A New Development of Adaptive Model Predictive Control
نویسندگان
چکیده
An adaptive radial basis function (RBF) neural network model is developed in this paper for nonlinear systems using the recursive orthogonal least squares (ROLS) algorithm. The model is used in a nonlinear model predictive control (NMPC). The developed adaptive NMPC is applied to a chemical reactor rig. On-line control performance is presented and it demonstrates superiority over the fixed parameter PID control. Copyright © 2005 IFAC
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تاریخ انتشار 2005