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<p>The work provides a non-fragile proportional-integral (PI) tracking control technique in order to efficiently operate the dual active bridge (DAB) converter considering external uncertainties. The primary goal is to ensure that the plant output accurately tracks the reference signal despite uncertain conditions and gain variations. For theoretical foundation, the Lyapunov-Krasovskii approach is used in combination with the average dwell time (ADT) method to establish conditions for the stability of the system and the design of the proposed PI, modified equivalent input disturbance (MEID), and Astrom modified Smith predictor (ASP)-based control technique. Adequate conditions for ensuring exponential stability of the system are derived in the form of linear matrix inequalities (LMIs). The proposed control strategies are validated using a 10 kW DAB model, specifically designed for electric vehicle (EV) applications. The results demonstrate that the proposed control technique offers accurate tracking performance and effectively estimates external uncertainties.</p>

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Advanced modified Astrom-Smith predictor controller for disturbance attenuation in electric vehicle application

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月3日

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  • T. Deepti,
  • K. Deepa,
  • S. Mohanapriya,
  • E. A. Gopalakrishnan,
  • Deepa Gupta,
  • Joyti Mudi,
  • Somnath Ganguly,
  • Joon-Ho Choi

摘要

The work provides a non-fragile proportional-integral (PI) tracking control technique in order to efficiently operate the dual active bridge (DAB) converter considering external uncertainties. The primary goal is to ensure that the plant output accurately tracks the reference signal despite uncertain conditions and gain variations. For theoretical foundation, the Lyapunov-Krasovskii approach is used in combination with the average dwell time (ADT) method to establish conditions for the stability of the system and the design of the proposed PI, modified equivalent input disturbance (MEID), and Astrom modified Smith predictor (ASP)-based control technique. Adequate conditions for ensuring exponential stability of the system are derived in the form of linear matrix inequalities (LMIs). The proposed control strategies are validated using a 10 kW DAB model, specifically designed for electric vehicle (EV) applications. The results demonstrate that the proposed control technique offers accurate tracking performance and effectively estimates external uncertainties.