Design robust controllers for load reduction in wind turbines

This thesis determines a design methodology of robust and multivariable controllers based on the H∞ norm reduction and on LPV (Linear Parameter Varying) techniques for load reduction in wind turbines. In order to do this, a 5 MW offshore wind turbine model based on the ‘Upwind’ European project is developed using GH Bladed, which is a wind turbine modelling specific software package. These controllers work in the above rated control zone, where the non-linearities of the wind turbine appear with more intensity. The main control objective in this zone is to keep the generator working at the nominal values of rotational speed and torque to correctly extract the nominal electric power in high winds. Furthermore, new control objectives are included to mitigate the loads in different components of the wind turbine, which involves the need of a multivariable control design. The family of linear models extracted from the non-linear model is used to design the proposed controllers. In this work, the family of linear models extracted from the GH Bladed is high ordered due to the complexity and accuracy of the wind turbine model. The Robust Control and LPVMAD MATLAB toolboxes are used to make the controller synthesis. LPVMAD is a toolbox developed by the scientific control group directed by Prof. Dr. Carsten Scherer at the Stuttgart University. After an exhaustive analysis of the State of the Art about the wind turbine control systems, a baseline control strategy based on classical control methods is initially designed. Five monovariable, MISO (Multiple Input Single Output) and multivariable robust control strategies, based on the H∞ norm reduction, are presented to improve the benefits of the baseline controller. These controllers fulfill some control objectives to mitigate the loads in the wind turbine: generator speed regulation, drive train mode damping, tower first fore-aft and side-to-side first mode damping and rotor alignment. The designed H∞ controllers generate control signals of generator torque, collective pitch blade angle and individual pitch angles for each blade. On the other hand, two LPV control strategies are designed to improve the generator speed regulation in the above rated zone generating collective pitch angle set-point values. The first LPV controller consists of the interpolation of three H∞ controllers designed in three different operational points. The second LPV controller synthesis is based on a LMI (Linear Matrix Inequalities) solution using the LPVMAD toolbox and a wind turbine LPV model. The wind turbine multivariable LPV modelling process is also explained in this thesis. The designed controllers are validated in GH Bladed and an exhaustive analysis is carried out to calculate the fatigue load reduction on the wind turbine components, as well as to analyze load mitigation in some extreme cases. The controllers are tested in a real time prototype which allows to carry out HIL (Hardware in the Loop) simulations. A GUI interface tool is developed in MATLAB to determine a sequential method making easier the controller design explained in this thesis. Finally, the proposed design methodology of robust and multivariable controllers is applied to a commercial 3 MW wind turbine.Tesi honek aldagai anitzeko kontrolatzaile sendoak diseinatzeko metodologia bat ezartzen du, non kontrolatzaileak H∞ normaren gutxitzean eta LPV (Linear Parameter Varying) kontrol-tekniketan oinarrituta dauden, haize-errotetako karga mekanikoak murrizteko. Horretarako, 'Upwind' europar proiektuan definitutako 5 MWeko itsas haize-errotaren eredua garatu da GH Bladed softwarean. Kontrolatzaile horien diseinua 'above rated' izeneko funtzionamendu-zonalderako da. Zonalde horretan haize-erroten ez-linealtasunak garrantzi handikoak dira eta haize-errotaren funtzionamendua biratze-abiadura eta momentu nominaletan egin nahi da, horrela haize altuetan potentzia nominala lortu ahal izateko. Hauxe helburu nagusia izanda, beste kontrol-helburuak ere kontuan hartzen dira: haize-errotaren osagai desberdinetan karga mekanikoak txikitzea kontrolatzaileen diseinua aldagai anitzeko ikuspuntu batetik eginez. GH Bladed paketean definitutako eredu ez-linealaren linealizaziotik lortzen den eredu linealen familia erabiltzen da kontrolatzaileak diseinatzeko, nahiz eta oso orden handiko ereduak izan modelatze-konplexutasuna dela-eta. Kontrolatzaileak sortzeko MATLAB-eko kontrol sendoaren 'toolbox'-a erabiltzen da eta baita Dr. Carsten Scherer-en lantaldeak garatutako LPVMAD 'toolbox'-a ere. Haize-errotentzako kontrol-sistemen Arte-Egoeraren analisi sakon baten ondoren, hasieran, erreferentzi kontrolatzaile bat diseinatzen da, normalean erabiltzen diren kontrolatzaile klasikoetan oinarrituta. Tesian bost kontrolatzaile sendo, H∞ normaren txikitzean oinarrituak, aurkezten dira, aldagai bakarrekoak, MISO (Multiple Input Single Output) eta aldagai aniztzekoak, alde batetik erreferentzi kontrol-estrategiaren prestazioak hobetzeko eta beste aldetik haize-errotetan karga mekaniken murrizketak eragiten dituzten helburuak betetzeko: sortzailearen abiadura angeluarra erregulatzea, potentzi trenaren modua moteltzea, dorrearen aurre-atzerako eta alboko lehenengo bibrazio-moduetan haizearen efektuak murriztea eta errotorea lerrokatzea. Kontrolatzaileek sortzaileentzako momentuen kontrol-seinaleak, itxoroskientzat pitch-angelu kolektiboa eta baita itxoroski bakoitzarentzat pitch-angelu independenteak ere sortzen dituzte, inposatutako kontrolhelburuak betetzeko. Horietatik at, beste bi LPV kontrol-estrategia diseinatzen dira 'above rated' funtzionamendu-zonaldean sortzailearen abiadura angeluarraren kontrola hobetzeko pitch-angelu kolektiboaren kontsignen bidez. Lehenengo LPV kontrolatzailea hiru funtzionamendu-puntu desberdinetan diseinaturiko hiru H∞ kontrolatzaileen interpolazioan datza. Bigarren LPV kontrolatzailearen diseinua, ordea, LMI (Linear Matrix Inequalities) sistema baten askatzean datza, LPVMAD 'toolbox'-a eta haize-errotaren LPV eredu bat erabiliz. Haize-errota baten aldagai anitzeko LPV modelatze-prozesua ere zehatz-mehatz azaltzen da tesi honetan. Diseinatutako kontrolatzaileak GH Bladed paketean balioztatu dira analisi sakon baten bidez, non neke-kargen eta mutur-kargen murrizketak haize-errotaren osagai desberdinetan kalkulatzea ahalbideratzen baita. Kontrolatzaileak HIL (Hardware in the Loop) simulazioak egitea errazten duen denbora errealeko prototipo batean ere probatu dira, kontrolatzaileen funtzionamendu egokia ziurtatzen duena. Garatutako kontrolatzaileen diseinua errazteko interfaze grafiko bat gauzatu da MATLAB-en, non tesian aurkeztutako kontrolatzaile bakoitzaren diseinua prozedura sekuentzial baten bidez egin ahal izan den. Azkenean, aldagai anitzeko kontrolatzaile sendoen diseinurako proposaturiko metodologia 3 MWeko haize-errota komertzial batean aplikatu egin da.Esta tesis establece una metodología de diseño de controladores robustos multivariables basados en la reducción de la norma H∞ y en técnicas de control LPV (Linear Parameter Varying) para la reducción de cargas en aerogeneradores. Para ello, se ha desarrollado un modelo de un aerogenerador offshore de 5 MW definido en el proyecto europeo 'Upwind' mediante el software de modelado específico de aerogeneradores GH Bladed. El diseño de estos controladores se centra en la zona de funcionamiento denominada 'above rated', donde se manifiestan con mayor importancia las no-linealidades del aerogenerador y en la que se pretende mantener el funcionamiento del generador en sus valores nominales de velocidad de giro y par para la correcta extracción de potencia nominal a vientos altos. Además de este objetivo principal, se incluyen nuevos objetivos de control que minimicen las cargas en las diferentes partes del aerogenerador haciendo que el diseño de los controladores requiera un punto de vista multivariable. Para el diseño de los controladores se utiliza la familia de modelos lineales extraída de la linealización del modelo no lineal, en este caso definido en GH Bladed, siendo estos modelos de un orden elevado debido a la complejidad del modelado. Para la síntesis de los controladores se utiliza las 'toolbox' de MATLAB de control robusto y la 'toolbox' LPVMAD desarrollada por el grupo de trabajo del Prof. Dr. Carsten Scherer. Tras un profundo análisis del estado del arte sobre los sistemas de control en los aerogeneradores, inicialmente se diseña una estrategia de control referencia basada en los controladores clásicos comúnmente utilizados. En la tesis se presentan cinco controladores robustos monovariables, MISO (Multiple Input Single Output) y multivariables basados en la reducción de la norma H∞ para mejorar las prestaciones de la estrategia de control referencia y que cumplen con diferentes objetivos de control que implican una reducción de cargas en el sistema: regulación de la velocidad angular del generador, amortiguamiento del modo del tren de potencia, reducción del efecto del viento sobre los primeros modos adelante-atrás y lateral de la torre y alineamiento del rotor. Los controladores generan señales de control de par en el generador, ángulo de pitch colectivo en las palas y ángulos independientes de pitch para cada pala con la finalidad de satisfacer los objetivos de control impuestos. Por otro lado, se diseñan dos estrategias de control LPV para mejorar la regulación de velocidad angular del generador en la zona de 'above rated' mediante consignas de ángulo de pitch colectivo. El primer control LPV consiste en la interpolación de tres controladores H∞ diseñados en tres puntos de operación diferentes, mientras que la síntesis del segundo controlador LPV se basa en la solución de un sistema LMI (Linear Matrix Inequalities) mediante la toolbox LPVMAD y utilizando el modelo LPV del aerogenerador. El proceso de modelado LPV multivariable de un aerogenerador también es explicado con detenimiento en esta tesis. Los controladores diseñados son validados en GH Bladed mediante un exhaustivo análisis que permite calcular la reducción de cargas extremas y cargas de fatiga en los diferentes componentes del aerogenerador. Los controladores son probados en un prototipo en tiempo real que permite realizar simulaciones HIL (Hardware in the Loop) que ratifican el correcto funcionamiento de los controladores. Para facilitar el diseño de estos controladores se ha implementado una interfaz gráfica en MATLAB que permite establecer un procedimiento secuencial para el diseño de cada controlador explicado en la tesis. Finalmente, la metodología propuesta para el diseño de controladores robustos multivariables se ha aplicado a un aerogenerador comercial de 3 MW

LPV MODELLING, IDENTIFICATION AND CONTROL INCLUDING FAULT TOLERANCE MECHANISMS: APPLICATION TO A TWO-DEGREE OF FREEDOM HELICOPTER

Questa tesi presenta la modellazione, l’identificazione ed il controllo LPV (Linear Parameter Varying, sistemi lineari con parametri varianti) con meccanismi di tolleranza ai guasti di un Twin Rotor MIMO System (TRMS). Il modello non lineare del TRMS è trasformato in un modello quasi-LPV ed è approssimato in maniera politopica. Dopodiché, i parametri del modello sono stati identificati con un approccio d’identificazione basato sui minimi quadrati non lineari. Una volta ottenuto un modello calibrato, un simulatore è stato costruito e validato con dati reali. Usando un approccio di piazzamento dei poli mediante risoluzione di disuguaglianze matriciali lineari (LMI), sono stati progettati un osservatore ed un controllore LPV, e questi sono stati testati sia sul simulatore che sul sistema reale, provando la loro efficacia e le loro prestazioni. Infine, una strategia di controllo tollerante ai guasti basata sull’idea dei sensori e degli attuatori virtuali è stata applicata in maniera LPV. Per implementare tale strategia, una stima dei guasti è richiesta; per questo motivo è stato implementato un metodo per identificare i guasti attraverso la formulazione di un problema di stima dei parametri. La metodologia è stata applicata al simulatore ed al sistema reale, mostrando la sua efficacia, ma anche i suoi limiti

Control Methods for High-Speed Supercavitating Vehicles

Supercavitation is an emerging technology that enables underwater vehicles to reach un- precedented speed. With proper design of cavitator attached to the vehicle nose, the vehicle body is surrounded by water vapor cavity, eliminating skin friction drag. This technology offers unprecedented drag reduction, though poses problems for vehicle design. The gas bubble surrounding the hull introduces highly coupled dynamic behavior, representing a challenge for the control designer. Development of stable, controllable supercavitating vehi- cles requires solution for several open problems. This dissertation addresses the problem of control oriented modeling, stability augmentation, and reference tracking using parameter dependent control techniques for supercavitating vehicles.\ud The thesis is divided into three parts. A nonlinear dynamical model capturing the most important properties of the vehicle motion is developed from a control design perspective. The model includes memory effects associated with the time evolution of the cavity and uses lookup tables to determine forces.\ud To aid understanding the cavity-vehicle interaction, a longitudinal control scenario is developed for a simplified longitudinal dynamical model with guaranteed properties. Sig- nificant insight is gained on planing behavior and operating envelope using constrained control inputs.\ud Extending the longitudinal control problem, a linear parameter varying model of the coupled motion is developed to provide a platform for parameter dependent control syn- thesis. The mathematical model is scheduled with aerodynamic angles, uses steady-state approximation of the cavity, leading to uncertainty in the governing equations. Two Linear Parameter Varying (LPV) controllers are synthesized for the angle rate tracking problem, taking uncertainty into account. One uses traditional decoupled loops for pitch-, roll- and yaw-rate tracking. Ignoring the cross coupling, leads to more tractable subproblems . A controller, taking advantage of the coupling, is also presented in the thesis. The complexity of the coupled dynamics prohibits the synthesis of the controller as a single entity. Sev- eral LPV controllers synthesized for smaller overlapping regions of the parameter space are blended together, providing a single controller for the full flight envelope. Time-domain simulations of different vehicle-controller configurations, implemented on high-fidelity sim- ulations, provide insight into the capabilities of the supercavitating vehicle

Switching LPV Controllers for a Variable Speed Pitch Regulated Wind Turbine

This paper deals with the control of a variable speed, pitch regulated wind turbine in the whole plant operating area. The wind turbine operating area can be divided into several zones, depending on the wind speed, and the control objectives are different for each operating zone. An hybrid control system composed by several LPV controllers which switches during transitions from one operating area to another is designed in order to ensure asymptotic stability and a good level of performances in the whole operating area. The LPV controllers are calculated from a convex LMI formulation of the problem in order to minimize an H2=H¥ criteria that optimizes the energy conversion of the system and that reduces the mechanical fatigue of the plant mechanical structure. The proposed controller is finally compared with two more conventional ones

Fuzzy control turns 50: 10 years later

In 2015, we celebrate the 50th anniversary of Fuzzy Sets, ten years after the main milestones regarding its applications in fuzzy control in their 40th birthday were reviewed in FSS, see [1]. Ten years is at the same time a long period and short time thinking to the inner dynamics of research. This paper, presented for these 50 years of Fuzzy Sets is taking into account both thoughts. A first part presents a quick recap of the history of fuzzy control: from model-free design, based on human reasoning to quasi-LPV (Linear Parameter Varying) model-based control design via some milestones, and key applications. The second part shows where we arrived and what the improvements are since the milestone of the first 40 years. A last part is devoted to discussion and possible future research topics.Guerra, T.; Sala, A.; Tanaka, K. (2015). Fuzzy control turns 50: 10 years later. Fuzzy Sets and Systems. 281:162-182. doi:10.1016/j.fss.2015.05.005S16218228