Compensation Control Research Articles

An Image Motion Compensation Control Method for the Dynamic Scan and Stare Imaging System

An Image Motion Compensation Control Method for the Dynamic Scan and Stare Imaging System

High-Speed and Low-Noise Gear Finishing by Gear Grinding and Honing: A Review

AbstractGears are important mechanical parts for transmitting power and play an increasingly important role in the machinery industry. The electric vehicle industry developed rapidly and became a vital development field of the automotive industry over the past few years. The conversion of energy increases the requirements for electric vehicle transmissions, which promotes the development of high-speed and low-noise transmission gear. This paper elaborates on the research progress of high-speed and low-noise gear finishing methods. Firstly, this review analyses the machining requirements, finishing, and specific machining technologies of high-speed and low-noise gears. The importance of gear grinding and honing in high-speed and low-noise gear machining is highlighted. Secondly, the applications of gear grinding and honing in gear modification, error compensation, and texture control are analyzed. Furthermore, the role of precision machining technology in improving gear performance is clarified. Finally, the design and processing methods of the modified tooth flank for gear modification are summarized. In addition, the influence of tooth surface texture on noise is described, and the texture change methods are explored. The well-known open problems of gear finishing are finally identified, and some new research interests are also pointed out. This review will provide valuable references for further research on gear finishing.

Linear Disturbance Observer-Enhanced Continuous-Time Predictive Control for Straight-Line Path-Following Control of Small Unmanned Aerial Vehicles

This paper studies the straight-line path-following problem on the lateral plane for fixed-wing unmanned aerial vehicles (FWUAVs) which are susceptible to uncertainties. Firstly, based on the natural frame’s location on the prescribed reference paths, the command yaw angle (which is the basis for yaw angle control system design) is solved analytically by combining it with the errors of path following, attack angle, sideslip angle, attitude angles, and geometric parameters of the prescribed reference paths. Secondly, by considering complicated dynamic characteristics, a linear extended state observer is designed to estimate uncertainties such as nonlinearities, couplings, and unmodeled dynamics whose estimated values are incorporated into the continuous-time predictive controllers for feedback compensation. Finally, numerical simulations are conducted to demonstrate the advantages of the proposed method, including reduced tracking errors and enhanced robustness in the closed-loop system, as compared to the conventional nonlinear dynamic inversion and sliding mode control approaches.

Control of transient power compensation for virtual impedance VSG in Quasi-Z-source photovoltaic grid integration system

The virtual impedance solution effectively addresses the power coupling issues and improves small-signal stability in grid-connected Virtual Synchronous Generator (VSG) systems but can deteriorate the system's transient synchronous stability, particularly in high-voltage lines with significant line inductance exacerbating this effect. To address these contradictions, the paper first analyzes the power coupling mechanisms of the system, highlighting how the line reactance ratio (R/X) and power angle (δ) affect system stability, and describes the transient stability of VSGs using the equal area criterion. Leveraging the advantages of quasi-Z-source inverters, they are applied to VSG grid-connected systems, proposing an improved VSG control strategy tailored for quasi-Z-source photovoltaic grid-connected systems. This strategy introduces virtual active power at the point of common coupling (PCC) and uses it as power feedback in the control loop, instead of using real active power. The control model is validated on an experimental platform, demonstrating that the VSG control strategy with transient power compensation significantly enhances system transient stability while preserving small-signal stability. This comprehensive approach bridges the gap between maintaining essential stability functions and enhancing dynamic performance under various operational conditions.

Prediction-Based State Estimation and Compensation Control for Networked Systems with Communication Constraints and DoS Attacks

Prediction-Based State Estimation and Compensation Control for Networked Systems with Communication Constraints and DoS Attacks

Enhanced predictive PDF control of stochastic distribution systems with neural network compensation and its application

Compared to the conventional control algorithms that use mean and variance as indicators, predictive probability density function (PDF) control can effectively handle the output PDF control problem of non-Gaussian stochastic distribution systems. However, the existing predictive PDF control method does not consider the construction error between output PDF and weight, thus the control performance is still unsatisfactory. Therefore, this paper proposes a new Enhanced Predictive PDF control method (En-PDF) to improve the output PDF control performance of stochastic distribution systems. The proposed method mainly consists of two parts: the predictive PDF control part and the neural network compensation control part aiming to reduce the bias of output PDF. First, the Radical Basis Functions (RBFs) are used to approximate the PDF of the stochastic systems output, and then a prediction model representing the relationship between input and weight is established using the subspace identification algorithm to design the predictive PDF control for the stochastic systems. Next, the Kullback-Leibler (KL) divergence is used to measure the similarity between the output PDF and the set PDF, combined with the weight error and compensation to design a new performance index. Based on this, the parameters of the neural network are adjusted using the gradient descent algorithm to obtain the optimal compensation, and the stability and tracking performance of the proposed algorithm are analyzed using inductive reasoning method. Finally, the predictive PDF control input with the compensation work together on the controlled plant to achieve high-performance control of the output PDF of non-Gaussian stochastic distribution systems. Both simulation experiments and physical control experiments validate the effectiveness and superiority of the proposed method.

Sliding mode control for finite-time projective synchronisation in distinct Caputo fractional-order delayed neural networks with inconsistent orders

This manuscript delves into the realm of projective synchronisation in delayed neural networks governed by Caputo fractional-order dynamics, addressing the intricate challenges of attaining finite-time synchronisation in networks with distinct structures, functions, and orders. To start, the integration of a compensation controller within the control architecture is examined, aiming to formulate the projection error dynamics. By leveraging projection error system analysis alongside output observation and sliding mode control, a meticulously crafted derivative-based sliding mode surface along with a sliding mode controller are devised, ensuring both convergence and seamless sliding motion. Afterwards, the accessibility of the surface is assessed through relevant lemmas, Caputo derivative characteristics and the Lyapunov direct approach. The subsequent stability of sliding path is corroborated, and indispensable prerequisites for achieving finite-time projective synchronisation are outlined. Furthermore, the establishment of an upper bound for synchronisation time of distinct Caputo fractional-order delayed neural networks (CFDNNs) with inconsistent orders is carried out. Ultimately, simulations on distinct CFDNNs with consistent and inconsistent orders are conducted to exemplify our approach, employing the continuous frequency distribution model.

Hysteresis Compensation and Trajectory Tracking Control Model for Pneumatic Artificial Muscles

The optimum performance position control of pneumatic artificial muscles (PAM) is restricted by their in-built hysteresis and nonlinearity. The hysteresis is usually depicted by a phenomenological model, while the model mentioned above always only describes the hysteresis phenomenon under certain conditions. Thus, the universality of the compensator is due to its weakness in handling disparate outside conditions. Our research employs the FN–QUPI (feedforward neural network–quadratic unparallel Prandtl–Ishlinskii) model to depict the phenomenon of pressure-displacement hysteresis in PAMs. This model has high-precision expression and generalization ability for the PAM hysteresis phenomenon. According to this, an inverse model of the QUPI operator is established as a feedforward control while combining with the feedback control of incremental PID-type iterative learning. The results show that due to the hysteresis of PAM, the compound control of feedforward control and iterative learning has better tracking performance than the ordinary PID compound control in terms of convergence rate and stability. According to the mean absolute error (MAE) and root mean square error (RMSE) of the tracking process, it can be seen that the control model can achieve accurate nonlinear compensation, and the control system shows excellent robustness to different input signals.

Maximum power point tracking control of wind turbines based on speed hysteresis loop to reduce drive-train loads

By adding compensation torque based on the optimal torque, the torque compensation control method expands the unbalanced torque at varying wind speeds, thereby improving the maximum power point tracking (MPPT) performance of wind turbines (WT). However, while improving the wind energy capture efficiency, such methods will lead to drastic fluctuations of generator torque, resulting in significantly increased drive-train loads. To solve this problem, based on the amplitude-frequency characteristics analysis of the WT system transfer function, it is found rotor speed information can not only reflect the main trend of wind speed changes, but also has the characteristics of not being easily affected by the high-frequency component of wind speed. Therefore, setting compensation torque according to it can effectively alleviate the above phenomenon. On this basis, the MPPT control of WT based on speed hysteresis loop to reduce drive-train loads is proposed. The speed information is used to replace the torque information to set the compensation torque amplitude term, and the speed hysteresis loop is introduced to improve the design of the compensation torque symbol term, which can significantly decreased drive-train loads without compromising on power capture. Finally, the effectiveness of the proposed method is verified by the experiments.

Angle stability improvement using optimised proportional integral derivative with filter controller

Load inconsistency has disrupted the power system, causing rotor angle fluctuation that leads to angle instability in the system. This research suggests an innovative proportional integral derivative with filter (PIDF)-based thyristor-controlled series compensator (TCSC) controller that utilise an evolutionary programming sine cosine algorithm (EPSCA) for hybrid optimisation to increase the angle stability of the power system. The challenge of the PIDF-TCSC design is transformed into an optimal control problem with respect to performance indices, such as the maximum imaginary part of system eigenvalues, damping ratio and damping factor, where another multi-objective function is utilised to determine the best stabiliser settings. Eigenvalue analysis is used to conduct the stability study in a linearised paradigm of the single-machine infinite-bus (SMIB) network. The resilience of the PIDF controller was tested using a SMIB power network under various operating circumstances. Simulation results are used to evaluate the system's effectiveness with the proposed optimised PIDF-TCSC controller to that of the system using the proportional integral derivative, proportional integral, and base case PIDF-TCSC approaches. The research findings demonstrate the efficacy of EPSCA in implementing PIDF-TCSC motif and its excellent resilient performance for improving power system stability as related to other strategies in various situations.

A nonlinear hysteresis compensation control of hydro-viscous drive in air transport operations

The Hydro-Viscous Drive (HVD) speed regulating system finds extensive application in air transport transmission systems to regulate the stepless speed or conduct overload protection. However, its intrinsic hysteretic behaviors, such as the asymmetric hysteretic and dead zone, could introduce inaccuracy and delay in control applications, posing challenges to system regulation. This paper investigates a Nonlinear Hysteresis Compensation Control (NHCC) that consists of two parts to control the HVD output speed by operating the valve under different engine operating conditions. In the first part, the Inverse Hysteresis Compensator (IHC) based on major loop data is introduced for the asymmetric hysteresis characterization and compensation of the HVD speed control system of the power generation and distribution, which aims to reduce the hysteresis and dead zone effect and expand the effective input range. In the second part, the Active Disturbance Rejection Controller (ADRC) is employed to mitigate the hysteresis effects of the compensated system and remove the steady-state error, which allows real-time compensation of the estimated perturbations as state feedback to achieve the required performance. An experimental laboratory station has been fabricated to evaluate the proposed method. The test results show that the NHCC method can regulate the fan speed to the desired value (|e|< 45 r/min at steady state) and broaden the effective input range to the full range under different engine conditions. Besides, the proposed control method can reduce the non-linearity of the input and output curves (from 18% to 4%) and compensate for the asymmetric hysteresis (from 38% to 5%).

Harmonic voltage compensation and harmonic current sharing strategy of grid-forming inverter

In a multi-inverter parallel system, the harmonic governance control strategy may worsen the system's current circulation problem due to the line impedance difference, which could further affect the stable operation of the system. To solve the problem, the strategy considering both power sharing and harmonic control is proposed in this paper. First, the microgrid system with background harmonics is modeled and analyzed. Based on the modeled system, a comprehensive control strategy for the grid inverter with harmonic voltage compensation and harmonic current sharing is established. In this paper, the output signal is controlled by frequency division. This paper adopts grid-forming control in the fundamental wave domain and employs harmonic voltage compensation control in the harmonic domain. The harmonic voltage is synthesized by collecting the specific harmonic current through the band-pass filter, compensating for the harmonic voltage drop on the line to improve the harmonic voltage quality of the point of common coupling(PCC). Aiming at the sharing problem caused by line impedance difference, virtual impedance control is introduced, harmonic impedance is redesigned according to the adjusted output impedance, and the harmonic output impedance before and after adjustment is measured and compared. The simulation results show that the proposed control strategy can not only reduce the harmonic content of the PCC voltage but also achieve the effect of equal harmonic current division.

Financial stress and leadership behavior: The role of leader gender.

Concern about personal finances is one of the most widespread and salient sources of stress. We advance our emerging understanding of the work-related impacts of financial stress by examining the consequences of personal financial stress on leadership behavior. Drawing on compensatory control theory, we propose that financial stress positively relates to abusive supervision via a lowered sense of personal control. Integrating social role theory, we propose that these effects are stronger for leaders who are men than leaders who are women. We test our model in a vignette-based study using a sample of leaders (N = 201) and a second multiwave, multisource field survey study among leaders and their subordinates (N = 119 leader-subordinate dyads). Across both studies, we found that financial stress was positively associated with abusive supervision via lack of control and that this relationship was stronger for men than women. In Study 2, we examined an alternative tend-and-befriend theoretical account, proposing that leaders who are women exhibit more communion-striving motivation and empathic leadership as a result of financial stress. We found some support for this alternative pathway, though not gender differences in it, and in doing so we uncovered novel outcomes of financial stress. Our results offer implications for supporting employee financial health and uncover a context wherein men (and their subordinates), rather than women, experience the costs of misalignment with societal gender expectations. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Gap compensation control method for robotic electrochemical milling machining based on multi-physics field coupling

Gap compensation control method for robotic electrochemical milling machining based on multi-physics field coupling

Adaptive hysteresis compensation control of a macro-fiber composite bimorph by improved reinforcement learning

The hysteresis characteristics related to the frequency and amplitude of the control signal seriously affect the precision of the displacement tracking control of the macro-fiber composite (MFC) bimorph. The traditional feedforward compensator tends to exhibit low precision in controlling displacement. Although it enhances the control accuracy to a certain extent by incorporating a feedback controller, the existing feedback controller has a weak adaptive ability. Thus, the Q-learning (QL) algorithm is combined with the Bouc-Wen (BW) feedforward compensator in this study. The output voltage from the BW compensator has a more significant impact on the control accuracy and convergence speed of the QL algorithm. Therefore, this paper proposes an improved QL (IQL) algorithm that leverages the control error. Moreover, a BW-IQL adaptive control method is proposed to realize precise adaptive control of the MFC bimorph. Experimental comparisons are performed with the proposed method and the traditional BW, BW-PID, and BW-fuzzy PID controllers. The BW-IQL controller reduces the average relative errors of the three controllers by 86.9%, 59.9%, and 41.8%, respectively. Meanwhile, the Q̄ table plays a major role in error suppression in the IQL controller. These results verify that the BW-IQL control method has higher adaptability and accuracy.

Adaptive Current Angle Compensation Control Based on the Difference in Inductance for the Interior PMSM of Vehicles

Achieving good performance in terms of a fast and accurate maximum torque per ampere (MTPA) control method depends on both accurate parameter estimation and a sophisticated control strategy. However, it often requires a complex and long computational process. This paper proposes an efficient control method using the relationship of torque and current angle for maximum torque per ampere control of the interior permanent magnet synchronous motor (IPMSM) for vehicle application. It was found that it is not necessary for the control method to determine the inductance in the d-q axes; the identification of the difference between each axis is enough. Furthermore, this paper presents a simple and effective procedure to estimate the difference in inductance online, where the linear iron loss calculation method is also designed to support the above process. The proposed control method was experimentally validated on a 5 kW prototype by a TMS320F28335 microcontroller and DSPACE synchronized with a personal computer. The results show that the control process has faster and more accurate performance than the conventional method.

Adaptive control of networked control systems under DoS attacks

This research introduces a new adaptive control approach tailored for networked control systems, aimed at addressing the challenges of Denial of Service (DoS) attacks and round-trip time delays. Initially, a compensation mechanism based on estimated values is introduced to counter DoS attacks; subsequently, for round-trip time delay issues, a predictive delay compensation control strategy is designed. The proposed control strategy does not rely on the specific structure or a particular model of the system, but instead solely updates the controller using the system's input and output values. Moreover, we successfully demonstrate the bounded stability of the system using the direct Lyapunov method. Ultimately, the effectiveness and practicality of this method are confirmed through simulation results.

Intelligent vehicle lateral control strategy research based on feedforward + predictive LQR algorithm with GA optimisation and PID compensation

Targeting the lateral motion control problem in the intelligent vehicle autopilot structural system, this paper proposes a feedforward + predictive LQR algorithm for lateral motion control based on Genetic Algorithm (GA) parameter optimisation and PID steering angle compensation. Firstly, based on the vehicle dynamics tracking error model, the intelligent vehicle LQR lateral motion controller as well as the feedforward controller are designed, and upon which the predictive controller is added to eliminate the system lag.Subsequently, exploiting the advantage that the PID algorithm is not model-based, a PID steering angle compensation controller that can directly control and correct the lateral error is designed. Second, a LQR controller based on path tracking deviation is designed by using the parameter rectification method of genetic algorithm (GA), which optimizes the control parameters of the lateral motion controller and improves the adaptivity of the control accuracy. Finally, Based on the Carsim-Simulink co-simulation platform, the simulation validation and analysis of double lane change (DLC) test and circular condition test (CCT) are carried out, and the results indicate that compared with the other two LQR controllers, the optimised controllers improved more than 50% in lateral error and heading error control, and the vehicle sideslip angle and vehicle yaw rate are in the range of −0.05° to 0.05° and − 0.15 rad/s to 0.10 rad/s, and it showed improved performance in tracking accuracy and satisfied vehicle stability constrains.

Takagi–Sugeno Fuzzy Parallel Distributed Compensation Control for Low-Frequency Oscillation Suppression in Wind Energy-Penetrated Power Systems

In this paper, a Takagi–Sugeno fuzzy parallel distributed compensation control (TS-PDCC) is proposed for low-frequency oscillation (LFO) suppression in wind energy-penetrated power systems. Firstly, the fuzzy C-mean algorithm (FCMA) is applied to cluster the daily average wind speed of the wind farm, and the obtained wind speed clustering center is used as the premise variable of TS-PDCC, which increases the freedom of parameter setting of the TS fuzzy model and is closer to the actual working environment. Secondly, based on the TS fuzzy model, the TS-PDCC is designed to adjust the active power output of the wind turbine for LFO suppression. To facilitate the computation of controller parameters, the stability conditions are transformed into a set of Linear Matrix Inequalities (LMIs) via the Schur complement. Subsequently, a Lyapunov function is designed to verify the stability of the wind energy-penetrated power system and obtain the parameter ranges. Simulation cases are conducted to verify the validity and superior performance of the proposed TS-PDCC under different operating conditions.

Output speed control for hydro-mechanical continuously variable transmission of tractor.

In order to improve the speed stability of tractors equipped with hydro-mechanical continuously variable transmission (HMCVT) during field operations, the speed regulation characteristics, torque characteristics, and power diversion characteristics of HMCVT are analyzed. And a comprehensive control strategy for HMCVT output speed is proposed by analyzing the factors affecting the fluctuation of output speed, which combines engine speed control and displacement ratio control of hydraulic speed control system. This strategy adopts fuzzy control to regulate the engine speed to maintain the stability of engine operation. Moreover, adopting feed forward compensation control for speed compensation enhances the anti-interference ability of the hydraulic speed control system. And combined with model predictive control, adjust the swash plate swing angle of the variable pump to reduce the fluctuation of HMCVT output speed. By establishing joint simulation model, the effectiveness of the control strategy was verified using tractor acceleration mode and step load disturbance mode. The results show that the strategy can reduce the fluctuation rate of engine speed and impact degree, shorten the adjustment time, and improve the stability of tractor operating speed.