Model-free control
Michel Fliess,Cédric Join +1 more
TLDR
Model-free control and the corresponding ‘intelligent’ PID controllers (iPIDs), which already had many successful concrete applications, are presented here for the first time in an unified manner, where the new advances are taken into account.Abstract:
''Model-free control'' and the corresponding ''intelligent'' PID controllers (iPIDs), which already had many successful concrete applications, are presented here for the first time in an unified manner, where the new advances are taken into account. The basics of model-free control is now employing some old functional analysis and some elementary differential algebra. The estimation techniques become quite straightforward via a recent online parameter identification approach. The importance of iPIs and especially of iPs is deduced from the presence of friction. The strange industrial ubiquity of classic PID's and the great difficulty for tuning them in complex situations is deduced, via an elementary sampling, from their connections with iPIDs. Several numerical simulations are presented which include some infinite-dimensional systems. They demonstrate not only the power of our intelligent controllers but also the great simplicity for tuning them.read more
Citations
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Journal ArticleDOI
On the centrality of disturbance rejection in automatic control
TL;DR: A novel, unifying concept of disturbance rejector is proposed to compliment the traditional notion of controller, leading to a Copernican moment where the model-centric design philosophy is replaced by the one that is control-centric in the following sense.
Journal ArticleDOI
Control: A perspective
Karl Johan Åström,P. R. Kumar +1 more
TL;DR: A perspective on feedback control's growth is presented, and the interplay of industry, applications, technology, theory and research is discussed.
Posted Content
Formulas for Data-driven Control: Stabilization, Optimality and Robustness
Claudio De Persis,Pietro Tesi +1 more
TL;DR: A parametrization of linear feedback systems is derived that paves the way to solve important control problems using data-dependent linear matrix inequalities only and is remarkable in that no explicit system's matrices identification is required.
Proceedings ArticleDOI
The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?
TL;DR: This paper studies the kinematic bicycle model, which is often used for trajectory planning, and compares its results to a 9 degrees of freedom model, and proposes a simple and efficient consistency criterion to validate the use of this model for planning purposes.
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