In this article, we present an implementation of a low-memory footprint model predictive control (MPC)-based controller in programmable logic controllers (PLCs). Automatic code generation of ...standardized IEC 61131-3 PLC programming languages is used to solve the MPC's optimization problem online. The implementation is designed for its application in a realistic industrial environment, including timing considerations and accounting for the possibility of the PLC not being exclusively dedicated to the MPC controller. We describe the controller architecture and algorithm, show the results of its memory footprint with regard to the problem dimensions, and present the results of its implementation to control a hardware-in-the-loop multivariable chemical plant.
SMK Negeri 1 Balige memiliki konsentrasi bidang teknik instalasi tenaga listrik dan perlu ditingkatkan kemampuannya dalam otomasi industri, khususnya Programmable Logic Controller (PLC). Berdasarkan ...kebutuhan ini, tim pengabdian kepada masyarakat (PkM) tergerak untuk dapat ikut berkontribusi dalam diseminasi pengetahuan dibidang otomasi PLC. Kegiatan pelatihan dilaksanakan dengan mengkombinasikan sesi pelatihan teori secara daring dan praktik menggunakan PLC Trainer KIT OMRON. Selama pelatihan, peserta telah memperoleh pengetahuan dan keterampilan PLC level dasar. Hasil evaluasi menunjukkan terjadinya peningkatan kemampuan PLC sebesar 0,3 (kategori sedang). Pendampingan dan pelatihan PLC ini perlu dilanjutkan guna memberikan wawasan dan ketrampilan tambahan bagi para siswa/i SMK Negeri 1 Balige dalam upaya peningkatan daya saing tenaga kerja di bidang otomasi industri.
This article presents the concept of boundary-based predictive controller (BBPC) as an effective tool to control industrial processes with on- - off actuator, for which the control goal is defined to ...keep the process output within the desired range. An example use of BBPC is shown in application to control of dissolved oxygen (DO) concentration in the laboratory activated sludge setup with biological reactor. It is suggested how to identify dynamical parameters of the proposed DO concentration model and how to provide adaptability required to ensure desired control performance in the presence of significant changes of process load disturbance. Practical implementation in programmable logic controller in the form of a general purpose library function block is also presented. Experimental comparison with conventional on - off controller shows robustness and superiority of the proposed BBPC.
Nuclear Power Plants (NPPs) are physically isolated from external networks and have different operational environments than conventional information technology (IT) systems. Accordingly, NPPs were ...regarded as safe from external cyber-attacks. However, it was later determined that isolated networks are not safe from cyber-attacks. Malicious data injection attacks on Programmable Logic Controllers (PLCs) deployed in the safety system of NPPs are critical to nuclear facilities, as they were in the Stuxnet attack. It is necessary to monitor the integrity of PLC data and protect the PLCs from cyber threats such as modification of deployed logic or setpoints. To address this problem, this paper proposes a novel system for monitoring data integrity of PLCs using blockchain technologies. Considering the NPP environment, we developed a private blockchain system to monitor the data integrity of PLCs. The new concept that is Proof of Monitoring (PoM) for data integrity of PLCs was proposed to overcome the limitation for applying the private blockchain to the cybersecurity of NPPs. Additionally, we developed an integrity monitoring system for the Reactor Protection System (RPS)-a safety system in NPPs-using the developed blockchain. It can detect cyber-attacks (such as false code injection attacks on PLCs) and monitor which PLC integrity has been compromised in real-time. A validation experiment using a false data injection attack on PLCs was performed on the developed system, and the results confirmed that the developed system successfully monitored the modification of data in the PLCs.
Traditionally, proportional-integral-derivative (PID) based hydro turbine governors are mainly used due to their robustness and simple implementation. However, the weakness of these controllers is ...their design based on linear models and fixed parameters structure. This implies that the controller's parameters are usually calculated for the critical operating point leading to the controller's underperformance when operating away from the critical operating point. This paper introduces a Model Predictive Control (MPC) based hydro turbine's governor load/frequency controller whose linear prediction model parameters are updated depending on the operating point. The main intention of the paper is to reduce the gap between theoretical contributions and industrial practice. The experimental validation is achieved by implementing the introduced MPC algorithm to a laboratory hydro power plant's governor Programmable Logic Controller (PLC) and comparing its response with the responses of the gain-scheduled PI (GS-PI) controller, PI controller based on Particle Swarm Optimization (PSO-PI) and the controller based on exponential control law (EXP).
Programmable logic controller (PLC) system, a typical member in the embedded family, is now widely applied in industry. For safety critical PLC systems, reliability is of top significance. However, ...due to subcomponents' temporal correlations caused by the run-time execution of embedded ladder programs, the complexity of reliability analysis is greatly increased. In this paper, we propose a novel probabilistic model to analyze reliability of PLC systems, called run-time reliability model (RRM). RRM is automatically constructed based on the structure and run-time execution of the embedded ladder program. Moreover, it is also a dynamic bayesian network (DBN) capturing full dependencies in a PLC system. Then, according to execution semantics of RRM nodes, we present customized conditional probability distribution (CPD) tables to calculate final reliability of the system, with failure probability of every referenced component as refinement. The strength of this model is that not only does it explicitly specify the correlations between run-time execution of embedded software and system components, but also it serves as a computational mechanism for probabilistic inference. Besides, the proposed approach is superior to previous works in both accuracy and efficiency. Compared to monte carlo based simulation, the average error rate of reliability values inferred from RRM model is small.
A programmable logic controller (PLC) executes a ladder diagram (LD) using input and output modules. An LD also has PID controller function blocks. It contains as many PID function blocks as the ...number of process parameters to be controlled. Adding more process parameters slows down PLC scan time. Process parameters are measured as analog signals. The analog input module in the PLC converts these analog signals into digital signals and forwards them to the PID controller as inputs. In this research work, a field-programmable gate array (FPGA)-based multiple PID controller is proposed to retain PLC scan time at a lower value. Concurrent execution of multiple PID controllers was assured by assigning separate FPGA hardware resources for every PID controller. Digital input to the PID controller is routed by the novel idea of analog to digital conversion (ADC), performed using a digital to analog converter (DAC), comparator, and FPGA. ADC combined with dedicated PID controller logic in an FPGA for every closed-loop control system confirms concurrent execution of multiple PID controllers. The time required to execute two closed-loop controls was identified as 18.96000004 ms. This design can be used either with or without a PLC.
Edge computing allows for data processing at reduced latency since the computational power is moved close to the data sources. Traditionally, edge computing has been often used in industrial ...scenarios for implementing gateways between the operational technology (OT) world and the IT (cloud) world. Recently, big manufacturers of industrial programmable logic controller (PLC) started promoting the use of containerized virtual PLC (vPLC) hosted inside edge computing platforms. They foresee an innovative integration of container based applications, including automation control, with all the data-centric services and applications already available for edge ecosystems. Even if a clear advantage from the scalability and maintainability could be expected, would vPLCs meet the stringent requirements of industrial automation? This article is part of a multistage research work, and as a first step, it is focused on the evaluation of the performance of vPLC when exchanging data with other machines, controllers, supervisors, and data acquisition systems in a machine-to-machine (M2M) scenario. After a brief overview of the involved technology, the design of a methodology for comparing real PLC and vPLC is described. Then, performance metrics, and an experimental setup for the evaluation of existing devices are defined taking care of the sources of uncertainty. The effectiveness of the proposed methodology is demonstrated by considering a real use case. Through the use of the suggested methodology, important insights into the use case are revealed: for instance, the considered vPLC could work as fast as a real PLC with minimum communication latency in the order of 3 ms but, currently, there is a random delay with an average of 50 ms whose source has been identified to be the IP stack implementation of the vPLC. Finally, the proposed methodology allows for the creation and validation of analytical models of the use case.
The Internet of Things (IoT) has become critical to the implementation of Industry 4.0. The successful operation of smart manufacturing depends on the ability to connect everything together. In this ...research, we applied the TOC (Theory of Constraints) to develop a wireless Wi-Fi intelligent programmable IoT controller that can be connected to and easily control PLCs. By applying the TOC-focused thinking steps to break through their original limitations, the development process guides the user to use the powerful and simple flow language process control syntax to efficiently connect to PLCs and realize the full range of IoT applications. Finally, this research uses oil–water mixer equipment as the target of continuous improvement and verification. The verification results meet the requirements of the default function. The IoT controller developed in this research uses a marine boiler to illustrate the application. The successful development of flow control language by TOC in this research will enable academic research on PLC-derivative applications. The results of this research will help more SMEs to move into smart manufacturing and the new realm of Industry 4.0.
Programmable logic controllers (PLC), which are widely applied in modern industrial control systems (ICS), work as the controller of sensors and actuators in ICS. These systems require strict ...correctness, especially for safety-critical systems. Currently, increasingly ICS move to "come online" scenarios to enhance cyber-physical features, but it makes them more vulnerable due to acquiring increased interconnection accompanied by weakening physical isolation. Moreover, with the more complex controlling environment, such as hundreds of more I/O points and more diverse field buses, the incorrect executions of PLC might cause the failure of the overall ICS. In this article, we examine how the security and safety of running PLC could be enhanced in both developing and deploying stages of ICS. We propose a novel application of runtime verification to guarantee the security and safety of real-world ICS. As a variant of temporal logic, PLC past linear temporal logic (PPLTL) is proposed to specify the security and safety properties of PLC. Using PPLTL, we synthesize monitors to improve the PLC program's security and safety as a partner of testing and static verification. Our monitors provide twofold processing in a nonintrusive manner: One is filtering abnormal input data before invading the original programs, the other is double-checking the output signals before driving the actuators. We use several case studies and benchmarks to demonstrate the efficiency of the approach. The empirical results show that the time overhead and memory occupation are tiny.
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