Multiple use of an industrial‐distributed control system in control engineering education

Education in Control Engineering for the Designers of Environmental Processes

The new requirements of modern real-time distributed supervision and control systems such as more flexibility, interoperability, and cost savings, have motivated the use of software-intensive solutions both in academia and industry. Following this trend we have presented, in a previous publication, the design rationale and implementation issues of a flexible and reusable software platform (ARCOS) that relies on the CORBA component model (CCM/CIAO), the DAIS (data acquisition from industrial systems) standard, and framework technologies. This paper builds on this previous publication by presenting a new assembly tool that allows for the visual component-based implementation of ARCOS-based systems and the automatic generation of the related CCM/CIAO/ARCOS artifacts. To demonstrate the power of such a tool, two example applications are presented.

Structures and criteria of distributed process automation systems

The need for high performance control systems has accelerated over the past decade. This need has been pushed by economic pressures related to increased throughput, higher quality products produced more consistently, increased utilization of raw materials and decreased energy utilization. The rise of environmental and safety issues and a tighter material and energy integration has also added to the demands of modem control systems. At the same time, increased computational power through modern distributed control systems has provided the means to implement many advanced control algorithms at reasonable costs.

The paper presents educational issues related to the development and implementation of low-cost control solutions and algorithms used in the syllabus of control engineering courses applied to the Magnetic Levitation System with 2 Electromagnets laboratory equipment. Real-time experiments are included to accompany the laboratory-based education in control engineering.

7 - Distributed control systems (DCS)

The distributed control system (DCS) is the most prevalent means of implementing batch and continuous control in the process industry. The DCS platform may also be effectively used for the evaluation and demonstration of innovative algorithms developed at a university. The integrated online advanced controls, diagnostics, data analytics, and process modeling capability of a DCS facilitate university research. This working environment also prepares students for careers in industry. The paper discusses the industrial standards adopted by the DCS that allow students and researchers to concentrate on the application of new control capabilities. External applications such as Matlab can be used with the DCS to explore control and process modeling. In this environment, the student and researchers may take advantage of preconfigured and automated features of the DCS. Process simulations may be integrated into the DCS to create a virtual plant capability that is capable of running faster than real-time. The DCS supports wireless and internet access to the virtual plant which increases ease of use in a lab or pilot plant. The DCS system enables rapid exploration, discovery, and prototyping of process modeling and control technologies in a university environment and deployment in industry.

Traditional control engineering teaching methods heavily rely on abstract mathematical concepts, often leaving students puzzled about real-world applications. Common simulation tools, such as MATLAB and Simulink provide a good visual demonstration but don't necessarily bridge the gap between theory and application. The proposed ‘lab-in-a-box’ approach offers a tangible method for students to connect control theory with a practical control engineering experience. The literature has observed a shift towards such portable labs, given the advancements in compact computing devices such as Raspberry Pi and Arduino boards in electronics and control teaching. The primary goal of these labs is to deliver an authentic engineering experience with essential hardware. Evaluation of this method, through the student module evaluation questionnaire (MEQ), revealed a significant increase in student satisfaction after its introduction. While the results are promising, challenges remain, such as the initial set-up of the kits. However, the ‘lab-in-a-box’ is found to be a valuable tool in control engineering education, bridging the gap between theoretical and practical understanding. An on-going development includes updating of the kits to match future engineering challenges and needs, e.g., electrification and autonomy of vehicles.

Searching for more efficient ways to improve process quality and increase plant throughput has encouraged changes in the control system architecture toward greater distribution. A distributed control system, illustrated in Fig.15.1, can be defined as control systems in which functions around a plant are distributed into computing nodes (i.e., control computers and smart devices) that are physically separated; and all the computing nodes are interconnected by digital communication networks (e.g., fieldbuses). Distributed control systems are now found in many industrial fields, such as oil and gas production (Hars, 1994), automobiles (Hansson et al., 1997), and gas turbine engine control (Shaffer, 1999). Advances in distributed control system technology have been driven by the ever increasing performance of smart field devices and fieldbuses using smaller, less expensive and more functional microprocessors. In fact, the goal of a distributed control system is the same as its centralised counterpart; that is, to get input from the plant through its sensors and give output using its actuators. However, the use of field-buses and smart devices introduces many advantages into a distributed control system over a centralised one. Not only does a distributed architecture offer reduced wiring and simplified maintenance, it also provides the opportunity to implement different control strategies. Consequently, the emergence of distributed control systems is promoting changes in control systems design issues. One of the key changes from conventional control techniques is driven by the local processing power. In distributed architectures, smart devices employing a built-in microprocessor with a fieldbus interface offer the possibility of the faster and more reliable self-diagnosis and self-compensation. Several researchers (Henry 1993; Koscielny et al 1997) have discussed the benefits of local fault-diagnosis. Extra information about the element status reported through a fieldbus network is also very beneficial for reconfigurable control. For example, Lee et al. (2001) presented an on-line retuning strategy for PI control to tolerate actuator faults using this information.

Emerging IT technologies, specially Internet communication and webbased technologies are adopted to the modern distributed control systems. This paper defines a functional framework for the webbased applications of a distributed control system connected by Internet. XML(eXtensible Markup Language) is used for representing a control system and control devices. These IT technologies make a distributed control system more flexible and scalable than existing distributed control systems with the standard RMI protocols such as CORBA or DCOM.

Distributed Control System (DCS) has been widely recognized in the field of modern thermal power thermal control, and has significant effects in the application process. Today, the monitoring of electrical quantities is included into the DCS system, thus replacing the traditional "one to one" manual mode of operation in electrical control. It is to further improve the main works of the station automation and control systems. Combined with the actual project needs, this study focuses on the components of electrical control included in DCS system, the implementation of software and hardware features, and the measures to improve reliability. In addition, useful discussions have been made for some technical problems. In the DCS system, the electrical control inclusion is not just a perfection thermal power plant electrical control system, but a big improvement as well. In addition, it is a new attempt. At present, most of the electrical control parts of control system included into the DCS system with the manual operation are basically cancelled, but there are some problems, for example many of the designs do not match with the original operating habits, etc., which will have a certain impact on the tradition. In the transformation process of system, some of the designs are good but cannot be achieved currently. They still need further research and improvement, for example how can the electrical control of system enter into the DCS in a better manner, how can the display of light texts upon failure or abnormal time weaken electric signals in a more comprehensive and rapid manner, what are the new requirements for anti-interference, and other sequential control functions to be improved and perfected.

Real-Time Control of Tokamak Plasmas: from Control of Physics to Physics-Based Control

Abstract: Brusoni, Prencipe, and Pavitt (2001) posited that the digitization of aircraft engine control systems in the early 1980s caused loose organizational coupling. During this period, the number of control parameters indeed increased significantly with the introduction of full authority digital engine control (FADEC). However, during the period categorized by Brusoni et al. (2001) as the (analog) generation, digital technologies such as analog electronic and supervisory controls were gradually introduced. Moreover, with regard to technological changes in aircraft turbofan engines and control systems, technological improvements in engine power systems were evident in the 1960s and 1970s in terms of the bypass ratio, overall pressure ratio, and turbine inlet temperature. Although engine power systems witnessed negligible technological innovation in the 1980s, control systems improved as the number of control parameters increased due to the advent of FADEC. Subsequently, in the 1990s, great technological strides were made in engine power systems. Hence, technological changes in engine power systems and control systems always occurred alternately. Brusoni et al.'s claim that the decline in organizational coupling was due to the even rate of technological change in engines and control systems or the predictability in their interdependence miss the mark in light of the transition history of engine and control systems.Keywords: analog (hydromechanical), digital, aircraft engine control system, technological imbalance1. IntroductionBrusoni, Prencipe, and Pavitt (2001) categorized aircraft engine control systems from the 1950s to the 1970s as hydromechanical (analog) and those from the 1980s to the 1990s as digital. Brusoni et al. (2001) described the scope for change in the organizational structure and knowledge of three companies1 from the perspective of the evolution of control system technology. However, they barely mentioned the change in control system technology from analog to digital, nor did they focus on the changes in the engine power systems, which are associated with changes in control system technology. Referencing Brusoni et al.'s arguments, this study focuses on the transition of engine control systems from analog to digital and the associated technological changes in the power systems in order to review the technologies analyzed by Brusoni et al.2. Technological Change of Engine Control System:From Hydromechanical to DigitalBrusoni et al. (2001) focused on the control systems of aircraft turbofan and turbojet engines. A turbojet engine comprises an air intake, a fan/compressor, combustion chamber, turbine, afterburner, and tail nozzle. The pilot adjusts the position of the throttle lever to achieve the required thrust. The engine control system provides the necessary thrust by receiving the lever position as input and adjusting the fuel flow, thereby accelerating or decelerating the engine's revolutions per minute (RPM). Furthermore, it confirms whether the thrust corresponds with the pilot's intention and maintains the required thrust levels (Yoshinaka, 2010).Compared with the digital system, the analog system could control only a limited number of items. The following section discusses the evolution of jet engine control technologies based on Endoh (2004), Sugiyama (2004), Sono (2008), and Yoshinaka (2010).2.1. Hydromechanical controlThe jet engine was first adopted as a source of thrust in aircrafts in the 1930s. Simple mechanical fuel controls comprising cams and levers were used in reciprocating engines, which constituted the majority at the time. The control required by jet engines was comparatively complex, and the existing technology was inadequate. Even in the case of early post-war turbojet engines, variables of fuel flow or bleed valve could only be controlled. Subsequently, advances in the level of precision and miniaturization in the areas of mechanics and oil hydraulics led to progress in the control technologies of aircraft engines. …

In response to the article Undergraduate control education: an ME perspective, by Agrawal, this article presents the author's view on several key issues in control engineering education, some are pertinent to electrical engineering (EE), some are more general. These issues include: 1) in comparison to mechanical engineering (ME) and other engineering disciplines, what does EE have to offer in control engineering education? and 2) does an undergraduate control curriculum have to start from LTI system theory? The author proposes some radical thoughts about fundamental changes in the infrastructure and pedagogical structure for control engineering education with ramifications to control engineering practices. These suggestions include: 1) seriously considering the advantages and drawbacks of centralized and independent control and systems engineering program, and 2) changing the entry point to control engineering curriculum from LTI to nonlinear system theory.

Within industry today, advancements in process and control technologies have given way to differing control systems in the form of programmable logic controllers (PLC) and distributed control systems (DCS). Over the past decade, PLCs have now been able to bridge certain gaps within process and control systems that were capabilities only typically found within DCS environments. This paper will provide an overview of various control system strategies and design considerations with regard to both PLC and DCS schemes within petrochemical applications.