References
- Bai, E. (1998). An optimal two-stage identification algorithm for Hammerstein–Wiener nonlinear systems. Automatica, 34(3), 333–338.
- Bai, E. (2002). A blind approach to the Hammerstein–Wiener model identification. Automatica, 38(6), 967–979.
- Bloemen, H., Boom, T., & Verbruggen, H. (2001). Model-based predictive control for Hammerstein–Wiener systems. International Journal of Control, 74(5), 482–495.
- Bloemen, H., Chou, C., Boom, T., Verdult, V., Verhaegen, M., & Backx, T. (2001). Wiener model identification and predictive control for dual composition control of a distillation column. Journal of Process Control, 11(6), 601–620.
- Boutayeb, M., & Aubry, D. (1999). A strong tracking extended Kalman observer for nonlinear discrete-time systems. IEEE Transactions on Automatic Control, 44(8), 1550–1556.
- Boutayeb, M., & Darouach, M. (1995). Recursive-identification method for MISO Wiener–Hammerstein model. IEEE Transactions on Automatic Control, 40(2), 287–291.
- Chen, H.F. (2007). Adaptive regulator for Hammerstein and Wiener systems with noisy observations. IEEE Transactions on Automatic Control, 52(4), 703–709.
- Chen, H.F., & Guo, L. (1991). Identification and stochastic adaptive control. Boston, MA: Birkhauser.
- Ding, B., & Huang, B. (2007). Output feedback model predictive control nonlinear systems represented by Hammerstein–Wiener model. IET Control Theory Applications, 1(5), 1302–1310.
- Ding, B., Huang, B., & Xu, F. (2011). Dynamic output feedback robust model predictive control. International Journal of Systems Science, 42(10), 1669–1682.
- Ding, B., & Ping, X. (2012). Dynamic output feedback model predictive control for nonlinear systems represented by Hammerstein–Wiener model. Journal of Process Control, 22(9), 1773–1784.
- Ding, B., & Xi, Y. (2006). A two-step predictive control design for input saturated Hammerstein systems. International Journal of Robust Nonlinear Control, 16(7), 353–367.
- Ding, B., Xi, Y., & Li, S. (2004). On the stability of output feedback predictive control for systems with input nonlinearity. Asian Journal of Control, 6(3), 388–397.
- Ding, F., & Chen, T.W. (2005). Identification of Hammerstein nonlinear ARMAX systems. Automatica, 41(9), 1479–1489.
- Ding, F., Chen, T.W., & Iwai, Z. (2007). Adaptive digital control of Hammerstein nonlinear systems with limited output sampling. SIAM Journal of Control and Optimization, 45(6), 2257–2276.
- Dolanc, G., & Strmcnik, S. (2008). Design of a nonlinear controller based on a piecewise-linear Hammerstein model. Systems & Control Letters, 57(4), 332–339.
- Figueroa, J.L., Cousseau, J.E., Werner, S., & Laakso, T. (2007). Adaptive control of a Wiener type system: application of a pH neutralization reactor. International Journal of Control, 80(2), 231–240.
- Fruzzetti, K., Palazoglu, A., & McDonald, K. (1997). Nonlinear model predictive control using Hammerstein models. Journal of Process Control, 7(1), 31–41.
- Fu, Y., & Chai, T. (2013). Robust regulation of discrete time nonlinear systems with arbitrary nonlinearities. Automatica, 49(8), 2567–2570.
- Giri, F., & Bai, E. (2010). Block-oriented nonlinear system identification. London: Springer.
- Giri, F., Rochdi, Y., & Chaoui, F.Z. (2009). Hammerstein system identification in presence of hard nonlinearities of preload and dead-zone type.IEEE Transactions on Automatic Control, 54(9), 2174–2178.
- Goodwin, G.C., & Sin, K.S. (1984). Adaptive filtering, prediction and control. Englewood Cliffs, NJ: Prentice-Hall.
- Harinischmacher, G., & Marquardt, W. (2007). Nonlinear model predictive control of multivariable processes using block-structured models. Control Engineering Practice, 15(10), 1238–1256.
- Kim, K., Rios-Patron, E., & Braatz, R. (2012). Robust nonlinear internal model control of stable Wiener systems. Journal of Process Control, 22(8), 1468–1477.
- Kothare, M., Balakrishnan, V., & Morari, M. (1996). Robust constrained model predictive control using linear matrix inequalities. Automatica, 32(10), 1361–1379.
- Kung, M., & Womack, B. (1983). Stability analysis of a discrete-time adaptive control algorithm having a polynomial input.IEEE Transactions on Automatic Control, 28(12), 1110–1112.
- Liu, Y., & Bai, E. (2007). Iterative identification of Hammerstein systems. Automatica, 43(2), 346–354.
- Ljung, L. (1999).System identification: Theory for the user. Englewood Cliffs, NJ: Prentice-Hall.
- Lo, K., Jiang, R., & Li, D. (2009). Adaptive one-step-ahead optimal controller based on WLS schemes. International Journal of Adaptive Control and Signal Processing, 23(3), 241–259.
- Lv, X., & Ren, V. (2012). Non-iterative identification and model following control of Hammerstein systems with asymmetric dead-zone nonlinearities. IET Control Theory and Applications, 6(1), 84–89.
- Moreno-Valenzuela, J. (2013). Adaptive anti control of chaos for robot manipulators with experimental evaluations. Communication in Nonlinear Science and Numerical Simulation, 18(1), 1–11.
- Norquay, S., Palazoglu, A., & Romagnoli, J. (1998). Model predictive control based on Wiener models. Chemical Engineering Science, 53(1), 75–84.
- Pajunen, G. (1992). Adaptive control of Wiener type-nonlinear systems. Automatica, 28(4), 781–785.
- Patikirikorala, T., Wang, L., Colman, A., & Han, J. (2012). Hammerstein–Wiener nonlinear model based predictive control for relative QoS performance and resource management of software systems. Control Engineering Practice, 20(1), 49–61.
- Patwardhan, R., Lakshminarayanan, S., & Shan, S. (1998). Constrained nonlinear MPC using Hammerstein and Wiener models: PLS framework. AIChE Journal, 42(7), 1611–1622.
- Ping, X., & Ding, B. (2013). Off-line approach to dynamic output feedback robust model predictive control. Systems & Control Letters, 62(11), 1038–1048.
- Voros, J. (1999). Iterative algorithm for parameter identification of Hammerstein systems with two-segment nonlinearities. IEEE Transactions on Automatic Control, 44(11), 2145–2149.
- Voros, J. (2003). Modeling and identification of Wiener systems with two-segment nonlinearities.IEEE Transactions on Control Systems Technology, 11(2), 253–257.
- Yu, F., Mao, Z., & Jia, M. (2013). Recursive identification for Hammerstein–Wiener systems with dead-zone input nonlinearity. Journal of Process Control, 23(8), 1108–1115.
- Zhao, W., & Chen, H. (2009). Adaptive tracking and recursive identification for Hammerstein systems. Automatica, 45(12), 2773–2783.
- Zhu, Y. (2002). Estimation of an N-L-N Hammerstein–Wiener model. Automatica, 38(9), 1607–1614.