<?xml version="1.0" encoding="UTF-8"?>
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  <title>DSpace Collection:</title>
  <link rel="alternate" href="http://hdl.handle.net/10174/141" />
  <subtitle />
  <id>http://hdl.handle.net/10174/141</id>
  <updated>2026-04-08T09:47:49Z</updated>
  <dc:date>2026-04-08T09:47:49Z</dc:date>
  <entry>
    <title>Adaptive  Predictive Controller Applied to an Open Water Canal</title>
    <link rel="alternate" href="http://hdl.handle.net/10174/1583" />
    <author>
      <name>Rato, Luís</name>
    </author>
    <author>
      <name>Salgueiro, Pedro</name>
    </author>
    <author>
      <name>Lemos, João Miranda</name>
    </author>
    <author>
      <name>Rijo, Manuel</name>
    </author>
    <id>http://hdl.handle.net/10174/1583</id>
    <updated>2012-10-18T15:10:00Z</updated>
    <published>2007-04-30T23:00:00Z</published>
    <summary type="text">Title: Adaptive  Predictive Controller Applied to an Open Water Canal
Authors: Rato, Luís; Salgueiro, Pedro; Lemos, João Miranda; Rijo, Manuel
Abstract: This paper concerns to the application of adaptive control to a large scale water canal experimental plant. Water canals are complex spatially distributed systems which aim at distributing water either for irrigating, or domestic, or industrial purposes.&#xD;
In this paper a predictive adaptive control algorithm (MUSMAR) is &#xD;
applied to a large scale experimental water canal prototype.&#xD;
The experimental facilities with a fully instrumented canal, a PLC network and a SCADA system, &#xD;
are briefly described. This paper describes the &#xD;
 developed software module and the MUSMAR control algorithm.&#xD;
Finaly, Some&#xD;
 experimental results obtained in the &#xD;
 experimental water canal, are presented.</summary>
    <dc:date>2007-04-30T23:00:00Z</dc:date>
  </entry>
  <entry>
    <title>M-Traﬃc - A Traﬃc Information and Monitoring System for Mobile Devices</title>
    <link rel="alternate" href="http://hdl.handle.net/10174/1443" />
    <author>
      <name>Romão, Teresa</name>
    </author>
    <author>
      <name>Rato, Luís</name>
    </author>
    <author>
      <name>Fernandes, Pedro</name>
    </author>
    <author>
      <name>Alexandre, Nuno</name>
    </author>
    <author>
      <name>Almada, Antão</name>
    </author>
    <author>
      <name>Capeta, Nuno</name>
    </author>
    <id>http://hdl.handle.net/10174/1443</id>
    <updated>2009-04-07T14:38:06Z</updated>
    <published>2006-04-30T23:00:00Z</published>
    <summary type="text">Title: M-Traﬃc - A Traﬃc Information and Monitoring System for Mobile Devices
Authors: Romão, Teresa; Rato, Luís; Fernandes, Pedro; Alexandre, Nuno; Almada, Antão; Capeta, Nuno
Abstract: This paper presents Mobile Traﬃc (M-Traﬃc), a multiplat-&#xD;
form online traﬃc information system, which provides real time traﬃc&#xD;
information based on image processing, sensor’s data and traveller be-&#xD;
haviour models. In order to estimate route delay and feed the optimal&#xD;
routing algorithm a traﬃc microscopic simulation model is developed and&#xD;
simulation results are presented. This mobile information service ubiqui-&#xD;
tously provides users with traﬃc information regarding their needs and&#xD;
preferences, according to an alert system, which allows a personalised&#xD;
pre-deﬁnition of warning messages.</summary>
    <dc:date>2006-04-30T23:00:00Z</dc:date>
  </entry>
  <entry>
    <title>KNOWLEDGE REPRESENTATION APPROACH TO CLOSED LOOP CONTROL SYSTEM - A TANK SYSTEM CASE-STUDY</title>
    <link rel="alternate" href="http://hdl.handle.net/10174/1373" />
    <author>
      <name>Rato, Luís</name>
    </author>
    <author>
      <name>Rodrigues, Irene Pimenta</name>
    </author>
    <author>
      <name>Gomes, Rui</name>
    </author>
    <id>http://hdl.handle.net/10174/1373</id>
    <updated>2016-03-29T11:11:05Z</updated>
    <published>2005-08-31T23:00:00Z</published>
    <summary type="text">Title: KNOWLEDGE REPRESENTATION APPROACH TO CLOSED LOOP CONTROL SYSTEM - A TANK SYSTEM CASE-STUDY
Authors: Rato, Luís; Rodrigues, Irene Pimenta; Gomes, Rui
Abstract: Control engineering problems are dealt within a plethora of methods and approaches depending on the a priori&#xD;
knowledge, the description of the process to control, and the main control goal. Classical control theory is&#xD;
mainly based on properties of numerical models. This paper presents an approach that applies to a class of&#xD;
processes described by numerical and logical relations using inference and a knowledge base system. To attain&#xD;
this goal an ontology for control systems is constructed. The work presented in this paper is based in a three&#xD;
tank system benchmark.</summary>
    <dc:date>2005-08-31T23:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Predictive Adaptive Control of water level in canal pools</title>
    <link rel="alternate" href="http://hdl.handle.net/10174/1372" />
    <author>
      <name>Lemos, João Miranda</name>
    </author>
    <author>
      <name>Rato, Luís</name>
    </author>
    <author>
      <name>Machado, Fernando</name>
    </author>
    <author>
      <name>Nogueira, Nuno</name>
    </author>
    <author>
      <name>Salgueiro, Pedro</name>
    </author>
    <author>
      <name>Rijo, Manuel</name>
    </author>
    <id>http://hdl.handle.net/10174/1372</id>
    <updated>2008-12-23T11:58:07Z</updated>
    <published>2007-08-31T23:00:00Z</published>
    <summary type="text">Title: Predictive Adaptive Control of water level in canal pools
Authors: Lemos, João Miranda; Rato, Luís; Machado, Fernando; Nogueira, Nuno; Salgueiro, Pedro; Rijo, Manuel
Abstract: A case study on the use of a predictive adaptive algorithm to control pool level in a pilot water distribuition&#xD;
canal is described. The algorithm is a modification of the basic MUSMAR controller that includes parallel&#xD;
integral action and, in the case of multiple pools, feedforward action to coordinate the gates. Experimental&#xD;
results in the case of a single pool and simulations for multiple pools are presented. The contributions of the&#xD;
paper stem from the explicitation of rules for tuning the adaptive controller in a practical situation and from the&#xD;
coordination of different pools using reduced complexity controllers and feedforward in a multivariable setting</summary>
    <dc:date>2007-08-31T23:00:00Z</dc:date>
  </entry>
</feed>

