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Using the concept of weighting functions, asymmetric hardness dependency is also taken into account.
To achieve stability, weighting functions are designed in favor of variables on the upstream side.
Careful tuning of weighting functions are necessary for H∞ design method.
Three kinds of weighting functions, namely linear, cubic splines and Gaussian functions are compared.
Finally, the system's stability and performance were compromised by introducing weighting functions to the controller's design.
Weighting functions are first selected and tuned to achieve minimum tracking error and robust performance.
Firstly, the local models and weighting functions are estimated separately using optimization methods.
The problem is casted into the H∞ framework, using frequency weighting functions to specify design requirements.
The model is augmented with weighting functions specified by the performance demands and the uncertainty assumption.
The proposed model and weighting functions are then used to design robust controllers.
Figure 11c visualizes the values of the weighting functions Wn=1,2,3 in colors.
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