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Output Feedback Robust MPC Based on Off‐line Observer for LPV Systems via Quadratic Boundedness
Author(s) -
Ping Xubin
Publication year - 2017
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 - 10.1002/asjc.1469
Subject(s) - control theory (sociology) , continuous stirred tank reactor , bounded function , quadratic equation , model predictive control , observer (physics) , line (geometry) , robust control , scheduling (production processes) , mathematics , computer science , mathematical optimization , control system , control (management) , engineering , physics , geometry , electrical engineering , quantum mechanics , artificial intelligence , mathematical analysis , chemical engineering
For the linear parameter varying (LPV) system with available scheduling parameter and bounded disturbance, a synthesis approach to output feedback robust model predictive control (OFRMPC) is considered. By applying the technique of quadratic boundedness, the on‐line method with the refreshment of the bounds of estimation error guarantees the robust stability of the augmented closed‐loop system. For reducing the on‐line computational burden, the look‐up table that stores off‐line optimized control laws and the corresponding regions of attraction is constructed. The on‐line control law is searched based on the bounds of estimation error set and the region of attraction with the closest containment of the real‐time estimated state. A continuous stirred tank reactor (CSTR) model is given to illustrate the effectiveness of the method.