Robust Control Design for Three-Phase Power Inverters using Genetic Algorithm

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Natthaphob Nimpitiwan
Somyot Kaitwanidvilai

Abstract

This paper proposes a new technique to design a fixed-structure robust controller for grid connected three-phase inverter systems. The proposed technique applies the Genetic Algorithm to evaluate the optimal controller parameters. The integral squared error (ISE) of the controlled system is minimized and the robust performance (RP) of the system is satisfied. In the proposed design, the structure of controller is specified as a decentralized Proportional- Integral (PI) controller which is preferred for practical implementations. Simulation results show that the proposed technique is promising. Applying the proposed technique ensures wide operating conditions for three-phase power inverters.

Article Details

How to Cite
Nimpitiwan, N., & Kaitwanidvilai, S. (2011). Robust Control Design for Three-Phase Power Inverters using Genetic Algorithm. ECTI Transactions on Electrical Engineering, Electronics, and Communications, 10(1), 80–88. https://doi.org/10.37936/ecti-eec.2012101.170463
Section
Controls

References

[1] I. Kitsios, T. Pimenides, “Structured-specified robust-multivariable-controller design for pratical applications using genetic algorithms,” in Proc. IEE Control Theory Appl., vol. 150, no. 3, pp. 317-323, 2003.

[2] C. Bor-Sen, C. Yu-Min, “A structure-specified H∞ optimal control design for practical applications: a genetic approach,” IEEE Trans. Control Systems Technology, vol. 6, no. 6, pp. 707-718, 1998.

[3] C. Bor-Sen, C. Yu-Min, L. Ching-Hsiang, “A genetic approach to mixed H2/H∞ optimal PID control,” IEEE Control Systems, vol. 15, no. 5, pp. 51-60, 1995.

[4] H. Shinn-Jang, H. Shinn-Ying, H. Ming-Hao, S. Li-Sun, H. Hui-Ling, “Designing structurespecified mixed H2/H∞ optimal controllers using an intelligent genetic algorithm IGA,” IEEE Trans. Control Systems Technology, vol. 13, no. 6, pp. 1119-1124, 2005.

[5] O. Wasynczuk, N. A. Anwah, “Modeling and dynamic performance of a self-commutated photovoltaic inverter system,” IEEE Trans. Energy Conversion, vol. 4, no. 3, pp. 322-328, 1989.

[6] Y. A. R. I. Mohamed, E. F. El-Saadany, “A Control Method of Grid-Connected PWM Voltage Source Inverters to Mitigate Fast Voltage Disturbances,” IEEE Trans. Power Systems, vol. 24, no. 1, pp. 489-491, 2009.

[7] N. Kroutikova, C. A. Hernandez-Aramburo, T. C. Green, “State-space model of grid-connected inverters under current control mode,” IET Electr. Power Appl., vol. 1, no. 3, pp. 329-338, 2007.

[8] A. Yazdani, P. P. Dash, “A control methodology and characterization of dynamics for a photovoltaic (PV) system interfaced with a distribution network,” IEEE Trans. on Power Delivery, vol. 24, no. 3, pp. 1538-1551, Jul. 2009.

[9] W. Li, L. Ying-Hao, “Small-signal stability and transient analysis of an autonomous PV system,” in Proc. Transmission and Distribution Conf. and Expo. (IEEE/PES), pp. 1-6, 2008.

[10] Z. Shi-cheng, W. Pei-zhen, G. Lu-sheng, “Study on Pwm Control Strategy of Photovoltaic Gridconnected Generation System,” in Proc. Int. Conf. IPEMC Power Electronics and Motion Control, vol. 3, pp. 1-5, 2006.

[11] D. E. Goldberg, Genetic algorithms in search, optimization, and machine learning. Reading, Mass.: Addison-Wesley Pub. Co., 1989.

[12] A. A. Rodriguez, Analysis and design of mul- tivariable feedback control systems. Tempe, AZ: Control3D, 2005.

[13] A. D. Hansen, P. Sørensen, L. H. Hansen, H. Bindner, “Models for a Stand-Alone PV System,” Risø National Laboratory, Roskilde 2000.

[14] Y. Ting-Chung, C. Tang-Shiuan, “Analysis and simulation of characteristics and maximum power point tracking for photovoltaic systems,” in Proc. Int. Conf. Power Electronics and Drive Systems, pp. 1339-1344, 2009.

[15] L. Fangrui, K. Yong, Z. Yu, D. Shanxu, “Comparison of P&O and hill climbing MPPT methods for grid-connected PV converter,” in Proc. Industrial Electronics and Applications Conf., pp. 804-807, 2008.