Comparison of Fuzzy Logic and GA-PID Controller for Position Control of Inverted Pendulum

Lukman A. Yusuf(1*), Nuraddeen Magaji(2)

(1) Bayero University Kano., Nigeria
(2) Electrical Engineering Department, Bayero University Kano., Nigeria
(*) Corresponding author

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Stability is very necessary in control system and it becomes more difficult to achieve for a non-linear system. This paper considered two control schemes: Fuzzy Logic Control (FLC) and Proportional-Integra-Derivative optimized with Genetic Algorithm (GA-PID) Controller on Inverted pendulum for the control of the angle position. The FLC scheme was designed with the joint angle error and its derivative as the input of the controller, the Fuzzy controller provides control signal (force) that keep the angle of the pendulum at an equilibrium point despite disturbances. Fuzzy logic toolbox in MATLAB Simulink environment was used. On the other hand, a Matlab script for genetic algorithm was written with the aim of obtaining the best PID parameters that would keep the pendulum angle at equilibrium by minimizing a given objective function: Integral time average error (ITAE). The results obtained in both schemes shows that there was no specific controller between the two that shows superiority in the entire performance index used.

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Fuzzy Logic; PID; Pendulum Angle; Non-Linearity; Genetic Algorithm; Stability

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O.T. Altinoz and A.E. Yilmaz,”Gerhard Wilhelm weber chaos Particle swarm Optimized PID Controller for the inverted pendulum system,” presented at 2nd International Conference on Engineering Optimization. September 6-9,2010,Lisbon,Portugal.

P. Kokotovic J. Hauser, S. Sastry. Nonlinear control via approximate input-output linearization: The ball and beam example. IEEE Trans. Auto. Control, 37(3):392–398, March 1992.

Yizhon Wang.” Nonlinear Control of cart pendulum systems.” 2011.

R.S.D. Wahida Banu, S. A. Banu. and D. Manoj.” Identification and control of Non-linear system using soft computing technique.” International Journal of Modeling and Optimization. Vol. 1, No. 1, April 2011.

K. Pandalai, M. Kataria.” Inverted pendulum system.”

P.Van Overschee et al., RAPID: The end of heuristic PID tuning, Journal A, vol.38, no3, pp6-10.

R. Ciancone and T. Marlin, Tune controllers to meet plant objectives, control May, pp50-57, 1992.

A. Lopez P. Murrill and C. Smith, Tuning PI and PID digital controllers Instruments And control vol.42 pp89-95 1969

L. R. Haupt and S. E. Haupt. “Practical Genetic Algorithms. Second Edition” A john Wiley & Sons, Inc., Publication.

Kajan, S., Didekova, Z., Kozak, S., Linder, M., Neural-genetic control algorithm of nonlinear systems, (2013) International Review of Automatic Control (IREACO), 6 (2), pp. 206-210.

P. I-Hailin, S. Hwang and J. Chou. “Comparison on Fuzzy Logic and PID controls for a D.C motor position controller” Indiana-Pardo University Fort wayne.

F. L. Bernard. “Control system design.” Published: New York. 1987.

Abdellah, A., Abdelhafid, A., Mostafa, R., Combining sliding mode and linear quadratic regulator to control the inverted pendulum, (2013) International Review of Automatic Control (IREACO), 6 (1), pp. 69-76.

S. Sumathi, S.Paneerselian, Computational Intelligence Paradigms: Theory & Applications using MATLAB, CRC Press; 1 edition.

Ciganek, J., Noge, F., Kozak, S., Modeling and control of mechatronic systems using fuzzy logic, (2014) International Review of Automatic Control (IREACO), 7 (1), pp. 45-51.

I.J. Nagrath, M. Gopal. “Control Systems Engineering” Published by New Age International (P) Ltd, Fifth Edition. 2007 pp783-800.

N. Magaji, M. W. Mustafa, Optimal Location and Signal Selection of SVC Device for Damping Oscillation, (2009) International Review on Modelling and Simulations (IREMOS), 2 (2), pp. 144-151.

Elham Ataei, Rouhollah Afshari, Mohammad Ali Pourmina, Fuzzy Logic Control of a Multifingered Hand Robot Using Genetic Algorithm Based on DSP, (2011) International Review of Automatic Control (IREACO), 4 (6), pp. 963-968.


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