CHEN, W-H., 2004. Predictive control for general nonlinear systems using approximation. IEE proceedings: control theory and applications, 151 (2), pp. 137-144
This paper addresses a tracking problem for general nonlinear systems using model
predictive control (MPC). After approximating the tracking error in the receding horizon
by its Taylor series expansion to any specified order, an analytic solution to the
MPC is developed and a closed-form nonlinear predictive controller is presented. Different
from other nonlinear model predictive control (NMPC), there is a built-in integral
action in the developed scheme and the implementation issues are discussed.
Further more, it is pointed out that the proposed NMPC derived using approximation
can stablise the original nonlinear systems if certain condition, which can be met by
properly choosing predictive times and the order for Taylor expansion, is satisfied.
Simulation demonstrates the effectiveness of the proposed NMPC.
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