Adaptive Vibration Control Research Articles

Adaptive vibration control of a flexible structure based on hybrid learning controlled active mass damping

Natural disasters such as earthquakes and strong winds will lead to vibrations in ultra-high or high-rise buildings and even the damages of the structures. The traditional approaches resist the destructive effects of natural disasters through enhancing the performance of the structure itself. However, due to the unpredictability of the disaster strength, the traditional approaches are no longer appropriate for earthquake mitigation in building structures. Therefore, designing an effective intelligent control method for suppressing vibrations of the flexible buildings is significant in practice. This paper focuses on a single-floor building-like structure with an active mass damper (AMD) and proposes a hybrid learning control strategy to suppress vibrations caused by unknown time-varying disturbances (earthquake, strong wind, etc.). As the flexible building structure is a distributed parameter system, a novel finite dimension dynamic model is firstly constructed by assumed mode method (AMM) to effectively analyze the complex dynamics of the flexible building stucture. Secondly, an adaptive hybrid learning control based on full-order state observer is designed through back-stepping method for dealing with system uncertainties, unknown disturbances and immeasurable states. Thirdly, semi-globally uniformly ultimate boundedness (SGUUB) of the closed-loop system is guaranteed via Lyapunov’s stability theory. Finally, the experimental investigation on Quanser Active Mass Damper demonstrates the effectiveness of the presented control approach in the field of vibration suppression. The research results will bring new ideas and methods to the field of disaster reduction for the engineering development.

Influence of pre-structure orientation on the linear viscoelastic limit of magnetorheological elastomers

Magnetorheological elastomers (MREs) have been developed as a new class of smart materials for such diverse applications as adaptive vibration control of systems and energy dissipation. The linear viscoelastic (LVE) behavior of MREs is expected to play a significant role in determining filler morphology (structure, size, and aspect ratio) and working conditions. The LVE behavior of pre-structures, especially anisotropic structures, has not been clearly explained. To this end, this study aimed to analyze the LVE behavior and dynamic properties according to different pre-structures of magnetic particles. This is based on MRE pre-structures oriented at 0°, 30°, 45°, and 90° using oscillatory shear excitation as a function of frequency and amplitude sweep tests. For the latter, the excitation frequency and magnetic field intensity were analyzed. These analyses were performed for both storage modulus and loss factor corresponding to 10% strain amplitude from the roughly level linear line of the LVE region. The results showed that increasing the frequency or magnetic field intensity to increase anisotropy reduced the LVE limit. For every oriented pre-structure and analyzed frequency tested, the magnetic field decreased the LVE limit. Thus, the orientation of the carbonyl iron particles in the matrix enhanced the viscoelastic properties.

Adaptive Neural Network Vibration Control for an Output-Tension-Constrained Axially Moving Belt System With Input Nonlinearity

In this article, to suppress the vibration of an axially moving belt system of surface-mounted technology, which is working with S-curve acceleration/deceleration, an adaptive neural network controller is proposed utilizing backstepping method and Lyapunov’s theory. Considering input nonlinearity, external disturbance, and system uncertainty, radial basis function (RBF) neural networks are adopted to eliminate the effect of these uncertain terms. Besides, in order to ensure the production quality of the equipment and for the sake of safety, both the deformation constraint and tension constraint are taken into account, and a barrier Lyapunov function is employed to guarantee the restrictions. The stability of the closed-loop system is proved and simulations are given to illustrate the well performance of the proposed control strategy.

Adaptive Robust Control for a Spatial Flexible Timoshenko Manipulator Subject to Input Dead-Zone

This article investigates the adaptive robust spatial vibration control for a flexible Timoshenko manipulator subject to input dead-zone nonlinearity characteristic. The “disturbance-like” terms and dead-zone nonlinearity are first incorporated into the context of control design, and the new boundary robust adaptive control laws are constructed to reduce the shear deformation and elastic oscillation, ensure the expected angle orientation, handle the input dead-zone, and estimate the upper bound of compound disturbances. The convergence of states and the stability of the system are analyzed and proven without simplifying the infinite dimensional dynamics. In the end, the effectiveness of the presented scheme is demonstrated by the result of simulation research.

A new adaptive vibration control of magnetorheological damper system and its application to washing machine

Some undamped vibrations may cause undesirable behavior such as noise, overloads, excessive displacements, and early fatigue failures in the mechanical systems. Active vibration control is crucial for some of the mechanical systems such as washing machines. This article proposes a new vibration control strategy (VCS) for reduction of vibrations in washing machine. VCS utilizes adaptive nonlinear terminal sliding mode control (NTSMC) of double coil shear mode magnetorheological (MR) dampers and DC-DC buck converter. To achieve this goal, a control mechanism was designed that consists of two loops. The first loop implemented a force feedback control using proportional integral (PI) control and load cells. The second loop consists of adaptive NTSMC that was applied on buck converter to control current flow in MR dampers. The control law and finite convergence time to the equilibrium point were guaranteed for the current error using NTSMC. Moreover, an adaptive law was incorporated in NTSMC for the dynamic current control of MR dampers. The stability analysis of adaptive NTSMC was carried out using Lyapunov stability theory. An experimental setup was established for VCS that helps to study the performance of washing machine. A comparative analysis is presented for VCS with the passive dampers and other vibration control techniques that are reported in literature for washing machines.

Nonlinear partial differential equation modeling and adaptive fault‐tolerant vibration control of flexible rotatable manipulator in three‐dimensional space

SummaryIn this article, we investigate the problem of nonlinear modeling and adaptive boundary vibration control with actuator failure for a flexible rotatable manipulator in three‐dimensional space, which is made up of a rotatable base and a flexible manipulator. In order to accurately reflect the characteristics of the distributed parameters, the Hamilton principle is introduced to derive the dynamic model expressed by partial differential equations (PDEs). Based on the model, an innovative boundary control scheme is proposed to eliminate the deflection and vibration simultaneously, and to guarantee that the rotatable base and the flexible manipulator can track the desired angle respectively. The adaptive law is developed to estimate the loss of the actuator. The effectiveness of the designed controller is verified from both theoretical analysis and numerical simulation.

Research developments in adaptive intelligent vibration control of smart civil structures

Control algorithms are the most critical aspects in the successful control of civil structures subjected to earthquake and wind forces. In recent years, adaptive intelligent control algorithms are emerging as an acceptable substitute method to conventional model-based control algorithms. These algorithms mainly work on the principles of artificial intelligence (AI) and soft computing (SC) methods that make them highly efficient in controlling highly nonlinear, time-varying, and time-delayed complex civil structures. The current research probes to control algorithms, that this article set forth an inclusive state-of-the-art review of adaptive intelligent control (AIC) algorithms for vibration control of smart civil structures. First, a general introduction to adaptive intelligent control is presented along with its advantages over conventional control algorithms. Second, their classification concerning artificial intelligence and soft computing methods is provided that mainly consists of artificial neural network-based controller, brain emotional learning-based intelligent controller, replicator dynamics-based controller, multi-agent system-based controller, support vector machine-based controller, fuzzy logic control, adaptive neuro-fuzzy inference system-based controller, adaptive filters-base controller, and meta-heuristic algorithms-based hybrid controllers. Third, a brief review of these algorithms with their developments on the theory and applications is provided. Fourth, we demonstrate a summarized overview of the cited literature with a brief trend analysis is presented. Finally, this study presents an overview of these innovative AIC methods that can demonstrate future directions. The contribution of this article is the anticipation of detailed and in-depth discussion into the perspective of AI and SC-based AIC method advances that enabled practical applications in attenuating vibration response of smart civil structures. Moreover, the review demonstrates the computing advantages of AIC over conventional controllers that are important in creating the next generation of smart civil structures.

Energy-Harvesting Adaptive Vibration Damping in High-Speed Train Suspension Using Electromagnetic Dampers

Electromagnetic damper cum energy harvester (EMDEH) is an emerging dual-function device that enables simultaneous energy harvesting and vibration control. This study presents a novel energy-harvesting adaptive vibration control application of EMDEH on the basis of the past EMDEH development in passive control. The proposed EMDEH comprises an electromagnetic damper connected to a specifically designed energy harvesting circuit (EHC), wherein the EHC is a buck–boost converter with a microcontroller unit (MCU) and a bridge rectifier. The effectiveness of the energy-harvesting adaptive vibration damping is validated numerically through a high-speed train (HST) model running at different speeds. MCU-controlled adaptive duty cycle adjustment in the EHC enables the EMDEHs to adaptively offer the optimal damping coefficients that are highly dependent on train speeds. In the meantime, the harvested power can be stored in rechargeable batteries by the EHC. Numerical results project the average output power ranging from 40.5[Formula: see text]W to 589.8[Formula: see text]W from four EMDEHs at train speed of 100–340[Formula: see text]km/h, with a maximum output power efficiency of approximately 35%. In comparison to energy-harvesting passive vibration control and a pure viscous damper, the proposed energy-harvesting adaptive control strategy can improve vibration reductions by approximately 40% and 27%, respectively, at a speed of 340[Formula: see text]km/h. These numerical results clearly demonstrate the benefit and prospect of the proposed energy-harvesting adaptive vibration control in HST suspensions.

Modelling and neural adaptive vibration control for three-dimensional Timoshenko beam with output restrictions and external disturbances

In this paper, the dynamic modelling and adaptive boundary control of a three-dimensional Timoshenko beam are presented for vibration suppression. In order to ensure that no modal information is left out, partial differential equations (PDEs) are employed to describe the nonlinear dynamic characteristics of the system by applying the extended Hamilton’s principle. Based on the established model, barrier Lyapunov functions (BLFs) are utilised for dealing with system output restrictions. For practical consideration, parameter uncertainties and external disturbances are also taken into account. Under the proposed neural adaptive control scheme, undesirable elastic vibration of the three-dimensional Timoshenko beam is restricted and constrained within given bounds even subject to external perturbations, without needing to know any system parameters. The system stability is proved by the Lyapunov’s direct method. The control performance is verified via using numerical simulations.

Adaptive Deterministic Vibration Control of a Piezo-Actuated Active–Passive Isolation Structure

With the improvement of the performance of optical equipment carried by on-orbit spacecraft, the requirements of vibration isolation are increasing. Passive isolation platforms are widely used, but the ability to suppress the low-frequency deterministic vibration disturbance is limited, especially near the system’s natural frequency. Therefore, an active vibration control strategy is proposed to improve passive isolation performance. In this paper, a Youla parameterized adaptive active vibration control system is introduced to improve the isolation performance of a piezo-actuated active–passive isolation structure. A linear quadratic Gaussian (LQG) central controller is first designed to shape the band-limited local loop of the closed-loop system. Then, the central controller is augmented into a Youla parameterized adaptive regulator with the recursive least square adaptive algorithm, and the Youla parameters (Q parameters) can be adjusted online to the desired value to suppress the unknown and time-varying multifrequency deterministic vibration disturbance. In the experiment, the residual vibration with respect to the combination of multiple frequencies is effectively suppressed by more than 20 dB on average, and a quick response time of less than 0.3 s is achieved when the deterministic residual vibration changes suddenly over time. The experimental results illustrate that the proposed adaptive active vibration control system can effectively suppress the low-frequency deterministic residual vibration.

Research on the variable mechanical properties and application in vibration control of soft magnetic entangled metallic wire material

A novel soft magnetic entangled metallic wire material (SM-EMWM) is investigated in this article, which is manufactured using the magnetoelectric-sensitive soft magnetic wires. The mechanical properties (tangent modulus, loss factor) of SM-EMWM can be tunable in the magnetic field rapidly and reversibly, and thus can be applied to vibration control systems. The quasi-static and dynamic tests in different magnetic fields were carried out, and the results show that the tangent modulus of SM-EMWM samples in a magnetic field of 500 mT can increase 2–7 times on average compared with no magnetic field condition, while the loss factor can be improved above 50%. Therefore, with the enhancement of the intensity of the magnetic field, the resonant frequency of the system with SM-EMWM increases, the peak value of response curves decreases dramatically as well. Based on the results of dynamic tests, one suitable adaptive vibration control strategy was developed and used in the tests to avoid the resonant frequency of the system, by controlling the magnetic field condition appropriately. The results show that the peak vibration transmissibility of the controlled SM-EMWM system decreases over 50%, which reveals the excellent application prospect of the SM-EMWM for the active or semi-active control vibration control in mechanical structures.

Nonlinear Adaptive Harmonics Vibration Control for Active Magnetic Bearing System With Rotor Unbalance and Sensor Runout

Rotor unbalance (RUB) and Sensor Runout (SR) are two main vibration sources for active magnetic bearing (AMB) system, and they not only produce considerable harmonic vibration but also endanger the stability of AMB system. Therefore, a nonlinear adaptive algorithm, whose asymptotic stability is guaranteed by Lyapunov's theory, is proposed in this paper to suppress the harmonic vibration. Nevertheless, RUB and the synchronous component of SR have the same frequency with the rotational frequency, and it is highly necessary to distinguish them from each other for the compensation of displacement stiffness force. Hence, the scheme of changing rotor speed is adopted for the permanent magnet biased magnetic bearing system. As a consequence, the harmonic current caused by RUB and SR is effectively attenuated and the displacement stiffness force is correctly compensated. The results of the numerical simulations and experiments demonstrate that the harmonic vibration is dramatically suppressed through the proposed method.

Adaptive boundary iterative learning vibration control using disturbance observers for a rigid–flexible manipulator system with distributed disturbances and input constraints

In this article, an adaptive boundary iterative learning vibration control is developed for a class of the rigid–flexible manipulator system under distributed disturbances and input constraints. With the help of the virtual work principle, the dynamics of the rigid–flexible manipulator are modeled and described by coupled ordinary differential equations and partial differential equations. Based on the original infinite dimension system model, three compounded adaptive boundary iterative learning vibration control laws are constructed with disturbance observers and adaptive vibration laws, aiming to track the desired joint angular positions and achieve vibration suppression simultaneously. Three disturbance observers are proposed to determine the upper bounded approximation of the unknown external disturbances. Hyperbolic tangent and saturation functions are incorporated into adaptive vibration laws to handle input constraints. It is proved by Lyapunov–Krasovskii-like composite energy functions that elastic vibrations and tracking errors can asymptotically converge to zero along the iteration axis. Finally, the efficacy of the developed adaptive boundary iterative learning vibration control approach is illustrated by the simulation results under distributed disturbances and input constraints.

Adaptive fault-tolerant boundary vibration control for a flexible aircraft wing against actuator and sensor faults

The vibration control problem was investigated in this study in the presence of unknown loss of actuator effectiveness fault and loss of sensor effectiveness fault in a flexible aircraft wing system. A series of partial differential equations was used as the mathematical model of the wing with unknown boundary disturbances. An adaptive fault-tolerant boundary controller was designed accordingly. All signals of the closed-loop control system are globally uniformly bounded and the controlled state asymptotically converges. Numerical simulations were conducted to validate the proposed control scheme.

Self-sensing active control of emulated tangential tool vibration hardware-in-the-loop

This study tests the dual functionality of a piezoelectric transducer for active control of emulated tool vibration. The concept of a self-sensing actuator is here applied jointly with adaptive feedback active vibration control as hardware-in-the-loop. It controls pre-recorded tangential tool vibrations at the tool holder’s first bending mode. This work shows that the selected building blocks of the complete control loop are key to the design. It opens perspectives for a single transducer design and a simultaneous tool condition monitoring function. 10 dB attenuation of tool vibrations, bending-mode-focussed control command and feedback signal-to-noise-ratio of 20 demonstrate the system’s functionality.

Asymmetrical Barrier Function-Based Adaptive Vibration Control for Nonlinear Flexible Cantilever Beam With Obstacle Restriction

In this paper, a novel adaptive asymmetrical barrier function-based vibration control law is proposed for the nonlinear flexible cantilever beam system with obstacle restriction, model uncertainties, and distributed disturbances. Firstly, by employing the Hamilton’s principle and the Galerkin projection method, the dynamic of the nonlinear flexible cantilever beam with the piezoelectric actuator is constructed in partial differential equations and simplified to nonlinear ordinary differential equations for the control law design. Then, by introducing the fast nonsingular terminal sliding mode surface, a novel asymmetrical barrier function based sliding mode control law is proposed, in which by means of a novel asymmetrical barrier Lyapunov function is used to guarantee the finite time stability with the obstacle restriction. Further, to deal with the model uncertainties, an adaptive updating law is incorporated with the fast nonsingular terminal sliding mode control law based on asymmetrical barrier function, stability proof shows that the proposed control law can ensure the distributed disturbance rejection and the model uncertainties compensation simultaneously. Finally, the effectiveness of the proposed control laws is demonstrated by the numerical simulations.

Adaptive Vibration Control for an Active Mass Damper of a High-Rise Building

As a kind of large flexible structure, high-rise buildings need to consider wind-resistant and anti-seismic problems for the safety of occupants and properties, especially in coastal areas. This article proposes an infinite dimensional model and an adaptive boundary control law for an active mass damper (AMD) on this question. The dynamic model of the high-rise building is a combination of some storeys which have flexible walls and rigid floors under a series of physical conditions. Then the adaptive boundary controller is acted on an AMD which is equipped on the top floor, in order to suppress the vibration of every floor and guarantee the comfort of residents. Moreover, simulations and experiments are carried out on a two-floor flexible building to illustrate the effectiveness of the proposed control strategy.

Adaptive active vibration control for piezoelectric smart structure with online hysteresis identification and compensation

Smart structure vibration reduction based on adaptive active vibration control has become a hot research spot in recent years. A filtered-U least mean square algorithm based on an infinite impulse response filter structure is used to solve the interference of controller output to reference signal. The filtered-U least mean square algorithm is very suitable for the nonlinear vibration control of the flexible structure. This study focuses on the analysis and implementation of an adaptive active vibration control system for smart structure with a surface-bonded piezoelectric actuator. The piezoelectric actuator contained in the secondary path has nonlinear hysteresis property. The nonlinear hysteresis property will cause a nonlinear relationship between the structural vibration response and the control voltage, which deteriorates the robustness and control effect of the adaptive control. This study designs an improved version of the filtered-U least mean square algorithm with online hysteresis identification and compensation (filtered-U least mean square–online hysteresis identification and compensation) based on a discrete Prandtl–Ishlinskii model. The Prandtl–Ishlinskii model parameters of the nonlinear hysteresis property are identified online based on the least mean square algorithm. Based on the identified Prandtl–Ishlinskii model parameters, an inverse hysteresis compensator is established for feedforward compensation in the secondary path. Simulation results show that the proposed method can dynamically compensate the hysteresis nonlinearity of the secondary path, linearizing the nonlinear hysteresis. The vibration reduction effect of the proposed method is obviously better than that of other competing methods. A piezoelectric smart cantilever plate with PZT (or lead zirconate titanate, Pb (Zr, Ti)) actuators and sensors is designed to demonstrate the validity and efficiency of the proposed method by experiments. Experiment results demonstrate that the adverse effect of nonlinear hysteresis is eliminated well after feedforward hysteresis compensation is introduced; the unexpected frequency vibration caused by the hysteresis property is suppressed. The proposed methodology possesses an important advantage in application of the adaptive active vibration control of the piezoelectric smart structure.

Adaptive Torsional Vibration Control of the Nonlinear Rolling Mill Main Drive System with Performance Constraints and Sensor Errors

This paper studies the torsional vibration suppression control problem for the nonlinear rolling mill main drive system with performance constraint requirements and unknown measurement sensitivities. Firstly, considering the nonlinear friction between the roll gaps, a torsional vibration model of the main drive system of rolling mill is established. Then, with the asymmetric performance constraints transformation, the motor torque control law is proposed based on backstepping algorithm. By introducing an adaptive bound estimation approach, the multiple unknown parameters caused by the sensor sensitivities can be approximated with very few adaptive laws. The dynamic surface technology is introduced to simplified the control design procedure and solve the computational explosion problem. It is strictly proved that the resulting closed-loop system is stable in the sense of uniformly ultimately boundedness and both transient and steady-state performances of the load speed are preserved. Finally, the simulation is provided to show the validity and the advantages of the proposed techniques.

Regressor-free adaptive vibration control of constrained smart beams with axial stretching

This paper proposes an adaptive approximation control AAC technique (or so-called regressor-free adaptive control) for vibration regulation of constrained flexible smart beams with axial stretching. The key idea of the AAC is to control/regulate the target dynamic system while estimating the uncertainty using weighting and basis function terms with guaranteed stability based on Lyapunov theory. Accordingly, the dynamic equation of transverse vibration of the pinned–pinned smart beam is derived considering the effect of axial stretching. Due to the presence of a coupled tension-bending effect, a nonlinearly coupled cubic stiffness term appears in beam modelling making the dynamic system highly nonlinear. The resulted partial differential equation of the vibrating smart beam is discretized into definite N-mode shapes (definite degrees-of-freedom) using the Galerkin approach and a standard multi–input–multi–output ordinary differential equations system is established. Then two decoupled nonlinear control algorithms are designed based on the AAC for vibration attenuation of the nonlinear vibrating beam system. A pinned–pinned piezoelectrically-actuated/sensed flexible beam is simulated and the results show the validity of the proposed control architecture.