M.J.G.C. Mendes

Multi-agent Platform and Toolbox for Fault Tolerant Networked Control Systems

Industrial distributed networked control systems use different communication networks to exchange different critical levels of information. Real-time control, fault diagnosis (FDI) and Fault Tolerant Networked Control (FTNC) systems demand one of the more stringent data exchange in the communication networks of these networked control systems (NCS). When dealing with large-scale complex NCS, designing FTNC systems is a very difficult task due to the large number of sensors and actuators spatially distributed and network connected. To solve this issue, a FTNC platform and toolbox are presented in this paper using simple and verifiable principles coming mainly from a decentralized design based on causal modelling partitioning of the NCS and distributed computing using multi-agent systems paradigm, allowing the use of agents with well established FTC methodologies or new ones developed taking into account the NCS specificities. The multi-agent platform and toolbox for FTNC systems have been built in Matlab/Simulink environment, which is in our days the scientific benchmark for this kind of research. Although the tests have been performed with a simple case, the results are promising and this approach is expected to succeed with more complex processes.

Comparison of control strategies performance for a Wave Energy Converter

The Archimedes wave swing (AWS) is a a fully- submerged wave energy converter (WEC), that is to say, a device that converts the kinetic energy of sea waves into electricity. A first prototype of the AWS has already been built and tested. This paper presents simulation results of the performance of several control strategies applied to this device, including PID control, reactive control, phase and amplitude control, latching control, feedback linearisation control, internal model control, switching control, and combinations thereof. Linear, white-box nonlinear, and neural network models were employed. Significant (above threefold) increases in yearly energy production were found to be possible with properly designed control strategies.

Multi-agent platform for fault tolerant control systems

This paper proposes a new multi-agent platform for Fault Tolerant Control (FTC) Systems. Several multi-agent platforms exist to deal with different problems but none of them to deal with control systems tolerant to faults using the Matlab/Simulinkreg environment, which is in our days the scientific bench to this kind of research. When dealing with large-scale complex networked control systems (NCS), designing FTC systems is a very difficult task due to the large number of sensors and actuators spatially distributed and network connected. To solve this issue, the FTC platform presented in this paper uses simple and verifiable principles coming mainly from a decentralized design based on causal modelling partitioning of the NCS and distributed computing using multi- agent systems paradigm, allowing the use of agents with well established FTC methodologies or new ones developed taking into account the NCS specificities.

Fault Detection Approach Based on Fuzzy Qualitative Reasoning Applied to the DAMADICS Benchmark Problem

Abstract A computer assisted fault detection methodology based on a fuzzy qualitative simulation algorithm is described. The adoption of fuzzy sets allows a more detailed description of physical variables, through an arbitrary, but finite, discretisation of the quantity space. The fuzzy representation of qualitative values is more general than ordinary interval representation, since it can represent not only the information stated by a well defined real interval but also the knowledge embedded in the soft boundaries of the interval. Such a methodology was applied to a pneumatic servomotor actuated control valve that is the benchmark problem of the EC RTN DAMADICS.

NEURO-FUZZY STRUCTURES IN FDI SYSTEM

Abstract Fault diagnosis systems have an important role in industrial plants because the early fault detection and isolation (FDI) can minimize damages in the plants. The main aim of this work is to propose a two-stage neuro-fuzzy approach as a fault diagnosis system in dynamic processes. The first stage of the system is responsible for fault detection and is implemented using a neuro-fuzzy (N-F) model. The second stage of the system is responsible for fault isolation and is built using an hierarchical structure of fuzzy neural networks. The FDI system is applied to fault diagnosis in the actuators of one sugar factory.

Development of a multi-agent management system for an intelligent charging network of electric vehicles

Abstract This paper addresses the modelling and simulation of a battery charging infrastructure for electric vehicles, with the objective of pro-actively scheduling the charging of up to fifty vehicles so as not to overcharge the electrical network. Benefits of having the charging stations differ (as much as possible while satisfying end-user requirements) battery charging for those hours when electricity consumption is otherwise low include rendering electricity consumption more uniform along the day. A multi-agent system was used to design a distributed, modular, coordinated and collaborative multi-agent management system for this infrastructure. Simulation results show the effectiveness of this approach under the conditions of four real-life scenarios.

FAULT DIAGNOSIS SYSTEM BASED IN AGENTS

Abstract In this work is proposed a new agent based fault diagnosis system for complex and dynamic processes. The fault diagnosis systems of the future should have present the distribution and complexity of the processes and they must be able to cooperate and communicate with other systems to achieved a satisfactory performance. The fault detection and isolation (FDI) agents proposed here have hybrid architectures based in a horizontal layered architecture. The reactive layer of the FDI agents are based in decomposition wavelet methods for the fault detection and in neural networks for the fault isolation task. The new agent based FDI system is applied to fault diagnosis in a three tank process.

Design of Distributed Fault Tolerant Control Systems

Abstract When dealing with large-scale complex networked control systems, designing FDI/FTC systems is a very difficult task due to the large number of sensors and actuators spatially distributed and networked connected. Despite the research effort on developing FTC systems for NCS most of these developments still being designed globally leading to centralized FTC solutions inadequate to NCS or, assume the communication network and the process itself as two different entities loosing the potentiality of the integrated design. The FDI/FTC design method presented in this paper is able to use simple and verifiable principles coming mainly from a decentralized design, based on causal modelling partitioning of the NCS and distributed computing using multi-agents systems, allowing the use of well established FDI/FTC methodologies, or new ones, developed taking into account the NCS specificities. The design methodology is made easy using a FTCNS-MAS toolbox introduced in this paper.

An internet remote laboratory to teach Industrial Automation

This paper presents the new internet remote laboratory (IRL), constructed at Mechanical Engineering Department (MED), Instituto Superior de Engenharia de Lisboa (ISEL), to teach Industrial Automation, namely electropneumatic cycles. The aim of this work was the development and implementation of a remote laboratory that was simple and effective from the user point of view, allowing access to all its functionalities through a web browser without having to install any other program and giving access to all the features that the students can find at the physical laboratory. With this goal in mind, it has been implemented a simple architecture with the new programmable logic controller (PLC) SIEMENS S7-1200, and with the aid of several free programs, programming technologies such as JavaScript, PHP and databases, it was possible to have a remote laboratory, with a simple interface, to teach industrial automation students.

A multi-agent approach to a networked fault detection system

Nowadays, fault diagnosis systems design should have into account the distribution and complexity of the process and must be able to cooperate and communicate with other systems to achieve satisfactory performance. To this end a new agent based fault detection system for networked control process is proposed in this paper. A hybrid architecture based on horizontal layers as fault detection (FD) agents architecture is adopted. The reactive layer of the FD agents is based on neural networks models for residuals generation with adaptive threshold. The deliberative layers take into account the agent knowledge and goals, and also the process distribution and network. The new agent based FD system has been applied and tested with good results in a three tank process using a star Ethernet network topology.