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Original Articles

A multi-objective extremum-seeking controller design technique

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Pages 38-53 | Received 20 Aug 2013, Accepted 21 Jun 2014, Published online: 08 Aug 2014

References

  • Adetola, V. (2008). Integrated real time optimization and model predictive control under parametric uncertainties [Ph.D. Thesis]. Queen’s University.
  • Adetola, V., & Guay, M. (2007). Parameter convergence in adaptive extremum-seeking control. Automatica, 43, 105–110.
  • Adetola, V., & Guay, M. (2009). Robust adaptive MPC for systems with exogenous disturbances. American Control Conference, St Louis, MO.
  • Bemporad, A., & de la Pena, D.M. (2009). Multiobjective model predictive control. Automatica, 45, 2823–2830.
  • Cougnon, P., Dochain, D., Guay, M., & Perrier, M. (2011). On-line optimization of fedbatch bioreactors by adaptive extremum seeking control. Journal of Process Control, 21, 1526–1532.
  • De Vito, D., & Scattolini, R. (2007). A receding horizon approach to the multiobjective control problem. In Proceedings of 46th IEEE Conference on Decision and Control (pp. 6029–6034), New Orleans, LA.
  • Deb, K. (2001). Multi-objective optimization. Hoboken, NJ: John Wiley & Sons.
  • Flores-Tlacuahuac, A., Morales, P., & Rivera-Toledo, M. (2012). Multiobjective nonlinear model predictive control of a class of chemical reactors. Industrial & Engineering Chemistry Research, 51, 5891–5899.
  • Fu, L., & Özgüner, Ü. (2011). Extremum seeking with sliding mode gradient estimation and asymptotic regulation for a class of nonlinear systems. Automatica, 47, 2595–2603.
  • Ghaffari, A., Krstic, M., & Nesic, D. (2012). Multivariable Newton-based extremum seeking. Automatica, 48, 1759–1767.
  • Guay, M., & Dochain, D. (2013). A minmax extremum seeking control approach. IEEE Transactions on Automatic Control, 59(7), 1874–1886.
  • Guay, M., Dochain, D., & Dhaliwal, S. (2013). A time-varying extremum seeking control technique. Proceedings of the American Control Conference 2013, Washington, DC.
  • Guay, M., Dochain, D., & Perrier, M. (2004). Adaptive extremum seeking control of continuous stirred tank bioreactors with unknown growth kinetics. Automatica, 40, 881–888.
  • Khalil, H. (2002). Nonlinear systems (3rd ed.). Upper Saddle River, NJ: Prentice-Hall PTR.
  • Konak, A., Coit, D.W., & Smith, A.E. (2006). Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering & System Safety, 91, 992–1007.
  • Krstic, M. (2000). Performance improvement and limitation in extremum seeking control. Systems & Control Letters, 39, 313–326.
  • Krstic, M., Kanellakopoulos, I., & Kokotovic, P. (1995). Nonlinear and adaptive control design. Toronto: Wiley.
  • Krstic, M., & Wang, H. (2000). Stability of extremum seeking feedback for general dynamic systems. Automatica, 36, 595–601.
  • Leblanc, M. (1922). Sur l’électrification des chemins de fer au moyen de courants alternatifs de fréquence élevée [On the electrification of rail roads using high frequency alternating currents]. Revue Générale de l’Electricité, 12(8), 275–277.
  • Marler, R.T., & Arora, J.S. (2004). Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, 26, 369–395.
  • Marler, R.T., & Arora, J.S. (2010). The weighted sum method for multi-objective optimization: New insights. Structural and Multidisciplinary Optimization, 41, 853–862.
  • Moase, W.H., Manzie, C., & Brear, M.J. (2010). Newton-like extremum-seeking for the control of thermoacoustic instability. IEEE Transactions on Automatic Control, 55, 2094–2105.
  • Nesic, D., Mohammadi, A., & Manzie, C. (2010). A systematic approach to extremum seeking based on parameter estimation. In Proceedings of 49th IEEE CDC (pp. 3902–3907), Atlanta, GA.
  • Reyes-Sierra, M., & Coello, C.C. (2006). Multi-objective particle swarm optimizers: A survey of the state-of-the-art. International Journal of Computational Intelligence Research, 2, 287–308.
  • Schäffler, S., Schultz, R., & Weinzierl, K. (2002). Stochastic method for the solution of unconstrained vector optimization problems. Journal of Optimization Theory and Applications, 114, 209–222.
  • Tan, Y., Moase, W., Manzie, C., Nesic, D., & Mareels, I. (2010, July). Extremum seeking from 1922 to 2010. In Proceedings of 29th Chinese Control Conference (CCC) (pp. 14–26), Beijing, China.
  • Tan, Y., Nesic, D., & Mareels, I. (2006). On non-local stability properties of extremum seeking control. Automatica, 42, 889–903.
  • Zavala, V.M., & Flores-Tlacuahuac, A. (2012). Stability of multiobjective predictive control: A utopia-tracking approach. Automatica, 48(10), 2627–2632.
  • Zemin, L. (1996). The optimality conditions of differentiable vector optimization problems. Journal of Mathematical Analysis and Applications, 201, 35–43.
  • Zhang, C., & Ordóñez, R. (2009). Robust and adaptive design of numerical optimization-based extremum seeking control. Automatica, 45, 634–646.
  • Zhang, C., & Ordóñez, R. (2012). Extremum-seeking control and applications. London: Springer-Verlag.

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