Petr Kadera

Rockwell Automation's Holonic and Multiagent Control Systems Compendium

This paper provides a comprehensive overview of long-term R&D activities of the Rockwell Automation (RA) company in the field of holonic and agent-based manufacturing control systems. It presents a coherent framework of methodologies for designing agent-based control systems, tools that support implementation and validation of them, and agent applications that were developed for various industrial systems. The common attribute is the integration of novel techniques, such as multiagent systems or semantics with the current “old-fashioned” automation architectures represented mainly by programmable logic controllers. Retaining the ability of the control system to meet the strict real-time constraints and concurrently raise its intelligence has always been of highest importance. The paper does not focus merely on RAs work, but discusses all its aspects in a context of other existing works in this area.

Chilled Water System Control, Simulation, and Visualization Using Java Multi-agent System

Abstract This paper describes a multi-agent application for control of a simulated shipboard chilled water system (CWS) implemented in Java language. The multi-agent approach provides robustness, flexibility, and scalability. Elements of the CWS are represented by three types of agents. Agents of type “Chiller” provide cold water, agents “Service” require cold water, and agents “Valve” connect segments of water piping system. Agents take actions to dynamically create cooling paths, which enables agents “Service” to stay close to their required temperature. Ability to isolate a leakage, when it occurs, to keep other parts of the system healthy, is another feature of the system. The graphical user interface of the application allows a user to watch running processes in the system as well as edit the system configuration.

Big data analysis for sensor time-series in automation

The trend of large scale data production is observed not only within web companies, but is entering also other domains including automation domain. Smart sensors and smart devices contribute to growing amounts of data that need to be processed. An example of processing is prediction for better control, clustering for more effective maintenance, or improving the overall production in general. The so called Big Data paradigm shows new ways of handling bigger amounts of various data, including providing technologies that are able to handle them in an effective way. This paper examines the utilization of Big Data technologies for industry automation domain. The approach is illustrated on time series data measured from a passive house with the goal of detecting specific events. We show how the Big Data technologies allow data analysis that would be hard with traditional approaches.

Multi-agent system design and integration via agent development environment

Design and integration of multi-agent systems are becoming more and more important since there is evidence of a shift of multi-agent application deployment from academic or lab testing areas to real world applications such as manufacturing, aerospace, logistics, and networking. Therefore, utilization of an environment that guides the development process starting from the design of templates that can be reused multiple times up to the code generation and debugging is essential. In this manuscript we present advancements in the Agent Development Environment that can be used not only for the development of agents designed for high-level decision-making, but also for distributed low-level control that is automatically integrated.

Plan, Commit, Execute Protocol in Multi-agent Systems

In this paper we introduce changes made in Plan/Commit/Execute negotiation protocol originally developed for Agent Cooperation System and practically used in Chilled Water System application. This protocol is suitable for systems where the commitment of resources and execution of a plan require separated communication phases. The extension of the protocol with Reject Proposal message that is used for canceling unsatisfactory proposals is the most significant change. We also describe the deployment of the protocol in new version of Multi-agent System for Manufacturing.

Diagnostics of Distributed Intelligent Control Systems: Reasoning Using Ontologies and Hidden Markov Models

Abstract The distributed intelligent control systems based on multi-agent systems paradigm bring many important features, including their flexibility and extensibility. These features are even more apparent when the agents use ontologies as a base for their knowledge management – such ontologies can be regarded as models that to some degree drive the operation of the system. However, much of the information from knowledge bases of agents can be used also for other important ability of a control system – the diagnostics. In this paper, we demonstrate and discuss two approaches to diagnostics – one based on description logic reasoning and the other one based on Hidden Markov Models. Both of these approaches are illustrated on sample scenario from a transportation system.

Visualization of ontologies in multi-agent industrial systems

The development in the field of multi-agent systems used in the industrial distributed control systems has demonstrated the possibility of flexibility, fault tolerance and integration. It was shown that using ontologies for explicit description of the world has many advantages, including easier integration and extensibility. However, any more complex system, including multi-agent system, needs visualization for its easier development, debugging and monitoring. The fact that the knowledge in the system is expressed in a standardized semantic way contributes to the possibility of providing a uniform view on the system as a whole as well as on the individual agents. In this paper we describe and discuss possibilities of visualization of the state of the industrial control system based on ontologies. We demonstrate the visualization possibilities on the MAST system.

Performance Modeling Extension of Directory Facilitator for Enhancing Communication in FIPA-Compliant Multiagent Systems

The growing adoption of highly distributed and intelligent industrial systems frequently denoted as Industry 4.0 or Industrial Internet of Things brings great opportunities as well as new research questions because connection of single devices into a cooperating community creates much larger and complex systems with new challenges regarding verification and security. This paper proposes a method to solve problems related to setup of timeouts used in communication protocols. The static setup is replaced with an enhancement of directory facilitator that in cooperation with a specialized sniffer agent continuously monitors the system load and eventually postpones starts of new tasks. This precaution eliminates saturation of computational resources and preserves the maximal reachable system performance. The proposed method is demonstrated through a simulation of a chilled water system using a test-bed of six minicomputers Raspberry Pi that host agents implemented in Jade.

Engineering of Coupled Simulation Models for Mechatronic Systems

Simulation models play a crucial role in testing and fine-tuning of control systems for complex industrial systems. They are important parts of the sustainable, service-oriented manufacturing value chain by facilitating early and efficient defect detection and risk mitigation. However, the design phase of simulation models is time-consuming and error-prone, thus it should be improved to become more efficient. The design of simulation models for mechatronic systems has to cope with two basic challenges: (1) the heterogeneous nature of mechatronic systems, which are described with various overlapping engineering plans, and (2) the separation of monolithic simulations into distributed simulation modules, to better conquer the computational complexity of simulation models. This paper addresses both challenges: (a) we propose an application of semantic integration and linked data for sharing and capturing knowledge for simulation model design between various engineering plans; (b) we explain how to structurally connect simulation modules, which are dynamically coupled. The proposed method utilizes the extended bond-graph theory. The simulation modules work independently of each other but with interaction, similar to a multi-agent system. Since the computational execution of coupled simulations is a crucial obstacle especially for mechatronic systems, we show how performance analysis can significantly improve the definition of simulation workflows.

Integration of IEC 61499 with OPC UA

From the industrial point of view, the beginning of the 21th century is predominated by fast-changing demands of the global market. This phenomenon is referred to as a shift from mass production to mass customization and brings new challenges into the manufacturing domain. The physical changes in the production resources mean a need for dynamic reconfiguration at the control level. In order to achieve true reconfigurable of manufacturing systems, new software architectures and supportive tools are needed. The aim of this process is to transform industrial control systems from the standard automation pyramid structure into a reconfigurable system. 4DIAC, framework created according to the IEC 61499, allows developers to create flexible industrial control applications using functional encapsulation in function blocks (FBs) and event-driven execution of the control code. This paper extends the flexibility of IEC 61499 application using OPC UA communication protocol that enables robust, reliable and save communication over various industrial systems. The proposed solution automatically creates the address space (a concept provide by OPC UA) according to the structure of an IEC 61499 application.