Kaufmann. (Horn et Nafpliotis, 1993).

M. Sun, A. Stam, and al. (1996). "Solving multiple objective programming problems using feedforward artificial neural networks: the interactive FFANN procedure." Management Science 42(6): 835-849.

Jnjn B. Malakooti and Y. Q. Zhou (1994). "Feedforward artificial neural networks for solving discrete multiple criteria deci-sion making problem." Management Science 40(11): 1542-1561.

Gheng-Chung Sung, Gong Chen, "Optimal control systems design associated with genetic algorithm". Proceedings of 2006 CACS Automatic Control Conference St. John's University, Tamsui, Taiwan, Nov. 10-11, 2006.

C. P. Bottura and J. V. da Fonseca Neto. " “Rule based decision making unit for eigenstructure assignment via parallel genetic algorithm and LQR design. " Proceeding of the American Control Conference, Chicago, Illinois, Vol. 1, pp. 467- 471, 2000.

C. P. Bottura and J. V. da Fonseca Neto. " Parallel eigenstructure assignment via LQR design and genetic algorithms. " Proceeding of the American Control Conference, San Diego, Vol. 4, pp. 2295-2299, 1999.

Iraj Hassanzadeh, Saleh Mobayen and Abbas Harifi. " Input-output feedback linearization cascade controller using genetic algorithm for rotary inverted pendulum. " American Journal of Applied Sciences, 5 (10), pp: 1322-1328, 2008.

Hannane, A., Fizazi, H., Metaheuristics and Neural Network for Satellite Images Classification, (2016) International Review of Aerospace Engineering (IREASE), 9 (4).

Sayoti, F., Riffi, M., Random-Keys Golden Ball Algorithm for Solving Traveling Salesman Problem, (2015) International Review on Modelling and Simulations (IREMOS), 8 (1), pp. 84-89.

Al-Khafaji, A., Shaharuddin, N., Mat Darus, I., Modelling of a Flexible Single-Link Manipulator Using Metaheuristic Algorithms, (2014) International Review of Mechanical Engineering (IREME), 8 (6), pp. 1075-1092.

Otsmani, Z., Khiat, M., Chaker, A., Metaheuristic Method for Minimizing the Periodic Preventive Maintenance Cost in an Electrical System, (2013) International Review of Electrical Engineering (IREE), 8 (1), pp. 379-387.

Manzoor, M., Maqsood, A., Hasan, A., Quadratic Optimal Control of Aerodynamic Vectored UAV at High Angle of Attack, (2016) International Review of Aerospace Engineering (IREASE), 9 (3), pp. 70-79.

Liu, G., Zhang, C., LQR Control of Permanent Magnet Synchronous Motor Based on Exact State Feedback Linearization, (2013) International Review of Electrical Engineering (IREE), 8 (2), pp. 626-632.

El Majdoub, K., Ouadi, H., Touati, A., LQR Control for Semi-Active Quarter Vehicle Suspension with Magnetorhehological Damper and Bouc-Wen Model, (2014) International Review on Modelling and Simulations (IREMOS), 7 (4), pp. 703-711.


  • There are currently no refbacks.

Please send any question about this web site to
Copyright © 2005-2023 Praise Worthy Prize