A differential flatness based model predictive control approach

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 control. This results in a considerable reduction in computational effort. Input constraints are considered via a nonlinear transformation and the cost functional can be minimized by usage of a standard quadratic programming algorithm. A simulation example is given to demonstrate the usefulness of this new strategy.

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