Abstract
In this chapter, numerical optimization algorithms are presented, which allow to minimize cost functions even though they are not linear in parameters.
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References
Bähr J, Isermann R, Muenchhof M (2009) Fault management for a three mass torsion oscillator. In: Proceedings of the European Control Conference 2009 - ECC 09, Budapest, Hungary
van den Bos A (2007) Parameter estimation for scientists and engineers. Wiley-Interscience, Hoboken, NJ
Boyd S, Vandenberghe L (2004) Convex optimization. Cambridge University Press, Cambridge, UK
Conn AR, Scheinberg K, Vicente LN (2009) Introduction to derivative-free optimization, MPS-SIAM series on optimization, vol 8. SIAM, Philadelphia
van Doren JFM, Douma SG, van den Hof PMJ, Jansen JD, Bosgra OH (2009) Identifiability: From qualitative analysis to model structure approximation. In: Proceedings of the 15th IFAC Symposium on System Identification, Saint-Malo, France
Isermann R (2006) Fault-diagnosis systems: An introduction from fault detection to fault tolerance. Springer, Berlin
Isermann R, Lachmann KH, Matko D (1992) Adaptive control systems. Prentice Hall international series in systems and control engineering, Prentice Hall, New York, NY
Kennedy J, Eberhart RC, Shi Y (2001) Swarm intelligence. The Morgan Kaufmann series in evolutionary computation, Morgan Kaufmann, San Francisco, CA
Kötter H, Schneider F, Fang F, Gußner T, Isermann R (2007) Robust regressor and outlier-detection for combustion engine measurements. In: Röpke K (ed) Design of experiments (DoE) in engine development - DoE and other modern development methods, Expert Verlag, Renningen, pp 377–396
Ljung L (1999) System identification: Theory for the user, 2nd edn. Prentice Hall Information and System Sciences Series, Prentice Hall PTR, Upper Saddle River, NJ
Ljung L (2009) Experiments with identification of continuous time models. In: Proceedings of the 15th IFAC Symposium on System Identification, Saint-Malo, France
Mitchell M (1996) An introduction to genetic algorithms. MIT Press, Cambridge, MA
Nelles O (2001) Nonlinear system identification: From classical approaches to neural networks and fuzzy models. Springer, Berlin
Ninness B (2009) Some system identification challenges and approaches. In: Proceedings of the 15th IFAC Symposium on System Identification, Saint-Malo, France
Nocedal J, Wright SJ (2006) Numerical optimization, 2nd edn. Springer series in operations research, Springer, New York
Parillo PA, Ljung L (2003) Initialization of physical parameter estimates. In: Proceedings of the 13th IFAC Symposium on System Identification, Rotterdam, The Netherlands, pp 1524–1529
Press WH, Teukolsky SA, Vetterling WT, Flannery BP (2007) Numerical recipes: The art of scientific computing, 3rd edn. Cambridge University Press, Cambridge, UK
Ravindran A, Ragsdell KM, Reklaitis GV (2006) Engineering optimization: Methods and applications, 2nd edn. John Wiley & Sons, Hoboken, NJ
Rousseeuw PJ, Leroy AM (1987) Robust regression and outlier detection. Wiley Series in Probability and Statistics, Wiley, New York
Schneider JJ, Kirkpatrick S (2006) Stochastic optimization. Springer, Berlin
Snyman JA (2005) Practical mathematical optimization: An introduction to basic optimization theory and classical and new gradient-based algorithms. Springer, New York
Vanderplaats GN (2005) Numerical optimization techniques for engineering design, 4th edn. Vanderplaats Research & Development, Colorado Springs, CO
Verhaegen M, Verdult V (2007) Filtering and system identification: A least squares approach. Cambridge University Press, Cambridge
Xie LL, Ljung L (2002) Estimate physical parameters by black-box modeling. In: Proceedings of the 21st Chinese Control Conference, Hangzhou, China, pp 673–677
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Isermann, R., Münchhof, M. (2011). Iterative Optimization. In: Identification of Dynamic Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78879-9_19
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DOI: https://doi.org/10.1007/978-3-540-78879-9_19
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