Central Control System Research Articles

Collision avoidance and routing based on location access (CARLA) of mobile robots

Abstract The paper introduces a new path-planning robotic system methodology called Collision Avoidance and Routing based on Location Access (CARLA) for use in critical environments such as hospitals and crises where quick action and saving human lives are vital. The main focus of our framework is on accuracy and fast responses, such as delivering tools or items in a specific area while avoiding collisions with other robots and obstacles. CARLA is designed to provide quick responses during emergencies, unlike most existing algorithms that are integrated into site control units or distributed among mobile robots on-site. By being loaded onto a remote server node rather than individual robots, CARLA helps to conserve the robots' capabilities, hardware resources, and power consumption. Additionally, our system utilizes cloud computing and Fog servers technology to improve data transmission times between the cloud and smart devices, especially for applications with strict timing requirements like emergency response. The Fog platform is also leveraged to enhance on-site access to real-time interaction and location-based services by bringing processing power closer to the robots from far-off Cloud servers. CARLA has various applications, such as in factories and warehouses, where mobile robots need to be selected and directed by a central control system remotely. The proposed framework consists of three main modules: Robot Knowledge Module, Robot Selection Module, and Route Reservation Module, which will all be discussed in detail in this paper. The results of simulations using this framework show that the robots have improved flexibility and efficiency in terms of computing paths and successfully fulfiling requests without colliding, compared to traditional methods used in similar scenarios.

A Study on the Automatic IoT Based Multiple Solid Mixing and Product Measurement System

Abstract: This project presents an automated system for mixing multiple solid materials and measuring the final product, using Internet of Things (IoT) technology. The system automatically mixes different solid ingredients in the right proportions, ensuring consistency and accuracy. It uses sensors to monitor the mixing process in real-time, sending data to a central control system that makes adjustments as needed. The system also measures the weight and volume of the final product to ensure it meets the required specifications. With IoT integration, the system allows remote monitoring, data tracking, and performance analysis, reducing human error and improving efficiency. This technology is flexible and can be used in industries like food processing, pharmaceuticals, and chemicals, offering a more precise and automated approach to solid mixing and product measurement.

Socially driven negative feedback regulates activity and energy use in ant colonies.

Despite almost a century of research on energetics in biological systems, we still cannot explain energy regulation in social groups, like ant colonies. How do individuals regulate their collective activity without a centralized control system? What is the role of social interactions in distributing the workload amongst group members? And how does the group save energy by avoiding being constantly active? We offer new insight into these questions by studying an intuitive compartmental model, calibrated with and compared to data on ant colonies. The model describes a previously unexplored balance between positive and negative social feedback driven by individual activity: when activity levels are low, the presence of active individuals stimulates inactive individuals to start working; when activity levels are high, however, active individuals inhibit each other, effectively capping the proportion of active individuals at any one time. Through the analysis of the system's stability, we demonstrate that this balance results in energetic spending at the group level growing proportionally slower than the group size. Our finding is reminiscent of Kleiber's law of metabolic scaling in unitary organisms and highlights the critical role of social interactions in driving the collective energetic efficiency of group-living organisms.

Sistem Kontrol Dan Monitoring Kualitas Ph Air Pada Ground Tank Berbasis Mikrokontroller Di Bandar Udara Tjilikriwut Palangkaraya

Abstract – The centralized water pH quality monitoring control system uses a microcontroller as the control center and program. By using theoretical basics regarding relays, microcontrollers and other electronic components, the author designed a centralized monitoring control system using a computer HMI (Human Machine Interface) as a display with a pH sensor for each water quality situation. The pH sensor is an analog data reader, where the reading results will be processed by the microcontroller which will then activate the relays so that the acid-base solution pump is active when the water pH is unstable. Keywords — Monitoring controls, Microcontrollers, pH Sensors

Reimaging Music Education Through a Rhizomatic Approach Focusing on Performing, Creating, Responding, and Connecting

In music educators’ endeavoring to integrate equity into our curriculum, adopting a rhizomatic approach could provide a valuable perspective for reassessing the Western classical tradition as the norm. From a philosophical perspective, the rhizome is perceived as an interconnected multiplicity, where various elements are intricately connected without a central or hierarchical control system. In essence, a rhizomatic approach is more expansive than top-down alternatives and inherently places greater emphasis on equity. Given a rhizome’s noncentered and nonhierarchical nature, the concept of a rhizome encourages engagement with music comparatively or relationally, fostering a broad perspective that recognizes the interconnectedness between musics. More importantly, lessons using a rhizomatic approach may promote teachers and students to view all forms of musics as equally significant, honoring diverse musical traditions rather than exclusively prioritizing Western classical heritage.

Safety Concepts for Future Electromechanical Brake Central Control Systems

<div>Electromechanical brakes (EMB) are currently coming into focus in the automotive industry. This trend was confirmed in 2022, when a first automotive supplier [<span>1</span>] announced the series production of EMB systems. One major driver is safety, especially if EMB systems are implemented with smart actuators that install redundant electronic control units (ECU) and distributed software [<span>1</span>]. Earlier, the authors have addressed safety mechanisms in EMB actuators [<span>2</span>]. In this article the authors extend their investigation to address safety mechanisms in future EMB central control systems (CCS). Impact of different brake system topologies (X-, H-, centralized) vis-à-vis potential safety mechanisms within communication buses and ECUs is analyzed.</div>

Identifying the dominant operating variables to evaluate the cascading failure potential in the power system by theory of mutual information

In this study, the potential of cascading failure as a result of transmission line outages through large power systems is evaluated. Transmission lines are more dispose of the outage resulting from different fault occurrences and extend the uncontrolled failures compared to other power system devices. In this case, power system dynamic security must evaluate the possibility of cascading failures using a power system control center (PSCC) in order to limit the spread of outages caused by line failures. For this issue, using the PSCC online information consisting of power system operating variables, it is possible to present a variables-based scheme to estimate power system cascading failures concerning fault events. In order to cover the issue, based on developing a set of dominant operating variables (DOVs), this paper presents an online scheme of identifying cascading failures caused by line outages in the presence of line operational diversities and communication restrictions. In this scenario, during each time interval, by evaluating the proposed DOVs, the line information consisting of dynamic securities and sensitivities to cascading failure are investigated which the lines with the potential of cascading failures are identified online. Proper DOVs are determined for this issue by studying a variety of mathematical formulations according to theory of mutual information (MI) and measuring the entropy among the variables. In a real-time environment, by using the proposed DOVs and substituting them through online boundary equations based on the Least Square Error (LSE) method, the potentials of power system cascading failures without acting any line outage are provided. The effectiveness of the suggested technique is evaluated using a typical IEEE-39 bus and IEEE-118 bus, and proper results with high accuracy are achieved by evaluating the system potential concerning large cascading failures.

Математичне моделювання руху автобронетанкової техніки з колісною формулою 4×4 при зміні тиску в шинах коліс на прикладі КрАЗ-Спартан

The authors proposed a study of the passability of trucks and armored vehicles of the National Guard of Ukraine with a 4x4 wheel formula. The movement of armored vehicles (AMT) of the National Guard of Ukraine involves movement both on public roads and off-road. The possibility of increasing cross-country ability by ensuring optimal pressure distribution in the tires of the wheels is being considered. The increase in bearing capacity in difficult operating conditions can be estimated with the help of modern mathematical tools. This allows the vehicle equipment of the National Guard of Ukraine to study the cross-country ability and select optimal parameters when performing service and combat tasks with a certain ratio of technical characteristics in different operating conditions. As a result of the full-scale war of the Russian Federation against Ukraine, more serious technical requirements are imposed on the vehicles of the Armed Forces of Ukraine (AFU) and the National Guard of Ukraine (NGU) than in peacetime. Among these requirements, maneuverability is in the first place - controllability is ensured by the ability to move at high speed over rough terrain. The patency of the AMT of the National Guard of Ukraine depends on many factors, the main ones of which are: the type and quality of the surface on which movement takes place, the pressure in the tires of the wheels, the weight of the vehicle, the order of passing the route of the convoy, etc. The central air pressure control system in wheel tires (SRPRS) is widely used in various variants of automotive equipment with high traffic intensity, but the main disadvantage of such systems is the need to minimize tire pressure to improve cross-country ability on load-bearing surfaces with low load-bearing capacity. This tolerance can cause the tire to slip off the rim, overheat or burst. This is due to the fact that the maximum speed is limited due to the risk of system failure. It is recommended to determine the influence of various factors in order to ensure the required level of support patency and analyze it using the example of the KrAZ-SPARTAN armored car with a 4×4 wheel formula.

Transient and steady‐state performance improvement of two interconnected areas through VSC‐based HVDC transmission line using multi‐purpose control strategies

AbstractThis paper presents various control strategies to improve operations in two interconnected areas connected by a VSC‐HVDC transmission line. The main focus is on designing a central control system (CCS) that coordinates control units in both areas. In area 1, an AC voltage control unit is connected to the CCS. In area 2, three control units including a load power control unit, a fault detection unit, and an AC voltage control unit are also connected to the CCS. The CCS receives inputs from these units and generates commands for the DC voltage and active/reactive power control units on both sides of the DC line. The first proposed strategy addresses permanent voltage drops caused by load fluctuations in area 2. It adjusts the transmitted power from area 1 based on voltage variations in area 2. The second strategy focuses on mitigating faults in area 2 by injecting active and reactive power from area 1 during such events. The third strategy resolves transient voltage oscillations in both areas by controlling the reactive power of stations on either side of the DC line. Simulations using MATLAB‐SIMULINK demonstrate that these mechanisms successfully achieve their objectives.

Design and production of an automatic temperature regulation system for a biodigester (Republic of Guinea)

Automatic temperature regulation system is crucial to optimize the anaerobic fermentation process and maximize biogas production. In this study, we implemented an automatic system integrating GSM technology to enable remote temperature control and regulation. For this, we installed a temperature sensor inside the biodigester in order to monitor these thermal variations, the data collected by this sensor is transmitted to the central control system via an Arduino Uno module. The latter compares the received data with predefined thresholds and accordingly sends adjustment commands to the heating system. Operators can monitor and adjust temperature parameters remotely via SMS messages through the SIM800 GSM module. Through this system, the temperature of the biodigester can be maintained at optimal levels, thereby promoting efficient digestion of organic materials and continuous production of biogas, while providing convenient and responsive remote management.

IOT Based Smart Grid to Remotely Monitor and Control Renewable Energy Sources using Cloud Computing

Abstract: The growing demand for clean and sustainable energy sources necessitates advancements in grid structure. This project explores the potential of an IOT-based smart grid to remotely monitor and control renewable energy sources. In this, we use solar energy as a renewable energy source, and with the help of cloud computing, we monitor and control different types of loads. The paper highlights the key components, functionalities, and benefits of such a system.The increasing demand for sustainable energy solutions fuels the development of smart grid technologies. This project proposes an IOT (Internet of Things)-enabled smart grid architecture for remote monitoring and control of renewable energy sources. The core concept involves integrating sensors with renewable energy sources like solar or wind turbines. These sensors collect real-time data on energy generation, environmental conditions, and system health. This data is then transmitted over a network to a central control system or a cloud platform for further analysis. By implementing remote control capabilities, grid operators can: regulate energy production based on demand; integrate storage solutions for surplus energy; and improve overall grid stability and reliability. The project concludes by outlining the benefits of this approach, including a reduced carbon footprint, cost savings, and a more sustainable energy future.

A Lyapunov-based control design for centralised networked control systems under false-data-injection attacks

ABSTRACT A central processing unit receives data from all agents and transmits control commands in a Networked Control System (NCS) which is centralised. Centralised NCSs have numerous applications in industrial settings due to their efficiency, simplicity and cost-effective design. However, centralised NCSs are vulnerable to false data injection (FDI) attacks. Despite the fact that researchers have developed detection and mitigation defense mechanisms during past several years, most of these methods have focused on systems with linear dynamics. Furthermore, the existing literature only assumes the injection of FDI attacks on measurement signals. In this paper, we assume that an adversary has injected the FDI attack into both state measurements and control signals with nonlinear dynamics while considering communication noises and disturbances. We propose a secure nonlinear control design that mitigates FDI attacks in real time by combining learning and model-based approaches. We used Lyapunov stability analysis to design the controller, estimator and updating laws of the neural network (NN). In addition, we selected a network of two robots with Euler–Lagrange dynamics to illustrate the robustness of the proposed controller and estimator.

Smart Home Automation System

This project introduces the overall framework of an economical wireless home automation system (HAS). Its primary emphasis lies in establishing an Internet of Things (IoT)-centered home automation setup, capable of automatic configuration based on environmental conditions and capable of overseeing multiple devices remotely via the internet. The objective is to design firmware for intelligent control, ensuring automated functionality with minimal human intervention to uphold the well-being of all electrical appliances in the household. Node MCU, a widely recognized open-source IoT platform, has been employed for the automation process. Various transmission modes are implemented across distinct system components to relay user commands from Node MCU to the actual device. The central control system utilizes wireless technology, enabling remote accessibility via a smartphone. The incorporation of a cloud server-based communication system enhances project practicality, providing users unrestricted access to appliances, regardless of their spatial proximity. To fortify automation, a data transmission network has been established. The user-friendly interface, cost-effective construction, and straightforward installation make it an ideal solution for managing household electrical appliances and devices. Both control and appliance status can be monitored through an Android platform. The system's objective is to enhance the living conditions of elderly and disabled individuals by offering necessary support and assistance, ultimately elevating the overall home living experience with the concept of a smart home.

Detailed modelling and performance analysis of power flow topology in a hybrid electric vehicle having series-parallel architecture

Despite massive investment and carbon-neutral transition goals set around the world, gasoline-based internal combustion engine vehicles still form an absolute majority in the transportation sector. With the advent of technology, access to electricity, uncertainties in fuel prices and health awareness, people worldwide are moving towards a better, reliable, cost-effective and environmentally friendly mode of transportation, a hybrid electric vehicle. Such a vehicle, with its powerful electric motor and compact gasoline-based engine, offers better efficiency in terms of operating cost and reliability. Considering the advent of hybrid electric vehicles taking pace, studies related to its architecture types, power flow dynamics, control and modelling of its various components will form an essential part of the automobile industry and research. This paper proposes a power flow topology for a hybrid electric vehicle with series-parallel architecture. The developed vehicle model with such an architecture type consists of three main sub-systems: the electrical system, the control system and the mechanical system. The presented power flow topology being modelled and analysed in detail in the Simulink tool is being implemented via a mode logic controller, which forms part of the central control system. The developed hybrid electric vehicle model demonstrates various modes of operation, from starting to accelerating to de-accelerating and then finally coming to a complete rest. Each mode yields and explains the following: the vehicle reference speed; the engine and generator turn functions on/off; the dc bus and battery voltage; the motor, battery, and generator current; the motor, generator, and engine speed; engine torque; engine power; throttle demand; and the vehicle’s actual speed. The results thus obtained show that the waveforms associated with such topology, during its various modes of operation, are pretty stable and acceptable, thereby depicting and validating the operation of the developed hybrid electric vehicle model with proposed power flow topology in a precise and transparent manner.

Design and Analysis of 5-DOF Compact Electromagnetic Levitation Actuator for Lens Control of Laser Cutting Machine.

In laser beam processing, the angle or offset between the auxiliary gas and the laser beam axis have been proved to be two new process optimization parameters for improving cutting speed and quality. However, a traditional electromechanical actuator cannot achieve high-speed and high-precision motion control with a compact structure. This paper proposes a magnetic levitation actuator which could realize the 5-DOF motion control of a lens using six groups of differential electromagnets. At first, the nonlinear characteristic of a magnetic driving force was analyzed by establishing an analytical model and finite element calculation. Then, the dynamic model of the magnetic levitation actuator was established using the Taylor series. And the mathematical relationship between the detected distance and five-degree-of-freedom was determined. Next, the centralized control system based on PID control was designed. Finally, a driving test was carried out to verify the five-degrees-of-freedom motion of the proposed electromagnetic levitation actuator. The results show it can achieve a stable levitation and precision positioning with a desired command motion. It also proves that the proposed magnetic levitation actuator has the potential application in an off-axis laser cutting machine tool.

Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

PurposeIn order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.Design/methodology/approachFirst, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.FindingsThe cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/valueThis study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

Strengthening stability with centralized event-triggered control system with the disturbances and artificial time delay in wireless connected vehicle platooning (CVSs)

This paper addresses the difficulties with connected vehicle systems (CVSs), particularly with vehicle platooning, are examined in this paper. For leader and follower-connected vehicles, the control protocol (which includes artificial delays, disturbances and proportional gains) is implemented. With tracking error systems, system dynamics are modelled while taking outside influences into consideration. Using creative thinking, a centralized event-triggered control system is implemented to maximize fleet wide communication updates. System stability is guaranteed by this centralized method in combination with quadratic form Lyapunov stability analysis. The risk of zeno behaviour is reduced by an event-triggered communication condition that is activated when a threshold is exceeded. The effectiveness of the centralized event-triggered system in improving stability and resilience in connected vehicle platooning scenarios is evaluated numerically through simulations.

Railway Train Collision Avoidance on Same track and Animal Detection Using AI - IoT

The increasing demand for safer and more efficient railway transportation systems has prompted the exploration of advanced technologies to mitigate collision risks and address emerging challenges such as animal incursions on railway tracks. This paper proposes a comprehensive solution leveraging Artificial Intelligence (AI) and Internet of Things (IoT) technologies for real-time detection and avoidance of collisions between trains operating on the same track and encounters with animals. These sensors capture various environmental and operational data such as train positions, velocities, and track conditions. The AI algorithms analyze this data to identify potential collision risks and animal intrusions. Additionally, real-time communication between trains and the centralized control system enables timely intervention and rerouting decisions to ensure safe operations. The system incorporates advanced image recognition algorithms to detect and classify animals near railway tracks. Utilizing high-resolution cameras and IoT-connected devices, the system identifies animals in the vicinity and alerts train operators or initiates automated braking mechanisms to prevent accidents caused by animal incursions. Key features of the proposed system include scalability to accommodate varying railway infrastructures, adaptability to diverse environmental conditions, and interoperability with existing railway signaling and control systems. Moreover, the integration of AI and IoT technologies enhances the system's predictive capabilities, enabling proactive risk mitigation and improving overall.

IoT Based Real-Time Street Light Fault Detection and Maintenance System with Machine Learning Driven Solution Prediction

The proposed system provides a complete solution for fault prediction with suggested fixes, accurate position tracking, automated real-time streetlight fault detection, and an effective maintenance strategy. For both general city beauty and public safety, street lighting functionality is essential. Our technology makes use of the Internet of Things (IoT) to continuously monitor streetlights in real-time and quickly identify problems through machine learning. Every streetlight has sensors installed that can detect abnormalities instantly and provide information to a central control system for prompt defect finding. By ensuring a responsive and effective system, this method shortens the period between defect discovery and repair. The system's ability to provide accurate geographic information, offer remedies for errors that are recognized, and help maintenance workers locate and resolve problems more rapidly are some of its important features. By integrating geographic data, maintenance operations are directed and efficient, reducing downtime and improving system reliability overall. This study explores the technical features of the sensor-based system and highlights how effectively it functions as a reliable and straightforward option for regions trying to enhance their maintenance procedures for streetlights

A BIM-enabled robot control system for automated integration between rebar reinforcement and 3D concrete printing

ABSTRACT 3D concrete printing (3DCP) has attracted significant attention due to the benefits of enhanced productivity and sustainability. However, existing 3DCP techniques face challenges of automation and practicality in integrating conventional rebar reinforcement with printed concrete structures. This study presents an automated robot system coupled with Building Information Modeling (BIM) to address the challenge. Dynamo scripts in BIM were used to generate printing paths, further optimised by a proposed algorithm for incorporating rebar reinforcement. A deep learning model was adopted to identify rebars with large aspect ratios. The average accuracy of rebar recognition is 92.5%, with a position error within 2 mm. A centralised control system was developed for multiple-device communication, including a camera, a robot arm, and a gripper. Finally, a real-time demonstration was conducted, representing the first practical demonstration of an automated robotic system to integrate rebar reinforcement with printed structures using BIM-generated data in the physical world.