This paper addresses the problems faced in programmable logic controller(PLC)teaching in vocational colleges and proposes countermeasures to overcome these *** study emphasizes the need for a deeper understanding of f...
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This paper addresses the problems faced in programmable logic controller(PLC)teaching in vocational colleges and proposes countermeasures to overcome these *** study emphasizes the need for a deeper understanding of fundamental concepts and the integration of practical application in PLC *** suggests involving students in teacher-led projects to enhance their programming skills and problem-solving ***,the paper highlights the importance of interactive learning and collaborative discussions to foster student ***,it emphasizes the cultivation of innovation consciousness through participation in innovation competitions and *** implementation of these strategies has shown positive results in improving learning outcomes and preparing students for careers in automation and *** research contributes to the development of effective teaching approaches in PLC education in vocational colleges.
The world is undergoing significant changes in information technologies and industrial processes. The rise of Industry 4.0 and the advancement of artificial intelligence are creating new opportunities and challenges f...
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The world is undergoing significant changes in information technologies and industrial processes. The rise of Industry 4.0 and the advancement of artificial intelligence are creating new opportunities and challenges for industries. This study investigates the feasibility of substituting a traditional programmable logic controller (PLC) with a neural network-based control system for discrete event management within a robotic cell. The research assesses the feasibility of this replacement, analyzing the associated challenges, limitations, and advantages compared to traditional methods. Digital manufacturing software is employed for simulating and validating the proposed model through a Virtual Comissioning (VC). The control system of the proposed model utilizes artificial neural networks, trained using data derived from a Boolean logic model. The results indicate that it is possible to swiftly train an artificial neural network (ANN) to take over cell control. This approach opens up the possibility of implementing low-cost hardware, aligning the system with the concepts of Industry 4.0. Additionally, the virtual modeling conducted using digital manufacturing software paves the way for a future implementation of a digital twin. Findings indicate that the neural network control approach is feasible and offers operational advantages over traditional programming methods.
The security risk of semantic attacks to Industrial Control Systems (ICSs) is increasing. Semantic attacks manipulate targeted system modules by identifying the physical semantics of variables in programmablelogic Co...
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The security risk of semantic attacks to Industrial Control Systems (ICSs) is increasing. Semantic attacks manipulate targeted system modules by identifying the physical semantics of variables in programmable logic controllers (PLCs) programs, i.e., the sensing/actuating modules represented by the variables, which is usually and inefficiently achieved via manual examination of system documents and long-term observation of system behavior. In this paper, we design ARES, a method that Automatically Reverse Engineers the Semantics of variables in PLC programs without requiring any domain knowledge. ARES is built on the fact that the Supervisory Control And Data Acquisition (SCADA) system monitors the behavior of PLC using a fixed mapping between the variables of program code and data log, and the data log variables are marked with physical semantics. By identifying the mapping between PLC code and SCADA data (i.e., the code-data mapping), ARES reverse engineers the physical semantics of program variables. ARES also sheds light on the preferred defense strategies in implementing control rules that improve the resistance of PLC programs to semantic attacks, as well as in detecting and responding to semantics attacks in real time. We have experimentally evaluated ARES and the recommended defending practices on two ICS platforms.
In view of the temperature control system with programmable logic controller (PLC) as the core, the main problems focus on the inability to realize wireless communication, remote downloading, poor temperature stabilit...
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In view of the temperature control system with programmable logic controller (PLC) as the core, the main problems focus on the inability to realize wireless communication, remote downloading, poor temperature stability and poor anti-interference ability. A multi-channel Proportional Integral Differential (PID) temperature control system based on PLC and Internet of Things (IOT) is designed. It can not only adjust the temperature in real time. But also, the thirdparty cloud platform can be used through Message Queuing Telemetry Transport (MQTT) protocol, wireless data monitoring and remote control can also be carried out, and PLC programs can be downloaded remotely. Compared with the traditional wired monitoring system, it has great advantages and brings unprecedented convenience to the maintenance of the equipments. Based on the prototype, the multi-channel temperature stability and anti-interference tests, and wireless communication monitoring and alarm tests are carried out. The results show that the actual temperature of the system can change with the set value by PID control algorithm with the multi-channel heaters, and the temperature stability can reach +/- 0.1 degrees C in steady state. In addition, real-time data such as temperature, voltage and current can be obtained through the cloud platform monitoring interface. And after triggering the alarm, the mobile devices (such as mobile phones) receive messages in real time.
This paper investigates the response of the DynMo-CBC space nuclear reactor power system to simulated cybersecurity attacks during a startup transient and demonstrates the effectiveness of the mitigation measures. The...
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This paper investigates the response of the DynMo-CBC space nuclear reactor power system to simulated cybersecurity attacks during a startup transient and demonstrates the effectiveness of the mitigation measures. The system nominally generates 134 kW(electric) continuously for 12 years and does not have a single-point failure in reactor cooling and energy conversion. The reactor core is divided into three hydraulically independent sectors, each having a separate loop with a single shaft, closed Brayton cycle (CBC) turbomachinery unit. A He-Xe gas mixture with a molecular weight of 40 g/mol cools the reactor core sectors and is the CBC unit's working *** paper examines the effects of simulated false data injection attacks (FDIAs) on the operation parameters of the power system. The simulated FDIAs decrease or increase the external reactivity insertion beyond nominal to cause spikes in the reactor's power and temperatures. The results demonstrate the effectiveness of the programmable logic controller regulating the control drums' drive motors. It mitigates the effects of the simulated FDIAs on the transient operation of the power system and shortens the recovery time after the termination of the simulated cyberattacks.
The objective of this study was to design and implement a reinforcement learning-based controller for a nonlinear industrial system, specifically a liquid water tank controlled via a programmable logic controller to a...
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The objective of this study was to design and implement a reinforcement learning-based controller for a nonlinear industrial system, specifically a liquid water tank controlled via a programmable logic controller to achieve robust control in the presence of disturbances from the outlet drain valve at various ratios. Initially, the system's model parameters were determined, and a mathematical model was developed using the OpenAI Gym open-source platform. Subsequently, multilayer perceptron-based reinforcement learning (RL), adaptive proportional integral (A-PI), and reinforcement learning-integral (RL-I) controllers were trained and validated using the developed software model. The designed controllers were then implemented on the real system both fixed and variable drain valve ratios. Tests conducted with a fixed drain valve ratio revealed that the proposed RL-I controller outperformed the RL and A-PI controllers in terms of transient and steady-state responses. The error values of the RL-I controller were significantly lower than those of the other algorithms (p = 0.000). In the final test, where the drain valve was adjusted to different ratios, the RL-I controller demonstrated robust performance. This study successfully developed a novel, robust controller for nonlinear systems commonly encountered in industrial applications.
programmable logic controllers (PLCs) are widely used in industrial applications. Ensuring the correctness of PLC programs is important due to their safety-critical nature. Structured text (ST) is an imperative progra...
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ISBN:
(纸本)9783031711619;9783031711626
programmable logic controllers (PLCs) are widely used in industrial applications. Ensuring the correctness of PLC programs is important due to their safety-critical nature. Structured text (ST) is an imperative programming language for PLC. Despite recent advances in executable semantics of PLC ST, existing methods neglect complex multitasking and preemption features. This paper presents an executable semantics of PLC ST with preemptive multitasking. Formal analysis of multitasking programs experiences the state explosion problem. To mitigate this problem, this paper also proposes state space reduction techniques for model checking multitask PLC ST programs.
With the current trend of low product quality of oil and gas resources becoming more and more obvious, deepwater and ultra-deepwater oil and gas have become an important field of oil and gas development in various cou...
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With the current trend of low product quality of oil and gas resources becoming more and more obvious, deepwater and ultra-deepwater oil and gas have become an important field of oil and gas development in various countries. Deepwater oil and gas reservoirs are characterised by complex geological conditions and a narrow window of safe density, leading to the frequent occurrence of such complications as downhole kicks and overflows, which seriously threaten the lives of engineers and pollute the environment. The prerequisite for dealing with kick is to shut-in, but currently the drilling site shut-in relies on manual operation by multiple engineers, which not only takes a long time to operate, but is also affected by the subjective factors of the engineers. With the maturity of automation and artificial intelligence theory, well control shut-in also needs to develop in the direction of automation and intelligence, and carry out the research of well control automation shut-in system, so that the well can be shut-in quickly, automatically and efficiently when the drilling site kicks, blowouts and other complex situations. In this paper, using statistics and machine vision algorithms, an intelligent identification method of shut-in equipment operation status is established, and at the same time, a well control automated shut-in simulation system is designed based on PLC, and automated shut-in tests are carried out. The results show that the method of intelligent identification of operating status of shut-in equipment can identify the choke opening, the closure of each blowout preventer, and the working status of mud pump and top drive system in real-time without modifying the original equipment, and meanwhile, the well control automated shut-in simulation system can complete the shut-in within 5 min. This shows that the deepwater drilling well control automated shut-in method and simulation system can replace the engineer's operation to a certain extent, which provides
It is proposed that Personal Computers (PCs) can be used effectively for the same industrial applications as programmable logic controllers (PLCs). The basic concepts related to the operation of a PLC to emulate the b...
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It is proposed that Personal Computers (PCs) can be used effectively for the same industrial applications as programmable logic controllers (PLCs). The basic concepts related to the operation of a PLC to emulate the behavior of a relay panel are explained. This is used to build a simple model for using standard PCs in the same applications as PLCs. This is demonstrated using a simple example of an automated process. Sample code in a standard high level language is presented that can be used as a template for future developments. Finally, the potential advantages and enhancements that can result in using PCs for process control are presented. (C) 1997 Elsevier Science Ltd.
Photovoltaic pumping systems (PVPS) based on standard frequency converters (SFCs) are Currently experiencing a growing interest in pumping programmes implemented in remote areas because of their high performance in te...
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Photovoltaic pumping systems (PVPS) based on standard frequency converters (SFCs) are Currently experiencing a growing interest in pumping programmes implemented in remote areas because of their high performance in terms of component reliability, low cost, high power range and good availability of components virtually anywhere in the world. However, in practical applications there have appeared a number of problems related to the adaptation of the SFCs to the requirements of the photovoltaic pumping systems (PVPS). Another disadvantage of dedicated PVPS is the difficulty in implementing maximum power point tracking (MPPT). This paper shows that these problems can be solved through the addition of a basic industrial programmable logic controller (PLC) to the system. This PLC does not increase the cost and complexity of the system, but improves the adaptation of the SFC to the photovoltaic pumping system, and increases the overall performance of the system. (C) 2009 Elsevier Ltd. All rights reserved.
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