Robust Inverse Optimal Control for a Boost Converter

Mario Villegas-Ruvalcaba, Kelly Joel Gurubel-Tun and Alberto Coronado-Mendoza
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Mario Villegas-Ruvalcaba: Basic and Applied Sciences Department, University of Guadalajara, Guadalajara 45425, Mexico
Kelly Joel Gurubel-Tun: Studies on Water and Energy Department, University of Guadalajara, Guadalajara 45425, Mexico
Alberto Coronado-Mendoza: Studies on Water and Energy Department, University of Guadalajara, Guadalajara 45425, Mexico

Energies, 2021, vol. 14, issue 9, 1-17

Abstract: The variability of renewable energies and their integration into the grid via power electronics demands the design of robust control algorithms. This work incorporates two techniques to ensure the stability of a boost converter through its state equations, implementing the inverse optimal control and the gain-scheduling technique for robust control settings. In such a way that, under a single adjustment, it is capable of damping different changes such as changes in the parameters, changes in the load, the input voltage, and the reference voltage. On the other hand, inverse optimal control is based on a discrete-time control Lyapunov function (CLF), and CLF candidate depends on fixed parameters that are selected to obtain the solution for inverse optimal control. Once these parameters have been found through heuristic or artificial intelligence methods, the new proposed methodology is capable of obtaining a robust optimal control scheme, without having to search for new parameters through other methods, since these are sometimes sensitive changes and many times the process of a new search is delayed. The results of the approach are simulated using Matlab, obtaining good performance of the proposed control under different operation conditions. Such simulations yielded errors of less than 1% based on the voltage reference, given the disturbances caused by changes in the input variables, system parameters, and changes in the reference. Thus, applying the new methodology, the stability of our system was preserved in all cases.

Keywords: boost converter; inverse optimal control; stability analysis; gain-scheduling; renewable energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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