BibTex RIS Kaynak Göster

Artificial Bee Colony Algorithm Based Linear Quadratic Optimal Controller Design for a Nonlinear Inverted Pendulum

Yıl 2015, Cilt: 3 Sayı: 1, 1 - 6, 13.01.2015
https://doi.org/10.18201/ijisae.87020

Öz

This paper presents a linear quadratic optimal controller design for a nonlinear inverted pendulum. Linear Quadratic Regulator (LQR), an optimal control method, is usually used for control of the dynamical systems. Main design parameters in LQR are the weighting matrices; however there is no relevant systematic techniques presented to choose these matrices. Generally, selecting weighting matrices is performed by trial and error method since there is no direct relation between weighting matrices and time domain specifications like overshoot percentage, settling time, and steady state error. Also it is time consuming and highly depends on designer’s experience. In this paper LQR is used to control an inverted pendulum as a nonlinear dynamical system and the Artificial Bee Colony (ABC) algorithm is used for selecting weighting matrices to overcome LQR design difficulties. The ABC algorithm is a swarm intelligence based optimization algorithm and it can be used for multivariable function optimization efficiently.  The simulation results justify that the ABC algorithm is a very efficient way to determine LQR weighting matrices in comparison with trial and error method.

Kaynakça

  • K. J. Aström and K. Furuta, "Swinging up a pendulum by energy control," Automatica, vol. 36, no. 2, pp. 287-295, 2000.
  • J. Anderson, "Learning to control of an inverted pendulum using neural networks," IEEE Control Systems Magazine, vol. 9, no. 3, pp. 31-37, 1989.
  • A. Kuo, "The six determinants of gaint and the inverted pendulum analogy: Adynamic walking perspective," Human Movement, vol. 26, pp. 617-656, 2007.
  • S. Jeong and T. Takahashi, "Wheeled inverted pendulum type asistant robot: inverted mobile, standing and sitting motions," in IEEE/RSJ International Conferance on Intelligent Robots and Systems, 2007, 2007.
  • D. E. Kirk, Optimal control theory: an introduction, New Jersey: Prentice-Hall, Inc., 1970.
  • M. Athans, "The status of optimal control theory and applications for for deterministic systems," IEEE Transactions on Automatic Control, vol. 11, no. 3, pp. 580-596, 1966.
  • R. E. Kalman, "When is a linear control system optimal?," Journal of Basic Engineering, vol. 86, pp. 51-56, 1964.
  • H. Kwakernaak and R. Sivan, Linear optimal control systems, New York: Wiley-Interscience, 1972.
  • J. V. D. F. Neto, I. S. Abreu and F. N. Da Silva, "Neural-genetic synthesis for state-space controllers based on linear quadratic regulator design for eigenstructure assignment," Trans. Sys. Man Cyber. Part B, vol. 40, no. 2, pp. 266-285, 2010.
  • C. P. Bottura, J. V. da Fonseca Neto, "Parallel eigenstructure assignment via LQR design and genetic algorithms," in Proceedings of the American Control Conference 1999. Vol. 4. , San Diago, 1999.
  • S. Mobayen, A. Rabiei, M. Moradi and B. Mohammady, "Linear quadratic optimal control system design using particle swarm optimization algorithm," International Journal of the Physical Sciences, vol. 6(30), pp. 6958-6966, 2011.
  • K. Ogata, "Quadratic Optimal Control Systems," in Discrete-Time Control Systems 2nd Edition, Englewood Cliffs, NJ, Prentice-Hall, 1995, pp. 566-633.
  • D. Karaboga, "An idea based on honey bee swarm for numerical optimization," Erciyes University, Kayseri, Turkey, 2005.
  • D. Karaboga and B. Basturk, "An artificial bee colony (ABC) algorithm for numeric function optimization.," in IEEE Symp. Swarm Intelligence, Indianapolis, 2006.
  • D. Karaboga and B. Basturk, "On the performance of artificial bee colony (ABC) algorithm," Applied Soft Computing, vol. 8, no. 1, pp. 687-697, 2008.
  • D. Karaboga and B. Basturk, "A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm," Journal of Global Optimization, vol. 39, no. 3, pp. 459-471, 2007.
  • D. Karaboga and B. Akay, "A comparative study of Artificial Bee Colony algorithm," Applied Mathematics and Computation, vol. 214, no. 1, p. 108–132, 2009
  • "Detailed Pseudocode of the ABC Algorithm," 14 October 2008. [Online]. Available: http://mf.erciyes.edu.tr/abc/pub/PsuedoCode.pdf. [Accessed 1 March 2014].
  • R. Coban , "A fuzzy controller design for nuclear research reactors using the particle swarm optimization algorithm," Nuclear Engineering and Design, vol. 241, no. 5, pp. 1899-1908, 2011.
Yıl 2015, Cilt: 3 Sayı: 1, 1 - 6, 13.01.2015
https://doi.org/10.18201/ijisae.87020

Öz

Kaynakça

  • K. J. Aström and K. Furuta, "Swinging up a pendulum by energy control," Automatica, vol. 36, no. 2, pp. 287-295, 2000.
  • J. Anderson, "Learning to control of an inverted pendulum using neural networks," IEEE Control Systems Magazine, vol. 9, no. 3, pp. 31-37, 1989.
  • A. Kuo, "The six determinants of gaint and the inverted pendulum analogy: Adynamic walking perspective," Human Movement, vol. 26, pp. 617-656, 2007.
  • S. Jeong and T. Takahashi, "Wheeled inverted pendulum type asistant robot: inverted mobile, standing and sitting motions," in IEEE/RSJ International Conferance on Intelligent Robots and Systems, 2007, 2007.
  • D. E. Kirk, Optimal control theory: an introduction, New Jersey: Prentice-Hall, Inc., 1970.
  • M. Athans, "The status of optimal control theory and applications for for deterministic systems," IEEE Transactions on Automatic Control, vol. 11, no. 3, pp. 580-596, 1966.
  • R. E. Kalman, "When is a linear control system optimal?," Journal of Basic Engineering, vol. 86, pp. 51-56, 1964.
  • H. Kwakernaak and R. Sivan, Linear optimal control systems, New York: Wiley-Interscience, 1972.
  • J. V. D. F. Neto, I. S. Abreu and F. N. Da Silva, "Neural-genetic synthesis for state-space controllers based on linear quadratic regulator design for eigenstructure assignment," Trans. Sys. Man Cyber. Part B, vol. 40, no. 2, pp. 266-285, 2010.
  • C. P. Bottura, J. V. da Fonseca Neto, "Parallel eigenstructure assignment via LQR design and genetic algorithms," in Proceedings of the American Control Conference 1999. Vol. 4. , San Diago, 1999.
  • S. Mobayen, A. Rabiei, M. Moradi and B. Mohammady, "Linear quadratic optimal control system design using particle swarm optimization algorithm," International Journal of the Physical Sciences, vol. 6(30), pp. 6958-6966, 2011.
  • K. Ogata, "Quadratic Optimal Control Systems," in Discrete-Time Control Systems 2nd Edition, Englewood Cliffs, NJ, Prentice-Hall, 1995, pp. 566-633.
  • D. Karaboga, "An idea based on honey bee swarm for numerical optimization," Erciyes University, Kayseri, Turkey, 2005.
  • D. Karaboga and B. Basturk, "An artificial bee colony (ABC) algorithm for numeric function optimization.," in IEEE Symp. Swarm Intelligence, Indianapolis, 2006.
  • D. Karaboga and B. Basturk, "On the performance of artificial bee colony (ABC) algorithm," Applied Soft Computing, vol. 8, no. 1, pp. 687-697, 2008.
  • D. Karaboga and B. Basturk, "A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm," Journal of Global Optimization, vol. 39, no. 3, pp. 459-471, 2007.
  • D. Karaboga and B. Akay, "A comparative study of Artificial Bee Colony algorithm," Applied Mathematics and Computation, vol. 214, no. 1, p. 108–132, 2009
  • "Detailed Pseudocode of the ABC Algorithm," 14 October 2008. [Online]. Available: http://mf.erciyes.edu.tr/abc/pub/PsuedoCode.pdf. [Accessed 1 March 2014].
  • R. Coban , "A fuzzy controller design for nuclear research reactors using the particle swarm optimization algorithm," Nuclear Engineering and Design, vol. 241, no. 5, pp. 1899-1908, 2011.
Toplam 19 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Research Article
Yazarlar

Baris Ata

Ramazan Coban

Yayımlanma Tarihi 13 Ocak 2015
Yayımlandığı Sayı Yıl 2015 Cilt: 3 Sayı: 1

Kaynak Göster

APA Ata, B., & Coban, R. (2015). Artificial Bee Colony Algorithm Based Linear Quadratic Optimal Controller Design for a Nonlinear Inverted Pendulum. International Journal of Intelligent Systems and Applications in Engineering, 3(1), 1-6. https://doi.org/10.18201/ijisae.87020
AMA Ata B, Coban R. Artificial Bee Colony Algorithm Based Linear Quadratic Optimal Controller Design for a Nonlinear Inverted Pendulum. International Journal of Intelligent Systems and Applications in Engineering. Ocak 2015;3(1):1-6. doi:10.18201/ijisae.87020
Chicago Ata, Baris, ve Ramazan Coban. “Artificial Bee Colony Algorithm Based Linear Quadratic Optimal Controller Design for a Nonlinear Inverted Pendulum”. International Journal of Intelligent Systems and Applications in Engineering 3, sy. 1 (Ocak 2015): 1-6. https://doi.org/10.18201/ijisae.87020.
EndNote Ata B, Coban R (01 Ocak 2015) Artificial Bee Colony Algorithm Based Linear Quadratic Optimal Controller Design for a Nonlinear Inverted Pendulum. International Journal of Intelligent Systems and Applications in Engineering 3 1 1–6.
IEEE B. Ata ve R. Coban, “Artificial Bee Colony Algorithm Based Linear Quadratic Optimal Controller Design for a Nonlinear Inverted Pendulum”, International Journal of Intelligent Systems and Applications in Engineering, c. 3, sy. 1, ss. 1–6, 2015, doi: 10.18201/ijisae.87020.
ISNAD Ata, Baris - Coban, Ramazan. “Artificial Bee Colony Algorithm Based Linear Quadratic Optimal Controller Design for a Nonlinear Inverted Pendulum”. International Journal of Intelligent Systems and Applications in Engineering 3/1 (Ocak 2015), 1-6. https://doi.org/10.18201/ijisae.87020.
JAMA Ata B, Coban R. Artificial Bee Colony Algorithm Based Linear Quadratic Optimal Controller Design for a Nonlinear Inverted Pendulum. International Journal of Intelligent Systems and Applications in Engineering. 2015;3:1–6.
MLA Ata, Baris ve Ramazan Coban. “Artificial Bee Colony Algorithm Based Linear Quadratic Optimal Controller Design for a Nonlinear Inverted Pendulum”. International Journal of Intelligent Systems and Applications in Engineering, c. 3, sy. 1, 2015, ss. 1-6, doi:10.18201/ijisae.87020.
Vancouver Ata B, Coban R. Artificial Bee Colony Algorithm Based Linear Quadratic Optimal Controller Design for a Nonlinear Inverted Pendulum. International Journal of Intelligent Systems and Applications in Engineering. 2015;3(1):1-6.

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