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A Novel Surrogate Model-Based Solving Framework for the Black-Box Dynamic Co-Design and Optimization Problem in the Dynamic System

Author

Listed:
  • Qi Zhang

    (National Center of Technology Innovation for Intelligent Design and Numerical Control, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yizhong Wu

    (National Center of Technology Innovation for Intelligent Design and Numerical Control, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Li Lu

    (National Center of Technology Innovation for Intelligent Design and Numerical Control, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

When encountering the black-box dynamic co-design and optimization (BDCDO) problem in the multidisciplinary dynamic system, the finite difference technique is inefficient or even infeasible to provide approximate numerical gradient information for the optimization algorithm since it requires numerous original expensive evaluations. Therefore, a solving framework based on the surrogate model of the state equation is introduced to optimize BDCDO. To efficiently construct the surrogate model, a sequential sampling method is presented on the basis of the successive relative improvement ratio. Meanwhile, a termination criterion is suggested to quantify the convergence of the solution. Ultimately, the newly proposed sampling strategy and termination criterion are incorporated into the BDCDO solving framework to optimize two numerical examples and two engineering examples. The results demonstrate that the framework integrating the proposed sampling strategy and termination criterion has the best performance in terms of the accuracy, efficiency, and computational budget compared to the existing methods.

Suggested Citation

  • Qi Zhang & Yizhong Wu & Li Lu, 2022. "A Novel Surrogate Model-Based Solving Framework for the Black-Box Dynamic Co-Design and Optimization Problem in the Dynamic System," Mathematics, MDPI, vol. 10(18), pages 1-26, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:18:p:3239-:d:908185
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    References listed on IDEAS

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    1. Reza Rahmani & Saleh Mobayen & Afef Fekih & Jong-Suk Ro, 2021. "Robust Passivity Cascade Technique-Based Control Using RBFN Approximators for the Stabilization of a Cart Inverted Pendulum," Mathematics, MDPI, vol. 9(11), pages 1-11, May.
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    Cited by:

    1. Lee, Yong Hoon & Bayat, Saeid & Allison, James T., 2025. "Wind turbine control co-design using dynamic system derivative function surrogate model (DFSM) based on OpenFAST linearization," Applied Energy, Elsevier, vol. 396(C).
    2. Pang, Yong & Hu, Zhengguo & Zhang, Shuai & Guo, Guanchen & Song, Xueguan & Kan, Ziyun, 2024. "Co-design of an unmanned cable shovel for structural and control integrated optimization: A highly heterogeneous constrained multi-objective optimization algorithm," Applied Energy, Elsevier, vol. 376(PB).

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