Control System Research Articles

Tracking Differentiator-Based Identification Method for Temperature Predictive Control of Uncooled Heating Processes

The temperature control of uncooled heating processes presents challenges due to a substantial lag and the absence of active cooling mechanisms, which can lead to overshoot and oscillations. To address these issues, we propose an anti-disturbance identification method based on a tracking differentiator (TD) and an input-constrained temperature predictive control (ICTPC) strategy. Our approach specifically considers the impact of unknown disturbances on model identification within a second-order heating process. By employing a TD to differentiate the input and output signals, we effectively minimize the identification error caused by low-frequency disturbances, yielding a robust anti-disturbance identification technique. Following this, we establish input constraints to limit the amplitude and variation of the control input, ensuring a more controlled and predictable system response. Using the identified model, an ICTPC algorithm is designed to achieve stable temperature control in uncooled heating processes. Experimental results from a typical uncooled heating system demonstrate that our method not only significantly reduces overshoot but also effectively mitigates temperature fluctuations, leading to enhanced control performance and system stability. This study provides a practical solution for temperature control in systems without cooling capabilities, offering substantial improvements in the efficiency and quality of industrial production processes.

Delay-dependent stability criteria for LFC systems with electric vehicles: A delay-interval-based piecewise Lyapunov functional approach

This paper studies the delay-dependent stability problem of single-area load frequency control (LFC) systems with electric vehicles. A novel Lyapunov-Krasovskii functional (LKF), called the delay-interval-based piecewise Lyapunov functional, is introduced. This innovative LKF approach allows for the construction of distinct LKFs within specific delay intervals, relaxing the requirement that a single LKF must exist for the entire delay interval. By incorporating the zero equation method, less conservatism delay-dependent stability criteria for LFC systems are obtained. Simulations are performed to illustrate the effectiveness and superiority of the presented methods.

Ultra-short term wind power prediction method based on LightGBM and transformer

Abstract Accurate ultra-short-term wind power prediction is very important for the safe and stable operation of the power system. At present, most wind power forecasting systems use numerical weather forecast data and the data collected by the Supervisory Control And Data Acquisition (SCADA) system. However, these data have the characteristics of high data dimension, feature redundancy, and feature correlation. Therefore, in the process of ultra-short power prediction, it is necessary to select features with high power correlation and low cross-correlation between features. In this paper, a feature selection method for wind power prediction based on LightGBM is proposed to calculate the importance of all features and determine the preliminary selected features. Then, the maximum information coefficient is used to construct the correlation discriminant matrix, according to which the features with similar importance in a single screening are evaluated, and the input features with high similarity are discarded. In addition, in order to improve the accuracy of the system’s wind power prediction, this paper uses the effective features extracted by LightGBM to design an ultra-short-term power prediction method based on Transformer. The results show that the RMSE of ultra-short-term wind power prediction is 7.3%.

Quality control and evaluation system for general thoracic surgery

Quality control and evaluation system for general thoracic surgery

Recent achievements in nonlinear dynamics, synchronization, and networks.

This Focus Issue covers recent developments in the broad areas of nonlinear dynamics, synchronization, and emergent behavior in dynamical networks. It targets current progress on issues such as time series analysis and data-driven modeling from real data such as climate, brain, and social dynamics. Predicting and detecting early warning signals of extreme climate conditions, epileptic seizures, or other catastrophic conditions are the primary tasks from real or experimental data. Exploring machine-based learning from real data for the purpose of modeling and prediction is an emerging area. Application of the evolutionary game theory in biological systems (eco-evolutionary game theory) is a developing direction for future research for the purpose of understanding the interactions between species. Recent progress of research on bifurcations, time series analysis, control, and time-delay systems is also discussed.

Research on intelligent control and emergency response system for power cable tunnels based on AI image recognition and ultra-wideband technology

Research on intelligent control and emergency response system for power cable tunnels based on AI image recognition and ultra-wideband technology

Distributed Electric Propulsion and Flight Control Concept to Meet EASA SC-VTOL-01 10‐9 Catastrophic Failure Criteria

The objective of the current work was to develop an all-electric distributed propulsion and flight control (DPFC) architecture that will have no more than 10‐9 catastrophic failures per flight hour (pfh). The DPFC architecture was broken into four system design teams: (i) electrical power and distribution system, (ii) drive and power system, (iii) thermal management system, and (iv) flight control system. System designs were updated and iterated upon, working with reliability and safety analysis teams to develop compliant designs. The firm designs were reflected in a preliminary system safety assessment (PSSA) for initial verification of compliance. Additionally, design and analysis excursions are presented in which aircraft attributes were modified to investigate sensitivities to propulsion type, number of rotors, and control schemes. Excursion results found that all aircraft evaluated likely have paths to comply with the stringent, probabilistic catastrophic failure criteria. However, stability and control models showed large power transients that must be addressed, and PSSA results show that future work is needed in single load path structures, high voltage power storage and distribution, and motor/rotor overspeed protection.

Enhancing Delivery Efficiency on the MR-Linac: A Comprehensive Evaluation of Prostate SBRT using VMAT

PurposeLong treatment sessions are a limitation within MRIgART. This work aims for significantly enhancing the delivery efficiency on the MR-linac by introducing dedicated optimization and delivery techniques for VMAT. VMAT plan and delivery quality during MRIgART is compared to step-and-shoot IMRT for prostate SBRT. Methods and MaterialsTen prostate patients previously treated on a 1.5T MR-linac were retrospectively replanned to 36.25 Gy in five fractions using step-and-shoot IMRT and the clinical Hyperion optimizer within Monaco (Hyp-IMRT), the same optimizer with a VMAT technique (Hyp-VMAT), and a research-based optimizer with VMAT (OFL+PGD-VMAT). The plans were then adapted onto each daily MRI dataset using two different optimization strategies to evaluate the ATP workflow: “optimize weights” (IMRT-Weights and VMAT-Weights) and “optimize shapes” (IMRT-Shapes and VMAT-Shapes). Treatment efficiency was evaluated by measuring optimization time, delivery time, and total time (optimization + delivery). Plan quality was assessed by evaluating OAR sparing. Ten patient plans were measured using a modified linac control system to assess delivery accuracy via a gamma analysis (2%/2mm). Delivery efficiency was calculated as average dose rate divided by maximum dose rate. ResultsFor Hyp-VMAT and OFL+PGD-VMAT the total time was reduced by 124 ± 140 seconds (p = .020) and 459 ± 110 seconds (p < 0.001), respectively as compared to the clinical Hyp-IMRT group. Speed enhancements were also measured for ATP with reductions in total time of 404 ± 55 (p<0.001) for VMAT-Weights as compared to the clinical IMRT-Shapes group. Bladder and rectum DVH points were within 1.3 % or 0.8 cc for each group. All VMAT plans had gamma passing rates greater than 96 %. The delivery efficiency of VMAT plans was 89.7 ± 2.7 % compared to 50.0 ± 2.2 % for clinical IMRT. ConclusionsIncorporating VMAT into MRIgART will significantly reduce treatment session times while maintaining equivalent plan quality.

Simulation-Based Evaluation of Advanced Threat Detection and Response in Financial Industry Networks Using Zero Trust and Blockchain Technology

The financial sector is increasingly facing advanced cyber threats, necessitating a shift from traditional security measures to more dynamic frameworks. This study presents a novel integration of Zero Trust architecture with hybrid access control system and blockchain technology to enhance security in financial institutions. Zero Trust enforces continuous authentication and dynamic access controls, while blockchain secures digital identities and transaction logs through its immutable ledger, ensuring data integrity and non-repudiation. The proposed framework, evaluated using OMNeT++ simulations enhanced by Ethereum-Ganache, shows improved detection accuracy, reduced false positives, and increased resistance to insider threats and other attacks. It also strengthens compliance with regulatory requirements through robust audit trails, providing enhanced protection for sensitive financial data.

Developing a virtual physical system for vortex-induced vibration studies of a bluff body

A virtual physical system (VPS) for VIV studies of a bluff body is developed to replace the actual physical systems. It can arbitrarily and accurately control and edit the physical parameters, including mass, damping ratio and spring stiffness, specifically for the mass-spring-damper system. The recursive Duhamel integral method (DIM) with unconditional stability was used for the VPS control system, addressing real-time noise filtering problem and simplifying the system as a single input and single output (SISO) one. Delay compensation and inertial force elimination methods were investigated and proposed to overcome the crucial unwanted damping effects. An experimental facility for VIV model tests by VPS was manufactured, and the bluff body model with a measurement system was specially designed to accurately sense the hydrodynamic force during VPS operation. Systematic verification experiments for parameter editing and control of an actual physical target system were conducted, showing that the VPS can reproduce the equivalent spring-damper-mass system in high fidelity with an accuracy error of less than 5%. VIV model tests for a bluff body at Reynolds numbers (Re= UD/υ, where U is the flow velocity, D represents the diameter of cylinder model, and υ is the kinematic viscosity coefficient) of 5.7E4 and 2.3E5 were performed using the VPS experimental facility, presenting well-repeated VIV responses at low Re and unexpected VIV response with a large amplitude of 2.4 D at high Re, which can cause severe fatigue damage for relevant structures. The present VPS will provide promising and powerful experimental tools for VIV studies of a bluff body to reveal the related sensitive parameter effects.

OPTIMIZATION OF HEAT CONSUMPTION IN CENTRAL HEATING SYSTEMS AT COMMERCIAL FACILITIES

Rising energy prices and stricter environmental regulations are exacerbating the problem of inefficient heat consumption in the commercial sector. Central heating systems of office buildings, shopping malls, and industrial complexes are often characterized by excessive thermal energy consumption, which leads to significant economic losses and a negative impact on the natural environment. The purpose of the study is to study the directions and trends of optimization in the field under consideration (taking into account modern technological capabilities, and economic factors). There are disagreements in the professional community about the priority of measures to improve energy efficiency: some experts prefer improving the thermal insulation of buildings, others — the introduction of intelligent control systems, and others — the integration of renewable energy sources. The present study demonstrates that the greatest effect is achieved with a systematic approach combining various initiatives. The conclusion is formulated that in the current conditions and the future, a comprehensive application of modern thermal insulation materials, highly efficient heating equipment, intelligent management mechanisms, and alternative energy sources is required. The article is of interest to engineers-designers of heating systems, energy managers of commercial facilities, specialists in energy efficiency of buildings, and heads of companies interested in optimizing operating costs and improving the environmental friendliness of their real estate.

Design and research of serial communication system based on virtual instrument technology

Abstract In the measurement and automation control system, serial communication has been connected between the acquisition hardware (lower computer) and the upper computer between the easiest to realize and the most economical way. In view of the traditional instrument itself is relatively bulky, inconvenient to carry, this paper adopts the virtual instrument development environment to realize the realization of serial communication, in order to complete the subsequent data acquisition. When compared with other software development environment, LabWindows/CVI platform comes with a function library to make the program writing simple and flexible. In this paper, we designed the realization method of serial communication based on virtual instrument Labwindows/CVI environment, completed the design and realization of serial communication between PC and lower computer (microcontroller) based on Labwindows/CVI environment, and applied it to the example of serial communication with microcontroller to realize the data communication function. Practical results prove that the serial communication system based on virtual instrument technology has the advantages of friendly user interface, high stability, convenience and reliability, and can reliably and accurately complete the communication, and provide strong technical support for the system to follow up data acquisition.

Design and experiment of coconut picking robot with climbing

Due to the height of coconut trees and the high risks associated with manual picking, there is a severe shortage of labor in the coconut picking industry in Hainan. To address this issue, a coconut picking robot was designed and constructed. In this study, the robot was mainly composed of tree climber and 3 degree of freedom (DoF) manipulator. The robot integrated two functions of tree climbing and coconut picking. The 3D model of the picking robot was designed through SOLIDWORKS. Furthermore, the statics and dynamics simulation of the robot were implemented through ANSYS and ADAMS. With STM32 as the core, an embedded remote control system based on CAN bus communication protocol was developed. And a multi-channel remote controller handle was used to control the robot to realize tree climbing and coconut picking. According to the test results, the robot could successfully climb trees up to 13.42 m tall. The average climbing time of coconut picking robot on 10 coconut trees was 152.3 s, and the average picking time was 222.1 s. Specifically, for coconut trees with height ranging from 7.03 m to 11.5 m, inclination ranging from 78° to 90° and diameter ranging from 21.08 cm to 30.20 cm, the average climbing time of the coconut picking robot was 147.7 s. The average climbing time for the remaining trees was 162.9 s. For the above types of trees, the robot could climb to the top of the trees more quickly, demonstrating better climbing performance. This study provides technical support for mechanized coconut picking and will inspire the development of coconut picking robots.

Research on intelligent control system of dynamic magnetic tubular linear compressor

Abstract Addressing the cooling power control issue of linear compressors, a PID controller based on a cubic spline improved grey wolf optimization (tri-GWO) algorithm was designed. The mechanical and electromagnetic characteristics of the linear compressor were used to construct the cooling power transfer function of the linear compressor. The effects of different control algorithms on the cooling power of the linear compressor were studied in Simulink, and the response speed, settling time, and robustness of different algorithms were compared based on the simulation results. Further analysis was conducted on the impact of different algorithms in PID control. The results show that in terms of stability and robustness, the tri-GWO-PID controller has an overshoot close to 0 and quickly stabilizes at the target cooling power; in terms of tracking, the tri-GWO-PID controller exhibits the best tracking performance with the smallest cooling power deviation. The research results provide a reference for the study of cooling power control of linear compressors.

FusionOC: Research on optimal control method for infrared and visible light image fusion

Infrared and visible light image fusion can solve the limitations of single-type visual sensors and can boost the target detection performance. However, since the traditional fusion strategy lacks the controllability and feedback mechanism, the fusion model cannot precisely perceive the relationship between the requirements of the fusion task, the fused image quality, and the source image features. To this end, this paper establishes a fusion model based on the optimal controlled object and control mode called FusionOC. This method establishes two types of mathematical models of the controlled objects by verifying the factors and conflicts affecting the quality of the fused image. It combines the image fusion model with the quality evaluation function to determine the two control factors separately. At the same time, two proportional-integral-derivative (PID) control and regulation modes based on the backpropagation (BP) neural network are designed according to the control factor characteristics. The fusion system can adaptively select the regulation mode to regulate the control factor according to the user requirements or the task to make the fusion system perceive the connection between the fusion task and the result. Besides, the fusion model employs the feedback mechanism of the control system to perceive the feature difference between the fusion result and the source image, realize the guidance of the source image feature to the entire fusion process, and improve the fusion algorithm's generalization ability and intelligence level when handling different fusion tasks. Experimental results on multiple public datasets demonstrate the advantages of FusionOC over advanced methods. Meanwhile, the benefits of our fusion results in object detection tasks have been demonstrated.

Optimized Hybrid Osprey with PSO Control for Improved VSC-HVDC-Wind Power Integration

Innovative power systems include offshore wind farms (OWFs) to generate electricity from renewable sources. So, reliable control systems are also necessary to make sure these power systems run smoothly. The purpose of this study is to combine the Osprey Optimization with Particle Swarm Optimization (OOPSO) to fine-tune the gains of Proportional-Integral (PI) controllers within the investigated wind energy conversion system (WECS) to enhance its performance. The study confirms the effectiveness of using the Hybrid OOPSO algorithm to optimize PI controllers in a WECS. The WECS includes two voltage source converter (VSC) stations at each end of a high voltage direct current (HVDC) transmission system. The transmission system links OWFs to the grid. The research demonstrates that the Hybrid OOPSO algorithm is superior to the genetic algorithm (GA) and PSO by enhancing setup stability and allowing fast voltage regaining following different fault cases. The introduced method performs more remarkably than traditional methods such as GA and PSO. The results of this study have shown that the proposed OOPSO enhances the overshoot in onshore voltage transient response under a symmetrical fault condition by 26% over PSO, 24% over GA, and 16% over OOA. The study is conducted using MATLAB/Simulink. The study underscores the importance of advanced optimization methods to guarantee offshore wind energy systems' efficient and dependable functioning.

Event-Triggered Adaptive Neural Impedance Control of Robotic Systems.

This article presents an event-triggered adaptive neural impedance control (ETANIC) scheme for robotic systems, where the combination of impedance control (IC) and event-triggered mechanism can significantly reduce the computational burden and the communication cost under the premise of ensuring the stability and tracking performances of the robotic systems. The IC is used to achieve the compliant behavior of the robotic systems in response to the environment. The uncertainties of the robotic systems are estimated by the radial basis function neural network (RBFNN), and the update laws for RBFNN are derived from the designed Lyapunov function. The stability of the whole closed-loop control system is analyzed by the Lyapunov theory, and the event-triggered conditions are designed to avoid the Zeno behavior. The numerical simulation and experimental tests demonstrate that the proposed ETANIC scheme can achieve better efficiency for controlling the robotic systems to perform the interaction tasks with the environment in comparison to the adaptive neural IC (ANIC).

Fuzzy Logic-Based Feedwater Controller for the Super Fast Reactor

Abstract Super fast reactor is a Generation IV reactor with water coolant at supercritical pressure. It has advantages of having high efficiency of about 44%, more economical and excellent safety features. Its last core design which adopted one heating in one coolant cycle, however, results a large density change along the fuel channels. It leads to a sensitive steam temperature change against a change of power which might mismatch with the flow change. The sensitivity should be reduced to maintain the structure integrity of the reactor components. A feedwater controller which based on fuzzy logic was used to reduce the sensitivity. Method of fuzzy-based control is applied. Two signals of the temperature and the power changes were taken as the inputs of the fuzzy controller, and change of the feedwater coolant flow was taken as the control output. Fuzzifications used triangular member functions with Tsukamoto fuzzy model for inferencing process. Two control parameters of member function spread and signal values which lead to fuzzy degree of 1 were optimized so that the criteria of outlet coolant temperature and the stability were fulfilled. Test results of the control system showed that the deviation of the water temperature at outlet side could be kept within the criteria when mismatch change of power and water flow happened. The temperature deviation could be supressed by using the fuzzy-based control.

Design and Implementation of a Control System for Multifunctional Applications of a Battery Energy Storage System (BESS) in a Power System Network.

Design and Implementation of a Control System for Multifunctional Applications of a Battery Energy Storage System (BESS) in a Power System Network.

Implementation of a performance management system for environmental sustainability in an industrial organization

Abstract The paper explores the implementation of process performance management systems in the automotive industry, specifically focusing on improving the assembly line of an organization within this sector thanks to the introduction of cobots in the line of manufacturing electronic modules used in car seat control systems. With an emphasis on environmental sustainability and circular economy (CE) concepts, the study investigates the positive effects of optimizing mechanical and electromechanical systems within the assembly line. Leveraging concepts such as KAIZEN and Gemba Kaizen, along with the guiding principles of Just-In-Time (JIT), Continuous Improvement and Automation with a Human Touch (JIDOKA), the research aims to elucidate the potential benefits of such enhancements. Key performance indicators (KPIs) including Overall Equipment Effectiveness (OEE), First Pass Yield (FPY), and scrap rates were considered. Rejects, primarily stemming from human error in part handling, emerged as the major challenge facing this assembly line. To address this issue, collaborative robots were introduced to automate part handling, replacing manual processes with precise and reliable automation. Before the implementation, the cycle time stood at 13.6 units, which was reduced to 12.5 units post-implementation, resulting in a significant increase in productivity equating to 3000 more parts produced per week. OEE increasing from 80% to 87.74%, FPY rising from 96.42% to 98.48%, and the scrap rate decreasing from 0.06% to 0.02%. By addressing inefficiencies at the assembly line level, organizations can achieve significant improvements in performance metrics while concurrently contributing to a greener and more sustainable future.