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Design and Cascade PI Controller-Based Robust Model Reference Adaptive Control of DC-DC Boost Converter

Cagfer Yanarates, Zhongfu Zhou Orcid Logo

IEEE Access, Volume: 10, Pages: 44909 - 44922

Swansea University Authors: Cagfer Yanarates, Zhongfu Zhou Orcid Logo

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Abstract

In this paper, Cascade PI Controller-Based Robust Model Reference Adaptive Control (MRAC)of a DC-DC boost converter is presented. Non-minimum phase behaviour of the boost converter due to right half plane zero constitutes a challenge and its non-linear dynamics complicate the control process while o...

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Published in: IEEE Access
ISSN: 2169-3536
Published: Institute of Electrical and Electronics Engineers (IEEE) 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa59922
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Abstract: In this paper, Cascade PI Controller-Based Robust Model Reference Adaptive Control (MRAC)of a DC-DC boost converter is presented. Non-minimum phase behaviour of the boost converter due to right half plane zero constitutes a challenge and its non-linear dynamics complicate the control process while operating in continuous conduction mode (CCM). The proposed control scheme efficiently resolved complications and challenges by using features of cascade PI control loop in combination with properties of MRAC. The accuracy of the proposed control system’s ability to track the desired signals and regulate the plant process variables in the most beneficial and optimised way without delay and overshoot is verified using MATLAB/Simulink by applying comparative analysis with single PI and cascade PI controllers. Moreover, performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-time-interface (RTI) 1007 processor, DS2004 HighSpeed A/D and CP4002 Timing and Digital I/O boards. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed two times with considerably improved disturbance rejection.
Keywords: Cascade PI controller, control systems mathematical models, model reference adaptivecontrol, state-space averaging method, time and frequency domain analysis
College: College of Engineering
Funders: This work was supported in part by the European Regional Development Fund (ERDF) through the FLEXIS Project
Start Page: 44909
End Page: 44922