Structural Vibration Suppression by a Neural-Network Controller with a                 Mass-Damper Actuator

Yang, Shih-Ming; Chen, Chuen-Jyh; Huang, W. L.

doi:10.1177/1077546306064269

Cited by 31 publications

(23 citation statements)

References 13 publications

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“…For (21) and (24), is calculated as (25) to minimize the performance index . Here, is a unique positive-definite symmetric solution of the algebraic Riccati equation (26).…”

Section: B Sliding Surface Designmentioning

confidence: 99%

Novel Sliding Mode Vibration Controller With Simple Model-Free Design and Compensation for Actuator’s Uncertainty

2021

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“…For (21) and (24), is calculated as (25) to minimize the performance index . Here, is a unique positive-definite symmetric solution of the algebraic Riccati equation (26).…”

Section: B Sliding Surface Designmentioning

confidence: 99%

Novel Sliding Mode Vibration Controller With Simple Model-Free Design and Compensation for Actuator’s Uncertainty

2021

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“…The neural sensor is again shown faithfully simulating the displacement and velocity. In addition to the smart structure, a one-story shearbuilding structure model of 300 × 210 × 205 mm and weights 5.4 kg with an active mass damper (AMD) mounted on the top floor as shown in Figure 4(a) [17] is also applied to validate the neural sensor effectiveness. The structure mass is concentrated at the floor level, and the columns flexible to lateral deformation but rigid in vertical direction are assumed to be mass less.…”

Section: Learning Algorithmmentioning

confidence: 99%

Simulating Displacement and Velocity Signals by Piezoelectric Sensor in Vibration Control Applications

Sheu

Yang

Huang

2012

Smart Materials Research

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Intelligent structures with built-in piezoelectric sensor and actuator that can actively change their physical geometry and/or properties have been known preferable in vibration control. However, it is often arguable to determine if measurement of piezoelectric sensor is strain rate, displacement, or velocity signal. This paper presents a neural sensor design to simulate the sensor dynamics. An artificial neural network with error backpropagation algorithm is developed such that the embedded and attached piezoelectric sensor can faithfully measure the displacement and velocity without any signal conditioning circuitry. Experimental verification shows that the neural sensor is effective to vibration suppression of a smart structure by embedded sensor/actuator and a building structure by surface-attached piezoelectric sensor and active mass damper.

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“…However, there have been many criticisms on LQR controllers. It was stated by Yang et al [13] that LQR controllers are known to be ineffective for systems suffering from variation of parameters and excitations which are broadband. In addition, it has been mentioned by Aldemir and Bakioglu [14] that only classical closed-loop control is applicable to structural control problems, and the Riccati equation is derived by not considering the seismic excitation term.…”

Section: Introductionmentioning

confidence: 99%

Absolute Instantaneous Optimal Control Performance Index for Active Vibration Control of Structures under Seismic Excitation

Yanik

2019

Shock and Vibration

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In this paper, an instantaneous optimal control performance index for active control of structures under seismic excitation is analytically proposed. Absolute velocity and absolute displacement terms are implemented to the conventional state vector terms and eventually to the resulting performance index expression. The seismic response reduction effectiveness of the proposed performance index is compared with the linear quadratic regulator control (LQR). For numerical verification of the performance index, an eight-story shear building with a fully active tendon controller system under unidirectional earthquake is considered as the first example. For a more complex model, a three-dimensional tier building under the effect of bidirectional earthquakes is selected as second numerical example. Unidirectional near fault and bidirectional near fault earthquakes are used in the simulations. The control energy demand of each control method is also considered in the comparison. It is obtained from numerical simulations that the proposed performance index is as effective as LQR in attenuating structural vibrations. However, the resulting performance index does not require a priori knowledge of the seismic excitation like the LQR. The nonlinear Riccati matrix equation solution of the LQR is not required in the proposed performance index as well.

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Structural Vibration Suppression by a Neural-Network Controller with a Mass-Damper Actuator

Cited by 31 publications

References 13 publications

Novel Sliding Mode Vibration Controller With Simple Model-Free Design and Compensation for Actuator’s Uncertainty

Novel Sliding Mode Vibration Controller With Simple Model-Free Design and Compensation for Actuator’s Uncertainty

Simulating Displacement and Velocity Signals by Piezoelectric Sensor in Vibration Control Applications

Absolute Instantaneous Optimal Control Performance Index for Active Vibration Control of Structures under Seismic Excitation

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