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ON THE STABILITY OF OUTPUT FEEDBACK PREDICTIVE CONTROL FOR SYSTEMS WITH INPUT NONLINEARITY
Author(s) -
Ding BaoCang,
Xi YuGeng,
Li ShaoYuan
Publication year - 2004
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1111/j.1934-6093.2004.tb00214.x
Subject(s) - control theory (sociology) , stability (learning theory) , nonlinear system , observer (physics) , model predictive control , matrix (chemical analysis) , lyapunov function , lyapunov stability , domain (mathematical analysis) , mathematics , control system , control (management) , computer science , engineering , physics , mathematical analysis , materials science , quantum mechanics , machine learning , artificial intelligence , electrical engineering , composite material
For input saturated Hammerstein systems, a two‐step output feedback predictive control (TSOFPC) scheme is adopted. A receding horizon state observer is chosen, the gain matrix of which has a form similar to the linear control law. Through application of Lyapunov's stability theory, the closed‐loop stability for this kind of system is analyzed. The intermediate variable may or may not be available in real applications, and these two cases are considered separately in this paper. Furthermore, the domain of attraction for this kind of system is discussed, and we prove that it can be tuned to be arbitrarily large if the system matrix is semi‐stable. The stability results are validated by means of an example simulation.