Integrated Control System Research Articles

Wireless Dynamic Sensor Network for Water Quality Monitoring Based on the IoT

Water is a critical resource for human survival worldwide, and its availability and quality in natural reservoirs such as lakes and rivers must be monitored. In that way, wireless dynamic sensor networks can help monitor water quality. These networks have significantly advanced across various sectors, including industrial automation and environmental monitoring. Moreover, the Internet of Things has emerged as a global technological marvel, garnering interest for its ability to facilitate information visualization and ease of deployment—the combination of wireless dynamic sensor networks and the Internet of Things improves water monitoring and helps to care for this vital resource. This article presents the design and deployment of a wireless dynamic sensor network comprising a mobile node outfitted with multiple sensors for remote aquatic navigation and a stationary node similarly equipped and linked to a server via the IoT. Both nodes can measure parameters like pH, temperature, and total dissolved solids (TDS), enabling real-time data monitoring through a user interface and generating a database for future reference. The integrated control system within the developed interface enhances the mobile node’s ability to survey various points of interest. The developed project enabled real-time monitoring of the aforementioned parameters, with the recorded data being stored in a database for subsequent graphing and analysis using the IoT. The system facilitated data collection at various points of interest, allowing for a graphical representation of parameter evolution. This included consistent temperature trends, neutral and alkaline zone data for pH levels, and variations in total dissolved solids (TDS) recorded by the mobile node, reaching up to 100 ppm.

A Survey of Real-time Simulation and Hardware-in-the-loop Technology

This paper introduces the definition and background of real-time simulation and hardware-in-the-loop technology, and explains the concept, development process and application field of real-time simulation and hardware-in-the-loop technology, as well as its importance and advantages in practical applications. The research methods and technologies for real-time simulation and hardware-in-the-loop technology include commonly used methods and technologies for model establishment, control algorithm design, system integration, and experimental verification. For the application of real-time simulation and hardware-in-the-loop technology, specific cases in different fields are also listed, such as the design of distribution automation terminal in the kernel, the research of virtual test system of hardware-in-the-loop for unmanned vehicles, etc. Finally, the current challenges of real-time simulation and hardware-in-the-loop technology are stated, and the future development trend of the technology is summarized.

Integrated Control of Intelligent Vehicle Driving Stability Using Three-Dimensional Phase Space

<div>To enhance vehicle dynamic stability during driving, we developed a three-dimensional phase space model that incorporates the sideslip angle of center of mass, yaw rate, and lateral load transfer rate. This model enabled real-time evaluation and active control of vehicle stability. First, longitudinal and lateral controllers were implemented to ensure precise vehicle trajectory. Second, a hierarchical control strategy was designed to actively manage the desired sideslip angle, yaw rate, and roll angle based on the vehicle’s destabilizing conditions, thereby maintaining the vehicle within a stable state space. We simulated and tested the stability analysis methods and integrated control strategies for both cars and trucks under DLC (double lane change) and CDC (circular driving condition) scenarios using joint simulations with CarSim/TruckSim and Simulink. The proposed integrated stability control strategy, which combined MPC-based trajectory tracking with direct yaw moment control and active suspension control, enhanced the vehicle’s directional and roll stability. This approach effectively mitigated vehicle instability under extreme conditions. Compared to the MPC lateral tracking control system, the performance of the integrated control system was significantly improved. In the DLC scenario, the maximum values of the sedan’s lateral deviation, sideslip angle, yaw rate, and vehicle roll angle decreased by 22.6%, 33.9%, 5.5%, and 1.2%, respectively. In the CDC scenario, the truck’s lateral acceleration, sideslip angle, yaw rate, and vehicle roll angle decreased by 7.5%, 46.8%, 8.2%, and 80%, respectively. Additionally, open-loop simulation tests were conducted under fishhook steering conditions for both passenger cars and trucks. The results further validated the effectiveness of the integrated control strategy, demonstrating its ability to significantly improve yaw rate and roll response, thereby enhancing overall vehicle stability under challenging driving conditions.</div>

Reducing real driving fuel consumption and emissions with a hydraulic hybrid vehicle

We have successfully prototyped and tested the real-driving performance of a hydraulic hybrid heavy commercial vehicle. Hydraulic hybrid driveline technology was fitted to a Euro IV diesel truck equipped with a diesel particulate diffuser/filter and an exhaust gas recirculation system. An AVL portable emissions measurement system was fitted to the test vehicle to quantify gaseous and particle phase emissions species and an on-board diagnostic scan tool was used to obtain data from the trucks electronic control unit. Fuel consumption savings up to 17 % were accomplished in hydraulic hybrid mode when testing on a short urban driving route featuring a high intensity of stop-start activity. Average reductions in solid particle number concentration of 40 % were achieved along with increases in NOx, Hydrocarbons (THCs) and CO. Future work could target improved control system integration of the various driveline components to further reduce fuel consumption and emissions in an improved prototype design.

Integrated Chassis Control for Multi-Axle Vehicles: A Comprehensive Review

Multi-axle vehicles (MAVs) are used to transport heavy loads, navigate challenging terrain, and perform specific tasks. However, designing vehicle control systems for such vehicles is challenging. MAVs, such as trucks, buses, military vehicles, and multi-purpose vehicles, require sophisticated control techniques to increase the stability and ride comfort of such vehicles. This paper provides a comprehensive review of standalone control systems and integrated control systems (ICSs) for the steering, driving/braking, and suspension systems of MAVs, with a particular focus on the optimal tyre force distribution (TFD) in ICSs for MAVs. It also discusses various objective functions and optimisation methods used for the TFD. The findings indicate that optimising TFD significantly improves the stability of MAVs. As such, future studies may consider examining optimising three-axis TFD for MAVs to further improve vehicle stability.

Development of a Novel High Temperature Continuous Particle Mass Flow Measurement Device for Particle-Based CSP Applications

Particle-based concentrating solar power (CSP) technology is one of the generation three (Gen3) CSP technologies that has potential for lowering the levelized cost of electricity produced by this solar thermal power systems. Commercially available ceramic particles, which are rated for high temperature applications up to 1200 °C, were selected for this study. This medium is commonly used as an energy carrier or heat transfer medium in Gen3 CSP research and development efforts [1]. Prior studies at the National Solar Thermal Test Facility (NSTTF) have investigated and evaluated various mass flow measurement methods, and a simple gravimetric temporal load measurement method was chosen as the best candidate for the research purpose [2]. This mass flow measurement method is a batch process and is not a viable solution for commercial-scale power generation applications based on cost, space, process control, and practical system integration factors. In-line and continuous particle mass flow measurement will play an integral role in efficient and cost effective Gen3 CSP particle technologies. Process parameters, including energy absorbed by the particles, receiver efficiency, temperature dependent flow phenomena, and general high temperature measurement reliability are all rely on repeatable and accurate measurement of particle mass flow under various operating conditions. Ceramic particles, like those used in this application, are not conventionally used as an energy carrier. A novel concept for continuous particle mass flow at a wide range of operating temperatures is currently under development and planned to be tested at the NSTTF, called the Particle In-LinE (PILE) mass flow sensor.

Hydrogel Capacitors Based on MoS2 Nanosheets and Applications in Glucose Monitoring.

Non-invasive/minimally invasive continuous monitoring of blood glucose and blood glucose administration have a high impact on chronic disease management in diabetic patients, but the existing technology is yet to achieve the above two purposes at the same time. Therefore, this study proposes a microfluidic microneedle patch based on 3D printing technology and an integrated control system design for blood glucose measurement, and a drug delivery control circuit based on a 555 chip. The proposed method provides an improved preparation of a PVA-PEG-MoS2 nanosheet hydrogel, making use of its dielectric properties to fabricate a microcapacitor and then embedding it in a microfluidic chip. When MoS2 nanosheets react with interstitial liquid glucose (and during the calibration process), the permittivity of the hydrogel is changed, resulting in changes in the capacitance of the capacitor. By converting the capacitance change into the square-wave period change in the output of the 555 chip with the control circuit design accordingly, the minimally invasive continuous measurement of blood glucose and the controlled release of hypoglycemic drugs are realized. In this study, the cross-linking structure of MoS2 nanosheets in hydrogel was examined using infrared spectroscopy and scanning electron microscopy (SEM) methods. Moreover, the critical doping mass fraction of MoS2 nanosheets was determined to be 2% via the measurement of the dielectric constant. Meanwhile, the circuit design and the relationship between the pulse cycle and glucose concentration is validated. The results show that, compared with capacitors in series, the microcapacitors embedded in microfluidic channels can be connected in parallel to obtain better linearized blood glucose measurement results.

Improving Electric Power Stability and Efficiency Using an Integrated Control System for Refrigerated Containers

In this study, a method is proposed to minimize electrical load fluctuations and improve the efficiency of engine generator operation by managing refrigerated ship containers through an integrated control system. The proposed system actively controls the electrical load by assigning operational priorities based on cargo temperature deviations to existing independently operated refrigerated containers, ensuring that they operate only within the available power of the engine generator. As a result, the average specific fuel oil consumption can be reduced. A 70 h simulation of the refrigerated containers, a power system, and an integrated control system demonstrated in MATLAB/Simulink 2021b that the magnitude of electrical load fluctuations decreases from 37.6% to 9.6% of the engine generator’s rated power compared with the conventional operation of refrigerated containers. In addition, a 1.88% fuel saving is realized.

Design concept of intelligent integrated control system for neutral beam injection

Abstract Due to the specificity of neutral beam injection (NBI) system, the control of its actual physical system is achieved by the integrated control system (ICS). The current NBI ICS adopts a distributed design structure to balance the system load, which is also the mainstream system design and architecture model of ICS around the world. However, from a practical point of view, the distributed system architecture is not perfect. In the long run, upgrading the system intelligence and automation capabilities is an inevitable choice for the future, so it is necessary to explore ways to transform and upgrade the ICS. At present, Internet of Things (IoT), as an important part of the new generation information technology, can realize the control of everything through data exchange. This is because on the one hand, IoT has wide compatibility and powerful scenario-based capabilities, it not only has the advantages and characteristics of distributed design, but also can pull the NBI subsystems into the same level scenario and lay the foundation for the further construction of digital NBI; on the other hand, the intervention of artificial intelligence makes IoT have some new typical characteristics such as intelligent sensing, ubiquitous connectivity, precise control, digital modeling, real-time analysis and iterative optimization, which is enough to pull the current NBI ICS into a new intelligent control era. Finally, it is worth mentioning that due to its inherent design structure and functional characteristics, ICS tends to be broadly generic, so it is not exclusively used for NBI operation in nuclear fusion, and it can provide some insight into other application areas.

Towards Prosthesis Control: Identification of Locomotion Activities through EEG-Based Measurements

The integration of advanced control systems in prostheses necessitates the accurate identification of human locomotion activities, a task that can significantly benefit from EEG-based measurements combined with machine learning techniques. The main contribution of this study is the development of a novel framework for the recognition and classification of locomotion activities using electroencephalography (EEG) data by comparing the performance of different machine learning algorithms. Data of the lower limb movements during level ground walking as well as going up stairs, down stairs, up ramps, and down ramps were collected from 10 healthy volunteers. Time- and frequency-domain features were extracted by applying independent component analysis (ICA). Successively, they were used to train and test random forest and k-nearest neighbors (kNN) algorithms. For the classification, random forest revealed itself as the best-performing one, achieving an overall accuracy up to 92%. The findings of this study contribute to the field of assistive robotics by confirming that EEG-based measurements, when combined with appropriate machine learning models, can serve as robust inputs for prosthesis control systems.

Integrated Dynamic Photovoltaic Facade for Enhanced Building Comfort and Energy Efficiency.

This simulation study explores the potential of a novel façade design with integrated control system comprising a dynamic photovoltaic (PV) facade integrated with dimming lighting control to enhance the work environment in office buildings and achieve energy-efficient solutions. Parametric modeling using the Grasshopper plug-in for Rhino software 7, coupled with energy simulation through the Honeybee environmental plug-in for the EnergyPlus program, are used in the methodology. The integrated control strategy was simulated to study in a single office space, utilizing the Daysim engine to assess indoor daylight quality and focusing on Daylight Factor (DF) and Daylight Glare Probability (DGP). Additionally, two artificial lighting control systems were examined for potential integration with the dynamic PV facade to minimize lighting load. The study employs the Galapagos evolutionary solver function embedded within Grasshopper to identify optimum solutions. The dynamic PV façade achieves substantial reductions in overall energy consumption, cutting it by 73% in June, 54% in July, 54.5% in August, and 52.55% in September. The results demonstrate substantial reductions in total energy consumption, with notable savings in heating and cooling due to the dynamic facade's ability to balance and control solar radiation during working hours. Moreover, the dynamic PV facade contributes to electricity generation, demonstrating its potential to improve visual comfort, decrease energy consumption, and generate electric energy through rotational adjustments and varying transparency levels.

The Latest Research Progress on Bionic Artificial Hands: A Systematic Review.

Bionic prosthetic hands hold the potential to replicate the functionality of human hands. The use of bionic limbs can assist amputees in performing everyday activities. This article systematically reviews the research progress on bionic prostheses, with a focus on control mechanisms, sensory feedback integration, and mechanical design innovations. It emphasizes the use of bioelectrical signals, such as electromyography (EMG), for prosthetic control and discusses the application of machine learning algorithms to enhance the accuracy of gesture recognition. Additionally, the paper explores advancements in sensory feedback technologies, including tactile, visual, and auditory modalities, which enhance user interaction by providing essential environmental feedback. The mechanical design of prosthetic hands is also examined, with particular attention to achieving a balance between dexterity, weight, and durability. Our contribution consists of compiling current research trends and identifying key areas for future development, including the enhancement of control system integration and improving the aesthetic and functional resemblance of prostheses to natural limbs. This work aims to inform and inspire ongoing research that seeks to refine the utility and accessibility of prosthetic hands for amputees, emphasizing user-centric innovations.

Design and Simulation Implementation of Indoor Lighting Integrated Control System Based on Fuzzy Control

Abstract With the improvement of people’s living standards, higher requirements have been put forward for the quality of the living environment. The progress of science and technology has provided the possibility for the further development of intelligent buildings. As an important component of intelligent buildings, the intelligence level of intelligent lighting is relatively fall behind, especially energy-saving and comprehensive linkage are not considered in the scope of intelligent lighting. According to the characteristics of indoor environment control variables and controlled variables, this paper uses fuzzy control method to realize the comprehensive control of indoor lighting, summarizes the corresponding measures taken by experience into control rules, and constructs a controller to control the complex lighting process instead of people. Through the construction of control rules, the natural lighting is constrained under the full consideration of the influence of temperature and ventilation. The purpose of giving priority to the use of natural lighting and taking into account the overall energy optimization of the system is achieved. The energy-saving idea of combining lighting control with other systems of intelligent building is proposed, and the system performance is simulated and analyzed. It has the advantages of high integration, high degree of intelligence, energy saving and convenient use.

Integration of Ship Machinery Maintenance and Control Systems in Maritime Education: Enhancing Industry Readiness

Integration of Ship Machinery Maintenance and Control Systems in Maritime Education: Enhancing Industry Readiness

The possibility of unifying neural interfaces to create an integrated control system for prostheses: a brief review

The purpose of research. To date, neurointerfaces have not been unified to create combined prosthetic control systems. Based on this, this review is aimed at understanding the possibility of integrating neurointerfaces by clarifying the advantages and disadvantages of neurotechnologies related to prosthetics and the possible creation of a combined prosthesis control system.Methods. Analysis of brain-computer interfaces available in the literature in combination with neuroimaging experiments, especially in a hybrid system. A number of databases of scientific literature were used for the analysis, namely Google Scholar, scopus, etc. Links to the database data on the Internet: https://scholar.google.com/, https://www.mdpi.com/journal/sensors, elibrary.ru, https://www.refseek.com, https://link.springer.com/, https://www.base-search.netResults. Brain-computer interfaces are currently being used in a wide variety of fields, including to improve the lives of people with disabilities. However, individual neural interfaces have certain disadvantages that make it difficult to use them to control mechanical devices, including prosthetic limbs. Hybrid neural interface systems (as an integrated software and hardware complex) are significantly superior to those obtained using separate neural interfaces, and these systems can be used for medical purposes.Conclusion. This review provides a brief overview of the disability of people with missing upper limbs and how to improve their lives with prosthetics. The analysis of various hybrid methods of brain research is given. It can be noted that fNIRS technology is the closest technology that can facilitate the integration of neural interfaces, since it has advantages that make it a tool that complements other technologies, its advantages make up for the inherent disadvantages of fNIRS. It has been established that the hybrid system provides a clear advantage over individual neural interfaces.

Rise of Intelligent Machines: Influence of Artificial Intelligence on Mechanical Engineering Innovation

The integration of artificial intelligence (AI) into mechanical engineering has precipitated a profound transformation in the way engineers conceive, design, and execute projects. This paper explores the multifaceted impact of AI on mechanical engineering innovation, elucidating the myriad ways in which intelligent machines are revolutionizing traditional practices and catalyzing unprecedented advancements. In the realm of design, AI algorithms are revolutionizing the conceptualization and optimization processes. By leveraging machine learning and optimization techniques, engineers can explore vast design spaces with unparalleled efficiency, uncovering innovative solutions that might otherwise remain elusive. These AI-driven design tools not only expedite the development cycle but also enable the creation of products and systems with enhanced performance characteristics, such as improved energy efficiency, structural integrity, and functional versatility. Moreover, AI's influence extends beyond the design phase and permeates the entire manufacturing ecosystem. AI-driven automation is reshaping production lines, enabling agile and adaptive manufacturing processes that respond dynamically to changing demands and conditions. Through the integration of sensors, actuators, and AI-powered control systems, factories are becoming increasingly intelligent and autonomous, optimizing resource utilization, minimizing waste, and maximizing throughput.

Enhancing Efficiency and Safety in Self-Guided Logistics Vehicles: A Comprehensive Analysis and Integration of Hardware and Control Systems

Self-guided logistics vehicles have become increasingly popular in various industries and warehouses for material lifting and transportation purposes. These automated systems have proven to be valuable in both small-scale production lines and large areas. However, challenges persist in the field of logistics, where industries and factories face difficulties in efficiently transporting materials. In response to these challenges, self-guided vehicles have been employed, but issues such as collisions with obstacles, material falls, and rigid path constraints have been observed. This project aims to address these challenges by implementing hardware safety precautions and incorporating routing and scheduling capabilities to enhance system automation. The article presents a comprehensive analysis of hardware safety precautions and highlights key features including sensors, actuators, and control systems, which contribute to the overall efficiency and smooth operation of the self-guided logistics vehicle system. By integrating these elements, the system can overcome obstacles, ensure material safety, and adapt to changing traffic conditions, thereby optimizing logistics operations in industries and warehouses.

Challenges and strategic solutions in commissioning and start-up of subsea production systems

The commissioning and start-up of subsea production systems represent critical phases in offshore oil and gas operations, where meticulous planning and execution are essential for success. This abstract presents an overview of the challenges encountered during these phases and proposes strategic solutions to address them effectively. Environmental factors such as deepwater operations and subsea geology pose significant challenges to commissioning and start-up activities. Technical challenges include ensuring equipment reliability and seamless integration of control systems in harsh underwater conditions. Operational challenges such as remote monitoring and intervention and personnel safety further compound the complexities of these operations. Strategic solutions to mitigate these challenges include advanced planning and simulation using digital twin technology and scenario planning. Enhanced risk management strategies, including contingency planning and early detection systems, are vital to anticipate and manage potential issues effectively. Collaborative partnerships between stakeholders, including suppliers and cross-disciplinary teams, foster innovation and enhance project resilience. Drawing from successful case studies and lessons learned, this abstract emphasizes the importance of proactive planning, risk mitigation, and collaborative approaches in ensuring the successful commissioning and start-up of subsea production systems. By implementing these strategic solutions, operators can enhance operational efficiency, minimize downtime, and improve safety outcomes, ultimately contributing to the long-term viability and sustainability of offshore energy production.

Adapting To The New Normal: Assessing Levers Of Control Implementation In Indonesian Organizations Post-COVID

This systematic literature review investigates the application of the Four Levers of Control (4LOC) framework in Indonesian organizations post-COVID-19. The research method involved a systematic search of electronic databases and analysis of relevant literature. Major findings indicate that effective implementation of the 4LOC framework contributes to organizational resilience, performance improvement, and competitive advantage across various sectors. Cultural factors, leadership styles, and strategic alignment emerge as critical determinants of success. The study underscores the versatility and effectiveness of the 4LOC framework in navigating challenges posed by dynamic environments. Conclusions highlight the importance of adaptive strategies, cultural sensitivity, and integrated control systems in driving sustainable growth and organizational success in Indonesia. Results indicate that LoC implementation has positively impacted organizational performance across sectors such as hospitality, start-ups, state-owned enterprises, government organizations, manufacturing, and the service industry. Notably, effective utilization of belief systems, boundary systems, diagnostic control systems, and interactive control systems has been instrumental in fostering innovation, resilience, and strategic alignment. These findings underscore the importance of robust management control systems in achieving organizational objectives and navigating uncertainties. The review concludes by recommending further research to explore longitudinal effects, contextual influences, and the role of emerging technologies in enhancing LoC implementation.

Planning a Sewage Treatment System for Smart Housing Societies: A Review

Smart housing societies are increasingly incorporating sustainable practices, including on-site sewage treatment. This paper reviews key considerations for planning a sewage treatment system in such communities. Factors like resident population, water usage patterns, and available space are analyzed. Different treatment technologies, including activated sludge, constructed wetlands, and membrane bioreactors, are evaluated for their suitability in smart housing contexts. The integration of smart monitoring and control systems for optimizing treatment processes and water reuse is discussed. Finally, the importance of adhering to local regulations and involving residents in the planning process is highlighted.