Sludge population optimisation: a new dimension for the control of biological wastewater treatment systems

The activated sludge comprises a complex microbiological community. The structure (what types of microorganisms are present) and function (what can the organisms do and at what rates) of this community are determined by external physico -chemical features and by the influent to the sewage treatment plant. The external features we can manipulate but rarely the influent. Conventional control and operational strategies optimise activated sludge processes more as a chemical system than as a biological one. While optimising the process in a short time period, these strategies may deteriorate the long-term performance of the process due to their potentially adverse impact on the microbial properties. Through briefly reviewing the evidence available in the literature that plant design and operation affect both the structure and function of the microbial community in activated sludge, we propose to add sludge population optimisation as a new dimension to the control of biological wastewater treatment systems. We stress that optimising the microbial community structure and property should be an explicit aim for the design and operation of a treatment plant. The major limitations to sludge population optimisation revolve around inadequate microbiological data, specifically community structure, function and kinetic data. However, molecular microbiological methods that strive to provide that data are being developed rapidly. The combination of these methods with the conventional approaches for kinetic study is briefly discussed. The most pressing research questions pertaining to sludge population optimisation are outlined. (C) 2002 Elsevier Science Ltd. All rights reserved.

Combining nonthermal technologies to control foodborne microorganisms

Novel nonthermal processes, such as high hydrostatic pressure (HHP), pulsed electric fields (PEFs), ionizing radiation and ultrasonication, are able to inactivate microorganisms at ambient or sublethal temperatures. Many of these processes require very high treatment intensities, however, to achieve adequate microbial destruction in low-acid foods. Combining nonthermal processes with conventional preservation methods enhances their antimicrobial effect so that lower process intensities can be used. Combining two or more nonthermal processes can also enhance microbial inactivation and allow the use of lower individual treatment intensities. For conventional preservation treatments, optimal microbial control is achieved through the hurdle concept, with synergistic effects resulting from different components of the microbial cell being targeted simultaneously. The mechanisms of inactivation by nonthermal processes are still unclear; thus, the bases of synergistic combinations remain speculative. This paper reviews literature on the antimicrobial efficiencies of nonthermal processes combined with conventional and novel nonthermal technologies. Where possible, the proposed mechanisms of synergy is mentioned. (C) 2003 Elsevier Science B.V. All rights reserved.

Automation & control remote laboratory: evaluating a cooperative methodology

This paper presents a study carried out in order to evaluate the students' perception in the development and use of remote Control and Automation education kits developed by two Universities. Three projects, based on real world environments, were implemented, being local and remotely operated. Students implemented the kits using the theoretical and practical knowledge, being the teachers a catalyst in the learning process. When kits were operational, end-user students got acquainted to the kits in the course curricula units. It is the author's believe that successful results were achieved not only in the learning progress on the Automation and Control fields (hard skills) but also on the development of the students soft skills, leading to encouraging and rewarding goals, motivating their future decisions and promoting synergies in their work. The design of learning experimental kits by students, under teacher supervision, for future use in course curricula by enduser students is an advantageous and rewarding experience.

Predictive Optimal Matrix Converter Control for a Dynamic Voltage Restorer with Flywheel Energy Storage

This paper presents a predictive optimal matrix converter controller for a flywheel energy storage system used as Dynamic Voltage Restorer (DVR). The flywheel energy storage device is based on a steel seamless tube mounted as a vertical axis flywheel to store kinetic energy. The motor/generator is a Permanent Magnet Synchronous Machine driven by the AC-AC Matrix Converter. The matrix control method uses a discrete-time model of the converter system to predict the expected values of the input and output currents for all the 27 possible vectors generated by the matrix converter. An optimal controller minimizes control errors using a weighted cost functional. The flywheel and control process was tested as a DVR to mitigate voltage sags and swells. Simulation results show that the DVR is able to compensate the critical load voltage without delays, voltage undershoots or overshoots, overcoming the input/output coupling of matrix converters.

RFID together with multi-agent systems to control global value chains

Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.

A student personal system for Bologna process mobility

The Bologna Process aimed to build a European Higher Education Area with the objective of promoting students mobility. The adoption of Bologna Declaration directives requires a decentralized approach that accelerates student's mobility, based on frequently updated legislation. This paper proposes a student personal system to manage student's academic information. This system is supported by a flexible model that integrates, for instance, knowledge about the student attended courses or about a course that the student wishes to apply. Essentially, this model holds a (i) Student's Academic Record with skills acquired in academic course units, professional experience or training and an (ii) Individual Studies Plan, which places the student in a particular (iii) Course Plan setting the curricular structure that the student wishes to apply.

Scalable and efficient data processing in networked control systems

Network control systems (NCSs) are spatially distributed systems in which the communication between sensors, actuators and controllers occurs through a shared band-limited digital communication network. However, the use of a shared communication network, in contrast to using several dedicated independent connections, introduces new challenges which are even more acute in large scale and dense networked control systems. In this paper we investigate a recently introduced technique of gathering information from a dense sensor network to be used in networked control applications. Obtaining efficiently an approximate interpolation of the sensed data is exploited as offering a good tradeoff between accuracy in the measurement of the input signals and the delay to the actuation. These are important aspects to take into account for the quality of control. We introduce a variation to the state-of-the-art algorithms which we prove to perform relatively better because it takes into account the changes over time of the input signal within the process of obtaining an approximate interpolation.

Control of baker’s yeast fermentation: PID and fuzzy algorithms

A MATLAB/SIMULINK-based simulator was employed for studies concerning the control of baker’s yeast fed-batch fermentation. Four control algorithms were implemented and compared: the classical PID control, two discrete versions- modified velocity and position algorithms, and a fuzzy law. The simulation package was seen to be an efficient tool for the simulation and tests of control strategies of the nonlinear process.

Fuzzy linguistic controllers applied to decouple control loop effects

A fuzzy linguistic controller has been developed and implemented with the aim to cope with interactions between control loops due to coupling effects. To access the performance of the proposed approach several experiments have also been conducted using the classical PID controllers in the control loops. A mixing process has been used as test bed of all controllers experimented and the corresponding dynamic model has been derived. The successful results achieved with the fuzzy linguistic controllers suggests that they can be an alternative to classical controllers when in the presence of process plants where automatic control as to cope with coupling effects between control loops. © 2014 IEEE.

Letter names and sounds: their implications for the phonetisation process

Our aim was to analyse the impact of the characteristics of words used in spelling programmes and the nature of instructional guidelines on the evolution from grapho-perceptive writing to phonetic writing in preschool children. The participants were 50 5-year-old children, divided in five equivalent groups in intelligence, phonological skills and spelling. All the children knew the vowels and the consonants B, D, P, R, T, V, F, M and C, but didn’t use them on spelling. Their spelling was evaluated in a pre and post-test with 36 words beginning with the consonants known. In-between they underwent a writing programme designed to lead them to use the letters P and T to represent the initial phonemes of words. The groups differed on the kind of words used on training (words whose initial syllable matches the name of the initial letter—Exp. G1 and Exp. G2—versus words whose initial syllable is similar to the sound of the initial letter—Exp. G3 and Exp. G4). They also differed on the instruction used in order to lead them to think about the relations between the initial phoneme of words and the initial consonant (instructions designed to make the children think about letter names—Exp. G1 and Exp. G3 —versus instructions designed to make the children think about letter sounds—Exp. G2 and Exp. G4). The 5th was a control group. All the children evolved to syllabic phonetisations spellings. There are no differences between groups at the number of total phonetisations but we found some differences between groups at the quality of the phonetisations.

Optimising the energy consumption on pultrusion process

This study is based on a previous experimental work in which embedded cylindrical heaters were applied to a pultrusion machine die, and resultant energetic performance compared with that achieved with the former heating system based on planar resistances. The previous work allowed to conclude that the use of embedded resistances enhances significantly the energetic performance of pultrusion process, leading to 57% decrease of energy consumption. However, the aforementioned study was developed with basis on an existing pultrusion die, which only allowed a single relative position for the heaters. In the present work, new relative positions for the heaters were investigated in order to optimise heat distribution process and energy consumption. Finite Elements Analysis was applied as an efficient tool to identify the best relative position of the heaters into the die, taking into account the usual parameters involved in the process and the control system already tested in the previous study. The analysis was firstly developed based on eight cylindrical heaters located in four different location plans. In a second phase, in order to refine the results, a new approach was adopted using sixteen heaters with the same total power. Final results allow to conclude that the correct positioning of the heaters can contribute to about 10% of energy consumption reduction, decreasing the production costs and leading to a better eco-efficiency of pultrusion process.

Finite Element Analysis (FEA) applied to heat transfer optimization process of pultrusion die systems

The aim of this study is to optimize the heat flow through the pultrusion die assembly system on the manufacturing process of a specific glass-fiber reinforced polymer (GFRP) pultrusion profile. The control of heat flow and its distribution through whole die assembly system is of vital importance in optimizing the actual GFRP pultrusion process. Through mathematical modeling of heating-die process, by means of Finite Element Analysis (FEA) program, an optimum heater selection, die position and temperature control was achieved. The thermal environment within the die was critically modeled relative not only to the applied heat sources, but also to the conductive and convective losses, as well as the thermal contribution arising from the exothermic reaction of resin matrix as it cures or polymerizes from the liquid to solid condition. Numerical simulation was validated with basis on thermographic measurements carried out on key points along the die during pultrusion process.

Optimizing the embedded heaters position in the pultrusion process using finite element analysis

This study is based on a previous experimental work in which embedded cylindrical heaters were applied to a pultrusion machine die, and resultant energetic performance compared with that achieved with the former heating system based on planar resistances. The previous work allowed to conclude that the use of embedded resistances enhances significantly the energetic performance of pultrusion process, leading to 57% decrease of energy consumption. However, the aforementioned study was developed with basis on an existing pultrusion die, which only allowed a single relative position for the heaters. In the present work, new relative positions for the heaters were investigated in order to optimize heat distribution process and energy consumption. Finite Elements Analysis was applied as an efficient tool to identify the best relative position of the heaters into the die, taking into account the usual parameters involved in the process and the control system already tested in the previous study. The analysis was firstly developed with basis on eight cylindrical heaters located in four different location plans. In a second phase, in order to refine the results, a new approach was adopted using sixteen heaters with the same total power. Final results allow to conclude that the correct positioning of the heaters can contribute to about 10% of energy consumption reduction, decreasing the production costs and leading to a better eco-efficiency of pultrusion process.

The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process

This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.