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Economic MPC of nonlinear systems with nonmonotonic Lyapunov functions and its application to HVAC control
Author(s) -
Wang Zheming,
Hu Guoqiang
Publication year - 2018
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.4033
Subject(s) - lyapunov function , control theory (sociology) , lyapunov optimization , lyapunov redesign , model predictive control , nonlinear system , computer science , lyapunov equation , hvac , lyapunov stability , stability (learning theory) , convergence (economics) , mathematical optimization , control (management) , mathematics , engineering , air conditioning , artificial intelligence , mechanical engineering , physics , quantum mechanics , machine learning , economics , economic growth
Summary This paper proposes a Lyapunov‐based economic model predictive control (MPC) scheme for nonlinear systems with nonmonotonic Lyapunov functions. Relaxed Lyapunov‐based constraints are used in the MPC formulation to improve the economic performance. These constraints will enforce a Lyapunov decrease after every few steps. Recursive feasibility and asymptotical convergence to the steady state can be achieved using Lyapunov‐like stability analysis. The proposed economic MPC can be applied to minimize energy consumption in heating ventilation and air conditioning control of commercial buildings. The Lyapunov‐based constraints in the online MPC problem enable the tracking of the desired set‐point temperature. The performance is demonstrated by a virtual building composed of 2 adjacent zones.