Modeling and Simulation of a Wastewater Pumping Plant.

Modeling wastewater pumping plants is rarely addressed in the literature. Standard component models as found in fluid simulation tool libraries are too complex, due to their projected generality, to be used for these applications. Lack of models results in a burden on engineers who have to test their control scenarios on real implemented systems. This may lead to unexpected delays and painful costs. In this work, easily manageable component-oriented models are derived and applied to the modeling and simulation of a real wastewater pumping system. The model derived in this paper is implemented in Modelica, and it helps better understanding the system dynamics. Thereby, a tool is provided for evaluating the performance of possible control schemes

Data based modeling of a large scale water delivery system

Trabalho apresentado em 12th Portuguese Conference on Automatic Control, 2016, Guimarães, Portugalinfo:eu-repo/semantics/publishedVersio

Multi-Platform Controller Interface for SCADA Application

This paper concerns the development of a SCADA-Controller Interface (SCI) application for an open-channel experimental facility. Water delivery canals are complex and spatially distributed systems. The proposed application is to be applied to test control algorithms developed by several research groups with different technical approaches. The proposed interface allows the development of controllers in different environments - C/C++, MATLAB/Simulink and GNU Prolog - and may be easily extended to other environments. The experimental facilities with the used instrumented canal, the programmable logic controller (PLC) network and the SCADA system are also described in this paper. Finally, some software experimental results are presented

Improved Trade-based Multi-robot Coordination

International audienceTeam work is essential to multiple mobile robot systems. An important question is, which robot should implement which action? In our previous work, we presented a trade-based task allocation approach for coordinated multi-robot exploration, which simulates the relationship between buyers and sellers in a business system, to achieve dynamic task allocation by using a mechanism of unsolicited bid. This paper still addresses the problem of coordinating multi-robot exploration while presents an improved trade-based approach to raise the efficiency of task allocation by using the Hungarian method. The proposed approach has been implemented and evaluated in simulation. The experimental results demonstrate the total exploration time can be significantly reduced by the improved trade-based approach compared to previous approaches

Modelica-Based Model for Activated Sludge System

Activated sludge system is the most important stage in municipal wastewater treatment process. It is a biological operation used for treating sewage by means of microorganism. One type of activated sludge systems is the oxidation ditch. In this work, models derived through object-oriented programming will be used to build a simulation model for a typical oxidation ditch. The derived model was constructed and programmed using Modelica language. The simulation model will help better understand the system behavior. Thereby, the model will be provided as an assessment or evaluation tool for the performance of control schemes. The tool gave the expected results, in terms of reducing the concentration of organic matter in wastewater coming out from oxidation ditche

A Generic Multi-Layer Architecture Based on ROS-JADE Integration for Autonomous Transport Vehicles

The design and operation of manufacturing systems is evolving to adapt to different challenges. One of the most important is the reconfiguration of the manufacturing process in response to context changes (e.g., faulty equipment or urgent orders, among others). In this sense, the Autonomous Transport Vehicle (ATV) plays a key role in building more flexible and decentralized manufacturing systems. Nowadays, robotic frameworks (RFs) are used for developing robotic systems such as ATVs, but they focus on the control of the robotic system itself. However, social abilities are required for performing intelligent interaction (peer-to-peer negotiation and decision-making) among the different and heterogeneous Cyber Physical Production Systems (such as machines, transport systems and other equipment present in the factory) to achieve manufacturing reconfiguration. This work contributes a generic multi-layer architecture that integrates a RF with a Multi-Agent System (MAS) to provide social abilities to ATVs. This architecture has been implemented on ROS and JADE, the most widespread RF and MAS framework, respectively. We believe this to be the first work that addresses the intelligent interaction of transportation systems for flexible manufacturing environments in a holistic form.This work was financed by MINECO/FEDER, UE (grant number DPI2015-68602-R) and by UPV/EHU (grant number PPG17/56)

Planetary micro-rover operations on Mars using a Bayesian framework for inference and control

With the recent progress toward the application of commercially-available hardware to small-scale space missions, it is now becoming feasible for groups of small, efficient robots based on low-power embedded hardware to perform simple tasks on other planets in the place of large-scale, heavy and expensive robots. In this paper, we describe design and programming of the Beaver micro-rover developed for Northern Light, a Canadian initiative to send a small lander and rover to Mars to study the Martian surface and subsurface. For a small, hardware-limited rover to handle an uncertain and mostly unknown environment without constant management by human operators, we use a Bayesian network of discrete random variables as an abstraction of expert knowledge about the rover and its environment, and inference operations for control. A framework for efficient construction and inference into a Bayesian network using only the C language and fixed-point mathematics on embedded hardware has been developed for the Beaver to make intelligent decisions with minimal sensor data. We study the performance of the Beaver as it probabilistically maps a simple outdoor environment with sensor models that include uncertainty. Results indicate that the Beaver and other small and simple robotic platforms can make use of a Bayesian network to make intelligent decisions in uncertain planetary environments