Active response control of an offshore structure under wave loads using a modified probabilistic neural network

Chang, Seongkyu; Kim, Dookie; Chang, Ching‐Yao; Cho, Sung Gook

doi:10.1007/s00773-008-0040-3

Cited by 18 publications

(7 citation statements)

References 18 publications

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“…Hence, the study of stability problem comes down to the stability of the periodic solution. 28–30 To determine the solution stability, a perturbation is given to the system as …”

Section: Stability Analysis Of the Motion And Its Optimal Controlmentioning

confidence: 99%

“…The response of an off-shore structure under random ocean waves has been controlled using a modified probabilistic neural network. 29 The research mentioned above is concerned with the selection of feedback gain, which can enhance the control performance of nonlinear systems or change the position of the bifurcation point. However, all these papers failed to discuss how to choose control parameters for TDOF vibration system.…”

Section: Introductionmentioning

confidence: 99%

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Feedback control for two-degree-of-freedom vibration system with fractional-order derivative damping

Liu

Zhou

et al. 2017

Journal of Low Frequency Noise, Vibration and Active Control

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A two-degree-of-freedom nonlinear vibration system of a quarter vehicle suspension system is studied by using the feedback control method considered the fractional-order derivative damping. The nonlinear dynamic model of two-degree-of-freedom vehicle suspension system is built and linear velocity and displacement controllers are used to control the nonlinear vibration of the vehicle suspension system. A case of the 1:1 internal resonance is considered. The amplitude–frequency response is obtained with the multiscale method. The asymptotic stability conditions of the nonlinear system can be gotten by using the Routh–Hurwitz criterion and the ranges of control parameters are gained in the condition of stable solutions to the system. The simulation results show that the feedback control can effectively reduce the amplitude of primary resonance, weaken or even eliminate the nonlinear vibration characteristics of the suspension system. Fractional orders have an impact on control performance, which should be considered in the control problem. The study will provide a theoretical basis and reference for the optimal design of the vehicle suspension system.

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“…Hence, the study of stability problem comes down to the stability of the periodic solution. 28–30 To determine the solution stability, a perturbation is given to the system as …”

Section: Stability Analysis Of the Motion And Its Optimal Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Feedback control for two-degree-of-freedom vibration system with fractional-order derivative damping

Liu

Zhou

et al. 2017

Journal of Low Frequency Noise, Vibration and Active Control

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show abstract

“…Yue et al [27] used TMD in order to mitigate iceinduced jacket platform vibration in Bohai Sea and find this supplemental device favorably effective. The control forces derived from a LQG algorithm were employed to generate the training patterns for the modified probabilistic neural network (MPNN) in order to control the responses of offshore structures under random ocean waves by chang et al [28]. Tabeshpour et al [29,30] investigated the performance of TMD so as to suppress the dynamic responses of jacket and tension leg platforms.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Semi-Active Tunes Mass Damper Application in Suppressing Seismic-Induced Vibration of an Existing Jacket Platform

Babaei

Amirabadi

Taghikhany

2016

ijmt

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In this study, mass, stiffness and damping matrices of the Nosrat jacket; located in Persian Gulf; equipped with Semi Active Tuned Mass Damper (SATMD) system have been derived after modeling the structure in SACS software. Owing to huge number of the degrees of freedom in the model, computation of on-line control of SATMD was time consuming. For this purpose, the size of the model was reduced in the finite time and frequency intervals by programming in MATLAB software. The SATMD utilized in this study, contains a passive Tuned Mass Damper (TMD) and two Magneto Rheological (MR) dampers in order to illustrate the control effect of SATMD. The selected algorithm to control and optimize the performance of MR damper is Linear Quadratic Gaussian (LQG). Time history responses of the platform in cases with and without SATMD have been compared under three different ground motions. Results indicate that jacket equipped with SATMD can dramatically reduce the seismic-induced dynamic responses.

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“…The ANN is a type of artificial intelligence application that has been implemented by engineers to carry out specialized design tasks so far. ANNs have been widely used for the prediction of various structural quantities [12][13][14][15][16][17] structural damage diagnosis and detections [18,19], evaluation of RC buildings performance [20], active response control of offshore structures [21,22] and static model identification of an FRP deck [23] etc. ANNs thus have been a powerful tool in solution of various structural engineering problems.…”

Section: Introductionmentioning

confidence: 99%

An Ann Approaches on Estimating Earthquake Performances of Existing Rc Buildings

Arslan¹,

Ceylan²,

Koyuncu³

2012

NNW

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Genetic algorithms (GAs) are stochastic methods that are widely used in search and optimization. The breeding process is the main driving mechanism for GAs that leads the way to find the global optimum. And the initial phase of the breeding process starts with parent selection. The selection utilized in a GA is effective on the convergence speed of the algorithm. A GA can use different selection mechanisms for choosing parents from the population and in many applications the process generally depends on the fitness values of the individuals. Artificial neural networks (ANNs) are used to decide the appropriate parents by the new hybrid algorithm proposed in this study. And the use of neural networks aims to produce better offspring during the GA search. The neural network utilized in this algorithm tries to learn the structural patterns and correlations that enable two parents to produce high-fit offspring. In the breeding process, the first parent is selected based on the fitness value as usual. Then it is the neural network that decides the appropriate mate for the first parent chosen. Hence, the selection mechanism is not solely dependent on the fitness values in this study. The algorithm is tested with seven benchmark functions. It is observed from results of these tests that the new selection method leads genetic algorithm to converge faster.

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Active response control of an offshore structure under wave loads using a modified probabilistic neural network

Cited by 18 publications

References 18 publications

Feedback control for two-degree-of-freedom vibration system with fractional-order derivative damping

Feedback control for two-degree-of-freedom vibration system with fractional-order derivative damping

Assessment of Semi-Active Tunes Mass Damper Application in Suppressing Seismic-Induced Vibration of an Existing Jacket Platform

An Ann Approaches on Estimating Earthquake Performances of Existing Rc Buildings

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