Abstract

In the domains of industry process control, the model identification and predictive control of nonlinear systems are always difficult problems. To solve the problems, a section identification method based on least squares support vector machines about function approximation is utilized to identify a nonlinear autoregressive external input model which is then used to construct a novel nonlinear model predictive controller. In deriving the control law, a quasi-Newton algorithm is selected to implement the nonlinear model predictive control algorithm. The simulation result illustrates that this approach is effective and feasible.

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