Industrial Control Software Research Articles

Ranking guidance actions to support engineers in fulfilling process constraints

AbstractIn safety‐critical systems engineering, regulations such as Automotive SPICE, ISO26262, or ED‐109A mandate software quality assurance measures to provide evidence that the developed system is high quality. The constraints that define quality assurance conditions during the engineering life cycle are often non‐trivial. This paper addresses the challenges, engineers face who are unfamiliar with the precise constraints of various projects (e.g., when newly joining a company or switching between departments). Understanding how to fulfill a constraint is a time‐consuming and challenging task as an engineer needs to determine the most suitable option (out of potentially many) to fulfill a constraint violation. To this end, we propose a guidance action ranking framework to provide engineers with the most relevant guidance actions. Our primary ranking algorithm analyzes in the background the actions that engineers have made in the past to resolve a constraint violation without requiring explicit feedback from them. We evaluated our framework on two real‐world data sets: an open‐source drone management and an industrial air traffic control software system. Concretely, we replay past engineering activities and measured whether, in the case of a constraint violation, our suggested guidance actions were indeed selected by the engineer. The evaluation results revealed that learning from prior guidance actions effectively identifies the most appropriate guidance actions (ranked top 1 or 2) when compared to ranking algorithms based on action simplicity and artifact property change frequency. Specifically, we achieve a median MRR of 0.95 for the first case study and 0.94 for the second case study: an improvement of 80% and 100% over the baseline. Additionally, we observed that the simplicity of a guidance action does not reliably indicate its suitability for fulfilling a constraint, whereas learning from prior change operation property out‐performed simplicity‐based ranking but did not surpass guidance frequency‐based ranking.

Assessing the usefulness of a visual programming IDE for large-scale automation software

Industrial control applications are usually designed by domain experts instead of software engineers. These experts frequently use visual programming languages based on standards such as IEC 61131-3 and IEC 61499. The standards apply model-based engineering concepts to abstract from hardware and low-level communication. Developing industrial control software is challenging due to the fact that control systems are usually unique and need to be maintained for many years. The arising challenges, together with the growing complexity of control software, require very usable model-based development environments for visual programming languages. However, so far only little empirical research exists on the practical usefulness of such environments, i.e., their usability and utility. In this paper, we discuss common control software maintenance tasks and tool capabilities based on existing research and show the realization of these capabilities in the 4diac IDE. We performed a walkthrough of the demonstrated capabilities using the cognitive dimensions of notations framework from the field of human–computer interaction. We then improved the tool and conducted a user study involving ten industrial automation engineers, who used the 4diac IDE in a realistic control software maintenance scenario. Based on lessons learnt from this study, we adapted the 4diac IDE to better handle large graphical models. We evaluated these changes in a reassessment study with automation engineers from seven industrial enterprises. We derive general implications with respect to large-scale applications for developers of IDEs that we deem applicable in the context of (visual) model-based engineering tools.

Efficient absorption cooling for low district heating return temperatures

In the past years scientists of Technische Universität Berlin, developed a new generation of single stage H2O/LiBr absorption chillers in the range of 50 to 500 kW nominal cooling capacity. In 16 installations 25 absorption chillers have been monitored within a broad field test (FeldtestAbsorptionskälte für Kraft-Wärme-Kälte-Kopplung-Systeme, FAkS, funded by BMWi as project FKZ 03ET1171a-d) in the years 2013 to 2018. Annual performance figures of thermal coefficient of performance (COPth) in the range of 0.7 kWh 0/kWh 2 and electrical coefficient of performance (COPel) superior to 20 kWh 0/kWh el have been proven, serving district heat (DH) return line temperatures in the range of 62 °C to 68 °C.While the FAkS project focused on installation and operation of absorption chillers themselves, the follow-up project called ReKs (Regelungenergie-aufwandsoptimierterKälteerzeugungssysteme, FKZ 03ET1583), concentrates on overall system control and efficiency. Controlling absorption chiller cooling supply at low district heat return line temperatures is extended to an energy efficient control of all participating components including hot water, chilled water, heat sink pump and cooling tower fans. Models and strategies have been developed on thermal science theory and implemented in industrial control software. Proof of concept has been evaluated by monitoring field test installations while in parallel particular field test related parameters have been varied. Without diminishing quality of chilled water temperature and/or cooling capacity, electrical energy efficiency can at least be doubled, compared to the figures of FAkS installations. Moreover, new strategies enable efficient absorption cooling with DH return line temperatures in the range of 50 °C during moderate weather conditions periods. Field test results from 2020 and 2021 are presented here.

Dezyne: Paving the Way to Practical Formal Software Engineering

Designing software that controls industrial equipment is challenging, especially due to its inherent concurrent nature. Testing this kind of event driven control software is difficult and, due to the large number of possible execution scenarios only a low dynamic test coverage is achieved in practice. This in turn is undesirable due to the high cost of software failure for this type of equipment. In this paper we describe the Dezyne language and tooling; Dezyne is a programming language aimed at software engineers designing large industrial control software. We discuss its underlying two layered and compositional approach that enables reaping the benefits of Formal Methods, hereby strongly supporting guiding principles of software engineering. The core of Dezyne uses the mCRL2 language and model-checker (Jan Friso Groote et al.) to verify the correctness and completeness of all possible execution scenarios. The IDE of Dezyne is based on the Language Server Protocol allowing a smooth integration with e.g., Visual Studio Code, and Emacs, extended with several automatically generated interactive graphical views. We report on the introduction of Dezyne and its predecessor at several large high-tech equipment manufacturers resulting in a decrease of software developing time and a major decrease of reported field defects.

Industrial control via application containers: Maintaining determinism in IAAS

AbstractIndustry 4.0 is changing data collection, storage, and analysis in industrial processes fundamentally, enabling novel applications such as flexible manufacturing of highly customized products. However, real‐time control of these processes has not yet realized its full potential in using the collected data to drive further development. Indeed, typical industrial control systems are tailored to the plant they need to control, reusing, and adapting to challenge. In the past, the need to solve plant‐specific problems overshadowed the benefits of physically isolating a control system from its plant. We believe that modern virtualization techniques, specifically application containers, present a unique opportunity to decouple control from plants. This separation permits us to fully realize the potential for highly distributed and transferable industrial processes even with real‐time constraints arising from time‐critical subprocesses. This paper explores the challenges and opportunities of shifting industrial control software from dedicated hardware to bare‐metal servers or (edge) cloud computing platforms using off‐the‐shelf technology, that is, technologies commercially available. We present a migration architecture and show, using a specifically developed orchestration tool, that containerized applications can run on shared resources without compromising scheduled execution within given time constraints. Through latency and computational performance experiments, we explore three system setups' limits and summarize lessons learned.

Exploration of the Application of Artificial Intelligence Technology in Mechatronics Technology Based on

With the development of industrial control software technology, more and more control technology is practiced and landed, which also makes a lot of modern processing mode and means can be shaped, together with non-standard mechanical structure design, in many processing stations, can achieve subversion of the traditional efficient processing mode. With the emergence and development of artificial intelligence, the combination of the two has become a natural fit, bringing a boon to many manufacturing enterprises. In this context, this paper discusses the application of AI-based technology in mechatronics technology.

Active disturbance rejection control of torsional plant with unknown frequency harmonic disturbance

In this work, a new robust control algorithm is introduced for uncertain systems with harmonic disturbances of unknown frequencies. The proposed solution works under the active disturbance rejection control (ADRC) framework and utilizes a specialized observer for sinusoidal uncertainties, aided with an on-line harmonic disturbance frequency estimator. The entire governing structure is derived in a convenient error-based domain, easily deployable in various industrial control software. The idea behind the introduced approach is general, but is conveyed here using solely a three degrees-of-freedom torsional system, which is considered a benchmark for vibration phenomenon in many mechanical systems. The efficacy of the proposed control scheme is validated with a set of experiments on a laboratory testbed and a theoretical analysis based on theory of singular perturbation.

Hierarchical analytical and simulation modelling of human-machine systems with interference

The article considers the principles of building the analytical and simulation model of the human operator and the industrial control system hardware and software. E-networks as the extension of Petri nets are used as the mathematical apparatus. This approach allows simulating complex parallel distributed processes in human-machine systems. The structural and hierarchical approach is used as the building method for the mathematical model of the human operator. The upper level of the human operator is represented by the logical dynamic model of decision making based on E-networks. The lower level reflects psychophysiological characteristics of the human-operator.

Optimization of Multitask in Real-Time Control Based on Artificial Bee Colony Algorithm

Real-time industrial control software often has the characteristic of multitask communication within single thread, which can easily cause the thread to block. The problem can be abstracted into nonlinear constrained optimization model based on requirements of developing the industrial control software, and solved by artificial bee colony algorithm. The ABC algorithm needs less parameters, and has stronger capability of global search than other intelligent algorithms. Considering characteristics of the nonlinear constrained optimization model, three modifications are adopted to improve the capability of global search in this problem. They are a modification rate for generating a new solution, the probability of selecting a new solution by onlooker bees which is different between feasible solutions and infeasible solutions, Deb’s constrainted handling method. A comparing result shows that the modified ABC algorithm provides a better solution than GA algorithm does. By putting the solution into practice, high-speed and reliable communication can be realized between IPC, PLC and NC.

The Design Process of Defect Detection Method for Large Industrial Automatic Control Software

The current difference trend of automatic control software structure is more obvious, software integration makes linking correlation of overall structure appeared to play down. No significant linking characteristics exist between structural ports. The traditional detection methods of software defect are utilized to locate software defect under the differentiation structural framework, due to the lack of clear articulation feature to indicate the location region, resulting in unidentified area which software defect signal belong to and position deviation. In this paper, software defect detection method was proposed on the basis of difference structure fusion algorithm. The signal fusion technology was applied to mix the signal of software defect detection effectively, and chaos particle swarm algorithm optimization was employed to support vector machine parameters, establish the optimal models of software defect prediction, thus completing the software defect detection. Experimental results show that the algorithm for software defect detection, can greatly improve the accuracy of detection.

Model-driven engineering of process control software – beyond device-centric abstractions

This paper presents a new, two-level, model-driven engineering approach to industrial process control software. The first level (infrastructure engineering) is concerned with the following: the definition of the development process and guidelines, the definition of a domain-specific modeling language, the specification of the model transformations, and the development of a tool suite. This tool suite enables modeling of the process control software and the automatic code generation for programmable logic controllers. In the second level (application engineering), the process control software is engineered using the results of the infrastructure level. The approach is demonstrated on excerpts from an industrial project.

A Dynamic Software Configuration Model Based on Embedded System

With the embedded software development, the implementation and the logic of embedded software are required to detach in application. We proposed a configuration model of embedded software based on component technology and the configuration of industrial control software. This model can abstract the whole application into some independent components, and then combine these components together by customizing the configuration. It is proved that this model can enhance both the speed and efficiency of the embedded software development greatly, as well as improve the flexibility and logic scalability of embedded software. The embedded software with the dynamic software configuration model can guarantee the realization of the requirements to the fullest extent.

Behavioural inheritance in object-oriented models for mechatronic systems

This paper describes a formal framework for Object-Oriented (O-O) modelling of mechatronic systems, whose main contribution is, on the one hand, to unify the modelling approaches for dynamical systems and for industrial control software and, on the other hand, to provide a definition of inheritance, a cardinal concept in object-orientation, which emphasises the behavioural conformity of basic and derived classes of objects. The proposed framework exploits the coalgebraic description of software artefacts to provide a connection between the behavioural approach for modelling dynamical systems and the O-O approach for software modelling and design. In particular, our definition of inheritance aims to allow control engineers to apply the design by extension methodology, widely used in software engineering, to the development of mechatronic components for manufacturing systems.

Exception handling for PLC-based process control software

This paper deals with the possibility of introducing exception handling mechanisms into the specification and code of industrial process control software. Although exception handling is a very important aspect of process control applications, in most cases it is treated in an ad hoc and unstructured manner — which is mainly caused by the lack of appropriate constructs in programming languages for programmable logic controllers. A high degree of mastery of the development process can be achieved by applying an engineering process based upon life cycle and domain engineering concepts. The main result of domain engineering is a conceptual model of the domain in question. One of the elements of the conceptual model is the specification language with a defined exception handling construct. The exception handling construct is illustrated by a real application excerpt. It would be useful to include this exception handling construct into the Structured Text controller programming language.

Algorithms for industrial model predictive control

The article is concerned with control methods that have been embedded in an industrial model predictive control software package and that have been applied to a wide variety of industrial processes. Three methods are described and the various features are evaluated by considering a constrained multivariable simulation. One method has been in use since 1988 and is widely exploited in industry. The latest methods employ quadratic programming, which has become realistic to employ because of the advances in computing. The relative attributes are contrasted by assessing the ability of the controllers to recover effectively from the impact of a large unmeasured disturbance.

A hybrid, knowledge-based system as a process control ‘tool’ for improved energy efficiency in alumina calcining furnaces

This paper describes the development and implementation of a hybrid SCADA (Supervisory Control and Data Acquisition) system for the air suspension ‘flash’ alumina calciner at Aluminium de Grece St. Nicholas plant. The system includes two additional modules, an ‘expert system’ based on 10 years of commissioning and operating experience and a dynamic model continuously predicting the quality of the product. It is implemented on an industrial PC under an industrial control software environment and interfaces to the furnace through a programmable logic controller (PLC) system. The system guides the furnace operator to reduce sensible heat losses by operating with a marginal excess air flow rate, to take advantage of the higher energy efficiency at higher production rates and, at the same time, to avoid potentially dangerous operating conditions leading to loss of production and consequential energy losses. It also performs the traditional SCADA functions (data acquisition, maintaining history files for important parameters and display of important operating parameters in both a mimic process diagram and a series of graphs.) In addition to these tasks a simplified dynamic model gives the operator a prediction of the current value of the main product quality parameter, which can only be measured with laboratory equipment. Preliminary results have shown that reduction of secondary air flow rate and reduced downtime achieved by the operator under the guidance of the system can reduce energy consumption by as much as 10%. A similar, or even greater, improvement in energy efficiency can be expected by implementing a similar system to cement calcination kilns based on the same technology.

Identification of structurally constrained second-order Volterra models

Continuing advances in industrial control hardware and software have increased interest in the identification of nonlinear dynamic models from chemical process data. Two practically important issues are those of nonlinear model structure selection and input sequence design for adequate model identification. While the "general nonlinear model identification problem" is intractably complex, we may obtain useful insights into both of these issues by restricting our attention to special cases, building incrementally on our "linear intuition". We consider the special case of second-order Volterra models, focusing on the effects of structural restrictions and non-Gaussian input sequences on the model identification problem. The results presented build on the work of Powers and his co-workers, who considered the unconstrained Gaussian problem, certain constrained special cases (e.g., the Hammerstein model), and identification using non-i.i.d. input sequences. Besides extending these results to a wider class of model structure constraints and input sequences, the results presented yield some useful insights into the issue of input sequence design.

I-I-Con: A visual communications paradigm to integrate industrial control system engineering

The process control industries have seen a great explosion in different function block programming languages over the last five years. Each of these languages is proprietary meaning that there is no ability to port one function block program to another platform. Some standards for process control symbology have been developed, but they lack the richness of graphic expression often contained in the commercial products. There are also problems with integrating the continuous-time function block languages with discrete-event languages used on programmable logic controllers (PLCs), though the integration of these two types of control are often needed in practice. I-I-Con is being designed to provide an open-systems platform for both continuous-time PID control and discrete-event PLC control using a single integrated paradigm. The I-I-Con programming language is also intended to integrate industrial control software design with coding by capitalizing on the similarity of Petri-net like diagrams which have been used both to program PLCs and to perform general systems design and engineering. Thus, the same pictures which are used to perform systems design can then be used to code the control application. Here we describe the I-I-Con project at the University of Cincinnati. We intend for the I-I-Con project to have a major impact on how industrial control systems are developed in the future. We are currently soliciting suggestions and criticisms from the industrial controls community while the project is in its formative stages.

Design and Implementation of Process Control Software Under Realistic Environment Conditions

A software package is described which offers a systematic approach to development of industrial process control software. The procedure of con trol program implementation splits up in 3 basic steps or phases. Phase 1 covers control algorithm design and offline simulation. During phase 2 the real control programs are installed on process computer using results and experience of step one. Programs are thoroughly tested and evaluated in real time environment. The interplay of control software performance on the whole and its control behaviour can be investigated in closed loop simulation. Within phase 3 control software is tested on a dual computer system consisting of one computer simulating and a second computer controlling the plant. Both computers are coupled by realistic process interface equipment and are working asynchronously. Plant simulation and control software operate in parallel and in real-time. Phase 3 simulation supports final tuning and adapting of control algorithms and parameters. Concerning software engineering aspects an overall test and performance evaluation of the control system can be done. The system establishes a software and control engineering tool which makes control software development less costly and more reliable. Especially the transfer to real plant will become less risky after testing under realistic environment conditions.