DAI-DEPUR: an integrated and distributed architecture for wastewater treatment plants supervision

The activated sludge process - the main biological technology usually applied towastewater treatment plants (WWTP) - directly depends on live beings (microorganisms), and therefore on unforeseen changes produced by them. It could be possible to get a good plant operation if the supervisory control system is able to react to the changes and deviations in the system and can take thenecessary actions to restore the system’s performance. These decisions are oftenbased both on physical, chemical, microbiological principles (suitable to bemodelled by conventional control algorithms) and on some knowledge (suitable to be modelled by knowledge-based systems). But one of the key problems in knowledge-based control systems design is the development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from previous cases (spec@c experimental knowledge) and to acquire the domain knowledge (general expert knowledge). These problems increase when the process belongs to an ill-structured domain and is composed of several complex operational units. Therefore, an integrated and distributed AIarchitecture seems to be a good choice. This paper proposes an integrated and distributed supervisory multi-level architecture for the supervision of WWTP, that overcomes some of the main troubles of classical control techniques and those of knowledge-based systems applied to real world systems

Mikrokontrolleriohjaus led-ryhmälle

Luonnonvarojen ehtyminen ja ympäristön saastuminen on luonut kysyntää uusille, energiaa säästäville ja ympäristöystävällisille teknologioille. Valaistuksessa tällainen teknologia on led-tekniikka. Led-tekniikalla on useita etuja verrattuna kilpaileviin tekniikoihin kuten pitkä elinikä, ympäristöystävällisyys ja mekaaninen kestävyys. Ledejä käytetään nykyään laajalti erilaisissa erikoissovelluksissa, erityisesti jos vaatimuksena on valon värillisyys. Näihin päiviin asti ledien hinta ja heikko valontuotto ovat rajoittaneet led-valaisimien yleistymistä hehkulamppujen ja muiden valaisintyyppien korvaajina. Tekniikan nopea kehittyminen on tehnyt led-tekniikasta varteenotettavan vaihtoehdon myös yleisvalaistukseen. Uusimpien valkoisten ledien valotehokkuus on 2 - 5 -kertainen hehkulamppuun verrattuna. Led-tekniikassa on vielä paljon käyttämätöntä potentiaalia, tulevaisuudessa päästäneen 10 - 15 -kertaiseen valotehokkuuteen hehkulamppuun verrattuna. Työssä suunnitellaan mikrokontrolleripohjainen ohjausjärjestelmä valkoista valoa tuottavalle led-valaisimelle, jonka värisävyä ja kirkkautta käyttäjä voi säätää. Valkoinen valo synnytetään sekoittamalla neljän erivärisen led-rivin valoa. Mikrokontrolleri ohjaa kutakin led-riviä väriensekoitusteoriaan perustuen. Mikrokontrolleriohjaus huomioi myös ledien optisten ominaisuuksien muutokset lämpötilan suhteen. Mikrokontrolleriohjauksen suorituskyky todetaan käytännön mittauksilla.

Feromônios associados aos coleópteros-praga de produtos armazenados

One strategy to overcome risks of insecticide-based control in agriculture is to use semiochemicals. In the case of pheromones, these specific compounds can be applied in traps to detect and monitor the occurrence, abundance and distribution of insect pests. Reliable detection helps to time insecticide sprays, to decide the quantity of insecticide that will be used and the place where it will be applied. This manuscript aims to give an overview of the pheromones associated to coleopteran pests in stored products, and their utilization in integrated pest management.

Fraktioinnin tehostaminen lajittelussa

Painelajittimet ovat yleisimpiä hiokkeen lajitteluun käytettyjä lajittimia. Painelajittimien suorituskyky on parantunut viimeisten vuosikymmenien aikana niin paljon, että pyörrepuhdistuksesta on pääosin voitu luopua osana hiokkeen lajittelua. Painelajittimen erinomaisuus perustuu siihen, että sillä voidaan erottaa massasta hyvinkin erilaisia epäpuhtauksia. Nykyään vallitsevia painelajittelun trendejä ovat sakeuden nosto, energiankulutuksen vähentäminen sekä eri fraktioiden erottumisen tehostuminen. Kaikilla pyritään vähentämään vedenkäyttöä ja parantamaan massan ominaisuuksia jatkoprosesseja silmälläpitäen. Tässä työssä tarkasteltiin painelajittimen roottorin kierrosnopeuden vaikutusta akseptimassan laatuun. Luodaan malli freeness-pudotukselle lajittimen yli. Sekä tarkastellaan myös automaatioon pohjautuvan säädön käyttöönottoa lajittimen akseptimassan freenesvaihteluiden tasaamiseksi. Toisaalta tehdään myös suppea selvitys lajittimien energiankulutuksista erilaisilla roottorin pyörimisnopeuksilla. Tuotantokäytössä oleviin lajittimiin asennettujen invertterisäätöjen ja koepisteistä saatujen tulosten avulla voidaan todeta, että laskemalla roottorin pyörimisnopeutta voidaan lajittimessa tapahtuvaa freenespudotusta kasvattaa. Samalla saavutetaan hyötyjä myös muissa massan ominaisuuksissa, kuten vetolujuudessa. Automaattisäädön käyttöönotolla saavutetaan huomattavasti pienempi hajonta akseptimassan freeneksessä. Rejektilinjan lajittimissa hajonta lähes puolittui ja päälinjan lajittimissa päästiin noin kolmanneksen parannukseen. Energian kulutuksia tutkittaessa huomataan, että roottorin kierrosnopeutta alentamalla voidaan merkittävästi vähentää lajittimien energian kulutusta. Parhaassa tapauksessa voidaan säästää neljännes lajittelun energiakustannuksissa.

Hitsausvirtalähteen ohjaus lämmöntuonnin ja jatkuvan jäähtymisen S-käyrän perusteella

Lämmöntuonnilla on oleellinen vaikutus hitsausliitoksen ominaisuuksiin, koska se vaikuttaa liitoksen jäähtymisnopeuteen, jolla on puolestaan suuri vaikutus jäähtymisessä syntyviin mikrorakenteisiin. Jatkuvan jäähtymisen S-käyrältä voidaan ennustaa hitsausliitokseen syntyvät mikrorakenteet. S-käyrät voidaan laatia hitsausolosuhteiden mukaisesti, jolloin faasimuutoskäyttäytyminen sularajalla saadaan selvitettyä. Tämän diplomityön tavoitteena oli kehittää hitsausvirtalähteen ohjaustapaa lämmöntuontiin ja jatkuvan jäähtymisen S-käyriin perustuen. Jatkuvan jäähtymisen S-käyrillä ja lämmöntuontiin perustuvalla hitsausparametrien säädöllä on yhteys. Työssä tutkittiin, miten haluttuun jäähtymisnopeuteen johtava lämmöntuonti voidaan määrittää S-käyrälle luotettavasti. Työssä perehdyttiin jatkuvan jäähtymisen S-käyriin ja eri jäähtymisnopeuksilla hitsausliitokseen syntyviin mikrorakenteisiin sekä hitsaus-inverttereiden ohjaus- ja säätötekniikkaan. Teoriaosuuden jälkeen tarkasteltiin eri vaihtoehtoja, miten hitsattavan materiaalin koostumusvaihtelut sekä lämmöntuontiin vaikuttavat tekijät voidaan ottaa huomioon virtalähteen ohjauksessa lämmöntuonnin perusteella. S-käyrältä määritettyjen lämmöntuonnin arvojen perusteella tehtiin kahdet koehitsaukset, joissa käytettiin kolmea eri aineenpaksuutta. Tulosten perusteella arvioitiin lämmöntuonnin arvojen toimivuutta käytännössä ja tutkittiin liitokseen syntyviä mikrorakenteita. Tutkimuksen pohjalta esitettiin jatkokehitystoimenpiteitä, joiden mukaan voidaan edetä lämmöntuontiin perustuvan säätöjärjestelmän kehitysprojektissa.

AMB system for high-speed motors using automatic commissioning

The general trend towards increasing e ciency and energy density drives the industry to high-speed technologies. Active Magnetic Bearings (AMBs) are one of the technologies that allow contactless support of a rotating body. Theoretically, there are no limitations on the rotational speed. The absence of friction, low maintenance cost, micrometer precision, and programmable sti ness have made AMBs a viable choice for highdemanding applications. Along with the advances in power electronics, such as signi cantly improved reliability and cost, AMB systems have gained a wide adoption in the industry. The AMB system is a complex, open-loop unstable system with multiple inputs and outputs. For normal operation, such a system requires a feedback control. To meet the high demands for performance and robustness, model-based control techniques should be applied. These techniques require an accurate plant model description and uncertainty estimations. The advanced control methods require more e ort at the commissioning stage. In this work, a methodology is developed for an automatic commissioning of a subcritical, rigid gas blower machine. The commissioning process includes open-loop tuning of separate parts such as sensors and actuators. The next step is to apply a system identi cation procedure to obtain a model for the controller synthesis. Finally, a robust model-based controller is synthesized and experimentally evaluated in the full operating range of the system. The commissioning procedure is developed by applying only the system components available and a priori knowledge without any additional hardware. Thus, the work provides an intelligent system with a self-diagnostics feature and an automatic commissioning.

Accuracy Analysis of Frequency Converter Estimates in Diagnostic Applications

Transportation of fluids is one of the most common and energy intensive processes in the industrial and HVAC sectors. Pumping systems are frequently subject to engineering malpractice when dimensioned, which can lead to poor operational efficiency. Moreover, pump monitoring requires dedicated measuring equipment, which imply costly investments. Inefficient pump operation and improper maintenance can increase energy costs substantially and even lead to pump failure. A centrifugal pump is commonly driven by an induction motor. Driving the induction motor with a frequency converter can diminish energy consumption in pump drives and provide better control of a process. In addition, induction machine signals can also be estimated by modern frequency converters, dispensing with the use of sensors. If the estimates are accurate enough, a pump can be modelled and integrated into the frequency converter control scheme. This can open the possibility of joint motor and pump monitoring and diagnostics, thereby allowing the detection of reliability-reducing operating states that can lead to additional maintenance costs. The goal of this work is to study the accuracy of rotational speed, torque and shaft power estimates calculated by a frequency converter. Laboratory tests were performed in order to observe estimate behaviour in both steady-state and transient operation. An induction machine driven by a vector-controlled frequency converter, coupled with another induction machine acting as load was used in the tests. The estimated quantities were obtained through the frequency converter’s Trend Recorder software. A high-precision, HBM T12 torque-speed transducer was used to measure the actual values of the aforementioned variables. The effect of the flux optimization energy saving feature on the estimate quality was also studied. A processing function was developed in MATLAB for comparison of the obtained data. The obtained results confirm the suitability of this particular converter to provide accurate enough estimates for pumping applications.

Modeling and Parameter Estimation of Double-Star Permanent Magnet Synchronous Machines

The power rating of wind turbines is constantly increasing; however, keeping the voltage rating at the low-voltage level results in high kilo-ampere currents. An alternative for increasing the power levels without raising the voltage level is provided by multiphase machines. Multiphase machines are used for instance in ship propulsion systems, aerospace applications, electric vehicles, and in other high-power applications including wind energy conversion systems. A machine model in an appropriate reference frame is required in order to design an efficient control for the electric drive. Modeling of multiphase machines poses a challenge because of the mutual couplings between the phases. Mutual couplings degrade the drive performance unless they are properly considered. In certain multiphase machines there is also a problem of high current harmonics, which are easily generated because of the small current path impedance of the harmonic components. However, multiphase machines provide special characteristics compared with the three-phase counterparts: Multiphase machines have a better fault tolerance, and are thus more robust. In addition, the controlled power can be divided among more inverter legs by increasing the number of phases. Moreover, the torque pulsation can be decreased and the harmonic frequency of the torque ripple increased by an appropriate multiphase configuration. By increasing the number of phases it is also possible to obtain more torque per RMS ampere for the same volume, and thus, increase the power density. In this doctoral thesis, a decoupled d–q model of double-star permanent-magnet (PM) synchronous machines is derived based on the inductance matrix diagonalization. The double-star machine is a special type of multiphase machines. Its armature consists of two three-phase winding sets, which are commonly displaced by 30 electrical degrees. In this study, the displacement angle between the sets is considered a parameter. The diagonalization of the inductance matrix results in a simplified model structure, in which the mutual couplings between the reference frames are eliminated. Moreover, the current harmonics are mapped into a reference frame, in which they can be easily controlled. The work also presents methods to determine the machine inductances by a finite-element analysis and by voltage-source inverters on-site. The derived model is validated by experimental results obtained with an example double-star interior PM (IPM) synchronous machine having the sets displaced by 30 electrical degrees. The derived transformation, and consequently, the decoupled d–q machine model, are shown to model the behavior of an actual machine with an acceptable accuracy. Thus, the proposed model is suitable to be used for the model-based control design of electric drives consisting of double-star IPM synchronous machines.

Classifying medication use in clinical research

Les données sur l'utilisation des médicaments sont généralement recueillies dans la recherche clinique. Pourtant, aucune méthode normalisée pour les catégoriser n’existe, que ce soit pour la description des échantillons ou pour l'étude de l'utilisation des médicaments comme une variable. Cette étude a été conçue pour développer un système de classification simple, sur une base empirique, pour la catégorisation d'utilisation des médicaments. Nous avons utilisé l'analyse factorielle pour réduire le nombre de groupements de médicaments possible. Cette analyse a fait émerger un modèle de constellations de consommation de médicaments qui semble caractériser des groupes cliniques spécifiques. Pour illustrer le potentiel de la technique, nous avons appliqué ce système de classification des échantillons où les troubles du sommeil sont importants: syndrome de fatigue chronique et l'apnée du sommeil. Notre méthode de classification a généré 5 facteurs qui semblent adhérer de façon logique. Ils ont été nommés: Médicaments cardiovasculaire/syndrome métabolique, Médicaments pour le soulagement des symptômes, Médicaments psychotropes, Médicaments préventifs et Médicaments hormonaux. Nos résultats démontrent que le profil des médicaments varie selon l'échantillon clinique. Le profil de médicament associé aux participants apnéiques reflète les conditions de comorbidité connues parmi ce groupe clinique, et le profil de médicament associé au Syndrome de fatigue chronique semble refléter la perception commune de cette condition comme étant un trouble psychogène

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Efficient Watermarking Schemes for Speaker Verification Guaranteeing Non-repudiation

Presently different audio watermarking methods are available; most of them inclined towards copyright protection and copy protection. This is the key motive for the notion to develop a speaker verification scheme that guar- antees non-repudiation services and the thesis is its outcome. The research presented in this thesis scrutinizes the field of audio water- marking and the outcome is a speaker verification scheme that is proficient in addressing issues allied to non-repudiation to a great extent. This work aimed in developing novel audio watermarking schemes utilizing the fun- damental ideas of Fast-Fourier Transform (FFT) or Fast Walsh-Hadamard Transform (FWHT). The Mel-Frequency Cepstral Coefficients (MFCC) the best parametric representation of the acoustic signals along with few other key acoustic characteristics is employed in crafting of new schemes. The au- dio watermark created is entirely dependent to the acoustic features, hence named as FeatureMark and is crucial in this work. In any watermarking scheme, the quality of the extracted watermark de- pends exclusively on the pre-processing action and in this work framing and windowing techniques are involved. The theme non-repudiation provides immense significance in the audio watermarking schemes proposed in this work. Modification of the signal spectrum is achieved in a variety of ways by selecting appropriate FFT/FWHT coefficients and the watermarking schemes were evaluated for imperceptibility, robustness and capacity char- acteristics. The proposed schemes are unequivocally effective in terms of maintaining the sound quality, retrieving the embedded FeatureMark and in terms of the capacity to hold the mark bits. Robust nature of these marking schemes is achieved with the help of syn- chronization codes such as Barker Code with FFT based FeatureMarking scheme and Walsh Code with FWHT based FeatureMarking scheme. An- other important feature associated with this scheme is the employment of an encryption scheme towards the preparation of its FeatureMark that scrambles the signal features that helps to keep the signal features unreve- laed. A comparative study with the existing watermarking schemes and the ex- periments to evaluate imperceptibility, robustness and capacity tests guar- antee that the proposed schemes can be baselined as efficient audio water- marking schemes. The four new digital audio watermarking algorithms in terms of their performance are remarkable thereby opening more opportu- nities for further research.

Interaction and Intelligent Behavior

We introduce basic behaviors as primitives for control and learning in situated, embodied agents interacting in complex domains. We propose methods for selecting, formally specifying, algorithmically implementing, empirically evaluating, and combining behaviors from a basic set. We also introduce a general methodology for automatically constructing higher--level behaviors by learning to select from this set. Based on a formulation of reinforcement learning using conditions, behaviors, and shaped reinforcement, out approach makes behavior selection learnable in noisy, uncertain environments with stochastic dynamics. All described ideas are validated with groups of up to 20 mobile robots performing safe--wandering, following, aggregation, dispersion, homing, flocking, foraging, and learning to forage.

DAI-DEPUR: an integrated and distributed architecture for wastewater treatment plants supervision

The activated sludge process - the main biological technology usually applied to wastewater treatment plants (WWTP) - directly depends on live beings (microorganisms), and therefore on unforeseen changes produced by them. It could be possible to get a good plant operation if the supervisory control system is able to react to the changes and deviations in the system and can take the necessary actions to restore the system’s performance. These decisions are often based both on physical, chemical, microbiological principles (suitable to be modelled by conventional control algorithms) and on some knowledge (suitable to be modelled by knowledge-based systems). But one of the key problems in knowledge-based control systems design is the development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from previous cases (spec@c experimental knowledge) and to acquire the domain knowledge (general expert knowledge). These problems increase when the process belongs to an ill-structured domain and is composed of several complex operational units. Therefore, an integrated and distributed AI architecture seems to be a good choice. This paper proposes an integrated and distributed supervisory multi-level architecture for the supervision of WWTP, that overcomes some of the main troubles of classical control techniques and those of knowledge-based systems applied to real world systems

An evaluation of the use of Cottonseed cake in the diet of growing pigs

An experiment was conducted to determine the effects of including cottonseed cake in rations for weaned growing pigs. Thirty-two Landrace x Large White pigs, weighing 20-24 kg, were included in four blocks formed on the basis of initial weight within sex in an otherwise completely randomized block design. The pigs were killed when they reached a live weight of 75.0 +/- 2.0 kg and the half careases were analysed into cuts and the weights of the organs were recorded. An estimate of the productivity of the pigs on each diet was calculated. Cottonseed cake reduced the voluntary feed intake (p < 0.001) and live weight gains (p < 0.001) and increased the heart, kidney and liver weights (p < 0.01). The pigs on the soya bean-based control diet took the shortest time to reach slaughter weight. The result was probably in part due to lysine deficiency and in part to the effect of free gossypol. It was found that it is at present cost-effective to include cottonseed cake in pig weaner grower diets up to 300 g/kg in Cameroon.

Muscle hypertrophy driven by myostatin blockade does not require stem/precursor-cell activity

Myostatin, a member of the TGF-beta family, has been identified as a powerful inhibitor of muscle growth. Absence or blockade of myostatin induces massive skeletal muscle hypertrophy that is widely attributed to proliferation of the population of muscle fiber-associated satellite cells that have been identified as the principle source of new muscle tissue during growth and regeneration. Postnatal blockade of myostatin has been proposed as a basis for therapeutic strategies to combat muscle loss in genetic and acquired myopathies. But this approach, according to the accepted mechanism, would raise the threat of premature exhaustion of the pool of satellite cells and eventual failure of muscle regeneration. Here, we show that hypertrophy in the absence of myostatin involves little or no input from satellite cells. Hypertrophic fibers contain no more myonuclei or satellite cells and myostatin had no significant effect on satellite cell proliferation in vitro, while expression of myostatin receptors dropped to the limits of detectability in postnatal satellite cells. Moreover, hypertrophy of dystrophic muscle arising from myostatin blockade was achieved without any apparent enhancement of contribution of myonuclei from satellite cells. These findings contradict the accepted model of myostatin-based control of size of postnatal muscle and reorient fundamental investigations away from the mechanisms that control satellite cell proliferation and toward those that increase myonuclear domain, by modulating synthesis and turnover of structural muscle fiber proteins. It predicts too that any benefits of myostatin blockade in chronic myopathies are unlikely to impose any extra stress on the satellite cells.