Real-Time Implementation of Input-State Linearization and Model Predictive Control for Robust Voltage Regulation of a DC-DC Boost Converter

Abstract

The use of DC-DC step-up converters has significantly increased due to their implementation as power interfaces in microgrids (MGs), smart grids (SGs) and electrical vehicles. Step-up converters adapt the source voltage or current to the load specifications through an appropriate control algorithm, which is linear in most cases. However, linear algorithms mostly guarantee the system's stability and desired performances only around a relatively small neighborhood of the equilibrium point. Model predictive controllers (MPCs) have been proposed to improve the performance of the converter and broaden its operating region. However, MPCs have mostly been based on an approximated linear model of the converter, which contributes to a relatively narrow operating region. This work proposes an MPC algorithm based on an exactly linearized converter model. The converter model is linearized according to an exact input-state linearization control (ILC). To the best of our knowledge, this is the first work to present a real-time implementation of the ILC in the context of nonlinear DC-DC boost converter control. The objective of exact linearization is to continue using the same reduced-complexity linear MPC while extending the operation area of the system compared to classic linear control. Simulations and experimental results show that the static and dynamic performances of the proposed control are significantly better than those of the standard linear control.

Keywords

• Real-time implementation
• model predictive control (MPC)
• nonlinear control (NLC)
• input-state linearization control (ILC)