OPTIMIZING LQR TO CONTROL BUCK CONVERTER BY MESH ADAPTIVE SEARCH ALGORITHM

  • M. M. Kanai, Department of Electrical and Electronics Engineering, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
  • J. N. Nderu Department of Electrical and Electronics Engineering, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
  • P. K. Hinga Department of Electrical and Electronics Engineering, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Keywords: Linear quadratic regulator (LQR), mesh adaptive search (MADS), DC-DC converter, voltage control

Abstract

In this study, control method to control Buck converters by Linear Quadratic Regulator (LQR) controllers is
employed. Systems with conventional LQR controllers present good stability properties and are optimal with
respect to a certain performance index. However, LQR control does not assure robust stability when the system is
highly uncertain. In this paper, a convex model of converter dynamics is obtained taking into account uncertainty
of parameters. In order to apply the LQR control in the uncertain converter case, the performance index is
optimized by using Mesh Adaptive Search (MADS). As a consequence, a new robust control method for dc–dc
converters is derived. This LQR-MADS control is compared with normal LQR design. All the analysis and simulations
on the above converter is by MATLAB software. The simulation results show the improvement in voltage output
response.

Published
2019-05-14