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The need to deal with rapid change in an environmentally and economically friendly manner has led to renewed interest in data-driven, online process optimization. Although various methods, such as economic model predictive control (EMPC), are available to achieve this goal, they require that the process model be available and relatively accurate and that there be no process changes. Recently, the...
In this contribution a novel extension to model predictive control for a certain class of input affine nonlinear systems is proposed, which satisfy the property of differential flatness and are of minimum phase. By feedforward linearization of the nonlinear system via a flatness based control law, the problem of nonlinear model predictive control is reduced to the well known linear model predictive...
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