Control of nonlinear structures using the fuzzy control approach

Casciati, Fabio; Faravelli, Lucia; Yao, Timothy

doi:10.1007/bf00045000

Cited by 37 publications

(10 citation statements)

References 13 publications

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“…The input variables of fuzzy control are the displacement and velocity response of the isolation layer, respectively and the output variable is the active control force required for MR dampers. (Casciati et al 1996;Teng et al 2000;Harris 2006). The fuzzy control rules for TISO are listed in Table 1.…”

Section: Control Strategymentioning

confidence: 97%

Control of Seismic Response of a Building Frame by Using Hybrid System with Magnetorheological Dampers and Isolators

Chen

Sun

et al. 2014

Advances in Structural Engineering

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The traditional isolation approach can suppress the seismic responses of upper structure and at the same time induce substantial deformation of isolation layer. Excessive base drift may cause the degradation and even the damage of the isolation system. Therefore, supplemental control devices can be implemented in the common base isolation system to construct hybrid control system and reduce the base drifts of structures. The seismic mitigation of a building frame with hybrid control system is carried out in this study. The mechanical model of magnetorheological (MR) damper is presented by involving the effects of brace stiffness of the damper. The equation of motion of a frame structure with stiffness eccentricity incorporated with intelligent hybrid control system disturbed by seismic excitations is established by considering the effects of both isolators and MR dampers. A clipped-optimal strategy based on fuzzy control principle is proposed for MR dampers. A building frame is taken as the example to examine the feasibility and reliability of the proposed intelligent control approach. The efficacy of the hybrid control approach is compared with the base isolation approach. An extensive parametric study is carried out to find the optimal parameters of MR dampers, by which the maximum reduction of seismic responses may be achieved, and to assess the effects of earthquake intensity and brace stiffness on damper performance. The work on example buildings showed that the installation of the smart dampers with proper parameters and proper control strategy could significantly reduce seismic responses of structures, and the performance of the smart damper is better than that of the common base isolation system. The optimal parameters of the MR dampers could be identified through a parametric study.

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Section: Control Strategymentioning

confidence: 97%

Control of Seismic Response of a Building Frame by Using Hybrid System with Magnetorheological Dampers and Isolators

Chen

Sun

et al. 2014

Advances in Structural Engineering

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“…The concept of fuzzy set theory was presented for solving a general structural optimization problem involving multiple objectives [8]. Control of nonlinear structures using fuzzy control approach was considered in the active control of hysteretic structures subjected to environmental loads [9].…”

Section: Modelling and Controlmentioning

confidence: 99%

Substructural control of fuzzy nonlinear flexible structures

Sunar

Toker

2007

Journal of the Franklin Institute

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“…Bani-Hini K et.al [5] proposed neural network for nonlinear structure control in which the initial parameter of neural network is difficult to define. F.Casciati [6] studied the fuzzy control of nonlinear structure, but this controller is nonadaptive in nature and is designed based on fuzzy rules which are predefined and require a full understanding of the system dynamics. Wang [7] described an adaptive fuzzy control strategy which included an adaptation law for adjustment of controller's parameters.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Based Control and Simulation Analysis for Nonlinear Structure

Dai

2010

2010 Second International Conference on Computer Modeling and Simulation

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The response of structures deforms into their inelastic range during intense ground shaking and exhibits nonlinear behavior, and as a whole, there is no systematic and effective means for nonlinear structure control. In this paper, the active control is applied to the nonlinear structure through the adaptive fuzzy sliding mode control strategy to eliminate the damage of structure and then we introduce the design of a fuzzy sliding mode controller and an adaptation law. The simulation is made on a three-story steel frame model which is referred to as the third generation Benchmark model. The control force is applied each floor through control devices that use the adaptive fuzzy sliding mode control algorithm. Then we calculated the response of the structure under earthquake and analysis the results. The results are satisfied in that they show adaptive fuzzy sliding mode control can utilize the advantage of the adaptive fuzzy control and the sliding mode control very well when applied to the nonlinear structure under the earthquake excitation.

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Control of nonlinear structures using the fuzzy control approach

Cited by 37 publications

References 13 publications

Control of Seismic Response of a Building Frame by Using Hybrid System with Magnetorheological Dampers and Isolators

Control of Seismic Response of a Building Frame by Using Hybrid System with Magnetorheological Dampers and Isolators

Substructural control of fuzzy nonlinear flexible structures

Fuzzy Logic Based Control and Simulation Analysis for Nonlinear Structure

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