Quantitative robustness analysis of model following control for nonlinear systems subject to model uncertainties

We investigate a model following control (MFC) design for nonlinear minimumphase systems subject to model uncertainties. The model following control architecture is a two degrees-of-freedom structure consisting of two control loops. The model control loop (MCL) includes a nominal model of the process. The design of the process control loop (PCL) is based on the error system resulting from the nominal design and the actual process. Both control loops are designed using (partial) feedback linearisation. We analyse the robustness in view of the norm of the uncertainty and the region of attraction compared to a single-loop (partial) feedback linearisation control. It turns out that the proposed approach is able to stabilize significantly larger uncertainties, shows better tracking performance, and exhibits a larger region of attraction (based on a quadratic Lyapunov function).


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