Robust PID Controller Tuning for 2D Gantry Crane Using Kharitonov's Theorem and Differential Evolution Optimizer

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PID (proportional+integral+derivative) controller is well known as a simple and easy-to-implement controller. However, the design procedure is not straightforward for multi-input multi-output (MIMO) systems. It is even more complicated when robustness criterion must be handled. In this paper, a stable robust PID controller for anti-swing control of automatic gantry crane is proposed. The proposed method employs an automatic tuning using DE (differential evolution) to search for a set of PID controller gains that satisfy Kharitonovs polynomials robust stability criterion. This robust stability criterion is used to deal with parametric uncertainty occurs in gantry crane model. The simulation results show that a satisfactory robust PID control performance can be achieved. The PID controller is able to quickly move the cart of the crane while suppressing the swing of the payload for various conditions, i.e. payload mass and cable length variations.

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Periodical:

Edited by:

Ahmad Razlan Yusoff and Ismed Iskandar

Pages:

267-272

DOI:

10.4028/www.scientific.net/AMR.903.267

Citation:

M. I. Solihin et al., "Robust PID Controller Tuning for 2D Gantry Crane Using Kharitonov's Theorem and Differential Evolution Optimizer", Advanced Materials Research, Vol. 903, pp. 267-272, 2014

Online since:

February 2014

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$35.00

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[1] Garrido, S., Abderahim, M., Gimenez, A., Diez, R. and Balaguer, C. (2008). Anti-swinging input shaping control of automatic construction crane. IEEE Transactions on Automation Science and Engineering, 5(3).

DOI: 10.1109/tase.2007.909631

[2] Gupta, S. and Bhowal, P. (2004). Simplified open loop anti-sway technique. Proc. of the IEEE India Annual Conference, pp.225-228.

DOI: 10.1109/indico.2004.1497743

[3] Sridokbuap, W., Nundrakwang, S., Benjanarasuth, T., Ngamwiwit, J. and Komine, N. (2007). I-PD and PD controllers designed by CRA method for overhead crane system. Proc. International Conference on Control, Automation and Systems. pp.326-330.

DOI: 10.1109/iccas.2007.4406931

[4] Chang, C.Y., Chiang, K.H. and Hsu, S.W. (2005). Fuzzy controller for the 3-D overhead crane system. Proc. of IEEE International Conference on Robotics and Biomimetics, pp.724-729.

DOI: 10.1109/robio.2005.246358

[5] Renno J.M., Trabia M.B. and Moustafa K.A.F. (2004). Anti-swing adaptive fuzzy controller for an overhead crane with hoisting. Proc. of IMECE ASME International Mechanical Engineering Congress & Exposition.

DOI: 10.1109/fuzzy.2006.1681777

[6] Wahyudi, Jalani, J., Muhida, R. and Salami, M.J.E. (2007). Control strategy for automatic gantry crane systems: a practical and intelligent approach. International Journal of Advanced Robotic Systems, no 4.

DOI: 10.5772/5669

[7] Hu, H., Hu, Q., Lu, Z. and Xu, D. (2005). Optimal PID controller design in PMSM servo system via particle swarm optimization. Proc. IEEE Annual Conference of Industrial Electronics Society, pp.79-83.

DOI: 10.1109/iecon.2005.1568882

[8] Gaing, Z.L. (2004). A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Transaction on Energy Conversion, Vol. 19(2), pp.384-391.

DOI: 10.1109/tec.2003.821821

[9] Zhao, J., Li, T. and Qian, J. (2005). Application of particle swarm optimization algorithm on robust PID controller tuning. Advances in Natural Computation: Book Chapter. Springer Berlin, pp.948-957.

DOI: 10.1007/11539902_118

[10] Ou, C. and Lin, W. (2006). Comparison between PSO and GA for parameters optimization of PID controller. Proc. IEEE International Conference on Mechatronics and Automation. Luoyang, China.

DOI: 10.1109/icma.2006.257739

[11] Solihin, M.I., Wahyudi, Kamal, M.A.S. and Legowo, A. (2008). Optimal PID controller tuning of automatic gantry crane using PSO algorithm. Proc. of International Symposium on Mechatronics and Its Application (ISMA 2008).

DOI: 10.1109/isma.2008.4648804

[12] Matsuo, T., Yoshino R., Suemitsu, H. and Nakano, K. (2004). Nominal performance recovery by PID+Q controller and its application to anti-sway control of crane lifter with visual feedback. IEEE Transactions on Control Systems Technology, vol. 2/1.

DOI: 10.1109/tcst.2003.821964

[13] Stefani, R.T. and Shahian, B. (2002). Design of feedback control systems. Oxford University Press.

[14] Solihin, M.I., Wahyudi and Legowo, A. (2010). Fuzzy-tuned PID Anti-swing Control of Automatic Gantry Crane. Journal of Vibration and Control, Vol. 16(1), pp.127-145.

DOI: 10.1177/1077546309103421

[15] Weisstein E.W., Vassilis P. (2006). Differential evolution. Web resource; http: /mathworld. wolfram. com/DifferentialEvolution. html.

[16] Yousefi, H., Handroos, H., Soleymani, A. (2008). Application of differential evolution in system identification of a servo-hydraulic system with a flexible load, Mechatronics 18 : 513–528.

DOI: 10.1016/j.mechatronics.2008.03.005

[17] R. Storn and K. Price. (1995). Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces. Technical Report, International Computer Science Institute, Berkley.

[18] K. V. Price. (1999). An introduction to differential evolution, in New Ideas in Optimization, D. Corne, M. Dorigo, and F. Glover, Eds. London: McGraw-Hill, p.79–108.

[19] Price, K., Storn, R., and Lampinen, J.A. (2005). Differential Evolution: A practical approach to global optimization. Springer-Verlag, Berlin Heidelberg.

[20] Storn, R and Price, K. (1997). Differential Evolution – A simple and efficient heuristic for global optimization over Ccontinuous spaces. Journal of Global Optimization, 11(4): 431–359.

[21] Iwan, M., Akmeliawati, R., Faisal, T., Al-Assadi, H.M.A. (2012). Performance comparison of differential evolution and particle swarm optimization in constrained optimization. Procedia Engineering, 41: 1323-1328.

DOI: 10.1016/j.proeng.2012.07.317

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