What is it about?
Despite advances in multi-model adaptive control theory, the question of how the synthesis of the pairs model/controller will affect transient and steady-state performance is not completely addressed.
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Why is it important?
In this work we show how the minimization of a suitable structural criterion can lead to improved performance of the multi-model adaptive scheme. The peculiarity of the resulting structural optimality criterion is that the optimization is carried out so as to optimize the entire behavior of the adaptive algorithm, i.e. both the learning transient and the steady-state response.
Perspectives
While in many alternative multi-model adaptive control schemes structural optimization methods have been developed only assuming steady-state ideal response (i.e. assuming convergence to the correct controller), here we do NOT neglect learning transients. This is of fundamental importance in adaptive control, since it is well know that even classical continuous adaptation schemes cannot guarantee convergence to the correct parameters.
Dr. Simone Baldi
Southeast University
Read the Original
This page is a summary of: Optimal model distributions in supervisory adaptive control , IET Control Theory and Applications, June 2017, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-cta.2016.0679.
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