Active Control Model Research Articles

Research on adaptive robust sliding mode control of Horizontal vibration of high-speed elevator car system considering time delay

In this paper, a new adaptive robust sliding mode control (ASMC) strategy is proposed for high-speed elevator car systems with input delay and unknown nonlinear dynamic characteristics. Firstly, considering the inherent time delay of the system, the active control model of the four-degree-of-freedom time-delay car system with the symmetrical distribution of the actuator is established. Then, for the car system with unknown disturbance, a robust integral sliding mode control strategy is designed, and an adaptive law is designed to ensure the reachability of sliding mode motion. Then, considering the time delay of vibration signal transmission and actuator actuation, a time-delay optimal adaptive robust sliding mode control strategy (TDASMC) based on the state transformation method is designed, and the stability of the system is proved by constructing the Lyapunov function. Finally, Matlab software is used for simulation analysis, and the results show that the proposed control strategy can attenuate more than 45% of the peak and RMS of the horizontal vibration acceleration, and the large vibration suppression degree is not more than 14% under different working conditions, which has good vibration suppression performance and robustness.

Active boundary control of spinning beams with elastic constraints using piezoelectric stack actuator

A spinning beam structure is usually subjected to severe vibration. To suppress this vibration, piezoelectric stacking actuators are installed on the boundary of the spinning beam. Here, an active boundary control model for the vibration of spinning beam structures with elastic constraints is established. The dynamic equation of motion of the coupled system is derived by combining the Lagrange equation with the modified Fourier series method. An active control strategy is used to suppress the vibration of the spinning beam with elastic constraints. The vibration suppression effect of the proposed method under different spinning speeds and different elastic boundary conditions is discussed. It is proven that the current active control scheme can quickly suppress the vibration of the spinning beam structure with elastic constraints. The present control method can provide a new way to suppress the vibrations of spinning beam structures with nonideal boundaries in practical engineering.

Active Support Pre-Synchronization Control and Stability Analysis Based on the Third-Order Model of Synchronous Machine

When traditional grid-forming converters directly participate in the grid-connected operation of the power grid, due to the lack of a pre-synchronization control system, the voltage amplitude and initial phase on both sides of the grid-connected point will deviate, resulting in voltage and current distortion during grid-connected mode. An active support phase-locked loop free pre-synchronization control strategy based on the third-order model of a synchronous generator is proposed to address the grid-connected problem of the grid-forming converter mentioned above. First, a model of active support control with frequency integral feedback at small signal levels was constructed. The root locus method was employed to examine how system parameters affect the stability of the active support control system. Second, by adding phase pre-synchronization controllers and amplitude pre-synchronization controllers to the active frequency loop and excitation voltage loop of the third-order model, it was ensured that the frequency, phase, and voltage amplitude of the unit are consistent with the power grid, achieving a fast and smooth grid-connected mode of the unit. Finally, by using a DC source to simulate all types of new energy power generation equipment, the active support pre-synchronization control system based on the three-order model of synchronous generator is built in the MATLAB/Simulink simulation environment, and the accuracy and effectiveness of the control strategy in this paper is verified.

Analysis, Modelling and Simulation for the Intelligent Active Vibration Control of a Combined Plant using a New Gyroscopic Combined Actuator Model

There have been several research conducted worldwide on analysis, modelling, and controlling for flexible manipulator architectures. In this paper, one of the most interesting areas in the science of rotational dynamics as the study of spinning solid objects, such as Gyroscopes (G) has been investigated as a new approach for the improvement of the gyroscope non-linear behaviour which controls the magnitude and the direction of the torque separately in the frequency domain by describing a New Graphical Combined Actuator Model (NGCAM) for the Intelligent Active Vibration Control (IAVC) of a Combined Plant (CP) as a linear-nonlinear combined single link Robotics Flexible Manipulator (RFM) structure which rotates in the horizontal plane with two degrees of freedom in order to have a performance assessment and suppressing vibrations. The effect of the parameter variation on the stability and dynamic nonlinear behaviour of the gyroscope in gimbals with a feedback sensor control system has been formed and optimized by the Modified Fuzzy Logic (MFL) algorithm as an artificial intelligence control technique and the Proportional, Integral and Derivative (PID) tuning by the modified Ziegler Nichols (ZN) method. To validate the gyroscope stabilization to be implemented into the RFM for controlling the vibration, the proposed method combines Active Force Control (AFC) technique with Fuzzy Logic (FL) and PID as the (AVC-FL-PID) controller for the NGCAM, CP and RFM by using MATLAB & SIMULINK program is created. For a linear-non-linear combination system, it is better to use a linear-non-linear combination controller. Simulation results illustrate the effectiveness of the proposed strategy which is significantly and quite satisfactory about 25 (%) generally better than compared to the other systems’ performance criteria and is so clear and significant optimization is visible than compared to the other conventional actuators such as PZTs and other control strategies in improvement stabilization and vibration control of RFM structures. The advantages of the proposed method and the possibilities of further improvements are discussed.

Analytical model of an active noise control system for performance analysis of adaptive algorithms in HVAC system

In real-world acoustic scenarios related to the problem with the low-frequency noise such as HVAC systems, the signal is a stochastic, non-stationary and time-varying process where the performance of the active noise control technique mainly depends on the characteristics of the adaptive filtering techniques. In this paper, a method for analytical modeling of active noise control of signals in MATLAB/Simulink is presented, in which the acquisition of audio signals is provided by using a National Instruments control and acquisition module. For the realization of the active noise control, an adaptive filtering system model for signal analysis has been developed, using three adaptive algorithms (LMS,RLS and NLMS). The analysis of the characteristics of each of the three investigated adaptive algorithms is performed according to four parameters: Mean Square Error (MSE), convergence speed, stability and robustness. The conclusions are presented through a comparative analysis of the results obtained from the implemented methodology. The individual characteristics and parameters that are observed for correct adaptation and optimal results of each of the adaptive filters are explained in detail.

Gain-Based Feedback for Shape Control of Antenna Reflectors Using Deep Q-Network Algorithm

An intelligent shape control method for antenna reflectors is proposed using gain feedback instead of displacement feedback, considering the limitations of high-precision deformation measurement on orbit. Moreover, the finite element method is used to establish an analysis model of a grid reflector with embedded piezoelectric actuators, and the antenna gain formula is derived. To solve the multidimensional control laws from a single gain dimension, an active shape control model training framework is proposed based on the deep Q-network algorithm, including the state space, action space, and reward function. Numerical simulations, with errors stemming from two typical thermal loads as the initial errors, are conducted to illustrate the effect of the proposed control method. The influence of the voltage step size on the shape control precision is analyzed, and further online training is discussed for implementing control. The results indicate that the proposed method reduces the root-mean-square (RMS) error by more than 50% The control effect of the trained control model on other error conditions does not perform as desired. However, online training can effectively solve this problem, achieving faster convergence and a significant reduction of the RMS error.

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.

Improved mortality analysis in early-phase dose-ranging clinical trials for emergency medical diseases using Bayesian time-to-event models with active comparators.

Emergency medical diseases (EMDs) are the leading cause of death worldwide. A time-to-death analysis is needed to accurately identify the risks and describe the pattern of an EMD because the mortality rate can peak early and then decline. Dose-ranging Phase II clinical trials are essential for developing new therapies for EMDs. However, most dose-finding trials do not analyze mortality as a time-to-event endpoint. We propose three Bayesian dose-response time-to-event models for a secondary mortality analysis of a clinical trial: a two-group (active treatment vs control) model, a three-parameter sigmoid EMAX model, and a hierarchical EMAX model. The study also incorporates one specific active treatment as an active comparator in constructing three new models. We evaluated the performance of these six models and a very popular independent model using simulated data motivated by a randomized Phase II clinical trial focused on identifying the most effective hyperbaric oxygen dose to achieve favorable functional outcomes in patients with severe traumatic brain injury. The results show that the three-group, EMAX, and EMAX model with an active comparator produce the smallest averaged mean squared errors and smallest mean absolute biases. We provide a new approach for time-to-event analysis in early-phase dose-ranging clinical trials for EMDs. The EMAX model with an active comparator can provide valuable insights into the mortality analysis of new EMDs or other conditions that have changing risks over time. The restricted mean survival time, a function of the model's hazards, is recommended for displaying treatment effects for EMD research.

Active control and prediction model for the dynamic shape of laminated plate/shell structures with piezoelectric actuators

This study establishes an active control and prediction model for the dynamic shape of laminated plates/shells with piezoelectric actuators. Firstly, transient responses of shell structures are numerically calculated by adopting the finite element method (FEM) and the Newmark formulae, then the Kuhn-Tucker equation is utilized to get the time-varying voltage values with a minimum shape control error. Subsequently, a backpropagation neural network (BPNN) is constructed to predict the control precision for cases with different piezoelectric actuator layouts. Finally, the proposed control model is demonstrated through numerical examples with a maximum relative control error of only 0.023% for a given desired shape and the average error of the prediction model with 98 input neurons is 18%, thereby satisfying the application requirements. Furthermore, for a model with 3870 degrees of freedom and 21 discrete time points, the computational time is reduced significantly from 8.24 s to 0.002 s through the prediction model, making it highly suitable for optimization problems by utilizing heuristic algorithms.

Insula-cortico-subcortical networks predict interoceptive awareness and stress resilience

BackgroundInteroception, the neural sensing of visceral signals, and interoceptive awareness (IA), the conscious perception of interoception, are crucial for life survival functions and mental health. Resilience, the capacity to overcome adversity, has been associated with reduced interoceptive disturbances. Here, we sought evidence for our Insula Modular Active Control (IMAC) model that suggest that the insula, a brain region specialized in the processing of interoceptive information, realizes IA and contributes to resilience and mental health via cortico-subcortical connections. Methods64 healthy participants (32 females; ages 18–34 years) answered questionnaires that assess IA and resilience. Mental health was evaluated with the Beck Depression Inventory II that assesses depressive mood. Participants also underwent a 15 minute resting-state functional resonance imaging session. Pearson correlations and mediation analyses were used to investigate the relationship between IA and resilience and their contributions to depressive mood. We then performed insula seed-based functional connectivity analyzes to identify insula networks involved in IA, resilience and depressive mood. ResultsWe first demonstrated that resilience mediates the relationship between IA and depressive mood. Second, shared and distinct intra-insula, insula-cortical and insula-subcortical networks were associated with IA, resilience and also predicted the degree of experienced depressive mood. Third, while resilience was associated with stronger insula-precuneus, insula-cerebellum and insula-prefrontal networks, IA was linked with stronger intra-insula, insula-striatum and insula-motor networks. ConclusionsOur findings help understand the roles of insula-cortico-subcortical networks in IA and resilience. These results also highlight the potential use of insula networks as biomarkers for depression prediction.

Active noise control modeling for an electric bus driving position and its effect on sound quality

Current electric bus has become an important public transport for people in China, and its interior sound quality directly affects the driver’s physical and mental health for a long working time and the comprehensive performance of the vehicle. Therefore, it is an inevitable and urgent trend to research electric bus interior sound quality. Aiming at the problem of subjective uncomfortable auditory sensation caused by different speeds, the noise signals near the driver’s ears were collected under two constant speed conditions. On the basis of principle analysis of feed-forward adaptive control system, the primary and secondary path transfer functions were presented using Simulink module in MATLAB to construct three active noise control models for an electric bus based on least mean square (LMS), normalized LMS (NLMS) and filtered-x LMS (FxLMS). Numerical simulation results indicate that the established control models are convergent, and four acoustic parameters are effectively reduced after controls to achieve the effect of improving the sound quality.

Four-Channel Active Noise Control Modeling and Offline Simulation for Electric Bus Sound Quality Based on Two FxLMS Algorithms

Four-Channel Active Noise Control Modeling and Offline Simulation for Electric Bus Sound Quality Based on Two FxLMS Algorithms

A novel aeroengine real-time model for active stability control: Compressor instabilities integration

Developing a high-confidence entire aeroengine model that accurately incorporating unstable modes is imperative for advancing active stability control. This paper proposes a real-time model for the active stability control of aeroengines, which integrates the compressor's instability into the classical component level model (CLM). Firstly, the principles of CLM and modeling methods for inlet distortion, compressor instability dynamics, and air injector are introduced. Then, the collaborative relationship between the compressor and the other engine's components are studied to construct a real-time model with coupled instability mechanisms, involving the extension of compressor characteristics and the parameters matching between various instability models and the CLM. Finally, simulation cases under multiple unstable modes are set up to verify the effectiveness of the model, and standard instability detection algorithms are employed to confirm the confidence of the unstable signals generated by the model. The results show that the proposed model effectively captures the dynamic characteristics of stall and surge, as well as the steady-state and dynamic simulation capabilities during full operating range. Besides, it can also simulate the impact of the inlet distortion and the air injection on compressor stability. The pulsating characteristics of pressure signals and the variations of performance parameters of the model during stall and surge are highly consistent with the real test data. Moreover, the model achieves a single-step run time of no more than 7.16 ms on the embedded platform, fulfilling real-time requirements. Consequently, the model can serve as a foundation for verifying three critical aspects of active stability control: instability detection, practical actuator, and feedback control algorithms.

Research on Optimal Fast Terminal Sliding Mode Control of Horizontal Vibration of High-speed Elevator Car System

An optimal fast terminal sliding mode control strategy is proposed to suppress effectively the horizontal vibration of the high-speed elevator car system is caused by uncertainties such as rail unevenness, elevator load variation, and component friction and wear. Firstly, considering the elevator's composition structure and vibration characteristics, a 4-degree-of-freedom car system horizontal vibration active control model with a symmetric distribution of the control center is established. Secondly, considering the nonlinear factors of the rolling guide shoe and the external excitation, an optimal fast terminal sliding mode controller (PFTSMC) based on the sliding mode variable structure control is designed to eliminate the horizontal vibration of the car, define the nonsingular terminal sliding mode surface, and introduce the fast terminal convergence law based on the fast terminal attractor to ensure the accessibility of the sliding mode motion and reduce the jitter vibration. In addition, optimization of controller parameters using random weight particle swarm algorithm (RNW-PSO) to improve the controller's vibration suppression performance and robustness. Finally, the proposed controller can achieve more than 51.2% attenuation of horizontal vibration acceleration and displacement, showing that PFTSMC can effectively reduce the horizontal vibration of high-speed elevator car systems and improve ride comfort.

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.

Hierarchical CNNPID Based Active Steering Control Method for Intelligent Vehicle Facing Emergency Lane-Changing

To resolve the response delay and overshoot problems of intelligent vehicles facing emergency lane-changing due to proportional-integral-differential (PID) parameter variation, an active steering control method based on Convolutional Neural Network and PID (CNNPID) algorithm is constructed. First, a steering control model based on normal distribution probability function, steady constant radius steering, and instantaneous lane-change-based active for straight and curved roads is established. Second, based on the active steering control model, a three-dimensional constraint-based fifth-order polynomial equation lane-change path is designed to address the stability problem with supersaturation and sideslip due to emergency lane changing. In addition, a hierarchical CNNPID Controller is constructed which includes two layers to avoid collisions facing emergency lane changing, namely, the lane change path tracking PID control layer and the CNN control performance optimization layer. The scaled conjugate gradient backpropagation-based forward propagation control law is designed to optimize the PID control performance based on input parameters, and the elastic backpropagation-based module is adopted for weight correction. Finally, comparison studies and simulation/real vehicle test results are presented to demonstrate the effectiveness, significance, and advantages of the proposed controller.

Sequence effects and speech processing: cognitive load for speaker-switching within and across accents.

Prior work in speech processing indicates that listening tasks with multiple speakers (as opposed to a single speaker) result in slower and less accurate processing. Notably, the trial-to-trial cognitive demands of switching between speakers or switching between accents have yet to be examined. We used pupillometry, a physiological index of cognitive load, to examine the demands of processing first (L1) and second (L2) language-accented speech when listening to sentences produced by the same speaker consecutively (no switch), a novel speaker of the same accent (within-accent switch), and a novel speaker with a different accent (across-accent switch). Inspired by research on sequential adjustments in cognitive control, we aimed to identify the cognitive demands of accommodating a novel speaker and accent by examining the trial-to-trial changes in pupil dilation during speech processing. Our results indicate that switching between speakers was more cognitively demanding than listening to the same speaker consecutively. Additionally, switching to a novel speaker with a different accent was more cognitively demanding than switching between speakers of the same accent. However, there was an asymmetry for across-accent switches, such that switching from an L1 to an L2 accent was more demanding than vice versa. Findings from the present study align with work examining multi-talker processing costs, and provide novel evidence that listeners dynamically adjust cognitive processing to accommodate speaker and accent variability. We discuss these novel findings in the context of an active control model and auditory streaming framework of speech processing.

Modeling and active control of geometrically nonlinear vibration of composite laminates with macro fiber composite

To study the active control of the geometrically nonlinear vibration of flexible composite laminates, it is necessary to create its dynamic model and predict the effect of vibration reduction. In this paper, geometrically nonlinear and active control are introduced through von Kármán large deformation theory and velocity feedback controller, respectively. On this basis, the active control model of geometrically nonlinear vibration of composite laminates with macro fiber composite (MFC) is established. For solving the nonlinear model, an improved Newmark-β method is proposed for solving differential equations with nonlinear terms, which has better consistency and higher solution efficiency than the classical fourth-order Runge-Kutta solution. The suppression effect of active control on the nonlinear vibration response of the structure and the accuracy of the geometrically nonlinear model are confirmed using the composite cantilever laminates with MFC sensor/actuator as an example. Based on the nonlinear model, the influence of the control gain and the different positions of the MFC actuators on the active control effect are analyzed, and then the appropriate control gain and the better position of the MFC are determined.

Coupled physics analysis of blended-wing-body underwater glider equipped with electromagnetic active flow control

Lift-drag ratio is an important index to determine the hydrodynamic performance, glide performance, and economy of the underwater glider(UG). Limited by many factors, the shape optimization method has been unable to meet the needs of UG hydrodynamic performance optimization. Aiming at this crucial problem, the electromagnetic active flow control method for the UG is proposed in this paper. The coupled physical analysis of the blended-wing-body underwater glider(BWB-UG) equipped with electromagnetic active flow control is carried out by numerical method. The numerical calculation model of electromagnetic active flow control is established. The coupled physical field structure of the BWB-UG equipped with electromagnetic active flow control is studied by Detached-Eddy Simulation. The mechanism of electromagnetic active flow control on the hydrodynamic performance of the BWB-UG is further revealed by coupling physics analysis. The results show that a layer of the periodically distributed electromagnetic force is formed on the surface of BWB-UG, and the boundary layer structure can be effectively controlled. By equipping with electromagnetic active flow control, the lift-drag ratio of BWB-UG can be increased by 11.659%.

Development of Multilayer Transducer and Omnidirectional Reflection Model for Active Reflection Control.

Underwater detection is accomplished using an underwater ultrasonic sensor, sound navigation and ranging (SONAR). Stealth to avoid detection by SONAR plays a major role in modern underwater warfare. In this study, we propose a smart skin that avoids detection by SONAR via controlling the signal reflected from an unmanned underwater vehicle (UUV). The smart skin is a multilayer transducer composed of an acoustic window, a double-layer receiver, and a single-layer transmitter. It separates the incident signal from the reflected signal from outside through the time-delay separation method and cancels the reflected wave from the phase-shifted transmission sound. The characteristics of the receiving and transmitting sensors were analyzed using a finite element analysis. Three types of devices were compared in the design of the sensors. Polyvinylidene fluoride (PVDF), which had little effect on the transmitted sound, was selected as the receiving sensor. A stacked piezoelectric transducer with high sensitivity compared to a cymbal transducer was used as the transmitter. The active reflection control system was modeled and verified using 2D 360° reflection experiments. The stealth effect that could be achieved by applying a smart skin to a UUV was presented through an active reflection-control omnidirectional reflection model.