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Design and Cascade PI Controller-Based Robust Model Reference Adaptive Control of DC-DC Boost Converter
IEEE Access, Volume: 10, Pages: 44909 - 44922
Swansea University Authors: Cagfer Yanarates, Zhongfu Zhou
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DOI (Published version): 10.1109/access.2022.3169591
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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Institute of Electrical and Electronics Engineers (IEEE)
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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.
Cascade PI controller, control systems mathematical models, model reference adaptivecontrol, state-space averaging method, time and frequency domain analysis
Faculty of Science and Engineering
This work was supported in part by the European Regional Development Fund (ERDF) through the FLEXIS Project