This paper proposes a novel AI agent for reasoning, planning, and testing industrial automation applications. The AI agent accepts operator instructions in natural language and performs semantic reasoning over functional requirements to generate an optimized cost-effective action plan. This plan comprises a sequence of executable actions that can be deployed in industrial control systems (ICS) to enable efficient and sustainable machine operation. Then the AI agent automates the testing of control systems by comparing the agent’s planned and executed actions against expected outputs, ensuring requirement conformance and enhancing system reliability. Experimental results demonstrate the effectiveness of the AI agent in generating sustainable operational plans and validating control system behavior for laboratory scale case studies, underscoring its potential in the future of intelligent industrial automation.

This paper introduces an innovative multiactor framework that harnesses the potential of LLMs to augment the functionalities of ICS. By integrating conversational AI technologies, this framework significantly improves human-machine interactions, enabling sophisticated analysis and visualization of intricate data sets. The core of the system comprises specialized LLM actors that interact through a LangGraph-based multiactor framework, addressing various aspects of IEC 61499 control systems including PLC code analysis, SQL query execution, and data visualization. This integration enables operators to interact with the control system using natural language, significantly reducing technical barriers and enhancing the accessibility and usability of complex industrial systems.

IEC 61499 is an executable, event-based language for control software that allows visual and textual implementation of individual software components (Function Blocks, FBs). The standardized visual service sequence model specifies the expected input/output behaviour of a component, thus supporting model-based testing. We present our approach for testing an FB on various platforms, which helps manage the variations in execution semantics between different vendors. First, service sequences are generated manually or derived from an existing (partial) implementation. Then, these service sequences serve as unit tests for this implementation. Finally, we create a test application that is executable on any IEC 61499-compliant platform. Executing tests directly in the target platform helps validate the correct functionality of an FB before deploying the control software to a cyber-physical system.

A learning management system (LMS) is a web-based technology developed to improve the learning process in educational institutions. This study addresses the drawbacks of existing LMS by developing DeLMS (Decentralized Learning Management System) and aims to revolutionize the way educational institutions manage and deliver educational content using Ethereum smart contracts and the IPFS (InterPlanetary File System). By leveraging Smart contracts and IPFS cutting-edge technologies, DeLMS provides a secure, transparent and decentralized platform for managing and delivering educational content. The content addressing feature of IPFS eliminates the need for constant requests to centralized servers for the location of files, resulting in faster file transfer and reduced energy consumption. The proposed system has the potential to change the way educational institutions operate, making it more accessible and beneficial for both students and educators.

In this paper, we describe a method to automatically derive the controller for an automated process by an interactive learning approach using a simulation model developed in Visual Components 3D simulation software. The latter is used to record the events of the processes and the controller is generated as an IEC 61499 function block. To create different process scenarios, the actuator signals are triggered manually in appropriate order. The controller logic in Petri net is derived by process discovery algorithms with help of recorded events and conversion of Petri net to IEC 61499 function blocks is done by a software tool configured with a set of transformation rules.

In this paper, we discuss how process mining techniques can be applied in industrial control systems for modeling, verification, and enhancement of the cyber-physical system based on recorded data logs. Process mining is used for extracting the process models in different notations from the recorded behavioral traces of the system. The output model of the system’s behavior is mainly derived using an open-source tool called ProM. The model can be used for such applications as anomaly detection, detection of cyber-attacks and alarm analysis in industrial control systems with the help of various control flow discovery algorithms. The extracted process model can be used to verify how the event log deviates from it by replaying the log on Petri net for conformance analysis.

This paper reports on a method of automatic generation of a formal model of plant from the behaviour traces recorded from its digital twin. The traces are observed from simulation in the loop of the digital twin in Visual Components connected with distributed automation software, developed in NxtSTUDIO according to IEC 61499. The generated modular formal model of the closed-loop system is transformed to the model of uncontrolled plant behaviour extended with nondeterminism. The model is then combined in closed-loop with the formal model of controller, generated from its source code using the fb2smv tool. The verification and simulation is done by the symbolic model checker NuSMV tool, which verifies various CTL/LTL specifications of the system.

This paper introduces a problem-oriented notation within the IEC 61499 syntax to be used for creating formal closed-loop models of cyber-physical automation systems. The proposed notation enables creation of a comprehensive tool-chain that can combine design, simulation, formal verification and distributed deployment of automation software. The proposed notation allows for definition of non-deterministic transitions in ECC of basic function blocks of IEC 61499.The tool chain includes an IEC 61499 compliant engineering environment, fb2smv converter of functions blocks to SMV code, the NuSMV model-checker and utilities for interpreting counterexamples.