Adaptive Vibration Research Articles

Active micro-vibration isolation system for adaptive vibration suppression tests using piezoelectric stack actuator

An active micro-vibration isolation system for adaptive vibration suppression using piezoelectric stack actuators is presented, along with the discrete time modelling method, real-time adaptive controller design, and hardware implementation. The system comprises piezoelectric stack actuators, capacitive displacement sensors, power amplifiers, signal conditioners, and a real-time computer. A discrete asymmetric Bouc-Wen model is developed to characterize the nonlinear behavior of the piezoelectric stack actuators. System identification is conducted using an improved particle swarm optimization method, specifically the Hybrid PSO-Jaya algorithm, which sequentially integrates the PSO algorithm with the Jaya algorithm. Additionally, an improved adaptive filtering algorithm employing affine projection, referred to as the FXAPA algorithm, is introduced to facilitate real-time control. The efficacy of the proposed active micro-vibration isolation technology is validated through micro-vibration suppression tests.

Adaptive vibration control for stabilisation of the Euler–Bernoulli beam with an unknown payload

In this paper, an adaptive boundary controller is designed to solve the boundary control problem of Euler–Bernoulli beams with an unknown payload. Therefore, a boundary controller with an adaptive law is designed to compensate for the parameter uncertainty of the system. Partial Differential Equations (PDEs) are used to describe the Euler–Bernoulli beam system. The well-posedness of the system under the action of an adaptive boundary controller is proved by using the linear operator semigroup method. Meanwhile, the asymptotic stability of the closed-loop system is derived from the extended Krasovskii–LaSalle invariance principle. The effectiveness and superiority of the proposed method are illustrated by simulation in comparison with the existing results.

Theoretical and experimental study of active vibration control of rotating composite laminated beams using Fx-NLMS algorithm

In the study, an adaptive active vibration control model of rotating composite laminated beam is presented by using the filtered-x normalized least mean square (Fx-NLMS) algorithm, and the experimental study is carried out based on the closed-loop control system. The macro fible composite (MFC) patches is employed to contruct the closed-loop control system of rotating composite laminated beam. By considering peizoelectric coupling effect and the influence of rotating angular velocity, the novel analysis model of vibration transfer function of rotating composite laminated beam with MFC patches is established. The calculation accurancy of the theoretical analysis model is validated by the experimental results. The experimental and simulation studies demonstrate that the low-frequnecy vibration of rotating composite beam is effectively controlled by using the lightweight system. The excellent stability and convergence effect of the closed-loop control system are obtained in the experimental testings. Moreover, the filter orders and learning factor on the active vibration control effect of the rotating composite beam are also stuided and discussed. This work provides a novel appoach for the low-frequency vibration control of the rotating cantilever beams by employing lightweight system.

Research on active-passive integrated vibration isolator based on metal rubber and piezoelectric actuator

Abstract The paper introduces a novel active-passive integrated vibration isolator based on metal rubber and piezoelectric actuator, along with an adaptive active vibration control strategy. The active control strategy employs the adaptive dynamic step filtered-x normalized least mean squares algorithm, allowing the step size to adaptively adjust with the error. The secondary control path of the algorithm is modeled using the enhanced rate-dependent Prandtl–Ishlinskii model and the auto-regressive with extra inputs model. The active-passive integrated vibration isolator achieves broadband vibration isolation from 10 to 200 Hz. Compared to passive isolation, the transmissibility decreases from 0.99 to 0.056 at 10 Hz, from 3.02 to 0.068 at the resonance frequency, and from 0.057 to 0.046 at 200 Hz. This study provides a theoretical and experimental foundation for the design of a novel, broadband, and efficient active-passive integrated vibration isolator structure and active control method.

Exploring the Structural Response of High-Rise Buildings using Fuzzy Logic and Genetic Algorithms

Exploring the dynamic behaviour of high-rise buildings presented a critical challenge. In this study, Fuzzy Logic and Genetic Algorithm (FLGA) were employed to comprehensively investigate the structural response of high-rise buildings (HRBs) for adaptive vibration control systems employing semiactive damper devices. The study integrated a fuzzy logic inference system with a Genetic Algorithm (GA) to create FLGA, which was then employed in a 3-story shear building under real earthquake conditions and multi-dimensional wind loads. The analytical model for a semi-active tuned mass damper (STMD) was examined and evaluated before integrating it into the proposed FLGA system. The results indicated that FLGA reduced story acceleration by an average of 20% and story drift by approximately 50% while efficiently controlling the structure within allowable movement limits and resident comfort criteria under multi-directional wind loads. The suggested optimal controller mitigated both displacement and acceleration responses by 15 to 20% without amplification. The study demonstrated FLGA's effectiveness as a model-free control strategy for managing structural response uncertainties.

A semi-active adaptive pneumatic vibration isolator based on frequency response analysis and nonlinear control

In this work, an adaptive nonlinear error feedback controller based on fuzzy state observer is proposed to a novel rubber pneumatic vibration isolator (PVI) system. First, a novel rubber PVI system is designed and developed. Harmonic balance method is applied to establish the dynamic model of the PVI system, so as to analyze the frequency response characteristics of the system. Second, to improve the PVI performance in low-frequency vibration, a nonlinear state error feedback control system based on fuzzy state observer is designed for the active PVI system. Furthermore, the experiment system is established. Finally, through the experimental comparison under 5 Hz, 7 Hz, 20 Hz, and 40 Hz, an adaptive PVI strategy is proposed. The experimental results demonstrate that the adaptive PVI shows better performance in vibration isolation.

Piezoelectric adaptive active vibration suppression for wind-tunnel model support sting

Due to flow separation and turbulence, the slender cantilever aircraft model support system is prone to low-frequency and large-amplitude resonance in the wind tunnel tests, resulting in a decrease in test data quality, a limited test envelope, and even threatening the safe operation of the wind tunnel. A piezoelectric active damping system based on the filtered-x least mean square algorithm is proposed to effectively suppress the vibration of the wind-tunnel model support sting. Firstly, a modified variable step least mean square algorithm is proposed to address the issue that the fixed-step algorithms limit each other in terms of convergence speed and steady-state error. Following that, a variable step filtered-x least mean square algorithm based on reference signal reconstruction is developed, and the corresponding feedback controller is designed to perform the ground tests of the piezoelectric active damping system for the wind-tunnel model support sting. The experimental results show that the proposed algorithm has a faster convergence speed and lower steady-state error than the traditional algorithms, as well as strong anti-noise and adaptive control abilities that significantly improve the active vibration suppression effect of the wind-tunnel model support sting.

Material Characterisation of Deflated Structured Fabrics

AbstractStructured fabrics are made by interwoven rigid elements that form flexible garments such as chain mail armours. Traditionally, the mechanical properties of these materials were considered fixed. However, recent research has revealed their mechanical properties may be varied. Notably, studies have demonstrated that applying vacuum pressure between layers of 3D-printed chain mails enclosed in a bag induces particle and layer jamming of the elements, thereby affecting the material’s bending modulus. This arises from both compressive frictional forces and the complex geometrical interlocking of the rigid elements. This paper presents a comprehensive set of experimental tests for the characterisation of the stiffness and damping properties with respect to the type and number of fabrics and with respect to the vacuum pressure. More specifically, the study examines experimentally the changes in static properties in response to vacuum pressure changes evaluated on a four- and six-point bending setups. The outcome of this measurement campaign is then reported into the Ashby diagrams to compare the mechanical properties of the in-vacuum structured fabrics with those of classical materials. The potential applications of this research include the development of lightweight adaptive and semi-active vibration mitigation devices.

Adaptive Real Time Efficient Control Algorithm for Buildings Under Wind and Earthquake Forces

The study aims to tackle two key issues: the dependency of optimal controllers on available training data and their limited capability in managing multi-component structural responses. Real Time Fuzzy Logic Efficient Control system (RTFLEC) was developed to address these challenges. This system integrates a fuzzy logic inference system with a multi-verse optimization algorithm and utilizes real time training for real-time optimal controller derivation. It incorporates decentralized systems and optimal controller memory concepts and employs a magnetorheological damper (MR) for adjustable vibration control. Two case studies were conducted to evaluate the RTFLEC system's effectiveness. The first study focused on a three-story shear building under seismic loads, while the second analyzed a 76-story building facing multi-directional wind loads. The results showed that RTFLEC system reduced structural drifts by 28.33% and 51.5% during near-field and far-field earthquakes, respectively. It also decreased structural acceleration by 27.66% and 53% during near-field and far-field earthquakes, respectively. For wind-induced structures, it reduced story displacement by 37.5%, 14.5%, and 12% against across-wind, along-wind, and rotational forces, respectively. RTFLEC system demonstrated robust performance against uncertainties in external excitations, providing exceptional structural responses. Its key advantage lies in real-time adaptability, requiring minimal training data and computational processing. These findings highlight its significant potential in enhancing the performance of adaptive vibration control systems under unpredictable real-world loads.

Youla Parameterized Adaptive Hybrid Control for Active Vibration Control Platform

Abstract To increase the vibration attenuation of the damped platforms, an adaptive hybrid vibration control algorithm based on Youla (Q) parameterization is proposed, where the vehicle suspension platform is considered as an application example. First, an inner controller is designed to keep the hybrid control system stable. Then, the controller is extended to the Youla parameterized controller set. Finally, the Q-parameters are adjusted online by using a recursive least squares (RLS) adaptive algorithm to eliminate vibration disturbances. Simulation results demonstrate that the hybrid algorithm is capable of effectively suppressing the vibration signals.

Investigation of Macroscopic Mechanical Behavior of Magnetorheological Elastomers under Shear Deformation Using Microscale Representative Volume Element Approach.

Magnetorheological elastomers (MREs) are a class of smart materials with rubber-like qualities, demonstrating revertible magnetic field-dependent viscoelastic properties, which makes them an ideal candidate for development of the next generation of adaptive vibration absorbers. This research study aims at the development of a finite element model using microscale representative volume element (RVE) approach to predict the field-dependent shear behavior of MREs. MREs with different elastomeric matrices, including silicone rubber Ecoflex 30 and Ecoflex 50, and carbonyl iron particles (CIPs) have been considered as magnetic particles. The stress-strain characteristic of the pure silicon rubbers was evaluated experimentally to formulate the nonlinear Ogden strain energy function to describe hyper-elastic behavior of the rubbery matrix. The obtained mechanical and magnetic properties of the matrix and inclusions were integrated into COMSOL Multiphysics to develop the RVE for the MREs, in 2D and 3D configurations, with CIP volume fraction varying from 5% to 40%. Periodic boundary condition (PBC) was imposed on the RVE boundaries, while undergoing shear deformation subjected to magnetic flux densities of 0-0.4 T. Comparing the results from 2D and 3D modeling of isotropic MRE-RVE with the experimental results from the literature suggests that the 3D MRE-RVE can be effectively used to accurately predict the influence of varying factors including matrix type, volume fraction of magnetic particles, and applied magnetic field on the mechanical behavior of MREs.

WITHDRAWN: Visualized neural network-based vibration control for pigeon-like flexible flapping wings

This study investigates pigeon-like flexible flapping wings, which are known for their low energy consumption, high flexibility, and lightweight design. However, such flexible flapping wing systems are prone to deformation and vibration during flight, leading to performance degradation. It is thus necessary to design a control method to effectively manage the vibration of flexible wings. This paper proposes an improved rigid finite element method (IRFE) to develop a dynamic visualization model of flexible flapping wings. Subsequently, an adaptive vibration controller was designed based on non-singular terminal sliding mode (NTSM) control and fuzzy neural network (FNN) in order to effectively solve the problems of system uncertainty and actuator failure. With the proposed control, stability of the closed loop system is achieved in the context of Lyapunov’s stability theory. At last, a joint simulation using MapleSim and MATLAB/Simulink was conducted to verify the effectiveness and robustness of the proposed controller in terms of trajectory tracking and vibration suppression.The obtained results have demonstrated great practical value of the proposed method in both military (low-altitude reconnaissance, urban operations, and accurate delivery, etc.) and civil (field research, monitoring, and relief for disasters, etc.) applications.

Adaptive Vibration Monitoring of Railway Track Structures Using the UWFBG by the Identification of Train-Load Patterns

Due to the capability of multiplexing thousands of sensors on a single optical cable, ultra-weak fiber Bragg grating (UWFBG) vibration sensing technology has been utilized in monitoring the vibration response of large-scale infrastructures, particularly urban railway tracks, and the volume of the collected monitoring data can be huge with the great number of sensors. Even though the train-induced vibration responses of urban railway tracks constitute the most informative and crucial component, they comprised less than 7% of the total operational period. This is mainly attributed to the temporal sparsity of commuting trains. Consequently, the majority of the stored data consisted of low-informative environmental noise and interference excitation data, leading to an inefficient structural health monitoring (SHM) system. To address this issue, this paper introduced an adaptive monitoring strategy for railway track structures, which is capable of identifying train-load patterns by leveraging deep learning techniques. Inspired by image semantic segmentation, a U-net model with one-dimensional convolution layers (U-net-1D) was developed for the pointwise classification of vibration monitoring data. The proposed model was trained and validated using a dataset obtained from an actual urban railway track in China. Results indicated that the proposed method outperforms the traditional dual-threshold method, achieving an Intersection over Union (IoU) of 94.27% on the segmentation task of the test dataset.

Shunted piezoelectric patch adaptive vibration absorber set to maximise electric power absorption: A comparison between parallel and series RL-shunts

This paper presents a comparative study on two types of shunted piezoelectric patch adaptive vibration absorbers, which can be bonded in batches on thin-walled structures to control the broad-band resonant response of low order flexural modes. The self-contained control units are formed by a thin piezoelectric patch connected either to a series or to a parallel resistive-inductive (RL) network. The two components of the shunt are adapted online in such a way as to maximise the time-averaged electric power absorbed by the shunt, which corresponds to minimising the time-averaged total flexural response of the hosting structure. The study considers a practical demonstrator formed by a thin rectangular plate with five piezoelectric patches connected to digital RL-shunts, which is excited in bending by a stationary white noise point force. The aim of the paper is to contrast the tuning and vibration control properties of the series and parallel RL shunts. More specifically, the online implementation of a recursive two-paths tuning strategy along R-constant and L-constant paths with an extremum seeking gradient search algorithm is analysed first for the two types of shunts. Then, the vibration control performance produced by the two types of shunts is investigated for the case where they are tuned to control the resonant response of the first flexural mode of the plate.

Exploiting multi-stiffness combination inspired absorbers for simultaneous energy harvesting and vibration mitigation

In scenarios where wide-amplitude shock excitation is encountered, a routine bistable configuration struggles to achieve satisfactory energy transfer, and a sensible combination of multiple nonlinear oscillators with different stiffness mechanisms can be exploited to achieve optimal vibration mitigation performance. In this paper, a nonlinear energy conversion and multi-stiffness combination inspired dynamic vibration absorber (NECMC-DVA) is proposed with a magnetic-spring tunable nonlinear stiffness element as the substructure. Parametric studies are performed for different modes of magnet-spring tunable nonlinear stiffness unit arrays considering transient impulses and harmonic excitation. The NECMC-DVA device, which comprises bistable oscillators, cubic stiffness oscillators, and hybrid stiffness oscillators, is also experimentally demonstrated for its synergistic performance in vibration mitigation and energy harvesting. The performance of the NECMC-DVA is measured under transient impulses and harmonic excitations. It has been found that the NECMC-DVA, which consists of a bistable oscillator, a cubic stiffness oscillator, a hybrid stiffness oscillator, energy-capture elements, and motor sequences, achieves high-efficiency nonlinear energy transfer and significant shock robustness in wide-amplitude impulsive scenarios. The NECMC-DVA with hybrid energy sinks demonstrates more remarkable targeted energy transfer and energy conversion performance than its pure bistable oscillator counterpart. Furthermore, the NECMC-DVA prototype can achieve adaptive vibration control modulation and energy conversion management through motion control boards by monitoring ambient excitation signals. Therefore, the NECMC-DVA enables integrated active and passive mitigation and energy harvesting to simultaneously accommodate multi-source indeterminate vibration and shock environments.

Optimal and Quasi-Optimal Automatic Tuning of Vibration Neutralizers

Vibration neutralizers are single-degree-of-freedom devices affixed to vibrating structures in order to reduce the response at a specific troublesome harmonic excitation frequency. As this frequency may vary over time, it becomes imperative to track and adjust the neutralizer to maintain the optimal performance. Recent years have witnessed the emergence of adaptive tunable vibration neutralizers, offering real-time adjustment capabilities through external actions. Thanks to real-time control algorithms, these devices enable the automatic mitigation of vibration levels in mechanical structures. A particularly successful algorithm for the automatic tuning of these devices leverages the phase angle between the base acceleration and the neutralizer’s mass. This study critically examines the justification for employing such an algorithm and scrutinizes its optimal applicability limits, particularly in the context of viscous and structurally damped systems. The findings reveal that this algorithm accurately approximates optimum tuning for systems with low damping. Moreover, from an engineering perspective, the algorithm remains acceptable even for heavily damped structures. Through a focused and comprehensive analysis, this paper provides valuable insights into the efficacy and limitations of the phase-angle-based tuning algorithm, contributing to the advancement of adaptive vibration control strategies in smart structures.

Event-triggered adaptive vibration control for a flexible satellite with time-varying actuator faults

In this study, vibration control is studied for the flexible satellite through wireless communication, and given the fact that the actuators are prone to unknown faults, the input signal event-triggering and time-varying actuator faults are considered for the flexible satellite simultaneously. The satellite system is composed of two symmetrical flexible panels attached to a centrebody, which is a distributed parameter system and the established model is represented by partial differential equations (PDEs). Based on the PDEs model of the flexible satellite, the input event-triggered mechanism using the relative threshold strategy is designed firstly to lower the communication burden, and then the event-triggered-based adaptive fault-tolerant control laws are developed with the aid of the designed auxiliary signals for the system with time-varying actuator faults. With the proposed control scheme, the vibration of the system is controlled to the small neighborhood of zero, and the angle of the panels is regulated to the desired position. Finally, numerical simulation results are given to further show the effectiveness of the designed control scheme.

A Flexible, Adaptive, and Self-Powered Triboelectric Vibration Sensor with Conductive Sponge-Silicone for Machinery Condition Monitoring.

Vibration sensors for continuous and reliable condition monitoring of mechanical equipment, especially detection points of curved surfaces, remain a great challenge and are highly desired. Herein, a highly flexible and adaptive triboelectric vibration sensor for high-fidelity and continuous monitoring of mechanical vibration conditions is proposed. The sensor is entirely composed of flexible materials. It consists of a conductive sponge-silicone layer and a fluorinated ethylene propylene film. It can detect vibration acceleration of 5 to 50 m s-2 and vibration frequency of 10 to 100Hz. It has strong robustness and stability, and the output performance barely changes after the durability test of 168000 working cycles. Additionally, the flexible sensor can work even when the detection point of the mechanical equipment is curved, and the linear fit of the output voltage and acceleration is very close to that when the detection point is flat. Finally, it can be applied to monitoring the working condition of blower and vehicle engine, and can transmit vibration signal to mobile phone application through Wi-Fi module for real-time monitoring. The flexible triboelectric vibration sensor is expected to provide a practical paradigm for smart, green, and sustainable wireless sensor system in the era of Internet of Things.

Adaptive optimal fault-tolerant vibration control and sensitivity analysis of semi-active suspension based on a self-powered magneto-rheological damper

To reuse the energy dissipated by vehicle suspension, a semi-active suspension with a self-powered magneto-rheological damper is proposed. An electromechanical coupling model of self-powered semi-active suspension is established. The energy conversion efficiency is defined and investigated by changing the electrical parameters. By considering unmodeled dynamics and perturbation values, an adaptive optimal fault-tolerant control algorithm is proposed to ensure the vibration-isolation performance. The robust index of the adaptive optimal fault-tolerant control algorithm is constructed using the Lyapunov equation and evaluated by changing the key parameters. The sensitivity of the key parameters to the damping force is investigated using a grey relation analysis approach. Furthermore, multi-objective optimization between the vibration-isolation capability and energy harvesting is conducted. Via analysis, the proposed suspension can harvest more energy near the second resonance range. Compared to passive control and self-powered mode, the adaptive optimal control algorithm mitigates vibration more significantly in the time and frequency domains, respectively, under stochastic excitation. The robust index is most sensitive to inductance and the diameter of the magnetism cylinder. The length of the damping channel and the diameter of the magnetism cylinder influence the sensitivity of key parameters to the damping force most obviously.

LQG/LTR based robust youla parameterized adaptive vibration control for the supporting platform of rotating liquid mirror

In mechatronic systems, the vibrations which commonly consist of band-limited random signals mixed with large multiple narrow-band deterministic signals may negatively impact the system performance. For example, due to the incomplete matching of the mechanism and the rotation of the motor, random and deterministic vibration disturbance may occur in the supporting platform of the rotating liquid mirror. In this paper, a robust Youla ( Q) parameterized adaptive regulation approach has been proposed to minimize such kind of vibration signals for the rotating platform system with model uncertainties. Firstly, the inner-loop robust controller with linear quadratic Gaussian with loop transfer recovery ( LQG/LTR) is optimally designed by choosing the suitable weighting functions to achieve the trade-off between robust stability and control performance to deal with random vibration signals. Then the Youla parameter is augmented to construct a set of Q-parameterized stabilizing controllers, and the robust stability of the system is analyzed through dual-Youla parameterization of the uncertain model. The recursive least squares (RLS) adaptive algorithm is developed to tune the Q parameter online to construct a desired adaptive controller for further residual vibration elimination. An experimental evaluation of the controller in reducing the vibration of the supporting platform of a rotating liquid mirror has been carried out, and the results illustrate that the proposed adaptive robust vibration regulation approach can effectively suppress the band-limited random and narrow-band deterministic vibration signals.