Abstract
Abstract The design and implementation of a new adaptive nonlinear predictive controller is presented using a general nonlinear model and variable transformations. The resulting controller is similar in form to standard linear model predictive controllers and can be tuned analogously. Alternative, the controller can be tuned using a single parameter. The design is computationally efficient. The controller is updated on-line without recalculating the controller gain matrix, which involves a matrix inversion. The new controller is compared to a PI controller and to an adaptive linear predictive controller through simulations of a continuous stirred-tank reactor. The effects of modeling errors on the new controller are also shown with simulations
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