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.
Highlights
Step-up DC-DC converters are attracting increasing interest in academia and industry, especially with their use in converting DC renewable power in microgrids (MGs) and smart grids (SGs) [1]–[4] and in electric vehicles
Linear algorithms are designed based on an approximated linear model of the converter derived around a specific equilibrium point
The main advantage of the Model predictive controllers (MPCs) is to anticipate the future value of the control signal to ensure an optimal reference tracking performance of the state variables
Summary
Step-up DC-DC converters are attracting increasing interest in academia and industry, especially with their use in converting DC renewable power in microgrids (MGs) and smart grids (SGs) [1]–[4] and in electric vehicles. Nonlinear control algorithms are based on a system nonlinear model, which is considered to more realistically describe the converter’s behavior and can improve the system robustness in the case of disturbances or parameter mismatches [11], [12] In this category, linearizing control (LC) [13] enables the transformation of a nonlinear state space affine model into its exact linear real-time equivalent using specific transformation functions. A nonlinear control that both improves the output voltage regulation and limits the inductor current inrush during start-ups is proposed. To achieve this objective, a linear-model-based MPC outer loop is cascaded with an exact input-state linearizing control inner loop. We combine the classic linear MPC and input-state controllers to improve the conventional MPC robustness to the changes in the source voltage or output load and to offer an improved closed-loop reference tracking ability. A conclusion is provided in the seventh section to summarize the key points of this work
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
