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Doucet, A., Gordon, N., & Krishnamurthy, V. (2001). Particle filters for state estimation of jump
markov linear systems. IEEE Transactions on Signal Processing, 49(3), 613 - 624.
Duda, R. O., Hart, P. E., & Stork, D. G. (2001). Pattern classi cation (2nd ed.). New York: Wiley.
Ferrari-Trecate, G., Muselli, M., Liberati, D., & Morari, M. (2001). A clustering technique for the
identification of piecewise affine systems. In Hybrid systems: Computation and control
(pp. 218
231). New York: Springer.
Ferrari-Trecate, G., Muselli, M., Liberati, D., & Morari, M. (2003). A clustering technique for the
identification of piecewise affine systems. Automatica, 39(2), 205
-
217.
Heemels, W. P., De Schutter, B., & Bemporad, A. (2001). Equivalence of hybrid dynamical
models. Automatica, 37(7), 1085
-
1091.
Henson, M. A., & Seborg, D. E. (1994). Adaptive nonlinear control of a ph neutralization process.
IEEE Transactions on Control Systems Technology, 2(3), 169
-
182.
Juloski, A., Weiland, S., & Heemels, W. (2005). A bayesian approach to identi cation of hybrid
systems. IEEE Transactions on Automatic Control, 50(10), 1520
-
1533.
Juloski, A. L., Paoletti, S., & Roll, J. (2006). Recent techniques for the identi cation of piecewise
af ne and hybrid systems. In Current trends in nonlinear systems and control (pp. 79 - 99).
New York: Springer.
Lai, C. Y. (2011). Identi cation and control of nonlinear systems using multiple models. Ph.D.
thesis.
Lai, C. Y., Xiang, C., & Lee, T. H. (2010). Identi cation and control of nonlinear systems via
piecewise af ne approximation. In The 49th IEEE Conference on Decision and Control (CDC)
(pp. 6395 - 6402).
Lassoued, Z., & Abderrahim, K. (2013a). A comparison study of some PWARX system
identification methods. In The 17th IEEE International Conference in System Theory, Control
and Computing (ICSTCC) (pp. 291
-
296).
Lassoued, Z., & Abderrahim, K. (2013b). A Kohonen neural network based method for PWARX
identification. In Adaptation and learning in control and signal processing, IFAC (Vol. 11,
pp. 742
-
747).
Lassoued, Z., & Abderrahim, K. (2013c). New approaches to identi cation of PWARX systems.
Mathematical Problems in Engineering. http://dx.doi.org/10.1155/2013/845826 .
Lassoued, Z., & Abderrahim, K. (2013d). A new clustering technique for the identi cation of
PWARX hybrid models. In The 9th IEEE Asian Control Conference (ASCC) (pp. 1
-
6).
Lassoued, Z., & Abderrahim, K. (2014a). An experimental validation of a novel clustering
approach to PWARX identi cation. Engineering Applications of Arti cial Intelligence, 28,
201 - 209.
Lassoued, Z., & Abderrahim, K. (2014b). New results on PWARX model identi cation based on
clustering approach. International Journal of Automation and Computing, 11(2), 180 - 188.
Lin, J., & Unbehauen, R. (1992). Canonical piecewise-linear approximations. IEEE Transactions
on Circuits and Systems I: Fundamental Theory and Applications, 39(8), 697 - 699.
Nakada, H., Takaba, K., & Katayama, T. (2005). Identification of piecewise affine systems based
on statistical clustering technique. Automatica, 41(5), 905
-
913.
Roll, J., Bemporad, A., & Ljung, L. (2004). Identification of piecewise affine systems via mixed-
integer programming. Automatica, 40(1), 37
-
50.
Salehi, S., Shahrokhi, M., & Nejati, A. (2009). Adaptive nonlinear control of ph neutralization
processes using fuzzy approximators. Control Engineering Practice, 17(11), 1329
-
1337.
Sander, J., Ester, M., Kriegel, H.-P., & Xu, X. (1998). Density-based clustering in spatial
databases: The algorithm gdbscan and its applications. Data Mining and Knowledge
Discovery, 2(2), 169
-
194.
Talmoudi, S., Abderrahim, K., Abdennour, R. B., & Ksouri, M. (2008). Multimodel approach
using neural networks for complex systems modeling and identi cation. Nonlinear Dynamics
and Systems Theory, 8(3), 299 - 316.
Vander-Schaft, A. J., & Schumacher, J. M. (1998). Complementarity modeling of hybrid systems.
IEEE Transactions on Automatic Control, 43(4), 483 - 490.
-
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