MACHINE LEARNING BASED ACTIVE CONTROL SYSTEM OF STRUCTURE EXPERIENCING DYNAMIC LOADS
The design of structures capable to resist dynamic load is becoming one of the challenges in civil engineering. Implementing active control system is an innovative solution to the problem. Active control strategy can be in form of an active mass damper (AMD) which uses actuator to control its moveme...
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| Institution: | Institut Teknologi Bandung |
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id-itb.:668212022-07-22T13:31:41ZMACHINE LEARNING BASED ACTIVE CONTROL SYSTEM OF STRUCTURE EXPERIENCING DYNAMIC LOADS Felix Sinjaya, Michael Indonesia Final Project active control system, active mass damper, machine learning, artificial neural network, LQR INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/66821 The design of structures capable to resist dynamic load is becoming one of the challenges in civil engineering. Implementing active control system is an innovative solution to the problem. Active control strategy can be in form of an active mass damper (AMD) which uses actuator to control its movement. This paper presented an analysis of a 3-storey experiment model. This structure is modelled numerically using finite element method and then, loaded it with some known earthquake excitations. Structure response is calculated using numerical method for a given load. The modelling is improved by implementing machine learning called artificial neural networks to active control systems using controlled responses of the structure with classical control algorithm (LQR) from random ground excitation as its training data. The result of structural response with and without control is analysed and compared. This paper will be a foundation to experimental research for writer’s master degree thesis. text |
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The design of structures capable to resist dynamic load is becoming one of the challenges in civil engineering. Implementing active control system is an innovative solution to the problem. Active control strategy can be in form of an active mass damper (AMD) which uses actuator to control its movement. This paper presented an analysis of a 3-storey experiment model. This structure is modelled numerically using finite element method and then, loaded it with some known earthquake excitations. Structure response is calculated using numerical method for a given load. The modelling is improved by implementing machine learning called artificial neural networks to active control systems using controlled responses of the structure with classical control algorithm (LQR) from random ground excitation as its training data. The result of structural response with and without control is analysed and compared. This paper will be a foundation to experimental research for writer’s master degree thesis.
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| format |
Final Project |
| author |
Felix Sinjaya, Michael |
| spellingShingle |
Felix Sinjaya, Michael MACHINE LEARNING BASED ACTIVE CONTROL SYSTEM OF STRUCTURE EXPERIENCING DYNAMIC LOADS |
| author_facet |
Felix Sinjaya, Michael |
| author_sort |
Felix Sinjaya, Michael |
| title |
MACHINE LEARNING BASED ACTIVE CONTROL SYSTEM OF STRUCTURE EXPERIENCING DYNAMIC LOADS |
| title_short |
MACHINE LEARNING BASED ACTIVE CONTROL SYSTEM OF STRUCTURE EXPERIENCING DYNAMIC LOADS |
| title_full |
MACHINE LEARNING BASED ACTIVE CONTROL SYSTEM OF STRUCTURE EXPERIENCING DYNAMIC LOADS |
| title_fullStr |
MACHINE LEARNING BASED ACTIVE CONTROL SYSTEM OF STRUCTURE EXPERIENCING DYNAMIC LOADS |
| title_full_unstemmed |
MACHINE LEARNING BASED ACTIVE CONTROL SYSTEM OF STRUCTURE EXPERIENCING DYNAMIC LOADS |
| title_sort |
machine learning based active control system of structure experiencing dynamic loads |
| url |
https://digilib.itb.ac.id/gdl/view/66821 |
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