Output tracking of constrained nonlinear processes with offset-free input-to-state stable fuzzy predictive control

• Published in: Automatica (Oxford) Vol. 45; no. 4; pp. 900 - 909
• Main Authors: Zhang, Tiejun, Feng, Gang, Zeng, Xiao-Jun
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.04.2009; Elsevier
• Subjects: Applied sciences; Computer science; control theory; systems; Constrained optimization; Control system analysis; Control theory. Systems; Exact sciences and technology; Fuzzy systems; Input-to-state stability; Linear matrix inequality; Model predictive control; Modelling and identification; Offset-free control; Output feedback; Output tracking; Model predictive control; Offset-free control; Input-to-state stability; Linear matrix inequality; Output tracking; Output feedback; Constrained optimization; Fuzzy systems; Error estimation; Non linear control; Feedback regulation; Semi definite programming; Modeling; Convex programming; Fuzzy control; Model matching; Observer; System identification; State estimation; Predictive control; Estimation error; Output signal; Closed feedback; Fuzzy logic; Input to state stability; Model reference adaptive control systems
• ISSN: 0005-1098; 1873-2836
• DOI: 10.1016/j.automatica.2008.11.016

This paper develops an efficient offset-free output feedback predictive control approach to nonlinear processes based on their approximate fuzzy models as well as an integrating disturbance model. The estimated disturbance signals account for all the plant–model mismatch and unmodeled plant disturbances. An augmented piecewise observer, constructed by solving some linear matrix inequalities, is used to estimate the system states and the lumped disturbances. Based on the reference from an online constrained target generator, the fuzzy model predictive control law can be easily obtained by solving a convex semi-definite programming optimization problem subject to several linear matrix inequalities. The resulting closed-loop system is guaranteed to be input-to-state stable even in the presence of observer estimation error. The zero offset output tracking property of the proposed control approach is proved, and subsequently demonstrated by the simulation results on a strongly nonlinear benchmark plant.