Optimizing Process Performance with IIoT and Advanced Intelligent Controllers

Due to its simple structure and robustness, the traditional proportional-integral-derivative (PID) controller is commonly used in the field of industrial automation and process control, but it does not function well with nonlinear systems, time-delayed linear systems and time-varying systems. A new type of PID controller based on artificial neural networks and evolutionary algorithms is presented in this paper. An powerful instrument for a highly nonlinear system is the Artificial Neural Network. The interest in the study of the nonlinear system has increased through the implementation of a high-speed computer system,. In complex systems such as robotics and process control systems, the Neuro Control Algorithm is often applied. Systems of process management is also nonlinear and hard to control consistently.. This paper presents a comprehensive analysis in Which is offline trained by a multilayered feed forward back propagation neural network to act as a process control system controller, That is to say, a temperature control device without prior knowledge of its dynamics. Via the implementation of a range of input vectors to the neural network, the inverse dynamics model is developed. Based on these input vectors, the output of the neural network It is being studied by explicitly configuring it to monitor the operation. In this paper, based on set-point adjustment, impact of disturbances in load and variable dead time, compassion between the PID controller and ANN is conducted. The outcome shows that ANN outperforms the controller of the PID.

This article explores the widespread application and importance of the Programmable Logic Controller (PLC) in industry. PLC, as an industrial controller designed specifically for industrial environments, occupies an important position in the field of industrial automation control due to its advantages of being less susceptible to interference, high reliability, easy programming, fast installation, and small size. With the rapid development of PLC technology, great progress has been made in the development of technology, hardware, and software, resulting in increasingly powerful functionalities and significantly enhanced system development and compatibility. This paper mainly analyzes the design ideas and applications of PLC in life and industry in detail, aiming to research PLC and find more scenes in industry fields in which PLC can participate. PLC has a wide range of applications and significant importance in industry. The continuous progress and innovation of its technology will bring more opportunities and challenges to the field of industrial automation control. In the future, with the deepening development of advanced manufacturing models such as Industry 4.0 and intelligent manufacturing, PLC technology is expected to play a greater role in more fields and promote industrial automation to a higher level.

This thesis dissertation mainly compares and investigates laboratory study of different implementation methodologies of applied control systems and how they can be adopted in industrial, as well as commercial, automation applications. Namely the research paper aims to assess or evaluate eventual feedback control loops' performance and robustness over multiple conventional or state-of-the-art technologies in the field of applied industrial automation and instrumentation by implementing a laboratory case study setup: the ball on beam system. Hence, the paper tries to close the gap between industry and academia by: first, conducting a historical study and background information of main evolutional and technological eras in the field of industrial process control automation and instrumentation. Then, some related basic theoretical as well as practical concepts are reviewed in Chapter 2 of the report before displaying the detailed design. After that, the next Chapter, analyses the ball on beam control system problem as the case studied in the context of this research through reviewing previous literature, modeling and simulation. The following Chapter details the proposed design and implementation of the ball on beam case study as if it is under the introduced distributed industrial automation architecture. Finally, Chapter 5 concludes this work by listing several points leaned, remarks, and observations, and stating possible development and the future vision of this research.

Deep research and communicating new trends in the design, control and applications of the real time control of intelligent sensors systems using advanced intelligent control methods and techniques is the main purpose of this research. The innovative multi-sensor fusion techniques, integrated through the Versatile Intelligent Portable (VIP) platforms are developed, combined with computer vision, virtual and augmented reality (VR&AR) and intelligent communication, including remote control, adaptive sensor networks, human-robot (H2R) interaction systems and machine-to-machine (M2M) interfaces. Intelligent decision support systems (IDSS), including remote sensing, and their integration with DSS, GA-based DSS, fuzzy sets DSS, rough sets-based DSS, intelligent agent-assisted DSS, process mining integration into decision support, adaptive DSS, computer vision based DSS, sensory and robotic DSS, are highlighted in the field of advanced intelligent control.

This paper studies the proportional-derivative (PD) control method in the control field, which can be applied in industrial automation, robot control, aerospace, process control, and other fields. This paper discusses the PD control to adjust the motor angle and the fuzzy proportional-integral (PI)-PD control of the brushless direct current (DC) motor. How to apply PD control theory to practice is a part worth exploring. In the traditional control field, proportional-integral-derivative (PID) control parameters cannot adjust the changes of controlled parameters, and the traditional PID control must cooperate with three parameters at the same time to work. Therefore, in this paper, PD control is applied to the adjustment of motor angle, and PI-PD fuzzy control is used to adjust the controller parameters in real time. This method can improve the response speed of the controller, apply the control theory to the actual motor control, and improve the anti-interference ability. This research can improve the application scope of PD control and combine it with a variety of control theories, to achieve a better effect of the control system, optimize the response speed of the motor, and achieve the target speed faster.

Cyber-physical systems (CPS) integrate computation with physical processes. For the last years, CPS have been in the focus of research and are getting adopted in multiple domains like health care, automotive and smart factories. The use of CPS promises dynamic adaption of systems to changing environmental and economic conditions through autonomous CPS decisions based on the physical process. In industrial process automation, research and adoption of CPS have to account for the severe safety restrictions that dominate the system design in this domain. To transfer the benefits of CPS application to process automation, the CPS must be able to formally verify the safety of its autonomous reconfiguration decisions. This paper proposes a domain model for safety-critical CPS in industrial process automation to serve as foundation for formal CPS algorithms.

Complexity in the design of plants and machines is permanently increasing. The introduction of model-driven design methodologies in the field of Industrial Automation and Control Systems helps to cope with requirements like limited budget and reduced ramp-up time. Simulation is a major key to enable a concurrent development in all involved domains. This work analyzed requirements for simulation of industrial plants and the aptitude of industrial control runtime environments. We propose the use of IEC 61499 industrial automation runtime environments to simulate plants or integrate specialized external simulation tools. By applying the concept of Instrumentation and Control points, in form of function blocks, which represent the components' I/Os, the transition from simulation to implementation is facilitated.

Determination of metallo-cyanides by capillary electrophoresis after concentration on supported liquid membranes

Industrial automation environments are undergoing profound changes due to the high level of digitization in the industry. This means that teaching methods and software tools need to be updated. Teaching automation and control concepts to students involves the use of many different software tools that are not easily accessible or configurable. In addition, the new teaching methods lead to delocalized and remote teaching. Therefore, this paper proposes the development of a remote access platform that uses pre-configured virtual machines with all the necessary software for teaching industrial automation, control and monitoring concepts. This platform allows students not only to access a real physical system and work remotely with all the software already configured, but also to download the virtual machine to run it on their own computers and easily switch between a connection to the real system and a realistic simulation of it. The platform also allows the management of different hands-on tasks for subjects of Master's degree related to industrial process automation.

RETRACTED: Real time speech recognition algorithm on embedded system based on continuous Markov model

Measurement parameter of color on yacon (Smallanthus sonchifolius) slices using a computer vision system

In the design of plants and machines the complexity is permanently increasing. Model-driven design methodologies in the field of Industrial Automation and Control Systems, as proposed by the MEDEIA project, help to cope with current requirements like limited budget and reduced ramp-up time. Concurrent development in all involved domains is facilitated by the introduction of simulation in the development process. We propose the use of an IEC 61499 industrial automation runtime environment to simulate plants' behavior. The concept for the simulation framework is based on the coupling of the control application and the plant simulation application via Instrumentation and Control points. The introduction of physical links in the plant simulation application enhances the behavior model of the plants, thus increasing the quality of the obtained simulation results.

In a highly competitive business environment, companies are looking for ways to increase efficiency and reduce costs in their production processes.  The automation of industrial processes is benefiting significantly from technological advances, offering alternatives to achieve these objectives more effectively and efficiently. Automation and artificial intelligence have played a key role in transforming industrial operations, driving progress and efficiency across different sectors.  Artificial intelligence, in particular, has impacted the industrial sector, driving advances in robotics, automation and operational efficiency, but also raising challenges in relation to social and economic aspects. Therefore, this work aims to address how artificial intelligence in the automation of industrial processes is essential in day-to-day industrial operations, as it allows repetitive, dangerous or complex tasks to be carried out more efficiently and safely.  It involves the use of automated systems and equipment to carry out activities such as assembly, transportation, packaging, quality control, among others. 

As the advantages of high performance and low power, the Loongson-1 processor has wide application prospects in industrial control, high-performance embedded, and other fields. Now the Loongson series platforms are mostly based on Linux operating system. However, VxWorks is a better choice for its high real-time performance and high reliability in the field of industrial control and high-performance embedded. In this paper, methods of transplanting VxWorks to the Loongson 1B platform are proposed which include VxWorks interrupt management, Cache library and VxBus device drivers. Through the implement of VxWorks running in the Loongson 1B board and the validation of checking the serial port equipment, the transplanting methods are feasible in this paper, and the transplantation of CPU performance is analyzed.

The software methods for monitoring network security (NSM - Network Security Monitoring) are discussed. With the growth and rapid development of mobile communications, rich data and artificial intelligence technologies, we are entering the era of the mobile Internet. With the continuous intellectualization of network security and infrastructure, information technology is widely used in the field of industrial control, making network security more and more open, bringing a new network security control system to the traditional relatively closed industrial control system. Currently, there is an increase in the number of information threats and factors leading to the unstable operation of data transmission networks. The prerequisites for this growth are the mass application, the complication of the hierarchy of computer networks and the increase in their structural complexity, the increase in the heterogeneity of software and hardware, the complication of the functionality of network services, which leads to the emergence of various vulnerabilities. Under such conditions, the development and improvement of methods for identifying information threats are of great importance. One of the components of ensuring information protection of networks is software systems designed to detect harmful or suspicious activity - network security monitoring methods (NSM). Network security monitoring techniques (NSM) are used to monitor network 133 communications for information security events. For maximum effect, a combination of capturing the entire packet in addition to logging network activity is recommended. This article provides definitions of network security monitoring methods, their classification, phases of the method cycle and their description. Some of the best known and widely used multi-module NSM solutions have been reviewed. The best known examples of such combinations are IDS/IPS, SEM/SIEM and UTM. Network security monitoring is important because it checks if the first lines of defense are working, gives us the opportunity to eliminate threats before they cause real damage if there is a vulnerability somewhere in your system, and allows us to understand where these vulnerabilities are and how to fix them before something will happen.