Control strategies and experimental verifications of the electromagnetic mass damper system for structural vibration control

Zhang, Chunwei; Ou, Jinping

doi:10.1007/s11803-008-0828-5

Cited by 15 publications

(4 citation statements)

References 19 publications

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“…The dynamic nature of mass-spring systems is useful for modeling real-world problems encountered in many industrial application areas [7]. The mass-spring system is a subject that has been studied in many literatures using classical control theories [8]. Classical control approaches aim to create a balancing control strategy using the mathematical model of the system.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence-based position control: reinforcement learning approach in spring mass damper systems

Demircioğlu,

Bakır

2024

Phys. Scr.

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This work examines the use of deep Reinforcement Learning (RL) in mass-spring system position control, providing a fresh viewpoint that goes beyond conventional control techniques. Mass-spring systems are widely used in many sectors and are basic models in control theory. The novel aspect of this approach is the thorough examination of the impact of several optimizer algorithms on the RL methodology, which reveals the optimal control tactics. The research applies a Deep Deterministic Policy Gradient (DDPG) algorithm for continuous action spaces, where the actor and critic networks are important components in assessing the agent's performance. The RL agent is trained to follow a reference trajectory using the Simulink environment for system modeling. The study provides insights into the agent's learning approach and performance optimization by evaluating the training process using force-time graphs, reward graphs, and Episode Manager charts. Furthermore, the effect of different combinations of optimizers on the control performance of the agent is examined. The outcomes highlight the importance of optimizer selection in the learning process by revealing significant variations in training times. As a result, a better understanding of the relationship between various optimizers and control performance is provided by this study's novel application of reinforcement learning in mass-spring system control. The results raise the possibility of more potent methods for controlling complex systems and add to the expanding field of study at the interface of control theory and deep learning.

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Section: Introductionmentioning

confidence: 99%

Artificial intelligence-based position control: reinforcement learning approach in spring mass damper systems

Demircioğlu,

Bakır

2024

Phys. Scr.

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“…The control algorithms used in the active control system were studied based on modern control theory considering the effect of interaction between the target structure and actuator . With the advancement in monitoring technology that provides high fidelity feedback of structural response, active vibration control techniques have been widely applied in civil engineering, mechanical engineering, aerospace engineering, and other fields …”

Section: Introductionmentioning

confidence: 99%

Swing vibration control of suspended structures using the Active Rotary Inertia Driver system: Theoretical modeling and experimental verification

Zhang

Wang

2020

Struct Control Health Monit

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Summary For the swing motion/vibration control of the suspended structural system, the tuned rotary inertia damper (TRID) has been proposed and investigated by the author previously. However it exhibits inherent robustness defect and limited applicability prospect due to its nature of being a passive tuning control system. In this paper, through the integration of active control philosophy with the rotary tuning control concept, an innovative control system named Active Rotary Inertia Driver (ARID) is proposed. First, based on the classical Lagrangian principle, the analytical model corresponding to the in‐plane swing vibration mode of the suspended structure subjected to point source excitations is established, where the structure is controlled by the ARID system. Second, the equations of motion are linearized for the purpose of engaging the classical linear control algorithm, for example, a linear quadratic regulator. The versatility of the proposed control strategy is analyzed. Furthermore, a shaking table experiment system is developed to validate the control effectiveness of the ARID system. The dynamic characteristics of the ARID system in terms of control capabilities, robustness, and stability are investigated through a series of designated shaking table tests. The performance of the ARID control system for swing vibration control of the suspended structure is successfully validated. The ARID system shows better robustness than the TRID system because it can apply control torque to the structure according to the structural response state feedback. The control algorithm and weight parameters can be designed according to need, which has been proven to be stable. The results of the paper establish a sound theoretical foundation for future investigations concerning the new control method and development.

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“…As a semi-active control, the input voltage of the magnetorheological (MR) fluid is calculated by the feedback of external excitation to change the viscous coefficient of the MR damper, which can approach the control effect of active control without a large amount of energy input [25][26][27][28][29][30][31][32][33], and it also performed well in the isolation layer [34][35][36][37][38][39][40][41][42][43][44]. Therefore, the control strategy of the MR damper is particularly important, and many scholars have done a lot of research on it [45][46][47][48][49][50]. However, the MR dampers also have the disadvantage of time-delay.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation on Semi-Active Control of Base Isolation System Using Magnetorheological Dampers for Concrete Frame Structure

Wei-qing

Zhang

et al. 2019

Applied Sciences

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The traditional passive base isolation is the most widely used method in the engineering practice for structural control, however, it has the shortcoming that the optimal control frequency band is significantly limited and narrow. For the seismic isolation system designed specifically for large earthquakes, the structural acceleration response may be enlarged under small earthquakes. If the design requirements under small earthquakes are satisfied, the deformation in the isolation layer may become too large to be accepted. Occasionally, it may be destroyed under large earthquakes. In the isolation control system combined with rubber bearing and magnetorheological (MR) damper, the MR damper can provide instantaneous variable damping force to effectively control the structural response at different input magnitudes. In this paper, the control effect of semi-active control and quasi-passive control for the isolation control system is verified by the shaking table test. In regard to semi-active control, the linear quadratic regulator (LQR) classical linear optimal control algorithm by continuous control and switch control strategies are used to control the structural vibration response. Numerical simulation analysis and shaking table test results indicate that isolation control system can effectively overcome the shortcoming due to narrow optimum control band of the passive isolation system, and thus to provide optimal control for different seismic excitations in a wider frequency range. It shows that, even under super large earthquakes, the structure still exhibits the ability to maintain overall stability performance.

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Control strategies and experimental verifications of the electromagnetic mass damper system for structural vibration control

Cited by 15 publications

References 19 publications

Artificial intelligence-based position control: reinforcement learning approach in spring mass damper systems

Artificial intelligence-based position control: reinforcement learning approach in spring mass damper systems

Swing vibration control of suspended structures using the Active Rotary Inertia Driver system: Theoretical modeling and experimental verification

Experimental Investigation on Semi-Active Control of Base Isolation System Using Magnetorheological Dampers for Concrete Frame Structure

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