Compensation Term Research Articles

Event-triggered robust model reference adaptive control for drag-free satellite

Aiming at the requirement of bounded disturbance suppression for low-frequency space gravitational wave detection satellite, a robust model reference adaptive drag-free control scheme is proposed in this paper via linear matrix inequalities (LMIs) approach. The multivariable model reference adaptive control (MRAC) scheme is applied to the drag-free control system with parameter uncertainties, which realizes the adaptive tracking to the reference state. The LMI system is established as an adaptive compensation term, which provides robustness against nonlinear disturbances. To reduce the communication burden of the actuation information and further save the total energies, an event-triggered mechanism (ETM) is introduced, with both the actuation inputs and the adaptive laws of the feedback gains updated only at the triggering time instants. The ultimately uniformly boundedness of the closed-loop signals is proved by Lyapunov analysis, with each system state convergence. From the feasibility analysis, Zeno behavior can be further proved to be strictly excluded. The numerical simulation verifies that the proposed scheme has efficient robustness to nonlinear disturbances with low energy cost, and achieves good effect in response to the requirements of space gravitational wave detection mission.

Improved denoising methods for smoothing frequency response functions

Measurement errors, including but not limited to noise, persist regardless of the sophistication of the experimental measurement system. Measurements contaminated with noise have proved challenging to work with from a post-processing standpoint, especially when the measurements are used directly in the analytical processing. Noise contamination in frequency response functions limits the accuracy of many applications, such as impedance modeling, requiring the direct use of measured frequency response function data. Existing approaches, such as Modal Parameter Estimation (curve-fitting), that address the de-noising of frequency response functions also suffer from various deficiencies. The errors associated with the estimation process, including modal truncation along with user interaction and interpretation, are often challenging to mitigate.Two alternative methods of frequency response function de-noising were developed in this work. The first method involves a direct approach that smooths measured frequency response functions without Modal Parameter Estimation or significant user interaction. The second approach works to alleviate the truncated effects of unmeasured modes in frequency response function synthesis more effectively than the existing upper and lower residual compensation terms. The proposed frequency response function de-noising methods are validated analytically and experimentally using various component finite element models and experimental tests.

ADC low-complexity modelling identification and mitigation of baseband intermodulation distortion with instantaneous frequency dependence

The linearization of active electronic components such as power amplifier or analog-to-digital-converter (ADC), is a vast subject. Many issues come into play, including behavioural modelling with the selection of a relevant model in terms of accuracy, complexity, identification, and compensation. In this paper we consider an ADC linearization problem, we propose an original low-complexity modelling identification and mitigation of baseband intermodulation distortion with instantaneous frequency dependence. Thus, we introduce a refinement of a power series model by adding a dependence on the variation of the instantaneous frequency of the signal. Based on this, we describe a method suitable for the model calibration using a two-tone signal. We finally present a measurement bench adapted to the calibration of the coefficients of the model, followed by some results of linearization. All the methods presented are intended to be operated in real time in embedded systems and are therefore studied to present very low computational complexities.

A high-accuracy voltage reference with high-order curvature compensation and base-current-canceling techniques

This paper presents a low dropout bandgap voltage reference circuit that combines high output voltage accuracy and low temperature-coefficient in a wide temperature range. The low temperature-coefficient is achieved by an advanced high-order curvature compensation technique, which is implemented by a novel exponential piecewise compensation term in a high-temperature range. A supply noise self-regulation technique is proposed to realize an excellent power supply rejection ratio (PSRR) without using any amplifiers in this paper. The proposed high-accuracy voltage reference is designed in a 2[Formula: see text][Formula: see text]m bipolar process. The circuit generates a reference voltage of 3.3[Formula: see text]V and can operate under a minimum supply voltage of 3.8[Formula: see text]V, while consuming 44.8[Formula: see text][Formula: see text]A. The output voltage accuracy is ± 0.15%. The PSRR at 10[Formula: see text]Hz and 1[Formula: see text]MHz is [Formula: see text][Formula: see text]dB and [Formula: see text][Formula: see text]dB, respectively. The line regulation is 2.45[Formula: see text]ppm/V in a supply voltage range from 3.8[Formula: see text]V to 20[Formula: see text]V. The average temperature coefficient is 11.9[Formula: see text]ppm/∘C in a temperature range from [Formula: see text]C to +125∘C.

Sliding-mode observer-based fault diagnosis and fault-tolerant control of the main drive system of rolling mill

In order to address the problem that the main drive system of rolling mill is easily affected by the impact of biting steel, and considering the nonlinear friction damping and the external perturbations of the main drive system of rolling mill during the rolling process, a fault model of the main drive system of rolling mill is established, and a fault diagnosis and fault tolerance control method of the main drive system of rolling mill based on the nonlinear sliding-mode observer is proposed. In order to suppress the influence of external perturbations on fault diagnosis, a nonlinear sliding-mode observer is constructed for fault diagnosis and fault reconfiguration of the system, and the robustness of the observer to fault reconfiguration is improved by using the sliding-mode control rate [Formula: see text], and the stability of the designed nonlinear sliding-mode observer is proved using Lyapunov’s stability theorem. In order to ensure that the system can operate normally even after a fault occurs, a reference model is designed, and a new controller is redesigned for fault-tolerant control of the system by adding a fault compensation term to the original control scheme using fault estimation information. Through the simulation study of the main drive system of stand F4 of 2030 mm cold rolling mill, it is verified that the observer can accurately track the system state with an angular velocity error of 2.45% and detect and estimate the main drive system failure of rolling mill with an estimation error of no more than 0.04% after a fault occurs; the fault-tolerant control of the main drive system of rolling mill is carried out by using the fault information to restore the system to its normal state, and the angular velocity error is 1.89%.

Adaptive Second-Order Fixed-Time Sliding Mode Controller with a Disturbance Observer for Electronic Throttle Valves.

In order to enhance the precision and speed of control for electronic throttle valves (ETVs) in the face of disturbance and parameter uncertainties, an adaptive second-order fixed-time sliding mode (ASOFxTSM) controller is developed, along with disturbance observer compensation techniques. Initially, a control-oriented model specifically considering lumped disturbances within the ETV is established. Secondly, to address the contradiction between fast response and heavy chattering of conventional fixed-time sliding mode, a hierarchical sliding surface approach is introduced. This approach proficiently alleviates chattering effects while preserving the fixed convergence properties of the controller. Furthermore, to enhance the anti-disturbance performance of the ETV control system, an innovative fixed-time sliding mode observer is incorporated to estimate lumped disturbances and apply them as a feed-forward compensation term to the ASOFxTSM controller output. Building upon this, a parameter adaptive mechanism is introduced to optimize control gains. Subsequently, a rigorous stability proof is conducted, accompanied by the derivation of the expression for system convergence time. Finally, a comparison is drawn between the proposed controller and fixed-time sliding mode and super-twisting controllers through simulations and experiments. The results demonstrate the superiority of the proposed method in terms of chattering suppression, rapid dynamic response, and disturbance rejection capability.

Sliding mode control strategy for grid-connected inverters based on boundary layer

A sliding mode controller is designed to effectively track the reference current for the characteristics of conventional grid-connected controllers that cannot perform static-free tracking. and aiming at the jitter phenomenon of sliding mode controller, a boundary layer-based sliding mode controller is designed, which adopts traditional linear control inside the boundary layer and sliding mode control outside the boundary layer. the error is limited to a certain range and a compensation term is used to improve the problem of slow control speed. The proposed strategy is validated by simulation using matlab simulation software, and the simulation results prove that the proposed strategy can achieve grid current and grid voltage in the same frequency and phase, which proves the effectiveness of the proposed strategy.

A Passive Decomposition Based Robust Synchronous Motion Control of Multi-Motors and Experimental Verification.

Recently, with the trend of redundancy design, the importance of synchronous motion control of multiple motors has been emphasized in various fields such as automotive, construction, and industrial engineering. Therefore, this paper proposed a novel passive decomposition-based robust synchronous control strategy for a multi-motor system, guaranteeing that both the tracking error of each motor and the synchronous error between motors are ultimately and synchronously bounded, even under the presence of parametric uncertainty and unstructured external disturbance. Specifically, a passive decomposition is used to obtain the locked and shape systems from the original system, and then a sliding mode control system along with robust compensations is designed for each decomposed system to achieve the precise synchronous motion control of the n number of motors. Here, the controller for the locked system reduces the tracking errors of motors for a given desired trajectory, while the controller for the shaped system decreases the synchronous errors between motors. Furthermore, the control system is generally and conveniently formulated to adopt the arbitrary n number of motors that must track a given desired trajectory and be synchronized. Compared to other related studies, this work especially focused on increasing the robustness of the entire system using both high-order sliding mode control and two separate compensation terms for model uncertainty and unstructured external disturbance. Finally, to validate the effectiveness of the proposed synchronous control strategy, the extensive experimental studies on two/three/four-geared BLDC motors with a high dead-zone effect were conducted, and we also compared the synchronous control performance of the proposed control strategy with the other representative control approaches, a master-slave control scheme and an independent one to address the superiority of the proposed control system. Regardless of the number of motors, due to the robustness of the control system, it is found that the proposed control ensures the tracking and synchronous errors are less than 1 degree for the sine-wave trajectory while it guarantees that the errors are below 1.5 degree for the trapezoidal trajectory. This control approach can be widely and generally applied to the multiple motor control required in various engineering fields.

Expropriation and other forms of reparation in terms of compensation for damage caused as a result of war crimes: International legal experience

As a result of international armed conflicts, questions always arise about the payment of post-war reparations. Although the process of reparation for damages caused as a result of war crimes, in most cases, begins only after the end of such a conflict, its duration and effectiveness depend on the preliminary analysis and choice of an existing reparation or development of a new model. The purpose of the work was the analysis of existing mechanisms for the payment of post-war reparations, and the search for the most effective models of compensation for Ukraine by Russia for the damage caused as a result of military aggression and the commission of international crimes. The dialectical, systemic-structural, historical, comparative, logical-formal, comparative-legal and systemic-functional methods were used. In the results, the legal nature and historical mechanisms of reparation of damage are explained, as well as problematic issues of this institution of the law of international liability are outlined. In the conclusions, different mechanisms of reparation that can be used by the State and those available to individuals, victims of violations of international crimes committed on their territory and mixed models are considered.

Deep learning discovery of macroscopic governing equations for viscous gravity currents from microscopic simulation data

Although deep learning has been successfully applied in a variety of science and engineering problems owing to its strong high-dimensional nonlinear mapping capability, it is of limited use in scientific knowledge discovery. In this work, we propose a deep learning based framework to discover the macroscopic governing equation of an important geophysical process, i.e., viscous gravity current, based on high-resolution microscopic simulation data without the need for prior knowledge of underlying terms. For two typical scenarios with different viscosity ratios, the deep learning based equations exactly capture the same dominant terms as the theoretically derived equations for describing long-term asymptotic behaviors, which validates the proposed framework. Unknown macroscopic equations are then obtained for describing short-term behaviors, and additional deep-learned compensation terms are eventually discovered. Comparison of posterior tests shows that the deep learning based PDEs actually perform better than the theoretically derived PDEs in predicting evolving viscous gravity currents for both long-term and short-term regimes. Moreover, the proposed framework is proven to be very robust against non-biased data noise for training, which is up to 20%. Consequently, the presented deep learning framework shows considerable potential for discovering unrevealed intrinsic laws in scientific semantic space from raw experimental or simulation results in data space.

Modified Active Disturbance Rejection Predictive Control: A fixed-order state–space formulation for SISO systems

This paper presents a novel control strategy that provides active disturbance rejection predictive control on constrained systems with no nominal identified model. The proposed loop relaxes the modelling requirement to a fixed discrete-time state–space realisation of a first-order plus integrator plant despite the nature of the controlled process. A third-order discrete Extended State Observer (ESO) estimates the model mismatch and assumed plant states. Moreover, the constraints handling is tackled by incorporating the compensation term related to the total perturbation in the definition of the optimisation problem constraints. The proposal merges in a new way state–space Model Predictive Control (MPC) and Active Disturbance Rejection Control (ADRC) into an architecture suitable for the servo-regulatory operation of linear and non-linear systems, as shown through validation examples.

An accelerated exact distributed first-order algorithm for optimization over directed networks

Distributed optimization over networked agents has emerged as an advanced paradigm to address large-scale control, optimization, and signal-processing problems. In the last few years, the distributed first-order gradient methods have witnessed significant progress and enrichment due to the simplicity of using only the first derivatives of local functions. An exact first-order algorithm is developed in this work for distributed optimization over general directed networks with only row-stochastic weighted matrices. It employs the rescaling gradient method to address unbalanced information diffusion among agents, where the weights on the received information can be arbitrarily assigned. Moreover, uncoordinated step-sizes are employed to magnify the autonomy of agents, and an error compensation term and a heavy-ball momentum are incorporated to accelerate convergency. A linear convergence rate is rigorously proven for strongly-convex objective functions with Lipschitz continuous gradients. Explicit upper bounds of step-size and momentum parameter are provided. Finally, simulations illustrate the performance of the proposed algorithm.

Robust adaptive quadrotor position tracking control for uncertain and fault conditions

The combination of nonlinear indirect and direct adaptive control with an active fault-tolerant framework is proposed in this paper for quadrotor position tracking control under uncertain and fault conditions. An inner loop direct model reference adaptive controller generates the required force while moving along the reference trajectory, while nonlinear indirect adaptive controller maintains the required attitude angles. Furthermore, for uncertain conditions, our proposed framework provides significantly stable characteristics. Otherwise, when a fault occurs at actuators or sensors, the quadrotor vehicle cannot guarantee global asymptotic stability. This study contributes to an active fault-tolerant control strategy for solving the complex position tracking problem using the adaptive two-stage Kalman filter (ATSKF). Based on the fault information, a fault compensation term is added to the control law to improve convergence and system robustness in the presence of uncertain and fault conditions. Finally, simulation results show satisfactory performance for quadrotor vehicle position tracking, even with actuator faults and uncertainties.

Pengaruh kompensasi, Stres Kerja dan Iklim Organisasi Terhadap Kinerja Karyawan Pada PT Cladtek BiMetal Manufactuing Batam

Human resources (HR) is one of the most important factors in a company that is used to drive other resource activities in running a company. Human resources (HR) have a fairly important position because they have a major role in company activities. PT Cladtek Bi Metal Manufacturing is a company engaged in industrial services for several jobs regarding metal materials, especially the Weld Overlay and Lining processes on carbon steel pipes aimed at industry. Compensation can motivate employees to improve work performance and compensation can also be a tool to provide or increase morale in workers. In terms of compensation at PT Cladtek Bi Metal Manufacturing, there are still some employees who feel that the compensation provided has not fully achieved the satisfaction felt by their employees. Likewise with the incident that occurred at PT Cladtek BiMetal Manufacturing, there were many employees who did not work optimally, this happened because in the assignment of very many responsibilities and also the work received was not in accordance with the field mastered, work deadlines, relationships between colleagues the work is not good and the work done is not in accordance with their abilities. The purpose of this is to determine whether compensation, work stress and organizational climate affect employee performance at PT Cladtek biMetal Manufacturing Batam. The method of data collection is through the distribution of questionnaires with a sample of 200 respondents. The type of research used by the researcher in this research is quantitative research with associative nature of research.

Consensus tracking control for a class of general linear hybrid multi-agent systems: A model-free approach

This paper studies the consensus tracking problem for a class of general linear hybrid multi-agent systems via a model-free approach. The hybrid multi-agent system is composed of N followers with discrete-time or continuous-time linear dynamics and one leader with discrete-time linear dynamics. The proposed distributed consensus tracking controller consists of a compensation term and an optimal control term. Specifically, the compensation term is introduced to address the effect of agents’ inherent dynamics on consensus tracking, and the optimal control term is designed to achieve the performance goal. By designing distributed observers for the following agents, we first propose a model-based distributed consensus tracking protocol. A model-free distributed consensus tracking protocol is further constructed via designing adaptive observers and identifying agents’ dynamics. The salient features of the model-free consensus tracking protocol are that the system matrix of the leader is only available for some followers and any follower does not need to know the eigenvalues of the graph matrix. Moreover, in order to reduce the computational burden, a system identification process is implemented based on the parallel learning method. Finally, the presented theoretical results are verified by simulation.

Adaptive robust FDI attack detection for cyber–physical​ systems with disturbance

This paper investigates the problem of attack detection for cyber–physical systems (CPSs) with disturbances, measurement noises, and false data injection (FDI) attacks. A classical linear discrete-time system attack model is constructed and a robust attack detector based on the mixed H_/H ∞ is designed. Firstly, a system with an actuator that suffered a malicious attack is modeled. Then, a robust attack detector based on the mixed H_/H ∞ is designed in which the H_ index and H ∞ index are used to characterize the sensitivity to attacks and robustness to disturbances and measurement noises, respectively. And an adaptive detection threshold with a compensation term is proposed. Besides, the designed robust attack detector enables the attack detection dynamic system to be asymptotically stable and to guarantee the H_/H ∞ performance, and the robust attack detector gains are solved from a convex optimization. Finally, the obtained theoretical results are validated through a numerical simulation and a three-area power system simulation.

YOLOv7‐EAS: A Small Target Detection of Camera Module Surface Based on Improved YOLOv7

AbstractThe camera module surface may introduce defects in the focusing process, and manual detection of these defects is inefficient and costly. To address this problem, a method to automatically expand the dataset for deep learning models with fewer original images is developed. A defect detection method is also presented, YOLOv7‐EAS, that enhances YOLOv7 for camera module images with complex backgrounds and small target defects. This method introduces NewEIOU Loss, a bounding box regression loss function that extends EIOU Loss with a nonlinear compensation term. This function improves the model's convergence rate to quadratic order. Moreover, the detection head based on ASFF is redesigned to adapt the layer features and spatially filter out irrelevant information to improve the detection rate of small targets. Finally, a 3D attention mechanism is applied to increase the model's ability to extract fine‐grained features without increasing the network parameters. Experimental results show that the improved YOLOv7 algorithm achieves 90.5% mAP for the camera module image dataset, which is 10.7% higher than the original algorithm, at 136 FPS. This method can perform the camera module surface defect detection task more accurately and meet the real‐time requirements of the production line.

Biomechanical characterisation of the pull-up exercise

PurposePerformance is the benchmark to assess the level of an athlete: in this respect, a more precise qualitative and quantitative evaluation of the performance represents an important target to be achieved.MethodsThe work presents a possible method, based on the biomechanical evaluation of the motor exercise with an optoelectronic system, to characterise single or multiple repetitions of pull-ups of 12 athletes of sport climbing and sportive healthy subjects, monitoring and scoring the performance and the safety of the executions. The analysis includes the time courses of the segmental kinematics and some newly developed synthetic indices in the form of performance and safety scores.ResultsThe time courses make it possible to analyse the linear and angular kinematics district-by-district and have a direct overview of the ranges of motion, the patterns of task execution, together with the possible strategies adopted to complete the exercise in terms of compensations. The proposed characterisation provides a condensed summary of the global execution quality and offers the possibility to identify which single biomechanical parameters are modified.ConclusionThe method is intended as a practical tool to enrich the training schedule in terms of the qualitative and quantitative evaluation of the performances and to increase the self-awareness while training.

Navigating Ethical Considerations in the Music Industry: Empowering Aspiring Music Entrepreneurs for a Responsible Future

This paper explores the ethical dimensions of the music industry and the role of aspiring music entrepreneurs in promoting a responsible and sustainable ecosystem. It highlights the challenges faced by hired artists and musicians in terms of financial compensation and professional conduct, drawing attention to anecdotal instances of malpractice. The paper presents solutions and strategies to counteract these malpractices, including comprehensive consultations, well-defined contracts, healthy management systems, and the power of saying "no" to unsuitable opportunities. Furthermore, it emphasizes the implications of these practices for aspiring music entrepreneurs in real-world professional practice and the responsibility they hold to elevate industry standards. By prioritizing fair compensation, transparency, and supportive environments, aspiring music entrepreneurs can contribute to the overall well-being of artists, musicians, and the industry as a whole. This paper encourages the integration of ethical considerations into higher education curricula and emphasizes the need for collaborative efforts to drive positive change and shape a responsible future for the music industry.

CEO career concerns in early tenure and corporate social responsibility reporting

AbstractThe literature on corporate social responsibility (CSR) disclosure focuses on its economic consequences, but little is known about motivations—especially CEO personal incentives—behind such disclosure. Using an array of CSR reporting measures, we find that career concerns of CEOs early in their tenure motivate them to use voluntary CSR reporting as a signaling mechanism. The negative association between CEO tenure and CSR reporting is more pronounced in firms with stronger information intermediaries—that is, a higher level of socially responsible investors, a higher number of analysts following, and a higher level of media coverage. We also find that CEOs early in their tenure receive more personal benefits after voluntary CSR reporting, in terms of higher total compensation, better reputation, and less turnover, than CEOs later in their tenure. Taken together, the findings of our study lend support to the conjecture that CEO career concerns early in their tenure can be an important determinant of firms' voluntary CSR reporting.