Output Control Research Articles

Enhancing Vapor Compression Refrigeration Systems Efficiency via Two-Phase Length and Superheat Evaporator MIMO Control

The present investigation focuses on enhancing the efficiency of a vapor compression refrigeration system (VCRS) by proposing a Multiple Input Multiple Output (MIMO) control strategy based on the evaporator’s two-phase length and superheat temperature. A moving boundary dynamic model for the VCRS is implemented using the Thermosys Matlab Toolbox. The study analyzes the influence of actuation parameters, specifically compressor speed and expansion valve opening, on control parameters, namely two-phase length and superheat temperature. A comprehensive analysis based on the first and second laws of thermodynamics is conducted across a wide range of operating conditions. Simulation results demonstrate that two-phase length can be effectively utilized as a control parameter by selecting operating points that maximize the system efficiency. Additionally, the study reveals that extending the evaporator’s two-phase length to 80–90% of its limit increases system efficiency, enabling a reduction in compressor speed while maintaining the cooling capacity.

Graded control of Purkinje cell outputs by cAMP through opposing actions on axonal action potential and transmitter release.

All-or-none signalling by action potentials (APs) in neuronal axons is pivotal for the precisely timed and identical size of outputs to multiple distant targets. However, technical limitations with respect to measuring the signalling in small intact axons have hindered the evaluation of high-fidelity signal propagation. Here, using direct recordings from axonal trunks and/or terminals of cerebellar Purkinje cells in slice and culture, we demonstrate that the timing and amplitude of axonal outputs are gradually modulated by cAMP depending on the length of axon. During the propagation in long axon, APs were attenuated and slowed in conduction by cAMP via specifically decreasing axonal Na+ currents. Consequently, the Ca2+ influx and transmitter release at distal boutons are reduced by cAMP, counteracting its direct facilitating effect on release machinery as observed at various CNS synapses. Together, our tour de force functional dissection has unveiled the axonal distance-dependent graded control of output timing and strength by intracellular signalling. KEY POINTS: The information processing in the nervous system has been classically thought to rely on the axonal faithful and high-speed conduction of action potentials (APs). We demonstrate that the strength and timing of axonal outputs are weakened and delayed, respectively, by cytoplasmic cAMP depending on the axonal length in cerebellar Purkinje cells (PCs). Direct axonal patch clamp recordings uncovered axon-specific attenuation of APs by cAMP through reduction of axonal Na+ currents. cAMP directly augments transmitter release at PC terminals without changing presynaptic Ca2+ influx or readily releasable pool of vesicles, although the extent is weaker compared to other CNS synapses. Two opposite actions of cAMP on PC axons, AP attenuation and release augmentation, together give rise to graded control of synaptic outputs in a manner dependent on the axonal length.

Research on relay safety output control method based on BP neural network

With the continuous improvement and expansion of the metro network, the issues of train safety capacity, transportation effi-ciency and maintenance cost will become increasingly prominent. As an indispensable switching and controlling device of train safety control system, the health status of relay is the foundation of low-cost, high safety and efficient development of subway. This paper designs and proposes a BP neural network based relay safety output control method, this method utilizes BP neural net-work on the basis of improved two-take-two hardware structure to do fault prediction and safety state management with real-time retrieved detection signals, finally uploads operation and mainte-nance logs to the platform to guide subsequent fault trouble-shooting and maintenance.

Vibration control and robustness analysis of tensegrity structures via fuzzy dynamic sliding mode control method

This study addresses the problem of mitigating vibration responses in tensegrity structures subjected to complex dynamic loading conditions. The overall purpose is to develop an effective control method to enhance the stability and performance of these structures. To achieve this, a fuzzy dynamic sliding mode control (FDSMC) method is proposed. The methodology involves deriving the state space expression of the controlled system based on the tensegrity structure's dynamic model, followed by designing a dynamic sliding mode controller using the reaching law. Fuzzy rules are incorporated to adaptively adjust the dynamic sliding mode parameters, accounting for uncertainties in controller parameters, thereby ensuring high efficiency and smooth controller output. A comparative analysis scheme, focusing on identical energy input on actuators, is utilized to evaluate the performance of various active vibration control methods. Two illustrative examples, a spatial double-layer tensegrity beam and a complex tensegrity spiral tower, are investigated in detail. The findings demonstrate that the FDSMC method significantly reduces structural dynamic responses and improves algorithm robustness compared to the conventional linear quadratic regulator (LQR) method, indicating its promising potential for relevant engineering applications.

An online comprehensive health monitoring system for automotive auxiliary converter

Abstract As an essential part of the electronic system in electric vehicles (EVs), the automotive auxiliary converter (AAC) connects the batteries and burdens the auxiliary power supply. This paper mainly proposes an online comprehensive health monitoring system for AAC. Firstly, based on the control diagram of the LLC resonant converter, three critical components are emerging, including capacitor, optocoupler, and semiconductor. These components can partly reflect the operation condition of the output loop, feedback loop, and control link, respectively. Then the characteristics parameters of these three components, equivalent series resistance (ESR) of the capacitor, current transfer ratio (CTR) of the optocoupler, and on-resistance of the semiconductor jointly construct the three-dimensional health monitoring vector. Finally, the online monitoring accuracy is verified and the proposed system can thus effectively promote the operation and maintenance of AAC. Furthermore, the online health monitoring system enables a flexible expansion, which can be further customized into different kinds of power converters, showing high applicability and practicality.

Sinusoidal control strategy applied to continuous stirred‐tank reactors: Asymptotic and exponential convergence

AbstractThe main goal of this proposal is to present a class of nonlinear controllers for regulation and set point changes in continuous chemical reactors. The proposed control law has in its mathematical structure a proportional term of the regulation error to provide closed‐loop stability and a sinusoidal term, which can compensate for the nonlinearities of the plant. The closed‐loop stability of the plant is demonstrated via Lyapunov analysis, which reveals an asymptotic convergence of the control output to the required set points. Furthermore, the analysis of the regulation error's dynamic under the considered assumptions leads us to conclude that exponential stability is also reached. The controller is implemented via numerical experiments in two examples to generalize the applicability of the proposed approach by considering continuous stirred‐tank reactors models. The first case considers autocatalytic chemical oscillatory reactions that induce chaotic behaviour. For the second case, a process of acetone, butanol, and ethanol (ABE) fermentation through Clostridium acetobutylicum is considered. The proposed strategy shows an adequate performance because it can reach the required set point without long time settings and overshoot. A comparison with a smooth sliding‐mode and a standard proportional‐integral (PI) controller indicates the advantages of the proposed control approach.

A unified approach to modeling and stability equivalence analysis for grid-forming and grid-following converters

With the increasing penetration of renewable energy generation, the large-scale integration of grid-connected converters, serving as interfaces, has led to the characteristics of a weak grid with low strength and low inertia, resulting in insufficient stability of existing grid-following (GFL) converters. Grid-forming (GFM) converters, by emulating the characteristics of traditional synchronous machines, can operate stably in weak grids, but their introduction creates a complex operational state with mixed modes, presenting unprecedented challenges to the system. To address this, this paper first analyzes the structure and GFM/GFL control strategies of grid-connected converters; based on this, a comprehensive model framework for GFM/GFL converters is established, and the control of the converters is divided into three parts: LCL with the grid, output control, and power control, each modeled with a small-signal approach; using the established small-signal models, the stability of GFM/GFL converters under different grid short circuit ratios (SCR) is analyzed. Finally, a 20 kW test platform was constructed, and the correctness of the modeling and analysis was jointly verified using simulation frequency sweep methods and experimental time-domain stability analysis techniques.

Finite-time adaptive control of output constrained nonlinear systems under deception attacks

Finite-time adaptive control of output constrained nonlinear systems under deception attacks

Event‐triggered output quantization control for asynchronously switched interval type‐2 fuzzy systems

AbstractThis article considers exponential stabilization (ES) of switched interval type‐2 (SIT2) fuzzy systems with asynchronous switching control. The SIT2 fuzzy system switches from one mode to another according to transition probabilities (TPs). A general SIT2 fuzzy quantized event‐triggered output controller (QETOC) is designed to save the communication resources. The QETOC employs distinctive membership functions from those of the IT2 fuzzy model and switches with mode‐pendent switching delay, which is more practical than asynchronously switched control techniques with a common switching delay and control schemes without TP. By designing discretized multiple Lyapunov function (DMLF) and using convex combination technique, sufficient conditions formulated by linear matrix inequalities (LMIs) are obtained to ensure that the DMLF does not ‘jump high’ at the moment of switching, and hence the conservatism of obtained results is significantly reduced since no additional dwell time is needed for the stabilization. It is discovered that the SIT2 fuzzy system is not necessary to be unstable on mismatched intervals, and it can be unstable on matched intervals. The advantages of theoretical analysis are verified by numerical simulations, and the classical assumption that each subsystem is unstable on mismatched intervals is conservative for control design.

Temporal patterns of food control outputs and outcomes and effects of targeted control interventions on compliance in food service establishments in Finland

Food control inspections are an essential control measure to ensure compliance, and it is important to understand possible patterns within inspections and their outcomes when developing food control. In this study, we analysed food control inspection reports (n = 86 223) concerning Finnish food service establishments from 2016 to 2021 to reveal temporal patterns in food control outputs and outcomes and the possible reasons behind them, and to evaluate the effects of targeted control interventions on inspection grades. The analyses revealed that the proportions of non-compliances were high throughout the study period in several inspected issues, such as temperature management (7.1–8.1%) and cleanliness (4.4–5.3%). Moreover, the inspection grades improved in only one of sixteen inspection subsections, but in five subsections the proportion of non-compliances increased significantly within the study period (linear regression analysis) and in seven subsections the inspection grades were inferior during the COVID-19 pandemic compared to the pre-pandemic years. In addition to the long-term variation in the level of non-compliances, we observed seasonal variation, with higher proportions of non-compliances in summer compared to other times. This study also showed that targeted food control interventions may influence both the number of inspections and the level of observed non-compliances. We also observed that almost half of the annual pre-planned inspections were made in the proximity of the inspection time in the previous year (44.6% within 30 days), decreasing the surprise factor of the inspections. These results can be used in developing the effectiveness of food control.

Dynamic Control Analysis of Various Side‐Stream Quaternary Extractive Distillation Configurations

AbstractA thermally coupled distillation technology can bring energy‐saving benefits, but it poses challenges to process control. This article explores dynamic control of different side‐stream quaternary extractive distillation configurations. One the one hand, the open‐loop controllability of these processes is analyzed in terms of various criteria by the control design interface technology of Aspen Plus Dynamics. On the other hand, their control structures are established and examined by introducing large feed flow and composition perturbations. The results show that the triple‐side‐stream distillation still performs the best state and input–output controllability in spite of the strongest nonlinearity, and is also well resistant to large feed perturbations using a simple control structure.

Wavelength-Dependent Multistate Programmability and Optoelectronic Logic-in-Memory Operation from the Narrow Bandgap pNDI-SVS Floating Gate.

This study introduces wavelength-dependent multistate programmable optoelectronic logic-in-memory (OLIM) operation using a broadband photoresponsive pNDI-SVS floating gate. The distinct optical absorption of the relatively large bandgap DNTT channel (2.6 eV) and the narrow bandgap pNDI-SVS floating gate (1.37 eV) lead to varying light-induced charge carrier accumulation across different wavelengths. In the proposed OLIM device comprising the p-type pNDI-SVS-based optoelectronic memory (POEM) transistor and an IGZO n-type transistor, we achieve controllable output voltage signals by modulating the pull-up performance through optical wavelength and applied bias manipulation. Real-time OLIM operation yields four discernible output values. The device's high mechanical flexibility and seamless surface integration among the paper substrate, pNDI-SVS, parylene gate dielectric, and DNTT region render it compatible for integration into paper-based optoelectronics. Our flexible POEM device on name card substrates demonstrates stable operational performance, with minimal variation (8%) after 100 cycles of repeated memory operation, remaining reliable across various angle measurements.

Induced ℒ∞ control for continuous-time nonlinear systems

In this paper, the problem of induced L ∞ control in the presence of disturbance signals in the control output of continuous-time nonlinear systems is considered. Under the condition that the system control output has a disturbance signal, the expected design conditions of the controller that satisfy the asymptotic stability and the specified performance are given. The sufficient conditions for such an induced L ∞ controller are expressed in terms of linear matrix inequalities (LMIs). Finally, the effectiveness and feasibility of the proposed induced L ∞ control design strategy is illustrated by a tunnelling diode circuit.

Output voltage control of DAB converters based on uncertainty and disturbance estimation.

The dual active bridge (DAB) converter is a power electronic device commonly used for DC voltage regulation and stabilization. However, during its control process, external disturbances, load variations, input voltage variations, switching tube voltage drops, dead time, etc. lead to errors in the control output, thus reducing the control accuracy of the system. Therefore, this article propose a robust control scheme for the output voltage based on uncertainty and disturbance estimator. In this article, an average small-signal model of the dual active bridge converter was established in terms of the basic principles and operation mechanisms, simplifying the controller's design. Then, the basic principles of the uncertainty and disturbance estimator (UDE) are introduced. The small-signal model of the dual active bridge (DAB) converter is applied to the UDE to minimize output voltage error by enabling the controller to directly regulate the shift ratio. Finally, this article discusses the application and effectiveness of the uncertainty and disturbance estimator (UDE) in the simulation and control of dual active bridge (DAB) converters. A series of experimental comparative studies are conducted, demonstrating that this scheme offers significant advantages in suppressing system uncertainties and disturbances.

Fault-Tolerant Control of Floating Wind Turbine With Switched Adaptive Sliding Mode Controller

The fast-growing development of floating wind turbines demands control systems capable of both reducing output power fluctuations and fault-tolerant function. In this paper, we propose an adaptive switched sliding mode controller to enhance the performance of floating wind turbine systems in the presence of environmental uncertainties and actuator faults. A control-oriented switched linear model for floating wind turbines is introduced, considering the average dwell time. Based on the proposed controller, a full-order state observer and an adaptive law compensate for the debilitated control outputs resulting from detecting errors, disturbances, and faults. The control parameters are derived by solving stability theorems, which are proved by the Lyapunov stability theory, linear matrix inequality technique, and average dwell time technique. The proposed model and controller are validated on the NREL 5MW wind turbine and spar-buoy platform using the high-fidelity fatigue, aerodynamics, structures, and turbulence (FAST) code. The performance of the proposed controller is compared with an optimal gain-scheduling proportional-integral controller under different wind-wave combined conditions. The results show that the proposed controller improves the power quality and attenuates mechanical loads of floating wind turbine under healthy and faulty conditions. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Floating wind turbines have drawn significant interest in renewable energy. When operating in the ocean far from shore, it is of great importance for floating wind turbines to have fault-tolerance capabilities for achieving stable power quality when faults occur in one or more components. A challenging problem is how to mitigate the fault effects on the wind turbine system. This paper proposes an adaptive fault-tolerant control strategy in the case of actuator fault occurrence in floating wind turbines.

Fuzzy Neural Network Control for a Reaction Force Compensation Linear Motor Motion Stage

Technological progress and market expansion in the semiconductor industry require ultra-precise and high-speed processing and motion systems. However, even though reaction force compensation (RFC) linear motor motion stages help reduce the transmitted reaction force, the residual vibration of the movable magnet track after motion acts as a disturbance, affecting settling time and tracking performance. To address this issue, this study introduces a fuzzy neural network controller for an RFC linear motor motion stage. Since non-linear factors, such as frictional forces from guide rails, make it difficult to accurately model the system, a Nonlinear Autoregressive Neural Network (NARX) is used to identify the nonlinearity from displacement and servo control outputs. The fuzzy logic controller, which takes into account the error and error rate, is then combined with the inverse model controller of NARX. Finally, the fuzzy neural network controllers are integrated with the existing PIV (proportional-integral-velocity) control in feedforward configurations. The experiments demonstrate the potential performance improvements of the proposed approach over the PIV controllers.

A Sub-Domain-Awareness Adaptive Probabilistic Event-Triggered Policy for Attack-Compensated Output Control of Markov Jump CPSs With Dynamically Matching Modes

A Sub-Domain-Awareness Adaptive Probabilistic Event-Triggered Policy for Attack-Compensated Output Control of Markov Jump CPSs With Dynamically Matching Modes

Linear dispersion (GDD) design using grating group

Precise control of dispersion output holds paramount significance across domains such as optical fiber communication, time stretching, and spectral interferometric ranging. In comparison to other dispersion elements, like prisms, gratings are widely applied in the field of dispersion control due to their advantages of broad spectral range, tunability, and high resolution. Moreover, linear dispersion is the most desired characteristic by designers in most cases. Here, we develop a dispersion model for grating groups to determine the optimal structural parameters for achieving linear dispersion in high-order grating arrays. Based on our model, we provide corresponding parameter selection methods that allow for quantitative design of the size and slope of output dispersion by adjusting input parameters such as angle, distance, and parallelism. Additionally, we experimentally establish a dispersion interferometry structure based on the grating ensemble that validates our proposed approach's capability for linear dispersion output (linearity better than 0.9998). We believe that our approach is universally significant and contributes to enhancing the performance of dispersion interferometric measurement systems, chirp amplification systems, and other related systems.

Uncovering Research Clusters in Job Satisfaction and Organizational Commitment: A VOSviewer Approach

Job satisfaction and organizational commitment are two key concepts that have attracted the attention of researchers and practitioners for a long time. Job satisfaction refers to how much an employee feels happy or satisfied with the work they do. The scope of work that employees do is connected to other factors, such as the work environment, as well as horizontal and vertical relationships in the workplace. On the other hand, organizational commitment refers to the employee's attachment to the organization. This study examines job satisfaction and organizational commitment in various industries using systematic Bibliographic Review. The data used is 150 articles in the Emerald database from 2019 to 2024. The keywords used in the search are "Job Satisfaction" AND "Organizational Commitment". The 150 articles were then processed using VOSviewer and then analyzed to find research maps and future research recommendations. shows that there is still an open possibility of research on variables that have not been explored much by previous studies. From the network visualization analysis, several variables that are still interesting to study include job dissatisfaction, psychological empowerment, remote workforce, social support, socio emotional resources, spiritual gain, material gain, salary satisfaction, supervisor citizenship behavior, and transparency practice. Based on overlay visualization analysis, several interesting variables to be studied include spiritual leadership, capability control, occupational strain, conscientiousness, and supervisory commitment. Meanwhile, based on the density visualization display, the variables that can still be explored include inclusive leadership, supervisory commitment, individual initiative, output control, psychological empowerment, and voluntary turnover intention. Keywords: VOSviewer, Systematic Bibliographic Review, Job Satisfaction, Organizational Commitment, Human Capital Management

Coordinated finite‐time control of multiple motors with saturation constraints

AbstractA multi‐motor coordinated tracking control strategy based on a disturbance sliding‐mode observer and an anti‐saturation non‐singular fast‐terminal sliding mode is proposed to address the issues of slow convergence and controller output saturation in multi‐motor coordinated control systems. Firstly, a mathematical model of a multi‐motor traction system considering uncertain parameter perturbations, external disturbances, and dead zones was established. Secondly, a disturbance sliding‐mode observer was designed based on the mathematical model to eliminate motor disturbances and estimate the torque. The observer's forward compensation was added to design a total‐consensus‐based fast non‐singular terminal sliding‐mode controller. Then, a fast anti‐saturation auxiliary system with fast finite‐time convergence was constructed. Finally, a comparative experiment was conducted with traditional anti‐saturation sliding‐mode control to demonstrate that the proposed method had faster convergence, stronger disturbance rejection, and better tracking performance in the presence of multi‐motor parameter perturbations, unknown disturbances, and input saturation.