Neuro-fuzzy control strategy for an offshore steel jacket platform subjected to wave-induced forces using magnetorheological dampers |
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Authors: | Sarrafan Atabak Zareh Seiyed Hamid Khayyat Amir Ali Akbar Zabihollah Abolghassem |
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Affiliation: | 1.School of Science and Engineering, Sharif University of Technology, Tehran, Iran ; |
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Abstract: | Magnetorheological (MR) damper is a prominent semi-active control device to vibrate mitigation of structures. Due to the inherent
non-linear nature of MR damper, an intelligent non-linear neuro-fuzzy control strategy is designed to control wave-induced
vibration of an offshore steel jacket platform equipped with MR dampers. In the proposed control system, a dynamic-feedback
neural network is adapted to model non-linear dynamic system, and the fuzzy logic controller is used to determine the control
forces of MR dampers. By use of two feedforward neural networks required voltages and actual MR damper forces are obtained,
in which the first neural network and the second one acts as the inverse dynamics model, and the forward dynamics model of
the MR dampers, respectively. The most important characteristic of the proposed intelligent control strategy is its inherent
robustness and its ability to handle the non-linear behavior of the system. Besides, no mathematical model needed to calculate
forces produced by MR dampers. According to linearized Morison equation, wave-induced forces are determined. The performance
of the proposed neuro-fuzzy control system is compared with that of a traditional semi-active control strategy, i.e., clipped
optimal control system with LQG-target controller, through computer simulations, while the uncontrolled system response is
used as the baseline. It is demonstrated that the design of proposed control system framework is more effective than that
of the clipped optimal control scheme with LQG-target controller to reduce the vibration of offshore structure. Furthermore,
the control strategy is very important for semi-active control. |
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