Active Vibration Control Algorithm Research Articles

PID Controller Parameter Tuning Based on a Modified Differential Evolutionary Optimization Algorithm for the Intelligent Active Vibration Control of a Combined Single Link Robotics Flexible Manipulator

This paper introduces some of the various techniques of vibration control and optimization for the purpose of vibration reduction and balancing. Here, in this research by comprising three of the most effective variational techniques now, a Modified Differential Evolutionary Optimization Algorithm (MDEOA) method is suggested to handle the challenge of adjusting the PID controller parameters for the Intelligent Active Vibration Control (IAVC) of a Combined Single Link Robotics Flexible Manipulator (CSLRFM) in order to reduce the undesired effects of vibration. The Crossover Probability Factor (CPF) as the Certain Ratio (CR) and the Mutation Factor (MF) of the algorithm are gradually altered during algorithm iteration to enhance the method's performance during optimization. On this foundation, the PID controller parameter tuning and the issue of CSLRFM mechanical vibrations are addressed using the MDEOA method. This research suggests an evolutionary algorithm that incorporates the variational techniques mentioned above, which will be combined by a certain ratio, and the specific computational procedure. In this strategy, a Strictly Bearish Distributed Exponential Function (SBDEF) has been used as the main target and the criteria and indicators for evaluating and measuring the optimal performance of differential evolution are the Integral Absolute Error (IAE) rate and the PID controller parameter values. According to simulation findings, the technique can be used to optimize the PID controller parameters settings for the IAVC of the CSLRFM and a reduction in the mechanical vibrations. Simulation results illustrate the effectiveness of the proposed MDEOA strategy which is significantly and quite satisfactory about 25 to 30 (%) better than comparing to the other algorithms in improvement stabilization and vibration control of CSLRFM.

Linear active disturbance rejection control algorithm for active vibration control of piezo-actuated beams: Theoretical and experimental studies

The active vibration control (AVC) of lightweight thin-walled structures on spacecraft has been a proven solution for vibration suppression. In this study, a linear active disturbance rejection control (LADRC) algorithm is presented for vibration suppression of piezo-actuated beams. Firstly, the governing equation of a piezo-actuated beam is obtained by using the Euler–Bernoulli beam theory and the Lagrange equation. The LADRC algorithm is designed for the piezo-actuated beam based on the governing equation. Then, the accuracy of the piezo-actuated beam model is confirmed by comparison with ANSYS and experiments. Finally, numerical simulations and experiments are carried out on the active vibration suppression of the piezo-actuated beam under the fixed harmonic excitation, variable harmonic excitation, and fixed harmonic excitation with measuring noise, respectively. The results show that the LADRC algorithm has an excellent control effect on structural vibration suppression, strong adaptability to various external excitations, and anti-noise ability.

A novel parallel multi-harmonic global multi-channel control algorithm for helicopter active vibration control

The vibrations of the helicopter fuselage are mainly induced by the rotor with blade pass frequency and the high order harmonics. The conventional filtered-x least mean square (FxLMS) control algorithm usually used a uniform convergence factor for all the harmonics which leads poor effect in controlling multi-harmonic vibration. In this paper, a novel parallel multi-harmonic global multi-channel (MHGMC) control method is proposed to suppress the multi-harmonic vibration components transmitted from the main rotor to the fuselage. Bandpass filters are used to separate multiple frequency components of the error signals, the control channel models are identified for the corresponding frequency range to independently control each frequency component, and the reconstruction of the reference input signals can be obtained from the separated error signal, effectively improving the performance of tracking interference signals. In addition, the coupling of the control channels is considered, and the global vibration optimization is taken as the control objective to update the weight coefficient of the controller. An active vibration control system of the helicopter main gearbox eight-strut installation configuration has been established. The simulation and experiment results show that the proposed controller has faster control convergence speed and better control effect of multiple harmonics than the conventional filtered-x least mean square algorithm, and the attenuations of the disturbing frequency harmonic components at all measurement points in the experiment are over 38dB. The experimental results of variable excitation also verify that the proposed control algorithm has excellent adaptability and strong robustness.

Investigation on active vibration control to improve surface quality in precision milling process

The tool-workpiece vibration in the precision milling process plays a pivotal role in influencing the surface quality. To solve the machining problem coming with the process vibration, the active vibration control model as well as the corresponding platform are developed, and the active vibration control algorithms are applied to reduce the relative vibrations and improve the surface quality. Firstly, the milling vibration reduction and surface quality improvement are modeled based on the active control algorithms and the system dynamic characteristics. Then, applying the different algorithm control strategies, such as PID, Fuzzy PID, BP neural network, and BP neural network PID control, the control effect is simulated and analyzed. Finally, an experimental platform is established to validate the system’s reliability. The efficiency of various active control methods is compared in terms of frequency vibration control and surface finish roughness improvement. The results indicate that under different milling parameters, the four algorithm control strategies exhibit optimal effects of 13.5%, 30.4%, 28.8%, and 40.1% respectively. These findings provide valuable insights into selecting the optimal vibration control method for precision milling.

Careful feedback active noise and vibration control algorithm robust to large secondary path changes

Feedback active noise and vibration control (ANVC) reduces narrowband noise and vibration when there is no reference signal. However, most ANVC algorithms require a secondary path (plant) model and can become unstable when this model is inaccurate. This work proposes an algorithm less sensitive to plant modeling errors and can cope with large and fast plant changes. This is achieved by modeling the plant and the noise using an autoregressive exogenous input (ARX) model. This model allows obtaining the expected values of the future residual noise and determining the optimal control signal. Since the model coefficient uncertainty (variance) is considered when calculating the expected value, the resulting controller is a careful controller. This allows solving problems due to significant model estimation errors when information is insufficient to estimate the full ARX model.

Multiple-input multiple-output active vibration control of a composite sandwich beam by fractional order positive position feedback

Positive Position Feedback (PPF) is an active vibration control algorithm widely employed for the vibration mitigation of thin-walled structures equipped with active flexural patches. Fractional order PPF (FOPPF) is a recent development of PPF that has been shown to achieve substantially better spillover characteristics, thanks to the inclusion of fractional calculus. However, so far, FOPPF literature has focused almost exclusively on single-input–single-output (SISO) applications, with little consideration of multiple-input-multiple-output (MIMO) capabilities and no experimental work on the subject. To fill this gap, a MIMO FOPPF control architecture was tested numerically and experimentally on a cantilever composite sandwich beam of rectangular section. The feedback algorithm involved two piezoelectric actuators and two piezoelectric sensors in a collocated configuration for the control of the lowest four resonances of the beam, excited by a random external excitation. The participation matrices, necessary for the simulation of the response of the electromechanical system, were obtained with a recently developed experimental method. The fractional orders of derivation, together with other controller parameters such as gain, resonant frequency and damping ratio, were chosen according to an optimization algorithm aimed at the vibration amplitude reduction of the first four resonances of the controlled system. As a result, the performance of the vibration control resulted superior to the equivalent PPF with integer exponents, both in simulations and experiments.

A Novel Active Vibration Control Method for Helicopter Fuselages Based on Diffusion Cooperation

Against the background of low-frequency vibration control for a helicopter fuselage in flight, active control of structural response (ACSR) has been employed for vibration control design. With the increase in control positions in the fuselage, more actuators and error sensors are needed to meet the vibration reduction requirements, forming a large-scale multichannel system. This leads to a rapid increase in the computation amount, causing the control performance of the conventional centralized algorithm main processor to become poor under overload operation. To this end, a novel distributed active vibration control algorithm based on the diffusion cooperative strategy was proposed and explored in this research. The diffusion cooperative strategy is widely used in complex wireless sensor network (WSN) systems to efficiently reduce the computation amount during data aggregation. This distributed algorithm utilizes the advantages of the diffusion-cooperative strategy to reduce the computation amount and coupling relationship of the secondary path in a large-scale multichannel system. First, a novel control law was established by introducing the network topology of the diffusion cooperation strategy into the classical filtered-x least mean square (FxLMS) algorithm, forming the diffusion FxLMS (DFxLMS) algorithm. Then, a secondary path trade-off quantization standard based on the complex undirected network connectivity condition was developed. It determined whether a secondary path was discarded or not and formed the topology of a large-scale multichannel system control network. To examine the effectiveness and superiority of the proposed DFxLMS algorithm, a comparative simulation with a scale of 1 × 10 × 10 was carried out for a simplified helicopter fuselage. Numerical results in realistic scenarios showed the ability of the DFxLMS algorithms to achieve good control performance when proper values of these parameters are chosen.

Design and Implementation of an Active Vibration Control Algorithm Using Servo Actuator Control Installed in Series with a Spring-Damper

The membrane-type air spring can be used to suppress lateral vibration of a vibration isolation table. However, compared to voice coil actuators, pneumatic actuators are difficult to use for precise vibration control, because servo valves have nonlinear dynamic characteristics. Therefore, actuators, such as voice coil actuators, can be placed in parallel with air springs, allowing force-type actuators to provide additional force to the system. These actuators generate force. In the case of a ball-screw mechanism device or a linear servomotor, it is an actuator that generates displacement. These actuators are represented as serial active systems. Serial active systems are structurally simpler than parallel active systems. However, there are very few studies on vibration isolation systems using serial active systems compared to parallel active systems. As the two are different types of systems, a new control algorithm suitable for the serial active system is needed. This study proposes a system in which an actuator capable of accurately controlling displacement is connected in series with a support spring-damper. A new active vibration control algorithm for the proposed control system is also developed, which is termed the position input and position output. The proposed control algorithm uses the displacement of the system as an input and outputs the desired displacement of the actuator installed in series with the damper and spring. The proposed control algorithm increases the damping at the target frequency and reduces the response of the system. Numerical studies and experiments were conducted on the single-degree-of-freedom and multi-degree-of-freedom systems. The results show the efficacy of the proposed control system and the novel control algorithm for the vibration suppression of the lateral vibration of a vibration isolation table.

An active multiobjective real-time vibration control algorithm for parallel hybrid electric vehicle

To improve the contradiction between vehicle dynamic performance and ride comfort by using the motor active output torque compensation method to reduce the torsional vibration of the hybrid electric vehicle (HEV) powertrain, an active multiobjective real-time vibration control (AMRVC) algorithm based on model prediction control (MPC) is proposed in this paper, and the current mainstream parallel HEV is taken as the research object to verify the proposed algorithm. Firstly, the torsional vibration model of the parallel HEV powertrain is established, simplified, and verified according to the experimental data, which provides the basis for the multimode adaptability and the application of the controller. Then, based on the state space equation of the torsional vibration system, the MPC controller considering the balance between ride comfort and power performance is designed, which can meet the multiobjective and real-time control effect of the hybrid power system while realizing the active vibration control. Finally, the effectiveness and real-time performance of the AMRVC algorithm are verified by multimode simulation analysis and hardware-in-the-loop (HIL) experiment. The simulation results show that the AMRVC algorithm based on MPC has good real-time application conditions, which can well coordinate the multiobjective requirements of vehicle ride comfort and dynamic performance, and remarkably improve the torsional vibration response of the powertrain by more than 55% in all HEV typical operating modes.

Reinforcement learning vibration control of a multi-flexible beam coupling system

An active vibration control algorithm based on reinforcement learning (RL) is applied to suppress the coupling vibration of a multi-flexible beam coupling system. The experimental setup of four-flexible beam coupling system is constructed. Piezoelectric sensors/actuators are used to detect vibration signals and suppress vibration. The finite element method (FEM) is used to establish the system dynamics model, and the model is modified by identifying parameters using the experimental data to obtain an accurate system model. The identified model is used as the simulation environment of RL algorithm. The multi-agent twin delayed deep deterministic policy gradient (MATD3) algorithm is designed to train the RL vibration controller through interaction with the simulation environment. The trained RL vibration controller is used to suppress the vibration of the four-flexible beam coupling system in simulation and experimental environment. Simulation and experimental results show that compared with proportional and derivative (PD) controller, the RL controller trained by the MATD3 algorithm has better control effect, especially for small amplitude vibration.

Active Control of Torsional Vibration during Mode Switching of Hybrid Powertrain Based on Adaptive Model Reference

When the energy management and coordinated control of the hybrid electric vehicle power system are not proper, torsional vibration problems will occur in various working states, especially in the mode switching process. These vibrations will affect the comfort, economy and emission of vehicles. In order to suppress the torsional vibration, this paper studied the active vibration control algorithm for the hybrid powertrains under the switching process of pure electric mode to hybrid mode. Primarily, the clutch combination process was divided into five stages and the dynamic models of the transmission system of each stage were established, respectively. Moreover, the principle of model reference adaptive control was analyzed. The applicability of the method to the torsional vibration of the driveline during mode switching was described. Furthermore, the clutch free displacement phase was used as the reference model. A model reference adaptive torsional vibration controller was built based on the controlled model. Finally, the efficacy of this active method for vibration reduction was simulated. The simulation results show that torsional vibration is most likely to occur in the speed coordination stage and the full participation stage. In these two stages, the designed controller can reduce the fluctuation of motor speed by 93.2% and 97.5%, respectively, the engine speed by 79.6% and 77.4%, respectively, the motor acceleration by 96.7% and 82.3%, respectively, and the engine acceleration by 88.9% and 82.3%, respectively. In addition, the controller can reduce the impact degree of the transmission system to within ±1 m/s3.

Vibration control of three coupled flexible beams using reinforcement learning algorithm based on proximal policy optimization

In order to suppress the vibration of a class of multi-coupling flexible beams, a three-coupling flexible beam experimental device is constructed. The vibration characteristics and active vibration control algorithms of three coupled flexible beams are studied. Due to the complex residual vibration of multi-coupled flexible beam structure, which shows the interaction between beams and close frequency characteristics, the dynamic model of coupled flexible beam structure is established by finite element method (FEM) and its theoretical modal analysis is carried out. Furthermore, the parameters of the experimental system are identified, and the close modal frequencies and damping ratios of the actual system are obtained. The characteristics of close modal vibration are verified. A reinforcement learning (RL) vibration controller based on proximal policy optimization (PPO) algorithm is designed. The algorithm mainly includes actor neural network and critic neural network, which are used to approximate the control strategy and evaluate state respectively. Based on theoretical modeling and experimental identification correction model, the agent learns offline, and then transfers the learned policy parameters to the experimental system for vibration control experiments. The experimental results demonstrate that the designed RL controller can effectively suppress the residual vibration of three coupled flexible beams.

Adaptive torsional vibration active control for hybrid electric powertrains during start-up based on model prediction

Torsional vibration occurs when the hybrid vehicle transmission system is influenced by the multiple excitations and the dynamic loads caused by mode switching. Torsional vibrations of transmission system directly affect the stability, reliability, and safety of vehicles. In order to suppress the torsional vibration, this paper studied the active vibration control algorithm for the hybrid powertrains under rapid acceleration. Primarily, the architecture and the dynamic modeling of the drive system of the hybrid vehicle was built. Moreover, the hybrid control system including engine controller, motor controller and transmission controller was proposed. Furthermore, an adaptive active control controller was constructed to solve the torsional vibration problem. And model prediction control (MPC) and Butterworth filter control were combined into the controller. Finally, the efficacy of this active method for vibration reduction under start-up conditions was simulated. The simulation results showed that the torsional vibration of the transmission system was reduced by 96%–99% with external interference and the system stabilization time was advanced by 93% without external interference. The adaptive control algorithm suggested in this paper effectively suppressed the torsional vibration of hybrid electric vehicles (HEV) when accelerating in pure electric mode, without affecting vehicles’ dynamic performance.

FxLMS Algorithm for Active Vibration Control of Structure By Using Inertial Damper with Displacement Constraint

Engine is the main source of vibration that generates unwanted noise and vibration of vehicle chassis. Especially, in submarine applications, radiation of noise signatures can be detected at some distance away from the submarine using a sonar array. Thus quiet operation is crucial for submarine’s survivability. This study addresses reduction of the force transmissibility originating from engines and transmitted to hull through engine mounts. An inertial damper, as an actuator of hybrid mount system, is addressed to reduce even further the level of vibration. Narrow band FxLMS algorithms are broadly used to cancel the vibration of engine mount because of its excellent performance of canceling narrow band noise. However, in real active dampers, the maximum displacement of damper mass is kinematically restricted. When the control input signal from the FxLMS algorithm exceeds this limitation, the damper mass will collide with the mechanical stops and results in many problems. Originated from these, a modified narrow band FxLMS algorithm based on the equalizer technique with the maximum allowable displacement of active damper mass is proposed in this study. Some simulation results showed that the propose algorithm is effective to suppress vibration of engine mount while ensuring given displacement constraint.

Research on Frequency-Selective Output Constraint Algorithm for Active Vibration Control

An algorithm is proposed to implement the frequency-selective output constraint control for active vibration control at target sub-frequencies. The main idea lies in that the Narrowband Filtered-X Least Mean Square (NFXLMS) algorithm is used for the frequency-selective active vibration control, after which a modified rescaling algorithm is applied to simultaneously implement the output constraints at target sub-frequencies. Besides, an amplitude compensation method is employed to accelerate the convergence rate at different frequencies. Eventually, numerical simulations are carried out, in which the results show that the proposed algorithm can be effectively used for frequency-selective output constraint control with much more accuracy and flexibility, less distortion and harmonics.

Multi-frequency micro-vibration control with hybrid adaptive control algorithm

As a popular adaptive algorithm for active vibration control (AVC), filtered-x least mean square (FxLMS) algorithm sometimes fails to suppress multiple narrowband disturbance. To control multi-frequency structure vibration, parallel-form FxLMS algorithm can be employed. However, the conventional parallel-form FxLMS does not perform well in the situation of disturbance frequency mismatch and wideband measurement noise. For this issue, the majority of the improvement approaches are based on adaptive frequency estimator. It increased the computational burden of the parallel-form FxLMS algorithm. Therefore, taking the advantage of feedback control, a hybrid adaptive control for AVC is proposed in this paper. And the “posterior” residual error is adopted for better robustness. The convergence analysis of the hybrid AVC algorithm is given. Co-simulations with ADAMS and SIMULINK are implemented to verify the effectiveness in micro-vibration control system. Some comparison experiments are implemented in a micro-vibration AVC experimental system for several typical disturbances. Experimental results confirm the feasibility and effectiveness of the proposed algorithm.

Fast multiline spectral reshaping algorithm for active vibration control

Multiline spectral vibration (or noise) is very common in rotating machinery like motor, gearbox, compressor, propeller, etc. Active reshaping of these vibrations is one of the most important branches for active vibration control, which may find application in fields of sound quality control, psychoacoustics, military camouflage, etc. The traditional filtered-reference LMS is the most popular structure for multiline spectral reshaping control. However, with the increase of spectral lines, vibration sources and observation points (feedback channels), the traditional structure will have extremely heavy computational complexity, especially for the system whose dynamic of secondary path is complex, since it requires two long filters for every single spectral line and secondary path to adjust the reference signals. In this study, we propose a fast-multiline spectrum reshaping algorithm for active vibration control. We first construct an equivalent system of the traditional multiline spectrum reshaping algorithm by introducing two extra control branches, which is able to improve the convergence property of the system. Then, we generate a group of pre-phase-scheduled reference signals using the phase information at certain frequencies of the secondary paths instead of using filters. Afterwards, we conduct a theoretical analysis of computational complexity of multiline spectrum reshaping and fast multiline spectrum reshaping algorithms. Finally, we carried out two case studies based on the FEMilS test-bed to verify the effectiveness of the proposed algorithm. The results show that the proposed algorithm performs an accurate residual vibration control with uniformed convergence speed and reduced computational complexity.

Vibration control subjected to windup problem: An applied view on analysis and synthesis with convex formulation

In this paper, the windup problem in active vibration control (AVC) is studied systematically. Instead of evaluating the performance of several anti-windup compensators implemented on independent abstract simulation problems, a unified benchmark setup in active-damping control (ADC) is used. The investigated anti-windup schemes (analysis and synthesis) are adapted to the disturbance rejection control. Large attention is given to capture the similarities and differences of the methods in dealing with the windup event in a practical context. Therefore, instead of categorizing the methods into static and non-static methods or model recovery and direct linear anti-windup schemes, a logical route is followed to highlight the significance of each method. The mathematical interpretations of the methods are provided for the vibration engineer while delivering forthright implementation algorithms for AVC. The tackled methods are unified on a state space model obtained from the frequency-domain subspace system identification approach. Practical issues that may raise for each technique are mentioned, and detained guidelines are provided for tuning each algorithm. Finally, in order to compare the compensated system’s performance, comprehensive time-domain studies are carried out by separating the transient response of the compensated systems to three modes: linear mode, where the actuation nonlinearity is inactive; the nonlinear mode, where the windup event is in progress, and finally, the output mismatch rejection mode, where the windup incident is over, but performance degradation is still present.

Active Vibration Control of a Doubly Curved Composite Shell Stiffened by Beams Bonded With Discrete Macro Fiber Composite Sensor/Actuator Pairs

Doubly curved stiffened shells are essential parts of many large-scale engineering structures, such as aerospace, automotive and marine structures. Optimization of active vibration reduction has not been properly investigated for this important group of structures. This study develops a placement methodology for such structures under motion base and external force excitations to optimize the locations of discrete piezoelectric sensor/actuator pairs and feedback gain using genetic algorithms for active vibration control. In this study, fitness and objective functions are proposed based on the maximization of sensor output voltage to optimize the locations of discrete sensors collected with actuators to attenuate several vibrations modes. The optimal control feedback gain is determined then based on the minimization of the linear quadratic index. A doubly curved composite shell stiffened by beams and bonded with discrete piezoelectric sensor/actuator pairs is modeled in this paper by first-order shear deformation theory using finite element method and Hamilton's principle. The proposed methodology is implemented first to investigate a cantilever composite shell to optimize four sensor/actuator pairs to attenuate the first six modes of vibration. The placement methodology is applied next to study a complex stiffened composite shell to optimize four sensor/actuator pairs to test the methodology effectiveness. The results of optimal sensor/actuator distribution are validated by convergence study in genetic algorithm program, ANSYS package and vibration reduction using optimal linear quadratic control scheme.

Spiking Neural Network and Bull Genetic Algorithm for Active Vibration Control

Spiking Neural Network and Bull Genetic Algorithm for Active Vibration Control