Semi-active vibration control of building structure by Self Tuned Brain Emotional Learning Based Intelligent Controller

Saeed, Muhammad Usman; Sun, Zhanquan; Elias, Said

doi:10.1016/j.jobe.2021.103664

Cited by 16 publications

(8 citation statements)

References 60 publications

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“…Minimal calculation intricacy, the online learning ability, and no requirement for previous understanding of system dynamics make BEL a specific method in compatison to other intelligent methods. Also, it doesn't necessitate an additional iterative process for training [27]. The BEL is growingly being used in control engineering [28], electrical motors [29], and AC microgrids [30].…”

Section: B Literature Reviewmentioning

confidence: 99%

Intelligent Power Control of Inverter Air Conditioners in Power Systems: A Brain Emotional Learning-Based Approach

Oshnoei

Sadeghian

Anvari‐Moghaddam

2023

IEEE Trans. Power Syst.

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Inverter air-conditioning (IAC) units have been proved to be effective in frequency regulation by providing flexible capacities. This paper proposes a brain emotional learning (BEL)-based controller to provide the IACs with control signals to be efficiently involved in the frequency regulation in power systems. The BEL-based controller can learn quickauto, making it appropriate in systems facing uncertainty. To assess the BEL controller performance in realistic conditions, the uncertainties as a consequence of variations in system parameters and load level are considered. The goal is to use the BEL controller to increase the IAC units' ability to track regulation signals accurately in uncertain circumstances. The controller is compared to a fuzzy-PI control, a proportional control scheme, a model predictive control and a linear quadratic regulator control. A delay-dependent stability criterion is used to calculate the highest time delay in the IACs response under which the system maintains stability. In addition, this paper presents an BEL-based coordinator to coordinate the IACs and traditional generation units for compensating considerable frequency variations caused by the time delays. Case studies are accomplished on a multi-area power system in MATLAB/Simulink environment. Eventually, real-time verifications by OPAL-RT real-time digital simulator on the simulated power system are executed to assess the control method.

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Section: B Literature Reviewmentioning

confidence: 99%

Intelligent Power Control of Inverter Air Conditioners in Power Systems: A Brain Emotional Learning-Based Approach

Oshnoei

Sadeghian

Anvari‐Moghaddam

2023

IEEE Trans. Power Syst.

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“…In which β and γ are Newmark's factors, and if the average acceleration method is used, they are taken as 1/4 and 1/2, respectively; and Δτ is the time step between two-time instances τ and τ þ Δτ. Substituting Equation (10) and (11) into Equation (1), the following equation can be derived:…”

Section: Mathematical Modelling Of Non-linear Benchmark Buildingmentioning

confidence: 99%

“…Hormozabad and Soto 10 used artificial intelligence (AI) to optimize the MR damper parameters for seismic response control of structures. Saeed et al 11 recently, proposed smart semi-active controllers using Brain Emotional Learning Based Intelligent Controller (BELBIC). It was found that the proposed self-tuned BELBIC (ST-BELBIC) effectively diminish the seismic responses of smart civil structure.…”

Section: Introductionmentioning

confidence: 99%

Seismic response control of building structures under pulse-type ground motions by active vibration controller

Elias

Djerouni

Domenico

et al. 2022

Journal of Low Frequency Noise, Vibration and Active Control

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Active vibration control systems are commonly reported to be the most robust and effective method for vibration control of structures. However, the type of ground motions and the type of analysis may greatly influence their performances. This study investigates the seismic response of building with and without an active controller under pulse-type ground motions. A 20-story non-linear steel benchmark building is considered. Linear and non-linear analysis is conducted to check the effectiveness of the active control system. Active control with a linear quadratic Gaussian (LQG) control algorithm is applied to the benchmark building for seismic control purposes. Initially, some ground motions are selected following earlier studies from the literature concerning the benchmark building. It is found that the LQG control algorithm is quite effective under the considered earthquakes, and the analysis type does not affect the effectiveness of the controller. Thereafter, a set of additional 69 pulse-type ground motions are considered to check the performance of the LQG control algorithm and to find the suitability of linear analysis. It is noticed that under such pulse-type ground motion, the LQG control algorithm is not much effective if the non-linear behavior of the structure is incorporated in the seismic analysis, whereas in case of linear analysis, the LQG control algorithm is still effective. It is concluded that neglecting the non-linear behavior may lead to unconservative estimates of the seismic response when performing seismic analysis and designing structures equipped with active vibration control systems.

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“…Efforts have been made to enhance the vibration control effect of ECD, such as optimal design, 10 coupling with another solid energy dissipation mechanism, 13 and adopting electro-magnetic technique and hybrid control strategy. 14,15 Utilizing the motion magnification mechanisms, like ball screw 16 or rack and gear, 17 to increase input velocity of ECD is another available method to improve eddy current damping effect. But installing these motion magnification mechanisms will change the nonlinearity of the relationship between eddy current damping force and velocity.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stochastic seismic analysis of structures with nonlinear eddy current dampers

Huo

Khalique

2022

Journal of Low Frequency Noise, Vibration and Active Control

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Eddy current damper (ECD), a contactless energy-dissipating device, is applying to control the vibration induced by earthquake and strong wind in civil structures. Combining with motion magnification mechanisms improves the damping effect of the ECD while significantly strengthens its nonlinearity. The response of single degree of freedom and multi-degree of freedom system with ECDs under a stationary stochastic earthquake characterized by the power spectral density function is evaluated using the stochastic linearization technique and expressions of the equivalent linear damping coefficient based on force criterion and energy criterion have been found, respectively. Comparisons with results obtained by Monte Carlo simulations confirm that for the nonlinearity of eddy current dampers the force-based criterion stochastic linearization technique gives accurate estimation.

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Semi-active vibration control of building structure by Self Tuned Brain Emotional Learning Based Intelligent Controller

Cited by 16 publications

References 60 publications

Intelligent Power Control of Inverter Air Conditioners in Power Systems: A Brain Emotional Learning-Based Approach

Intelligent Power Control of Inverter Air Conditioners in Power Systems: A Brain Emotional Learning-Based Approach

Seismic response control of building structures under pulse-type ground motions by active vibration controller

Stochastic seismic analysis of structures with nonlinear eddy current dampers

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