A method of LPV model identification for control

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 17, Issue 1 PART 1, 2008, Pages

  Zhu, Yucai ^a   Xu, Zuhua ^a  

^a NONE

Author keywords

Identification for control; Linear parametrically varying (LPV) methodologies; Nonlinear system identification

Indexed keywords

DATA SETS; IDENTIFICATION FOR CONTROL; LINEAR MODEL; LINEAR PARAMETER VARYING MODELS; LINEAR PARAMETRICALLY VARYING (LPV) METHODOLOGIES; LPV MODELS; MODEL IDENTIFICATION; NONLINEAR PROCESS IDENTIFICATION; NONLINEAR SYSTEM IDENTIFICATION; SIMULATION STUDIES; SUFFICIENT CONDITIONS; TRANSITION DATA; TRANSITION PERIOD; WORKING POINT;

NONLINEAR SYSTEMS; PARAMETER ESTIMATION; PREDICTIVE CONTROL SYSTEMS;

MODEL PREDICTIVE CONTROL;

EID: 79961018058     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20080706-5-KR-1001.4064     Document Type: Conference Paper

References (10)

1. Bamieh, B. and L. Giarre (2002). Identification for linear parameter varying models. Int. Jour. of Robust and Nonlinear Control, Vol.12, pp. 841-853.
2. Banerjee, A. and Y. Arkun (1998). Model predictive control of plant transitions using a new identification technique for interpolating nonlinear models. Journal of Process Control Vol. 8, Nos 5-6, pp. 441-457. (Pubitemid 128400783)
3. Jahansen, T.A. and B.A. Foss (1998). ORBIT: operating-regime-based modelling and identification toolkit. Control Engineering Practice. Vol.6, pp. 1277-1286.
4. Nemani, M., R. Ravikanth and B. Bamieh (1995). Identification of linear parametrically varying systems. In Proceedings of the 34th IEEE control and decision conference, vol.3 (pp. 2990-2995).
5. Rugh W.J. and J. Shamma (2000). Research on gain scheduling. Automatica, Vol.36, pp. 1401-1425.
6. Shamma, J. and M. Athans (1991). Guaranteed properties of gain scheduled control for linear parameter varying plants. Automatica, Vol.27, pp. 559-564. (Pubitemid 21651848)
7. Verdult, V. and M. Verhaegen (2002). Subspace identification of multivariable linear parameter-varying systems. Automatica, Vol.38, No.5, pp. 805-814. (Pubitemid 34201121)
8. Verdult, V. and M. Verhaegen (2005). Kernel methods for subspace identification of multivariable LPV and bilinear systems. Automatica, Vol.41, No.9, pp. 1557-1565. (Pubitemid 41000123)
9. Wei, X. (2006). Adaptive LPV Techniques for Diesel Engines. PhD Dissertation, Johannes Kepler University, Linz, Austria.
10. Zhu, Y.C. (1998). Multivariable process identification for MPC: the asymptotic method and its applications. Journal of Process Control, Vol.8, No.2, pp. 101-115.