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Structural Engineering and Mechanics Volume 85, Number 5, March10 2023 , pages 607-620 DOI: https://doi.org/10.12989/sem.2023.85.5.607 |
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Structural optimal control based on explicit time-domain method |
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Taicong Chen, Houzuo Guo and Cheng Su
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| Abstract | ||
| The classical optimal control (COC) method has been widely used for linear quadratic regulator (LQR) problems of structural control. However, the equation of motion of the structure is incorporated into the optimization model as the constraint condition for the LQR problem, which needs to be solved through the Riccati equation under certain assumptions. In this study, an explicit optimal control (EOC) method is proposed based on the explicit time-domain method (ETDM). By use of the explicit formulation of structural responses, the LQR problem with the constraint of equation of motion can be transformed into an unconstrained optimization problem, and therefore the control law can be derived directly without solving the Riccati equation. To further optimize the weighting parameters adopted in the control law using the gradient-based optimization algorithm, the sensitivities of structural responses and control forces with respect to the weighting parameters are derived analytically based on the explicit expressions of dynamic responses of the controlled structure. Two numerical examples are investigated to demonstrate the feasibility of the EOC method and the optimization scheme for weighting parameters involved in the control law. | ||
| Key Words | ||
| active control; explicit time-domain method; linear quadratic regulator; optimization; sensitivity analysis | ||
| Address | ||
| Taicong Chen: School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China; State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510640, China; Guangdong Artificial Intelligence and Digital Economy Laboratory, Guangzhou 510335, China Houzuo Guo: School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China; Department of Civil and Environmental Engineering, University of Macau, Macao 999078, China Cheng Su: School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China; State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510640, China; Guangdong Artificial Intelligence and Digital Economy Laboratory, Guangzhou 510335, China | ||