Extremum Seeking for Dead-Zone Compensation

13301甲第4148号博士（学術）金沢大学博士論文本文Full 以下に掲載：Journal of Automation and Control Engineering 3(4) pp.265-269 2015. Engineering and Technology Publishing. 共著者：Dessy Novita and Shigeru Yamamoto

Nonlinear control schemes for extremum power seeking and torsional vibration mitigation in variable speed wind turbine systems

Doctor of PhilosophyDepartment of Electrical and Computer EngineeringDon GruenbacherWarren WhiteThis dissertation presents nonlinear control schemes to improve the productivity and lifespan of doubly fed induction generator (DFIG)-based and permanent magnet generator (PMG)-based variable speed wind turbines. To improve the productivity, a nonlinear adaptive control scheme is developed to maximize power capture. This controller consists of three feedback loops. The first loop controls electrical torque of the generator in order to cancel the nonlinear term of the turbine equation of motion using the feedback linearization concept. The nonlinearity cancelation requires a real-time estimation of aerodynamic torque. This is achieved through a second loop which estimates the ratio of the wind turbine power capture versus the available wind power. A third loop utilizes this estimate to identify the shaft speed at which the wind turbine operates at a greater power output. Contrary to existing techniques in literature, this innovative technique does not require any prior knowledge of the optimum tip speed ratio. The presented technique does not need a dither or perturbation signal to track the optimum shaft speed at the maximum power capture. These features make this technique superior to existing methods. Furthermore, the lifespan of variable speed wind turbines is improved by reducing stress on the wind turbine drivetrain. This is achieved via developing a novel vibration mitigation technique using sliding-mode control theory. The technique measures only generator speed as the input signal and then passes it through a high-pass filter in order to extract the speed variations. The filtered signal and its integral are then passed through identical band-pass filters centered at the dominant natural frequency of the drivetrain. These two signals formulate a sliding surface and consequently a control law to damp the drivetrain torsional stress oscillations caused by electrical and mechanical disturbances. This technique provides a robust mitigation approach compared with existing techniques. These control schemes are verified through holistic models of DFIG- and PMG-based wind turbines. Except for wind turbine aerodynamics, for which an existing simulator is used, the developed models of all components including DFIG, PMG, converters, multi-mass drivetrain, and power line are presented in this dissertation

Dynamics, Control and Extremum Seeking of the Rectisol Process

Pendant la dernière décennie, les bioraffineries basées sur la gazéification ont fait l’objet de nombreuses études dans le cadre des efforts mondiaux visant à remplacer les combustibles fossiles qui produisent de l’énergie et des produits chimiques à valeur ajoutée. Une partie importante de ces bioraffineries est l’unité de purification des gaz de synthèse issus de l’oxydation partielle, qui enlève le CO2 et l’H2S. Un des procédés de purification considéré dans ces études est le Rectisol. Ce procédé est utilisé car il est plus environnemental et requière moins de coûts d’investissement et d’opération par rapport à d’autres procédés similaires. Afin de faire l’étude dynamique de ce procédé, une simulation en régime permanent à d’abord, été menée à l’aide du logiciel Aspen plus R. ----------ABSTRACT Gasification based biorefineries have been studied in the past decade as part of a global e↵ort to replace fossil fuels to produce energy and added value chemicals. An important part of these biorefineries is the acid gas removal units, that remove CO2 and H2S from the produced synthesis gas. One of the acid gas removal processes associated in these studies is Rectisol. Rectisol has been chosen since it’s environmental friendly and requires a lower amount of operational and capital costs compared to its opponents. To carry out a dynamic study of the process, as a first step, a steady-state simulation was carried out in Aspen Plus

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

Process Control of Crushing Circuits

Kivenmurskaus on keskeinen osaprosessi kiviaineksen, metallien ja sementin tuotannossa. Murskaamalla tuotetut raaka-aineet muodostavat nykyaikaisen infrastruktuurimme perustan. Huolimatta merkittävästä roolistaan, kivenmurskaus on yksi harvoista teollisista prosesseista, jonka prosessinohjaus toteutetaan edelleen kokemusperäisesti, ilman luotettavaa mittaustietoa suoritettujen ohjaustoimien vaikutuksista. Nykykäytäntö altistaa murskausprosessit prosessivaihteluille ja –häiriöille, ja johtaa viime kädessä tehottomaan tuotantoon ja kapasiteetin vajaakäyttöön. Pääsyinä nykytilaan voidaan pitää murskausprosessien puutteellista anturointia ja tutkimustiedon puutetta korkeamman automaatioasteen tuomista hyödyistä. Tässä väitöskirjassa pyrittiin ratkaisemaan edellä mainittu ongelma automaattisen prosessinohjauksen avulla. Päätavoitteena oli kehittää säätömenetelmät murskauspiirin suorituskyvyn saattamiseksi lähelle parasta saavutettavissa olevaa tasoa. Tämä tutkimus perustuu mallipohjaiseen säädönsuunnittelumenetelmään. Systemaattinen suunnitteluprosessi alkoi säätötavoitteiden määrittelystä ja dynaamisten prosessimallien kehittämisestä. Kehitettyjen prosessimallien avulla luotiin säätötavoitteet täyttävä säätöstrategia ja viritettiin strategian vaatimat prosessisäätimet. Lopuksi simulointimallien avulla kehitetty ja testattu säätöstrategia implementoitiin osaksi laitoksen automaatiojärjestelmää ja sen suorituskyky arvioitiin täyden mittakaavan prosessikokeiden avulla. Tämä väitöskirja on osoittanut, että murskauspiirin tehokas ja tarkoituksenmukainen toiminta vaatii eri kahden säätötavan toteuttamista: massataseen säätö ja hienonnusmäärän säätö. Massatasesäädön tavoitteena on varmistaa 100 % käyttöaste murskauspiirin pullonkaulassa. Hienonnusmäärän säätö varmistaa halutun murskaimen tuotemateriaalin partikkelikokojakauman. Kehitetyt hienonnusmäärän säätömenetelmät perustuvat itseoptimoituvaan säätötapaan, joka mahdollistaa likimain optimaalisen suorituskyvyn käyttämällä säätimessä vakio-asetusarvoa. Kun tämä asetusarvo valitaan optimaalisesti, mahdollistaa esitelty ohjausstrategia parhaan saavutettavissa olevan murskauspiirin suorituskyvyn. Työn merkittävä tunnuspiirre on erityisen kattava empiria. Kehitetyt menetelmät testattiin kattavasti useissa erilaisissa tuotantoskenaarioissa ja prosessikonfiguraatioissa. Täyden mittakaavan prosessikokeiden tulokset vastasivat hyvin lähelle simulaatioilla saatuja tuloksia. Tämä väitöskirja on merkittävä edistysaskel murskausprosessien säädössä. Työn tuloksena kehitetyt mittaus- ja säätötavat mahdollistavat tehokkaamman ja tarkoituksenmukaisemman raaka-ainetuotannon. Työn tuloksilla voidaan olettaa olevan merkittävä vaikutus siihen, miten ja millä tavoin murskausprosesseja ohjataan tulevaisuudessa. Työssä kehitetyn murskauspiirin automaattisen säätöstrategian voidaan olettaa toimivan perustana tulevaisuuden murskausprosessien prosessiautomaatio-toteutuksille.Crushing is an essential high-volume processing stage in the production of aggregates, metals and cement. Crushed products form the basis of our modern infrastructure and therefore play a major role in the economic growth and welfare. Despite its significant role in society, crushing is one of the few remaining industrial processes that is currently being operated using belief-based manual control without the possibility to quantify the consequences of performed control actions. This practice makes crushing processes vulnerable to process variation and exposes them to inefficient production and capacity underutilization. The aim of this thesis is to address this deficiency by bridging the gap between theoretically possible and realized crushing circuit performance, by means of automatic process control. This thesis covers the entire model-based control system design procedure – from the formulation of control objectives and development of dynamic process model(s), through the development of control strategy, to the control system implementation and performance evaluation – for crushing circuits. Research has led to significant advances within crushing process measurement and control. Developed methods have been rigorously tested in various production scenarios and circuit flowsheets, using both dynamic simulations and full-scale experiments. Experiments revealed expected behavior with a significant increase in performance. The results have shown that the efficient operation of a crushing circuit requires addressing two control tasks: mass balance control and size reduction control. The objective of mass balance control is to guarantee 100 percent circuit utilization, whereas size reduction control ensures the desired degree of size reduction. The ideal degree of size reduction is determined empirically to maximize the value of the used KPI. The developed control strategy delivers near-maximum circuit performance. This thesis represents a major leap forward in the area of process control of crushing circuits. It has opened entirely new possibilities by making it possible to quantify the instantaneous performance of crushing circuits and by introducing the ability to ensure consistent and efficient long-term production. These major breakthroughs can have a significant impact on how crushing plants will be operated in the future. Developed standard control practice can be expected to serve as a basis for future control system implementations of industrial crushing circuits

Least Squares Based Adaptive Control and Extremum Seeking with Active Vehicle Safety System Applications

On-line parameter estimation is one of the two key components of a typical adaptive control scheme, beside the particular control law to be used. Gradient and recursive least squares (RLS) based parameter estimation algorithms are the most widely used ones among others. Adaptive control studies in the literature mostly utilize gradient based parameter estimators for convenience in nonlinear analysis and Lyapunov analysis based constructive design. However, simulations and real-time experiments reveal that, compared to gradient based parameter estimators, RLS based parameter estimators, with proper selection of design parameters, exhibit better transient performance from the aspects of speed of convergence and robustness to measurement noise. One reason for the control theory researchers' preference of gradient algorithms to RLS ones is that there does not exist a well-established stability and convergence analysis framework for adaptive control schemes involving RLS based parameter estimation. Having this fact as one of the motivators, this thesis is on systematic design, formal stability and convergence analysis, and comparative numerical analysis of RLS parameter estimation based adaptive control schemes and extension of the same framework to adaptive extremum seeking, viz. adaptive search for (local) extremum points of a certain field. Extremum seeking designs apply to (i) finding locations of physical signal sources, (ii) minimum or maximum points of (vector) cost or potential functions for optimization, (iii) calculating optimal control parameters within a feedback control design. In this thesis, firstly, gradient and RLS based on-line parameter estimation schemes are comparatively analysed and a literature review on RLS estimation based adaptive control is provided. The comparative analysis is supported with a set of simulation examples exhibiting transient performance characteristics of RLS based parameter estimators, noting absence of such a detailed comparison study in the literature. The existing literature on RLS based adaptive control mostly follows the indirect adaptive control approach as opposed to the direct one, because of the difficulty in integrating an RLS based adaptive law within the direct approaches starting with a certain Lyapunov-like cost function to be driven to (a neighborhood) of zero. A formal constructive analysis framework for integration of RLS based estimation to direct adaptive control is proposed following the typical steps for gradient adaptive law based direct model reference adaptive control, but constructing a new Lyapunov-like function for the analysis. After illustration of the improved performance with RLS adaptive law via some simple numerical examples, the proposed RLS parameter estimation based direct adaptive control scheme is successfully applied to vehicle antilock braking system control and adaptive cruise control. The performance of the proposed scheme is numerically analysed and verified via Matlab/Simulink and CarSim based simulation tests. Similar to the direct adaptive control works, the extremum seeking approaches proposed in the literature commonly use gradient/Newton based search algorithms. As an alternative to these search algorithms, this thesis studies RLS based on-line estimation in extremum seeking aiming to enhance the transient performance compared to the existing gradient based extremum seeking. The proposed RLS estimation based extremum seeking approach is applied to active vehicle safety system control problems, including antilock braking system control and traction control, supported by Matlab/Simulink and CarSim based simulation results demonstrating the effectiveness of the proposed approach

Gain tuning of proportional integral controller based on multiobjective optimization and controller hardware-in-loop microgrid setup

Proportional integral (PI) control is a commonly used industrial controller framework. This PI controller needs to be tuned to obtain desired response from the process under control. Tuning methods available in literature by and large need sophisticated mathematical modelling, and simplifications in the plant model to perform gain tuning. The process of obtaining approximate plant model conceivably become time consuming and produce less accurate results. This is due to the simplifications desired by the power system applications especially when power electronics based inverters are used in it. Optimal gain selection for PI controllers becomes crucial for microgrid application. Because of the presence of inverter based distributed energy resources. In the proposed approach, a multi-objective genetic algorithm is used to tune the controller to obtain expected step response characteristics. The proposed approach do not need simplified mathematical models. This prevents the need for obtaining unfailing plant models to maintain the fidelity of modelling. Microgrid system and the PI controller are modelled in different software, hardware platform and tuned using the proposed approach. Gain values for PI controller in these different platform are tuned using the same objective function and multi-objective optimization. This proves the re-usability, scalability, and modularity of the proposed tuning algorithm. Three different combination of software, hardware platform are proposed. First, the process and the PI controller are modelled in a computer based hardware. In order to increase the speed of the multi-objective optimization in the computer based hardware parallel computing is employed. This is a natural fit for paralleling the GA based optimization. Second, both the plant and control representation are modelled in the real time digital simulator (RTDS). Finally, a controller hardware in loop platform is used. In this platform, the plant will be modelled in RTDS and the PI controller will be modelled in an FPGA based hardware platform. Results indicate that the proposed approach has promising potentials since it does not need to simplify the switching model and can effectively solve the complicated tuning procedure using parallel computing. Similar advantage could be said for RTDS based tuning because RTDS simulates the models in real time

Design and Control of Power Converters 2019

In this book, 20 papers focused on different fields of power electronics are gathered. Approximately half of the papers are focused on different control issues and techniques, ranging from the computer-aided design of digital compensators to more specific approaches such as fuzzy or sliding control techniques. The rest of the papers are focused on the design of novel topologies. The fields in which these controls and topologies are applied are varied: MMCs, photovoltaic systems, supercapacitors and traction systems, LEDs, wireless power transfer, etc

Improvement of voltage and power flow control in the GCC power grid by using coordinated FACTS devices

This work presents HVDC/FACTS control device implementation framework in the Gulf cooperative council’s countries. It comprises of five layers of FACTS control devices (STATCOM, SSSC, UPFC, HVDC and centralized/De-centralized Control). This five-layer architecture is designed in order to configure and produce the desired results; based on these outcomes, GCC power system network control and operational problems can be identified and addressed within the control architecture on the GCC power grid. In the context of power FACTS-FRAME, this work is to identify and determine a number of power systems operational and control problems which are persistent on the GCC power grid e.g. poor voltage quality (SAG-Swell), poor load flow control, and limited power transfer capacity issues. The FACTS-FRAME is configured and synthesized by integrating multiple FACTS control devices (STATCOM, SSSC, UPFC) in parallel at different locations on the GCC power grid in order to meet stringent power system control and operational requirements with improved power transfer capacity, controllability and reliability. The mathematical models are derived to indentify and determine operational constraints on the GCC power grid by incorporating real-time and estimated data and the acquired desired results. Herein, FACTS-FRAME is designed to handle distributed computation for intensive power system calculation by integrating multiple FACTS devices on multiple networks within the GCC power network. Distributed power flow algorithms are also derived in order to understand and implement centralized and decentralized control topologies as appropriate. The simulation results indicate the feasibility of FACTS devices implementation and their potential benefits under current operating conditions on the GCC power grid.EThOS - Electronic Theses Online ServiceGBUnited Kingdo