Vibration structure minimum norm control method based on dynamic compensator

Through dynamic compensator and QR decomposition optimization of control gain matrix, the problem of excessive energy consumption of vibration system control is solved, and optimal energy consumption control and performance improvement is achieved. It is suitable for vibration optimization of bridges, power systems and aviation aircraft.

CN120447374APending Publication Date: 2025-08-08ZHENGZHOU UNIVERSITY OF LIGHT INDUSTRY
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Patent Information

Application Number
CN202510561659.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-30
Publication Date
2025-08-08

AI Technical Summary

Technical Problem

When optimizing the controller design, existing vibration system control methods often ignore the problem of controlling energy consumption, resulting in excessive energy consumption when achieving system performance improvement, making it difficult to achieve optimal energy consumption control.

Method used

The vibration structure minimum norm control method of dynamic compensator is adopted, and the vibration structure model is established through finite element analysis, the dynamic compensator is designed, and the control gain matrix is optimized to reduce control energy consumption by using QR decomposition and gradient optimization methods.

Benefits of technology

It realizes that while improving the dynamic performance of the vibration system, it significantly reduces control energy consumption, provides sufficient parameterization freedom, and improves computing efficiency. It is suitable for bridge vibration design, low-frequency oscillation optimization of power system and vibration suppression of aviation aircraft.

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Abstract

The invention provides a vibration structure minimum norm control method based on a dynamic compensator, and the method comprises the steps: building a vibration structure model through a finite element analysis method, and designing the dynamic compensator; processing the unchanged feature structure matrix by adopting QR decomposition, and calculating a block matrix; performing QR decomposition on the correlation matrix of the closed-loop system, and calculating an actual representation matrix of an expected characteristic value and a matrix formed by an expected characteristic structure and compensator gain; a parameterized vector is selected, and parameterized dynamic compensator gain is calculated; if the cost function exceeds a set threshold value, the optimization function is optimized through a gradient optimization method according to any given initialization parameter vector, and a dynamic compensation gain matrix and a control gain matrix of the dynamic compensator are calculated through the optimal parameterization vector. According to the method, the calculation effectiveness is improved, the calculation complexity is reduced, meanwhile, the degree of freedom of the parameterized vector is not changed, and the sufficient optimization degree of freedom is ensured.
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