Performance Of Control Scheme Research Articles

Effects of different load variation rates on the operational stability in an S–CO2 Brayton cycle coupled natural circulation lead-cooled fast reactor

The thermal inertia results in net heat absorption in natural circulation lead-cooled reactors during power variation processes, increasing the risk of core meltdown. In this study, a dynamic simulation model of a natural circulation lead-cooled fast reactor coupled with a supercritical carbon dioxide Brayton Cycle power generation system has been developed based on Vpower. The influence of thermal inertia on system operating temperature under different power variation rates was discussed. The results indicate that during power reduction, different decline rates only affect the temperature variation range of the system without impacting the final stable state. However, during power increase, different ramp rates not only affect the temperature variation range but also lead to varying degrees of system temperature rise. To address this issue, an optimized turbine throttling scheme is proposed. Compared to the original plan, the new plan successfully stabilizes the temperature at the rated value after increasing the system power. This study provides insights for the operation control strategy of similar reactor types.

Observer-Based Fault-Tolerant Control for Uncertain Robot Manipulators without Velocity Measurements

In recent years, robot manipulator arms have become increasingly prevalent and are playing pivotal roles across various industries. Their ability to replace human labor in arduous and hazardous tasks has positioned them as indispensable assets. Consequently, there has been a surge in research efforts aimed at enhancing their operational performance. The imperative to improve their efficiency and effectiveness has garnered significant attention within the research community. In this study, a novel fault-tolerant control (FTC) scheme for robot manipulators to handle the effects of the unknown input is proposed to aid robots in achieving good tracking performance. In the first step, an extended state observer (ESO) is constructed to approximate both velocities and the unknown input in the robot system. The observer offers estimation information with good accuracy and quick convergence. The estimated signals are then combined with computed torque control (CTC), which is a useful control technique for trajectory tracking of robot manipulator systems, to construct an active FTC to decrease the influences of the unknown input. The proposed algorithm does not require velocity measurement in the design process. In addition, with a novel design approach, the combination of controller and observer provides a novel control signal that delivers higher tracking performance compared to the traditional design approach. The global and asymptotic stability of the suggested technique is proved through the Lyapunov theory. Finally, simulations are implemented on a 2-degree-of-freedom (DOF) robot manipulator to validate the efficiency of the proposed controller–observer method.

Research on Simulation and Power Regulation Control Strategy of Fengning Variable-Speed Pumped Storage Unit

Abstract Variable-speed pumped storage unit demonstrates rapid power response and flexible adjustment of unit speed, significantly enhancing unit operational efficiency and the power system’s stability. This paper focuses on simulating the control strategy of the Fengning variable-speed pumped storage unit. First, the water pump/turbine and motor models are established based on the relevant parameters of the Fengning variable-speed pumped storage unit. Second, according to the distinct responsibilities of the governor and the excitation system, the control strategies of the unit in the power priority mode and speed priority mode are designed. Finally, we compare and analyze the power response characteristics of a single-machine infinite bus system under various operating conditions and control strategies. We also summarize the applicable scope and existing problems under different operating conditions.

Recent advances on control strategies for microgrid islanding operation

In order to achieve the national strategic goals of peaking carbon emissions by 2030 and achieving carbon neutrality by 2060, the electricity-energy-ecosystem is undergoing significant transformation, presenting new opportunities for the development of new energy generation technologies. With the widespread adoption of renewable energy sources, such as solar and wind energy, microgrids have begun to play a prominent role as small-scale power systems. Microgrids, as small, autonomous power systems, have received significant attention in recent years. Microgrids can enhance energy sustainability by integrating renewable energy resources and energy storage systems, while also providing the capability to maintain power supply during main grid failures or planned maintenance. This article aims to review the advances in control strategy research for microgrid islanding operation, with a focus on the classification of control strategies, design principles, and their impact on microgrid stability. The article also explores potential directions for future research to enhance the efficiency and reliability of microgrid islanding operation, providing valuable references for future studies.

A multivariable control strategy based on fuzzy logic interference rule for a solar-driven, direct air-cooled H[formula omitted]O-LiBr absorption chiller

The operation of a solar-driven H2O-LiBr Absorption Chiller (AbC) is subjected to various limitations regarding its ability to satisfy efficiently the required cooling demand while avoiding certain internal conditions, such as H2O-LiBr solution crystallization and water freezing. These circumstances would lead to problematic situations and jeopardize the continuous operation of the system. Thus, the development of accurate control strategies is an issue of interest. A new operational control strategy approach is introduced and tested through simulation studies, by employing a transient model of the entire solar cooling application. A prototype under development is used for the parametrization of the direct air-cooled AbC model used in the simulations. The developed control strategy aims to minimize the electrical consumption of the auxiliary components of the AbC (i.e., fan, pumps) during the partial load operation period, by using a fuzzy logic interference rule for determining the cooling capacity demand and then applying an optimization algorithm for determining the velocity of the auxiliary components. Within the proposed control strategy, a fast-calculation model is embedded, which predicts the chiller’s capacity under variable external conditions and partial load operation. The electrical COP is increased up to 2.2 times with respect to a baseline case, based on a basic two-step control strategy, while allowing the chiller to operate smoother, minimizing the crystallization and freezing risk.

Design and Test of Intelligent Farm Machinery Operation Control Platform for Unmanned Farms

The unmanned farm control platform is of great significance in promoting the supervision of farm production with less manpower or autonomous operation of farm machinery and the construction of farm informatization. Addressing the existing control platform for farm location information acquisition is time-consuming, labor-intensive, and lacks the whole process control of multiple types of farm machinery. In this paper, we propose an Internet of Things (IoT) control scheme for intelligent farm machinery operation of unmanned farms and design the access standards for multiple types of farm machinery, as well as realize the remote control of intelligent farm machinery operation by constructing a remote control model. A high-precision map construction method is designed to improve the DeepLabV3+ algorithm to identify fields and roads. The control models of path planning, remote task, remote control, and safety system are built to achieve the remote control of intelligent agricultural machinery operation. The proposed technology is implemented in the platform integration and application tests are carried out. The error of the constructed high-precision map is less than 3 cm, the completeness rate of the automatic boundary extraction rate is 96.71%, and the correctness rate is 95.63%, which can be used to obtain the boundary instead of manual labeling or on-site point picking. The use of the platform for the simultaneous control of three farm machinery operations reduces the number of people in operation and production and reduces the professional requirements of the personnel, which will promote the management of the entire farm by one person or even by no one in the future.

Research on the optimization of the clean heating system for regional residential buildings based on the multi-objective optimization strategy

For the residential building district heating (RBDH) system, choosing the appropriate combination of heat sources according to local conditions is the key to improving economic efficiency. In this study, three climatic regions in China were selected, namely, a hot summer and cold winter region, cold region, and severe cold region. Among them, Nanjing, Tianjin, and Shenyang were selected as typical representative cities in the hot summer and cold winter region, cold region, and severe cold region, respectively. Taking the levelized cost of heat (LCOH) as the economic evaluation index and considering the carbon emission cost of the system operation, the energy consumption and the CO2 emissions were analyzed. TRNSYS software was used to simulate and analyze the system performance. The multi-objective optimization based on a genetic algorithm was proposed to optimize system parameters. From an economic point of view, the SA system was suitable for the hot summer and cold winter region, the SAS system was suitable for the cold region, and the SE system was suitable for the severe cold region. The operation control strategy based on quality adjustment can reduce heating energy consumption and maintain indoor temperatures at approximately 20°C. The proportion of clean energy heating in the optimized heating system decreased after the multi-objective optimization strategy. However, the initial investment and maintenance costs of the system were reduced, which reduced the LOCH of the system. Therefore, the multi-objective optimization strategy can effectively reduce the heating costs.

Constraint tightening-based control for small-satellite formations using differential aerodynamic forces

Aerodynamic forces hold significant promise for controlling small-satellite formations in low Earth orbit. However, significant challenges still exist regarding complex input constraints and their application to multi-satellite formations. This paper proposes a constraint tightening-based control scheme for small-satellite formations, utilizing differential drag and lift as actuating forces. Two attitude adjustment strategies, namely the reorientation strategy and the single-radial rotation strategy, are compared in terms of their control effectiveness and applicability. Relative aerodynamic coefficients are employed as control inputs in view of their solid reachable region, followed by the development of a decoupling algorithm for determining pointing angles. Through a method that tightens the reachable region using liner models, the input constraints are linearized and can be explicitly expressed. Subsequently, an observer-based Model Predictive Control (MPC) algorithm is formulated to meet these linearized input constraints and provide feedforward compensation for system disturbances. This discrete algorithm enables practical onboard implementations owing to its low computational complexity. Additionally, a concept of overall computation for all satellites’ attitudes is proposed to adapt the control scheme for multi-satellite formations. Hardware-in-the-loop simulations are conducted to evaluate the control scheme's performance in along-track and circular formations, accounting for uncertainties in aerodynamic forces and attitude dynamics.

Cooling performance and optimization of a thermal management system based on CO2 heat pump for electric vehicles

Efficient integrated thermal management scheme is crucial for improving the driving range, thermal comfort, and safety of electric vehicles. Compared with the synthetic refrigerant heat pump indirect cooling/heating on the vehicle electrical system, the natural refrigerant CO2 heat pump direct thermal controlling integrated into the thermal management system has advantages in the thermal cycle performance and environmental friendliness. The present study proposed a thermal management system based on CO2 heat hump with multiple working modes for enhancing vehicle energy utilization coefficient. The system thermal performance under the World Light Vehicle Test Cycle was investigated via energy and exergy analyses. The operational control strategies of the thermal management system were optimized for the thermal controls of the cabin, battery and motor. The results show that the minimum exergy destruction of the thermal system occurs at the optimal discharge pressure corresponding to the highest coefficient of performance. Ensuring two-phase latent heat transfer for battery cooling is the most effective measure to maintain battery temperature uniformity via dynamic collaborative regulation of expansion valves’ openings and compressor speed. Compared with constant expansion valve’s opening, the coefficient of performance of the system can be improved by a maximum of 10% with the saturated CO2 vapor at the outlet of battery cooling plate. Due to the low thermal capacitance and minimal thermal inertia of driving motor, its cooling performance is significantly influenced by the heat generation rate and refrigerant flow. Optimal motor cooling efficiency is achieved when controlling the refrigerant quality to 0.85 at the cooling passage outlet. Under the World Light Vehicle Test Cycle, the thermal management system effectively regulated the temperatures across different operating modes while operating at optimal discharge pressures.

Comprehensive evaluation of the working mode of multi-energy complementary heating systems in rural areas based on the entropy-TOPSIS model

BackgroundThe establishment of a multi-energy complementary heating system (MECHS) using abundant renewable energy is currently an effective way to solve the rapid growth of heating demands in rural areas. However, coupling schemes for different energy sources have become a critical barrier to the MECHS development. ObjectivesThe entropy-TOPSIS method was used to conduct a comprehensive evaluation of MECHS, which provided a basis for optimizing system operation strategy. MethodsWe built a test platform for MECHS based on solar-biomass-electricity energy in Tumxuk, Northwest China. Frist, six working modes were established according to the system operation control strategy. Second, we constructed the evaluation indexes of MECHS considering energy, environment and economy and determined their weights using entropy weight method. Third, the TOPSIS model was used to perform a comprehensive evaluation of the different working modes to identify optimal energy supply schemes. ResultsOur case study showed that the MECHS operated stably and met the indoor temperature demands of rural houses in cold regions. To maximize the heating efficiency of the system, it is necessary to reduce the types of energy appropriately. Next, based on entropy-TOPSIS model, the recommended order of energy supply mode for heating systems were solar-biomass energy (0.6202), solar-biomass-electric energy (0.6152), solar-electric energy (0.5895), biomass energy (0.4075), biomass-electric energy (0.3680), and electrical energy (0.3603). We found that the optimal energy supply mode was solar-biomass. ConclusionOur results indicated that the entropy-TOPSIS model could provide practical recommendations for the design and operation strategies of MECHS in cold rural areas.

A new tool for energy conservation in operating room: The role of machine learning models in enhancing airflow control

Maintaining high ventilation rates in operating rooms (ORs) is critical to ensure the safety of healthcare professionals and patients. Yet, the significant energy consumption associated with ventilation systems is a growing global concern. While traditional approaches have predominantly focused on optimizing ventilation design, limited attention has been given to operational control strategies. This study aims to control ceiling air supply speed by exposure aerosol concentrations exhaled by the patient. It achieves this by integrating empirical data with machine learning (ML) models, effectively balancing the need for maintaining optimal ventilation conditions and ensuring a safe aerosol exposure concentration. Experimental results from a full-scale OR setup, manipulating ceiling air supply speed, respiratory flow rate, and surgical bed height, generated 81 datasets. These datasets served as the basis for assessing the performance of 11 ML models. Notably, the extra trees (ET) and multi-layer perceptron (MLP) models outperformed the others, exhibiting impressive coefficient of determination (R2) values of 0.954 and 0.904, respectively. Moreover, the models were further enhanced by assessing their robustness with Gaussian noise and interval prediction. This study presents a novel approach that holds significant relevance for the practical control of ventilation systems, particularly with regard to health and energy efficiency considerations.

A decentralized approach for the aerial manipulator robust trajectory tracking.

This paper introduces a new decentralized control strategy for an unmanned aerial manipulator (UAM) constrained to the vertical plane. The control strategy comprises two loops: the first compensates for the aerial vehicle's impact on the manipulator; and the second one implements independent controllers for the aerial vehicle and the manipulator. The controller for the aerial vehicle includes an estimator to compensate for the dynamic influence of the manipulator, even if it is affected by external wind-gust disturbances. The manipulator has two revolute joints; however, it is modeled as an dynamically equivalent manipulator, with one revolute and one prismatic joint. The proposed control strategy's performance is evaluated using a simulator that includes the vehicle's aerodynamics and the manipulator's contact force and moment.

Experimental investigation on the open cathode air-cooled proton exchange membrane fuel cells: Optimum operating parameters and control strategies

Operating parameters and control strategies are crucial for the performance of open cathode air-cooled proton exchange membrane fuel cells. In present study, effects of hydrogen pressure, anode purging ratio and stack temperature on an open cathode air-cooled PEMFC with 40 single cells are experimentally explored. Comprehensive evaluations of operating parameters and control strategies are adopted from multiple aspects including output performance, stability, hydrogen consumption, and system efficiency. The results show that an anode pressure of 60–70 kPa and a 4% purging ratio can achieve not exceeding 5% ripple coefficient and not less than 35% system efficiency, and the optimum stack temperature is proved to be 54–60 °C. Adaptive purging strategies and temperature control strategies that vary with current are summarized which can be used for programming applications. Finally, these control strategies are executed under simulated loads to observe stack’s dynamic response and confirmed to maintain stable operation of the stack.

Research on Evaluation Method of Wind Farm Wake Energy Efficiency Loss Based on SCADA Data Analysis

The large size of wind turbines and wind farm clustering aggravate the effect of wake on output power, resulting in a reduction in the economic benefits of wind farms. This paper took the actual operating turbines of an onshore wind farm in China as the research object and analyzed the influence of wake on energy efficiency loss by combining SCADA data. The research established a complete loss assessment method and proposed the corresponding evaluation criteria. The results showed that typical wind turbines seriously affected by wake accounted for 32.8% of the wind farm. The actual output power was only 84.2% of the theoretical output power at the lowest month, and the wake loss of the wind farm is serious. The economic efficiency of the wind farm is lower in the summer months (June–August). The study can provide a theoretical basis for the arrangement of wind farms and the development of an operation control strategy.

A Layered Parallel Equaliser Based on Flyback Transformer Multiplexed for Lithium-Ion Battery System

An effective equaliser is crucial for eliminating inconsistencies in the connected serial batteries and extending the life of the battery system. The current equalisers generally have the problems of low equalisation efficiency, slow equalisation speed, and complex switching control. A layered parallel equaliser based on a flyback transformer multiplexed for a lithium-ion battery system is proposed. The equaliser employs both hierarchical and parallel equalisation techniques, allowing for simultaneous processing of multiple objectives. This enhances both the efficiency and speed of the equalisation process. The efficiency of equalisation can be further improved by implementing PWM control with deadband complement. Additionally, the flyback transformer serves as an energy storage component for both layers of the equalisation module, resulting in a significant reduction in the size and cost of the equaliser. The circuit topology of the equaliser is presented, and its operational principle, switching control, and equalisation control strategy are analysed in detail. Finally, an experimental platform consisting of six lithium-ion batteries is constructed, and equalisation experiments are conducted to verify the advantages of the proposed equaliser in terms of equalisation speed, efficiency, and cost.

Control strategy of bidirectional DC/DC converter under variable load state

To improve the stability of DC/DC converters under multiple load conditions, the control strategy of Buck-Boost bidirectional DC/DC converters under variable load conditions is studied in this paper, as well as the droop control strategy for parallel operation of two machines. Based on the topology and basic control strategy of the DC/DC converter, a load current feedforward compensation strategy to achieve ideal stability of output voltage during load switching is studied; then charging and discharging control switching strategy under external power supply is proposed, which achieves fast switching between charging and discharging by sampling battery current and load voltage; finally, a current sharing control method based on inductance current droop is proposed for the parallel operation of two machines, achieving the control effect of equal current sharing between the two modules. The effectiveness and feasibility of the control strategy were verified through prototype experiments.

An MV Hybrid Isolated DC Transformer for Wide Output Voltage Range Applications

DC transformer (DCT) is the key energy conversion equipment that converts medium voltage dc to low voltage dc. Aiming at the industrial loads requiring wide output voltage range and unidirectional power flow, a hybrid isolated DC transformer (HIT) as an alternative to the traditional MMC-DCT is proposed in this paper. It is composed by thyristors, diodes, and submodule (SM) based arms. The operation principle, circuit performance, and control strategy are introduced in detail. Particularly, a discontinuous input and continuous output currents (DICO) operation mode is further proposed to suppress submodule capacitor voltage ripple. Compared with the traditional MMC-DCT, HIT can save 50% SMs, 28% semiconductor cost and 46.3% total SM capacitance. The effectiveness and the theoretical analysis have been confirmed by both simulation and experimental results.

Novel Electric Propulsion System Analysis Method for Electric Vertical Takeoff and Landing Aircraft Conceptual Design

This paper proposes novel enhancements to the electric propulsion system analysis method for electric vertical takeoff and landing (eVTOL) aircraft conceptual design by considering the electrical characteristics of each electrical device in a more accurate manner. To this end, three modules for motor, inverter, and battery analysis are constructed using equivalent circuits and semi-empirical models. First, the motor analysis module is developed using equivalent circuit analysis with the operation control strategy for a permanent-magnet synchronous motor. Second, the inverter analysis module is built using average loss models for the switching and conduction losses. Third, the battery analysis module is improved using the near-linear discharge model to consider the voltage drop during operation. Moreover, additional modules, such as those for calculating the battery stack in series and parallel, as well as regression models for the motor and inverter performance parameters and consideration of the drive system type (direct or indirect, including a reduction gear), are implemented. A comparative study is presented from an analysis and design perspective while changing the drive system type (direct or indirect) and gear ratio, which highlights the importance of modeling electrical characteristics during eVTOL aircraft conceptual design.

Multitask control of aerial manipulator robots with dynamic compensation based on numerical methods

This paper presents a control scheme for aerial manipulators which allows to solve different motion problems: end-effector position control, end-effector trajectory tracking control and path-following control. The scheme has two cascaded controllers: i) the first controller is a minimum norm controller based on numerical methods, it solves the three motion control problems just by modifying the controller references. Also, since the aerial manipulator robot is a redundant system, i.e., it has extra degrees of freedom to accomplish the task, it is possible to set other control objectives in a hierarchical order. As a secondary objective of the control it is proposed to maintain a desired configuration for the robotic arm during the task. ii) The second cascade controller is designed to compensate the dynamics of the system which main objective is to drive the velocity errors to zero. The coupled dynamic model of the robotic system (hexarotor and robotic arm) is presented. This model is usually developed as a function of the forces and torques. However, in this work, it is written as a function of reference velocities which are usual references for these vehicles. The proposed control algorithms are given with the corresponding stability and robustness analysis. Finally, to validate the control scheme, experimental tests are performed in a partially structured environment with an aerial manipulator conformed by an aerial platform and a 3DOF robotic arm.

Further study on particle size, stability, and complexation of silver nanoparticles under the composite effect of bovine serum protein and humic acid.

Silver nanoparticles (AgNPs) are widely used due to their unique antibacterial properties and excellent photoelectric properties. Wastewater treatment plants form a pool of AgNPs due to the social cycle of wastewater. During biological treatment processes, the particle size and stability of AgNPs change. We studied the particle size changes and stability of silver nanoparticles in the presence of bovine serum albumin (BSA) and humic acid (HA). The experimental results indicated that silver nanoparticles can complex with the functional groups in BSA. For AgNP-BSA composites, as the BSA concentration increases, the size of the silver nanoparticles first decreases and then increases. AgNPs can combine with the amide, amino, and carboxyl groups in HA. As the concentration of HA increases, the particle size and large particle size distribution of AgNPs increase. This increasing trend is more obvious when the HA concentration is lower than 20 mg L-1. When HA and BSA exist at the same time, HA will occupy the adsorption sites of BSA on the surface of AgNPs, and the AgNP-HA complex will dominate the system. This study aims to provide key operational control strategies for the process operation of wastewater treatment plants containing AgNPs and theoretical support for promoting water environment improvement and economic development such as tourism.