On Modelling, System Identification and Control of Servo-Systems with a Flexible Load

The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.

Markkinoinnin seuranta - Case Telia Finland

Tutkimuksen tavoitteena oli selvittää, miten järjestetään yritysmarkkinoinnin seurantamalli sekä seurannan tietojärjestelmätuki. Erityistä huomiota kiinnitettiin markkinoinnin seurannan ja liiketoimintastrategian kytkökseen. Tutkimusmenetelmänä käytettiin case-tutkimusta. Käsittely oli lineaaris-analyyttinen. Markkinoinnin seurannan tietojärjestelmätuen kehittämisen osalta tutkimus omaa myös jonkin verran systeemianalyyttisiä piirteitä. Case-tutkimuksen tiedonhankinnassa käytettiin yrityksen markkinointihenkilöille jaettua kyselytutkimusta. Markkinoinnin seuranta jaoteltiin strategisen tason ja operatiivisen tason seurantaan. Tutkimuksessa todettiin, että liiketoiminnan kilpailuympäristö, valittu kilpailustrategia ja yrityksen elinkaariasema vaikuttavat liiketoimintastrategiaan ja sitä kautta markkinoinnin seurannan järjestämiseen ja että markkinoinnin strategisen tason seurannan tavoitteena on varmistaa, että markkinointitoiminta toteuttaa valittua liiketoimintastrategiaa. Markkinoinnin operatiivisen tason seurannan tehtäväksi todettiin yrityksen markkinointitoiminnan myynnillisten sekä taloudellisten tulosten, sekä kannattavuuden ja tehokkuuden seuranta ja raportointi. Yritysmarkkinoinnin strategisen tason seurantaan soveltuu parhaiten eteenpäinkytkentäinen, tavoiteltavia tuloksia edeltävien muutosten seurantaan keskittyvä malli. Markkinoinnin operatiiivisen tason seurantaan soveltuu laajan markkinoinnin seurannan perusmittariston sisältävä malli, jolla voidaan palvella nykyisiä seurannan tarpeita ja laatia tarvittaessa uusia seurantakokonaisuuksia. Yritysmarkkinoinnin seurannan tietojärjestelmätuen järjestämiseen soveltuu parhaiten asiakastietokantapohjainen tietojärjestelmämalli. Näin voidaan hallita asiakkaaseen kohdistetut markkinointitoimenpiteet sekä niiden seuranta. Case-tutkimus vahvisti tarpeen kehittää kokonaisvaltainen suunnitelma markkinoinnin strategisen ja operatiivisen tason seurannasta sekä sitä tukevista tietojärjestelmistä. Ilman kokonaissunnitelmaa seuranta muodostuu organisaatioyksiköittäin ja seuranta-alueittain epätasaiseksi, eikä yrityksen asemasta markkinoilla ole muodostettavissa kokonaiskuvaa.

Forecasting of wind speeds and directions with artificial neural networks

In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.

Effects of feed processing on the apparent ileal digestibility of amino acids in pig diets containing wheat bran or wheat middlings

Selostus: Prosessoinnin vaikutus vehnän sivutuotteita sisältävien rehuseosten aminohappojen ohutsuolisulavuuteen sioilla

Effect of anionic salts in concentrate mixture on some blood and urine minerals, acid-base balance and feed intake of dry pregnant cows on grass silage based feeding with high calcium intake

Selostus: Kationi-anionitasapaino ummessaolevien lypsylehmien säilörehuruokinnassa kalsiumin saannin ollessa runsas

Effect of anionic salts in concentrate mixture and calcium intake on some blood and urine minerals, acid-base balance and feed intake of dry pregnant cows on grass silage based feeding

Selostus: Kationi-anionitasapaino ja kalsiumin saanti ummessaolevien lypsylehmien säilörehuruokinnassa

Effects of blocking farm minkś feed access with open water

Selostus: Tarhatun minkin syömään pääsyn estäminen vesialtaalla

Impact dehulling oat grain to improve quality of on-farm produced feed 2

Selostus: Kauran kuorinnan aiheuttama jyvien rikkoutuminen ei heikennä säilyvyyttä

Impact dehulling oat grain to improve quality of on-farm produced feed 1

Selostus: Kotoisen kauran ravitsemuksellista arvoa ja energiapitoisuutta voidaan parantaa kuorinnalla

Messiah : He shall feed his flock

r1941.

Design and Analysis of Forward Error Control Coding and Signaling for Guaranteeing QoS in Wireless Broadcast Systems

Broadcasting systems are networks where the transmission is received by several terminals. Generally broadcast receivers are passive devices in the network, meaning that they do not interact with the transmitter. Providing a certain Quality of Service (QoS) for the receivers in heterogeneous reception environment with no feedback is not an easy task. Forward error control coding can be used for protection against transmission errors to enhance the QoS for broadcast services. For good performance in terrestrial wireless networks, diversity should be utilized. The diversity is utilized by application of interleaving together with the forward error correction codes. In this dissertation the design and analysis of forward error control and control signalling for providing QoS in wireless broadcasting systems are studied. Control signaling is used in broadcasting networks to give the receiver necessary information on how to connect to the network itself and how to receive the services that are being transmitted. Usually control signalling is considered to be transmitted through a dedicated path in the systems. Therefore, the relationship of the signaling and service data paths should be considered early in the design phase. Modeling and simulations are used in the case studies of this dissertation to study this relationship. This dissertation begins with a survey on the broadcasting environment and mechanisms for providing QoS therein. Then case studies present analysis and design of such mechanisms in real systems. The mechanisms for providing QoS considering signaling and service data paths and their relationship at the DVB-H link layer are analyzed as the first case study. In particular the performance of different service data decoding mechanisms and optimal signaling transmission parameter selection are presented. The second case study investigates the design of signaling and service data paths for the more modern DVB-T2 physical layer. Furthermore, by comparing the performances of the signaling and service data paths by simulations, configuration guidelines for the DVB-T2 physical layer signaling are given. The presented guidelines can prove useful when configuring DVB-T2 transmission networks. Finally, recommendations for the design of data and signalling paths are given based on findings from the case studies. The requirements for the signaling design should be derived from the requirements for the main services. Generally, these requirements for signaling should be more demanding as the signaling is the enabler for service reception.

Häiriöanalyysejä tehonkorotetun kiehutusvesivoimalaitoksen käytettävyyden varmistamiseksi

TVO suunnittelee reaktoritehon 10 %:n korotusta Olkiluoto 1 ja 2 -voimalaitoksille. Reaktoriteho nostetaan 2500 MW:sta 2750 MW:iin polttoaineen rikastusastetta nostamalla ja pääkiertovirtausta kasvattamalla. Samalla syöttövesivirtaus reaktoriin ja tuorehöyryvirtaus turpiineille kasvaa. Lauhteenpuhdistusjärjestelmän kapasiteettia ei voida kuitenkaan kasvattaa, joten massavirran lisäys toteutetaan ottamalla käyttöön korkeapainesivulauhteen eteenpäinpumppaus. Lauhteen esilämmityslinjojen, lauhteenpuhdistuksen ja syöttövesipumppujen massavirta säilyy siten nykyisellään. Muita merkittäviä tehonkorotukseen liittyviä laitosmuutoksia ovat pääkiertopumppujen uusinta ja korkeapaineturpiinin muutokset. Tehonkorotetun prosessin käytettävyyden varmistamiseksi tehdään häiriöanalyysejä Apros-prosessisimulointiohjelmistoa käyttäen. OL1 ja OL2 -laitoksista on olemassa validoitu 2500 MW:n laitosmalli, josta muokatulla 2750 MW:n laitosmallilla simuloinnit tehdään. Häiriöanalyysien avulla selvitetään säätöjärjestelmien kyky pitää prosessin tila hallinnassa ilman suojausautomaation laukeamista. Simuloituihin tapauksiin kuuluu pumppujen ja venttiilien vikaantumistapauksia sekä turpiini- ja reaktoripuolen pikasulku- ja osittaispikasulkutapauksia. Myös meriveden lämpötilan vaikutusta häiriötilanteisiin tarkastellaan. Analyysien perusteella voimalaitosten ohjaus- ja suojausautomaatio toimivat hyvin myös korotetulla teholla. Tehonkorotuksen jälkeiset suuremmat massavirrat aiheuttavat kuitenkin voimakkaampia reaktoripaineen ja -tehon vaihteluita varsinkin venttiilien sulkeutumistapauksissa. Simuloinnit osoittivat, että tehonkorotus 2500 MW:sta 2750 MW:iin on mahdollinen, mutta aiheuttaa pieniä muutoksia laitoksen suojausjärjestelmien laukaisurajoihin.

CFD modeling of dispersion water feed in wastewater cleaning application

Fluid particle breakup and coalescence are important phenomena in a number of industrial flow systems. This study deals with a gas-liquid bubbly flow in one wastewater cleaning application. Three-dimensional geometric model of a dispersion water system was created in ANSYS CFD meshing software. Then, numerical study of the system was carried out by means of unsteady simulations performed in ANSYS FLUENT CFD software. Single-phase water flow case was setup to calculate the entire flow field using the RNG k-epsilon turbulence model based on the Reynolds-averaged Navier-Stokes (RANS) equations. Bubbly flow case was based on a computational fluid dynamics - population balance model (CFD-PBM) coupled approach. Bubble breakup and coalescence were considered to determine the evolution of the bubble size distribution. Obtained results are considered as steps toward optimization of the cleaning process and will be analyzed in order to make the process more efficient.