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This article presents an innovative optimization-based solution to the collision avoidance challenge for autonomous vehicles. The presented approach consists in an online motion planner designed to define feasible and efficient paths able to deal with dynamic surroundings while implicitly ensure safety in the proposed maneuvers. The fact of considering moving obstacles inside the motion planner increases the complexity of the problem while forces it to be executed more frequently as others. To reduce this computational complexity, the approach presented counts with a two stages translation of the commonly used non-linear optimization-based structure into a QP formulation which can be easily solved. The first stage is based on the use of LPV matrices in the dynamic constraints of the vehicle. The second stage consists in performing a reachability analysis based on set propagation to obtain linear expressions of the permitted inputs and reachable states which guarantee safety conditions., This work has been co-financed by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SaCoAV (ref. MINECO PID2020-114244RB-I00) and by the DGR of Generalitat de Catalunya, Spain (SAC group ref. 2017/SGR/482)., Peer Reviewed, Postprint (published version)

This thesis presents the development and implementation of the Attitude Determination and Control System (ADCS) for the 3cat-8 satellite, a project undertaken by the UPC NanoSat Lab. The ADCS is essential for maintaining the desired orientation of the satellite, which is crucial for performing scientific experiments, gathering solar power and communicating with the ground station. This work primarily focuses on the complete modeling of a satellite using a hybrid Magnetorquer + Reaction wheel actuator scheme, and the control algorithms that needed to obtain and maintain a desired orientation during flight. Various options for representing attitude in space are explored, with quaternions chosen as the basis for the attitude determination and control algorithms. Space dynamics are also thoroughly examined in order to create the backbone for a simulation software with which the control laws will be tested and validated. To ensure that the simulation environment closely mirrors reality, state-of-the-art environmental models of the Earth are studied and implemented. Additionally, the disturbances acting upon the satellite are deeply analyzed and characterized, employing numerical and statistical methods to obtain accurate yet computationally efficient implementations of said disturbances. The actuation scheme has been found to impact the control algorithms used for attitude control in the pointing modes, creating the need for allocating the control commands across the actuator suite, as well as unloading the angular momentum stored in the reaction wheel. The final satellite model and the selected control laws have been tested in the simulated environment, demonstrating their correct functioning and mostly fulfilling the operational requirements initially set for the 3cat-8 satellite. The thesis concludes with suggestions for possible improvements in the attitude control scheme and recommendations for future work.

A novel fault diagnosis procedure is proposed in this paper to estimate faults using a linear parameter varying (LPV) model whose scheduling parameters depend on the fault. A wrong determination of the operating conditions could lead the system to an undesired performance or even to an unstable situation, when classical fault diagnosis approaches are applied. This paper addresses this issue by formulating fault diagnosis as a dynamic optimization problem, solved by using a novel hybrid technique that combines a Luenberger-based observer with artificial intelligent (AI) optimization-based algorithms. The observer supervises the health of the system, while AI-based algorithms are able to reconstruct the faulty signal in real-time when the observer determines that the system is under a fault. The efficiency of the proposed fault diagnosis scheme, the three AI-based algorithms based on artificial bee colony and particle swarm optimization, and the gradient-based algorithm developed in this paper, are assessed using a numerical example., This work has been co-financed by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SaCoAV (ref. MINECO PID2020-114244RB-100), by the European Regional Development Fund of the European Union in the framework of the ERDF Operational Program of Catalonia 2014-2020 (ref. 001-P-001643 Looming Factory) and by the DGR of Generalitat de Catalunya (SAC group ref. 2017/SGR/482)., Peer Reviewed, Postprint (author's final draft)

The design of a controller able to deal with uncertainties and physical constraints plays an essential role in fast and complex systems. Then, a reference governor approach based on model predictive control (MPC-RG) for an autonomous racing vehicle is proposed. The MPC-RG guarantees constraint satisfaction and recursive feasibility online while including obstacle avoidance capability and energy-aware management by solving a multi-objective optimization problem. In particular, a trade-off between maximizing the longitudinal velocity and the state of charge of the vehicle’s battery, as well as minimizing the variation of control actions is adopted. Moreover, the proposed MPC-RG is combined with a state-feedback linear quadratic regulator (LQR) and a Kalman filter (KF) to compensate for modeling errors and exogenous disturbances, as well as to estimate the unmeasured lateral velocity. In fact, for control and estimation purposes, a data-driven Takagi–Sugeno (TS) model trained by an adaptive neuro-fuzzy inference network is used. The performance of the developed approach is assessed in simulations using a well-known case study based on a scale RC electric car., This work has been co-financed by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SaCoAV (ref. MINECO PID2020-114244RB-I00) and by the DGR of Generalitat de Catalunya (SAC group ref. 2017 / SGR / 482). The work is also supported by a FI AGAUR grant (Ref. 2021FI-B1 00097)., Peer Reviewed, Postprint (author's final draft)

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., A reference governor approach based on model predictive control (MPC-RG) for an autonomous racing vehicle is developed in this work. This control strategy avoids constraint violations and includes online health management capabilities by solving a multi-objective optimization problem. In this case, a trade-off between the maximization of the state of charge of the battery and the longitudinal velocity, even the minimization of the control actions variation is carried out. In turn, the invariant zonotopic sets analysis ensures the convergence of states to a stable region. On the other hand, the proposed control scheme also combines a robust states feedback linear quadratic regulator (LQR) with a Kalman filter (KF) estimator to compensate for model uncertainty and exogenous disturbances, as well as, to estimate the unmeasured lateral velocity. Moreover, to represent the non-linear behaviour of the vehicle, a data-driven neuro-fuzzy Takagi-Sugeno (TS) model is employed. The developed approach is tested and evaluated in realistic environments by means of a simulated 1/10 Scale RC car., This work has been co-financed by the Spanish Research Agency (AEI) through the project SaCoAV (ref. MINECO PID2020-114244RB-I00)., Peer Reviewed, Postprint (author's final draft)

Data-driven prognostics and health management is an important part of the future industry. It allows the detection of system faults and estimation of its remaining useful life (RUL) to anticipate failures and schedule appropriate prescriptive maintenance actions. Moreover, with the development of data acquisition tools in such industries, it is possible to collect large amount of data from similar systems, which prompts the use of machine learning algorithms for efficient estimation of the system RUL. However, due to different type of faults and degradation rates that can occur in real processes, there exists high variability of the end-of-life (¿¿¿) time of each system degradation trajectory, making more difficult to fix a failure threshold and consequently generate several uncertainties in the estimation of RUL. To address this situation, this paper proposes a new data-driven approach for estimating the system RUL when dealing with the variability of degradation trends and unknown failure thresholds. Particularly, the proposed approach combines two RUL techniques, recursive and direct RUL estimation. First, the historical collected raw data are fed into a processing algorithm to construct prognostic health indicators (HIs) and choose the one that characterizes well the system’s degradation trajectory. This latter indicator allows identifying the high and low ¿¿¿ amplitude values from the historical data and is used to build a recursive prediction model that estimates in long-term the degradation trend evolution. After that, the trained model forecasts every degradation trend which ¿¿¿ amplitude is less than the predefined high value. Thus, a set of possible RULs of each trajectory can be predicted. Finally, the ensemble of the derived RULs and their HI trajectories are fused to directly estimate the final RUL. The proposed approach is applied to a subway door system with multiple degradation scenarios while taking into account different operating conditions., The project has been 65% cofinanced by the European Regional Development Fund (ERDF) through the Interreg V-A Spain France Andorra programme (POCTEFA 2014–2020). POCTEFA aims to reinforce the economic and social integration of the French-Spanish-Andorran border. Its support is focused on developing economic, social and environmental cross-border activities through joint strategies favoring sustainable territorial development. Also, this work was supported by the ANR DATAZERO (contract ‘‘ANR-15-CE25-0012’’) project and by the EIPHI Graduate school (contract "ANR-19-CE25-0016")., Postprint (published version)

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., In this work, the trajectory tracking problem of an autonomous racing electrical vehicle is addressed. Accordingly, a two-layer control scheme is developed, such that stability, recursive feasibility, and constraint satisfaction are guaranteed. The outer layer includes a zonotopic tube-based predictive control to ensure trajectory tracking while minimizing energy consumption considering the state of charge of the vehicle’s battery. Meanwhile, the inner layer combines a linear quadratic zonotopic controller with a zonotopic Kalman filter to reduce the effect of exogenous disturbances and modeling errors. Moreover, for control and estimation purposes, a data-driven Takagi–Sugeno (TS) model trained by an adaptive neuro-fuzzy inference system (ANFIS) is employed. To illustrate the performance of the proposed control scheme, a simulated 1/10 Scale RC car is used., This work was in part by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SaCoAV (ref. MINECO PID2020- 114244RB-I00), in part by the European Regional Development Fund of the European Union in the framework of the ERDF Operational Program of Catalonia 2014-2020 (ref. 001-P-001643 Looming Factory), and in part by the DGR of Generalitat de Catalunya (SAC group ref. 2017/SGR/482), and in part by the FI AGAUR under Grant 2021FI-B1 00097., Peer Reviewed, Postprint (author's final draft)

La principal motivación para llegar a cabo este estudio es la de mejorar la calidad de vida de un colectivo, el cual parece haber sufrido un estancamiento en lo que ha mejoras tecnológicas se refiere. Estudiando la viabilidad de Introducir un nuevo sistema de elementos capaz de mejorar la movilización en el transporte público, de las personas con poca o nula visibilidad, con intención de interpolar el modelo a otros ámbitos. Partiendo de un conocimiento ínfimo sobre el tema. A lo largo del estudio se presenta; el contexto socio cultural de las personas con baja visibilidad o ceguera, la retrospectiva de los elementos de reproducción del sonido y se propone un despiece de los elementos necesarios para el buen funcionamiento del sistema de dispositivos. La elaboración de un sistema de dispositivos normalizado necesita de conceptos específicos y técnicos, que sobre pasan mi conocimiento, de igual forma se han realizado explicaciones detalladas de los elementos que lo forman y su funcionamiento de la manera más cercana a la realidad para analizar de forma correcta el funcionamiento del sistema. Se propone un modelo organizativo de funcionamiento emisor- receptor, en el cual se especifica desde la ubicación de los emisores hasta las funciones que debe cumplir cada emisor de audio, sustentado mediante planos anexos al estudio. Finalmente se contempla que modelo económica se ajusta mejor, para el desarrollo del dispositivo.

© 2023 The Authors. This is an open access article under the CC BY-NC-ND license. Peer review under responsibility of International Federation of Automatic Control., In this paper an optimization-based solution to the collision avoidance challenge for autonomous vehicles is proposed. The presented approach consists in an online motion planner designed to define a feasible and efficient path which implicitly guarantees safety manoeuvres in dynamic surroundings. The fact of considering moving obstacles inside the motion planner increases the complexity of the problem while forces it to be executed more frequently as others. To reduce its computational complexity, this approach proposes a two stages translation of the commonly used non-linear optimization-based structure into a QP formulation which can be easily solved. The first stage is based on the use of LPV matrices in the dynamic constraints of the vehicle. The second stage consists in computing linear expressions by set propagation to obtain the set of permitted inputs and reachable states which guarantee safety conditions., This work has been co-financed by the Spanish State Research Agency (AEI) through the projects SaCoAV (ref. MINECO PID2020-114244RB-I00) and MASHED (TED2021-129927B-I00)., Peer Reviewed, Postprint (published version)

This bachelor final thesis delves into the computational resolution of transport equations, with a focus on introducing the student to Computational Fluid Dynamics (CFD) simulations. The objective of this research is achieved through the development of custom codes capable of solving problems presented by the Heat and Mass Transfer Technological Center (CTTC) [1] at the Technical University of Catalonia (UPC). Using the Finite Volume Method (FVM) and an algorithm based on the Fractional Step Method (FSM) for incompressible fluids, the equations of mass, momentum, and energy are solved. The student has personally programmed and verified all the codes using the C++ language. Special attention is given to comprehending the theoretical and computational implications of the Navier-Stokes equations, with a deliberate selection of progressively challenging problems that cover various aspects of these equations, culminating in the study of turbulence. The investigation extensively analyzes the contribution of convective and diffusive terms, beginning with the solution of a pure diffusion case and progressing to the numerical solution of a general convection-diffusion equation. Additionally, the study focuses on applied cases relevant to the aerospace industry, such as airflow around airfoils and cooled blades. However, this work only considers the convective and diffusive terms, as its primary goal is to lay the foundation for a future model examining the feasibility of hydrogen-powered aircraft engines in terms of turbine blade material resistance. The Fractional Step Method is applied to solve both internal flow scenarios, encompassing forced and natural convection, and external flow situations, specifically the flow around a square cylinder. The research investigates various aspects of turbulence and implements them in resolving the Burgers equation and a three-dimensional channel flow. Concluding the thesis, a proposal for future steps is presented, outlining an advance

(English) Maintenance is indispensable in every industry that uses machines and is inevitable regardless of the attention paid to it. The cumulative effect of its neglect or a non-optimized approach is a long or short-term shock on a company's growth. It, therefore, comes as no surprise, the overwhelming interest in the area of intelligent maintenance where comprehensive control units can detect, alert personnel, predict when a failure will occur, and manage faults to extend the life of components. Borne out of this is a new field of study, Prognostics and Health Management, which emerged only about two decades ago. This thesis contributes to this nascent field of study, and most importantly to a novel interest in the field of incorporating component prognostic information into control to manage the extent of influence degradation has on the efficient output of a plant. In sum, the thesis seeks to (1.) Contribute to component prognostics and how uncertainty can be efficiently handled and (2.) Promote the incorporation of prognostic information in a control scheme (i.e. Model Predictive Control). For prognostics, the thesis considers two critical components, a wind turbine blade composite material and an insulated gate bipolar transistor utilizing two different types of prognostic methods, the model and data-based methods respectively. Wind turbine blades are by far the most exposed component to damage predominately due to their level of mechanical activity in the turbine operation. Forces such as gyroscopic and gravity, debris in wind, and the effect of the stochastic nature of wind contribute to a gradual damaging effect culminating in a complete blade breakdown. Given that the blade material itself is innate, mathematical degradation equations dependent on material properties to predict the extent of the material damage in the absence of sensor information is used. Therefore, with a stiffness degradation algorithm aided by a zonotopic Kalman filter, the remaining, (Català) El manteniment és indispensable en tota indústria que utilitza màquines i és inevitable independentment de l'atenció que se li presti. L'efecte acumulat de la seva negligència o un enfocament no optimitzat és un xoc a llarg o curt termini en el creixement de l'empresa. Per tant, no sorprèn l'aclaparador interès en l'àmbit del manteniment intel·ligent on les unitats de control integrals poden detectar, alertar el personal, predir quan es produirà una fallada i gestionar les avaries per allargar la vida útil dels components. D'això neix un nou camp d'estudi, Pronòstic i gestió de la salut, que va sorgir fa només unes dues dècades. Aquesta tesi contribueix a aquest camp d'estudi naixent i, sobretot, a un nou interès en l'àrea d'incorporar informació pronòstica dels components al control per gestionar l'abast de la influència que té la degradació en la producció eficient d'una planta. En resum, la tesi pretén (1.) Contribuir al pronòstic dels components i com es pot gestionar de manera eficient la incertesa i (2.) Promoure la incorporació d'informació pronòstica en un esquema de control (és a dir, Model Predictive Control). Per al pronòstic, la tesi considera dos components crítics, un material compost de pales d'aerogenerador i un transistor bipolar de porta aïllada que utilitza dos tipus diferents de mètodes de pronòstic, el model i els mètodes basats en dades, respectivament. Les pales de l'aerogenerador són, amb diferència, el component més exposat a danys, principalment pel seu nivell d'activitat mecànica en el funcionament de la turbina. Forces com la giroscòpica i la gravetat, les deixalles del vent i l'efecte de la naturalesa estocàstica del vent contribueixen a un efecte danyós gradual que culmina amb una ruptura completa de la paleta. Atès que el material de la fulla en si és innat, s'utilitzen equacions de degradació matemàtiques que depenen de les propietats del material per predir l'abast del dany material en absència d'informació del sensor. Per t, Postprint (published version)

The uncertain parameters estimation problem for linear discrete-time systems modeled in regression form and assuming an unknown but bounded description of the noise, is the main subject of this work. Particularly, zonotopic sets for bounding the parametric uncertainty are considered. Then, a zonotopic recursive least-squares (ZRLS) estimator is proposed and compared with its stochastic counterpart (RLS), as well as with the set-membership (SM) approach. Likewise, the parameter estimation problem is addressed from the Bayesian general framework to define the relationship between stochastic and deterministic approaches. Moreover, both ZRLS and SM applications applied to fault detection are assessed taking as a reference the minimum detectable fault in the worst case. Finally, a well-known quadruple-tank process is used to illustrate the estimation and fault detection results., This work has been co-financed by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SaCoAV (ref. MINECO PID2020-114244RB-I00), by the European Regional Development Fund of the European Union in the framework of the ERDF Operational Program of Catalonia 2014–2020 (ref. 001-P-001643 Looming Factory) and by the DGR of Generalitat de Catalunya (SAC group ref. 2017/SGR/482). The author is also supported by a FI AGAUR grant (ref. 2021FI-B1-00097)., Peer Reviewed, Postprint (author's final draft)

Recent years have seen a great deal of innovation in the field of systems prognostics and health management. However, even with these advancements, some pertinent issues related with uncertainty in remaining useful life predictions are still open for investigation. One such area of interest is on how to account for the distribution of these predictions such that all uncertainty sources are duly captured and represented. Practically, these uncertainty quantification procedures must be computationally feasible for real-life deployment and reflect real-life situations devoid of strong assumptions. This article thus, proposes a data-based prognostics technique that uses a set-based quantification of uncertainty based on the set-membership paradigm, the interval predictor approach. The methodology is applied in the framework of the Evolving Ellipsoidal Fuzzy Information Granule which has recently proven its potency in prognostics applications. As a case study, the method is tested on the prognostics of insulated bipolar transistors utilising an accelerated aging IGBT dataset from the NASA Ames Research Center., Peer Reviewed, Postprint (author's final draft)

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works, This paper presents an economic reliability-Aware Model Predictive Control (MPC) approach for the Prognostics and Health Management (PHM) of generalized flow-based networks. The main enhancement with respect to some existing approaches relies on the integration of the network reliability model obtained from a Bayesian Network. In this case, the controller is able to optimally manage the supply taking into consideration the distribution of the control effort. The life of the actuators is extended by delaying as much as possible the network reliability decay. The proposed methodology also considers an optimal inventory replenishment policy based on a desired risk acceptability level, leading to the availability of safety stocks for unexpected excess demand in networks. The proposed implementation is illustrated with a real case study corresponding to an aggregate model of the Drinking Water transport Network (DWN) of Barcelona. © 2022 IEEE., Postprint (author's final draft)

The increasing application of power converter systems based on semiconductor devices such as Insulated-Gate Bipolar Transistors (IGBTs) has motivated the investigation of strategies for their prognostics and health management. However, physicsbased degradation modelling for semiconductors is usually complex and depends on uncertain parameters, which motivates the use of data-driven approaches. This paper addresses the problem of data-driven prognostics of IGBTs based on evolving fuzzy models learned from degradation data streams. The model depends on two classes of degradation features: one group of features that are very sensitive to the degradation stages is used as a premise variable of the fuzzy model, and another group that provides good trendability and monotonicity is used for the auto-regressive consequent of the fuzzy model for degradation prediction. This strategy allows obtaining interpretable degradation models, which are improved when more degradation data is obtained from the Unit Under Test (UUT) in real time. Furthermore, the fuzzy-based Remaining Useful Life (RUL) prediction is equipped with an uncertainty quantification mechanism to better aid decisionmakers. The proposed approach is then used for the RUL prediction considering an accelerated aging IGBT dataset from the NASA Ames Research Center., Postprint (published version)

This paper presents a model-based prognostics procedure using a zonotopic Kalman filter in tandem with a zonotopic set-based propagation of degradation, aiding in the quantification of uncertainties associated with prognostics. The prognostics procedure is then applied to the degradation of a wind turbine blade material subjected to a forecasted bounded set description of wind profile. To facilitate an online condition based implementation, an otherwise nonlinear based Kalman filter from the nonlinear wind turbine model is presented in a pseudolinear form, a polytopic linear parameter varying representation, decreasing computational cost and easing in the propagation of the positive invariant zonotopic uncertainty sets to a reachable set that triggers an end of life. Using this information of health, the remaining useful life with its associated uncertainties can be predicted., Peer Reviewed, Postprint (published version)

A robust economic model predictive control approach that takes into account the reliabilityof actuators in a network ispresented for the control of a drinking water network in the presence of uncertainties in the forecasted demands required forthe predictive control design. The uncertain forecasted demand on the nominal MPC may make the optimization processintractable or, to a lesser extent, degrade the controller performance. Thus, the uncertainty on demand is taken into accountand considered unknown but bounded in a zonotopic set. Based on this uncertainty description, a robust MPC is formulatedto ensure robust constraint satisfaction, performance, stability as well as recursive feasibility throughthe formulation ofan online tube-based MPC and an accompanying appropriate terminal set. Reliability is thenmodelled based on Bayesiannetworks, such that the resulting nonlinear function accommodated in the optimization setup is presented in a pseudo-linearform by means of a linear parameter varying representation, mitigating any additional computational expense thanks to theformulation as a quadratic optimization problem. With the inclusion of a reliability index to the economic dominant cost ofthe MPC, the network users’ requirements are met whilst ensuring improved reliability, therefore decreasing short and longterm operational costs for water utility operators. Capabilities of the designed controller are demonstrated with simulatedscenarios on the Barcelona drinking water network, Peer Reviewed, Postprint (published version)

This work proposes an economic model predictive control (EMPC) strategy in the linear parameter varying (LPV) framework for the control of dissolved oxygen concentrations in the aerated reactors of a wastewater treatment plant (WWTP). A reduced model of the complex nonlinear plant is represented in a quasi-linear parameter varying (qLPV) form to reduce computational burden, enabling the real-time operation. To facilitate the formulation of the time-varying parameters which are functions of system states, as well as for feedback control purposes, a moving horizon estimator (MHE) that uses the qLPV WWTP model is proposed. The control strategy is investigated and evaluated based on the ASM1 simulation benchmark for performance assessment. The obtained results applying the EMPC strategy for the control of the aeration system in the WWTP of Girona (Spain) show its effectiveness., This work has been co-financed by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SaCoAV (ref. MINECO PID2020- 114244RB-I00), by the European Regional Development Fund of the European Union in the framework of the ERDF Operational Program of Catalonia 2014–2020 (ref. 001-P-001643 Looming Factory), and by the DGR of Generalitat de Catalunya (SAC group ref. 2017/SGR/482)., Peer Reviewed, Postprint (author's final draft)

This paper presents a health-aware economic Model Predictive Control (EMPC) approach for the Prognostics and Health Management (PHM) of generalized flow-based networks. The proposed approach consists of the integration of the network reliability model obtained from a Bayesian network in the control model. The controller is then able to optimally manage the supply taking into consideration the distribution of the control effort, to extend the life of the actuators by delaying the network reliability decay as much as possible. It also considers an optimal inventory replenishment policy based on a desired risk acceptability level, leading to the availability of safety stocks for unexpected excess demand in networks. The proposed implementation is illustrated with a real case study corresponding to an aggregate model of the Drinking Water transport Network (DWN) of Barcelona., Peer Reviewed, Postprint (published version)

This paper addresses the system identification problem, as well as its application to robust fault detection, considering parametric uncertainty and using zonotopes. As a result, a Zonotopic Recursive Least Squares (ZRLS) estimator is proposed and compared with the Setmembership (SM) approach when applied to fault detection, taking as a reference the minimum detectable fault generated in the worst-case. To illustrate the effectiveness of the proposed robust parameter estimation and fault detection methodologies, a quadruple tank process is employed., This work has been co-financed by the Spanish State Research Agency (AEI) and the European Regional De- velopment Fund (ERFD) through the project SaCoAV (ref. MINECO PID2020-114244RB-I00 ), by the European Regional Development Fund of the European Union in the framework of the ERDF Operational Program of Catalo- nia 2014-2020 (ref. 001-P-001643 Looming Factory) and by the DGR of Generalitat de Catalunya (SAC group ref. 2017/SGR/482). The author is also supported by a FI AGAUR grant (Ref. 2021FI-B1 00097)., Peer Reviewed, Postprint (published version)

Inside this document you can follow the development of a project consisting of designing and building a gimbal to be used on a commercial drone. The project includes the design of the structure to be manufactured entirely with carbon fiber, the design of the electronics and the manufacturing of a control board, and the design of a model that provides the automatic control and stabilization to the gimbal.

La investigació sobre l’avenç i la innovació tecnològica és un dels principals objectes d’estudi en la indústria aeroespacial. El reús de vehicles espacials és un d’ells i es tracta d’un important aspecte per disminuir els grans costos i recursos que una missió espacial implica, minimitzant també l’impacte ambiental. Aquest treball desenvolupa l’estudi i la implementació del control per la recuperació segura dels sistemes de llançament d’un coet. Per tal d’assolir aquest anàlisis, s’avaluen els actuals coets reutilitzables, seleccionant el Falcon 9 del SpaceX com a model principal en el qual el projecte es centra. Un cop caracteritzat aquest sistema en particular, es determina la modelització d’equacions del problema amb l’objectiu de crear un programa en l’entorn de Matlab i efectuar simulacions. La necessitat d’un sistema de control és inferida mitjançant els resultats de les primeres simulacions a causa de l’absència dels paràmetres d’aterratge segur, d’entre els quals el més important és una velocitat final pròxima a 0. Conseqüentment, es proposen i comparen diferents controladors lineals a fi d’aconseguir el comportament desitjat del sistema. No obstant, les no-linealitats del problema sumades a les limitacions d’aquests controladors incrementa la complexitat, a causa de la considerable quantitat d’entrades de control. Per aquests motius, el sistema es simplifica englobant les forces i els moments en les corresponents resultants amb les quals la totalitat de les superfícies de control han de contribuir. Seguint aquesta metodologia, el sistema desenvolupat consisteix en controlar la velocitat mitjançant les forces i l’angle de capcineig amb els moments. D’aquest últim, s’extreu com a conclusió que el Control Predictiu basat en Model disposa d’una tendència a ajustar-se millor a la consigna que el PID. En definitiva, les limitacions d’aquests controladors tenen un impacte en la resposta final i, per aquesta raó, es requereixen de propostes més complexes per tal d, The research of advanced and innovative technologies is one of the main concerns within the aerospace industry. Spacecraft reusability is one of them, being an important aspect to diminish the huge costs and resources that a space mission implicate, minimising also the environmental impact. This thesis develops the study and the implementation of the control for the safe recovery of the launch system of a rocket. In order to accomplish this analysis, the current successful reusable rockets are evaluated and the Falcon 9 from the SpaceX is selected as the main model in which the project is focused on. Once characterised this particular system, the problem equation modelling is determined to create a framework within a Matlab environment and perform simulations. The need of a control system is inferred through the first simulations results due to the lack of the safe landing parameters, being the most important a final velocity close to 0. Consequently, different linear controllers are proposed and compared to achieve the desired behaviour from the system. Nevertheless, the non-linearity of the problem added to these controllers limitations increase the complexity, due to the considerable quantity of control inputs. For these reasons, the system is simplified by computing the resultant forces and moments that the overall control surfaces must contribute. Following this methodology, the developed system consists in controlling the velocity with the forces and the pitch angle with the moments. From this last, the extracted conclusion is the Model Predictive Control tendency to dispose of a better adjustment to the setpoint rather than the PID. In definitive, the limitations of these controllers have an impact to the final response and, for this reason, more complex proposals would be required to acquire an even closer approach to the real problem, such as nonlinear controllers or a second level of these type of controllers to determine the performance of each control de

This paper proposes a new algorithm to reduce the number of gains of a polytopic LPV controller considering generic tuples of vertices, for which a common controller gain can be used. The use of Frobenius norm and the inclusion of the input matrix in the LMIs perturbation matrix allows decreasing the conservativeness to select vertices which are combinable, with respect to a previous approach based on Gershgorin circles. A combinability metric that can be applied to an arbitrary partition of the set of vertices is defined. Then, a recursive algorithm finds a lesser-fragmented combinable partition at each iteration by combining together two elements of a partition. The algorithm aims at finding combinable partitions with minimal cardinality in fewer attempts, always preserving the original control performance specifications. The proposed method is validated using numerical examples, a twin rotor MIMO system and a two-link robotic manipulator., This work has been co-financed by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SCAV (ref. MINECO DPI2017-88403-R), by the European Regional Development Fund of the European Union in the framework of the ERDF Operational Program of Catalonia 2014-2020 (ref. 001-P-001643 Looming Factory) and by the DGR of Generalitat de Catalunya (SAC group ref. 2017/SGR/482)., Peer Reviewed, Postprint (author's final draft)

This thesis explores the necessities of simulators of the behaviour of turbomachinery and proposes an implementation of such a simulator. This simulator consists in the model of a turbojet, which is described and implemented, and an algebra subsystem that takes the model and produces a viable solution. Models for the different components of a turbojet are described. An algebra subsystem analogous to SPICE for electric circuits is proposed and developed. The results are examined, analyzed and discussed

Khoury Boutros et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited., Wind turbines generally operate under adverse conditions making them prone to relatively high failure rates. Due to the direct exposure of the blades to dynamic and cyclic loads of wind, the rotor and the blades unsurprisingly represent the most common major component damages of a wind turbine system, which is especially enhanced when located offshore. This paper presents a new model-based prognosis procedure based on a zonotopic Kalman filter (ZKF), which combines a physical model with observed data to assess the system degradation. Using this information and the model of the system, the end of life (EOL) and the remaining useful life (RUL) with its uncertainty can be predicted. The proposed prognostic method is applied to monitor the state of health of a wind turbine system specifically, its blades. The remaining useful life prediction will help in scheduling optimal maintenance and reducing the cost caused by wind turbine damage and unplanned shutdown., This work has been funded by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SCAV (ref. MINECO DPI2017- 88403-R), by the DGR of Generalitat de Catalunya (SAC group ref. 2017/SGR/482) and by SMART Project (ref. num. EFA153/16 Interreg Cooperation Program POCTEFA 2014- 2020)., Peer Reviewed, Postprint (published version)

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., In this paper, a robust economic model predictive controller is proposed for a water transport network. Considering that forecast of demand is required in the drinking water network (DWN) for future predictions of states in the MPC formulation, robustification of the proposed controller is undertaken considering demand uncertainties as unknown but bounded in a zonotopic set. Based on this uncertainty description, a robust MPC controller is designed that ensures that robust constraint satisfaction, stability and performance under uncertainties is guaranteed. The proposed approach is satisfactorily tested in a part of the Barcelona water transport network., Peer Reviewed, Postprint (author's final draft)

En aquest projecte de fi de grau s’estudiarà el disseny d’un prototip per a una plataforma estabilitzadora per a la compensació de tremolors dels braços. Aquest prototip va dirigit a persones que pateixen de tremolors, a les extremitats superiors en concret, entre d’altres produïts per la Malaltia del Parkinson, el Tremolor Essencial, i les discapacitats físiques que afecten al pacient. Aquest estudi consta de l’anàlisi del problema, el disseny lògic d’una solució en el que inclou l’explicació dels components a utilitzar, el disseny teòric del prototip i el sistema electrònic d’aquest. Un altre punt del projecte és el disseny d’una solució física per al prototip, en el qual s’inclouen les diferents peces i els plànols a implementar. Per finalitzar el projecte s’ha estudiat la viabilitat econòmica per a dur a terme el prototip i s’han proposat les possibles línies de futur

Wind turbine components are subject to considerable stress and fatigue due to extreme environmental conditions to which they are exposed to, especially when located offshore. Interest in the integration of control with system health monitoring has increased in recent years. The integration of a health management module with model predictive control (MPC) provides the wind turbine a mechanism to operate safely and optimize the trade-off between components’ life and energy production. In this paper, a health-aware LPV model predictive control approach for wind turbines is proposed. The proposed controller establishes a trade-off between the economic objective based on maximizing the energy production but at the same time taking into account the minimization of accumulated stress on the wind turbine blades. The controller uses an LPV model for dealing with the non-linearity of the wind turbine model and the inclusion of the stress model. The proposed approach is tested on a well-known wind turbine case., This work has been funded by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SCAV (ref. MINECO DPI2017-88403- R) and by the DGR of Generalitat de Catalunya (SAC group ref. 2017/SGR/482)., Peer Reviewed, Postprint (author's final draft)

A robust economic Model Predictive Control (EMPC) approach is presented in this paper for the control of a Drinking Water Network (DWN) albeit the presence of uncertainties in the forecasted demands required for the predictive control design. The uncertain forecasted demand on the nominal MPC has the possibility of rendering the optimization process infeasible or degrade the controller performance. In this paper, the uncertainty on demand is considered unknown but bounded in a zonotopic set. Based on this uncertainty description, a robust MPC is formulated to ensure robust constraint satisfaction, performance and stability of the MPC for DWN to meet user requirements whilst ensuring lower operational cost for water utility operators., Peer Reviewed, Postprint (author's final draft)

In this paper, a project oriented course on guidance and control of autonomous aerial vehicles (UAVs) is presented. The paper describes the di erent modules of the course and how they are addressed using the project oriented approach. The project uses a quadrotor UAV that is used as the case study during the course. In this course, the students learn how to mathematically model quadrotor UAV fight characteristics, develop feedback control algorithms to enable stable flight control and fuse sensor measurements using Kalman lter techniques to estimate the UAV position and orientation. Students develop these concepts through both simulation and interaction with UAV real measurements. Throughout the course, students build a full 6-degree-of-freedom simulation of controlled quadrotor UAV ight using MATLAB and Simulink., This work has been partially funded by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SCAV (ref. MINECO DPI2017-88403-R) and and by SMART Project (ref. num. EFA153/16 Interreg Cooperation Program POCTEFA 2014-2020)., Peer Reviewed, Postprint (author's final draft)

This paper proposes a model-based fault diagnosis and prognosis approach applied to brushless DC motors (BLDC). The objective is an early detection of mechanical and electrical faults in BLDC motors operating under a variety of operating conditions. The proposed model-based method is based on the evaluation of a set of residuals that are computed taking into account analytical redundancy relations. Fault diagnosis consist of two steps: First, checking if at least one of the residuals is inconsistent with the normal operation of the system. And, second, evaluating the set of the residuals that are inconsistent to determine which fault is present in the system. Fault prognosis consists of the same two steps but instead of considering current inconsistencies evaluates drift deviations from nominal operation to predict futures residual inconsistencies and therefore predict future fault detections and diagnosis. A description of various kinds of mechanical and electrical faults that can occur in a BLDC motor is presented. The performance of the proposed method is illustrated through simulation experiments., Postprint (published version)

A major goal in modern flight control systems is the need for improving reliability. This work presents a health-aware and fault-tolerant control approach for an octorotor UAV that allows distributing the control effort among the available actuators based on their health information. However, it is worth mentioning that, in the case of actuator fault occurrence, a reliability improvement can come into conflict with UAV controllability. Therefore, system reliability sensitivity is redefined and modified to prevent uncontrollable situations during the UAV’s mission. The priority given to each actuator is related to its importance in system reliability. Moreover, the proposed approach can reconfigure the controller to compensate actuator faults and improve the overall system reliability or delay maintenance tasks., Peer Reviewed, Postprint (published version)

La motivació d’aquest treball és l’optimització de la ruta d’un UAV a l’hora de realitzar treballs d’escombrat i navegació. Així doncs, es proposa l’estudi comparatiu sobre el seu comportament en medis sotmesos a pertorbacions estocàstiques quan l'UAV està governat mitjançant una Xarxa Neuronal o mitjançant models mesoscòpics de Masses Neuronals acoblats. Es comparan els resultats obtinguts, a través de simulacions, pels diferents mètodes de control aplicats, el primer de caire més artificial i el segon inspirat en comportaments biològics observats enpetites regions del cervell., Xarxes neuronals, neurociència i UAVs. L’aprenentatge autònom és una eina que s’utilitza en múltiples aplicacions avui dia, també en el camp de les aeronaus i concretament dels quadrirotors, que serà el framework del treball. En aquest estudi es modela una xarxa neuronal, que és un model d’aprenentatge autònom inspirat en els processos neuronals del cervell, mitjançant l’entrenament amb sèries de dades. La seva eficiència s’avalua amb un quadrirotor amb labors d’escombratge en mitjans estocàstics. Posteriorment, s’utilitza l’estructura trobada per a crear una segona xarxa neuronal, on cada cel·la inclourà un sistema dinàmic que simula el funcionament d’una columna cortical, anomenat Neural Mass (NM). Finalment, aprofitant la no-linealitat d’aquest model, s’avaluarà el rendiment d’aquest nou controlador per als diferents estats dinàmics de les NMs. Aquest estudi permet concloure si l’estructura òptima per a l’aprenentatge d’un robot ho és també per a un model alternatiu on les cel·les tenen una forta inspiració biològica. A més, utilitzant aquest segon model,s’observa en quin règim dinàmic s’obté un controlador més robust i es compara amb el que governa el còrtex habitualment

The goal of the TFG would be to implement an object recognition system for an autonomous robot within the GRASS (Ground Autonomous Student Station) project. The idea is to use two cameras and be able to juxtapose the images and create a 3D vision of what the system is seeing (in our case the rover), and be able to differentiate different predetermined objects by the shape, and if it's possible by the color. The purpose consists in recognizing the position and the orientation of these objects with respect to the rover as the considered reference system., The GRound Autonomous Student Station (GRASS) is a student organization with the objective of building an autonomous rover, and one of the capacities needed is the possibility of identifying objects. This project is focused on creating a recognition system capable of being incorporated on the Rover. The developed recognition system is focused on detection by colour and shape, using four colours and one predetermined cylindrical shape. The system has to identify the distance between the object and the camera. The developed system includes a Raspberry Pi system with his camera, using Python and OpenCV libraries as software. The developed system has been tried in a real model, but the final implementation has not been ended due to reasons related with the GRASS project. The structural and logistic parts of the project are developing a new space distribution in order to include eciently the recognition system, although the system has been tested. The developed system is capable of detecting determined objects with a simple shape in a maximum range of 12 meters. At the same time, it works on real environments, counting illumination and environmental visual noise.

The goal is to present a proposal of an UAV capable of a long-range search over the sea and equipped with computer vision technology to identify possible refugee boats. The UAV must be autonomous as much as possible and easy to use for people with basic knowledge about the technology.

Dins d’aquesta memòria es troba el desenvolupament del projecte de disseny i construcció d’un coet experimental amb un sistema d’estabilització mitjançant control actiu. Es descriu el procés de disseny de tots els apartats necessaris per al correcte funcionament del coet (fuselatge, electrònica, aletes, sistema de control i recuperació), la construcció d’aquests apartats, el desenvolupament dels programes de simulació i del control del coet, finalitzant amb les proves d’aquest en entorns reals.

El treball consisteix en el disseny d'una representació d'un UAV real mitjançant Matlab i Simulink, en el que es crearà un model basat en les seves característiques físiques per tal que es comporti com un UAV real. La calibració del model es farà gràcies a les dades d'entrades i sortides que proporcionen els sensors, com ara la posició, les acceleracions i velocitats de rotació dels rotors. Un cop realitzada la validació del model es dissenyarà i s'implementarà un sistema de control per al model que finalment s'aplicarà al sistema real un cop s'hagi comprovat el seu bon funcionament en simulació.

The project is based on the design of the control system of a chemical process through the engineering diagram. First, the process under consideration has been chosen. It consists in the mixture of two fluids, initially stored at different heights, which are mixed in a reactor. The reaction of this mixture where different condensation gases appear, are later reused to continue the mixture and obtain the final product. Next, the instrumentation required for the control system has been determined and then implemented in the process. In order to have a clearer view about that implementation, an engineering diagram has been sketched. Once the necessary process and instrumentation have been defined, the control system has been designed using a controller with different modules connected to it, which will allow to interconnect the elements of the process and the control software. Then, the programming has been realised using the software corresponding to the controller so as all the instrumentation works together and the process achieves the requirements imposed at the beginning of the project