کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4965704 | 1448458 | 2017 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A novel fast model predictive control with actuator saturation for large-scale structures
ترجمه فارسی عنوان
کنترل پیشگویی مدل جدید سریع با اشباع محرک برای ساختارهای بزرگ مقیاس
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کلمات کلیدی
سازه های بزرگ، اشباع رسانا، کنترل سریع پیش بینی مدل، فرم بیان صریح، برنامه نویسی درجه یک، خطی تکمیلی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
One of the most critical issues faced in the application of active control to engineering structures is actuator saturation. In this paper, a novel fast model predictive control with actuator saturation for large-scale structures is proposed. First, based on the second-order dynamic equation, the explicit expression form of the Newmark-β method is derived. Then, according to the parametric variational principle, the explicit structure of the model predictive control (MPC) saturation controller is obtained. A linear complementary problem for the proposed fast MPC saturation controller is developed, replacing the quadratic programming problem for the original MPC saturation controller. The optimal control input can be achieved by solving one linear complementarity problem and one transient analysis problem. Particularly, the physical meaning of the explicit expression form of the Newmark-β method is discovered and applied for increasing computational efficiency and saving memory. Finally, numerical simulations of a plane adjacent frame building subjected to earthquake ground motion demonstrate that the proposed fast MPC saturation controller is highly efficient and can be applied under a large step-length, especially for large-scale structural dynamic control problems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Structures - Volume 187, 15 July 2017, Pages 35-49
Journal: Computers & Structures - Volume 187, 15 July 2017, Pages 35-49
نویسندگان
Haijun Peng, Fei Li, Sheng Zhang, Biaosong Chen,