Robust fault detection for vehicle lateral dynamics: Azonotope-based set-membership approach

© 2018 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 worksIn this work, a model-based fault detection layoutfor vehicle lateral dynamics system is presented. The majorfocus in this study is on the handling of model uncertainties andunknown inputs. In fact, the vehicle lateral model is affectedby several parameter variations such as longitudinal velocity,cornering stiffnesses coefficients and unknown inputs like windgust disturbances. Cornering stiffness parameters variation isconsidered to be unknown but bounded with known compactset. Their effect is addressed by generating intervals for theresiduals based on the zonotope representation of all possiblevalues. The developed fault detection procedure has been testedusing real driving data acquired from a prototype vehicle.Index Terms— Robust fault detection, interval models,zonotopes, set-membership, switched uncertain systems, LMIs,input-to-state stability, arbitrary switching.Peer ReviewedPostprint (author's final draft

Tilt angle optimization of photovoltaic panels

© 2019 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.The solar PV power sector in Spain has been developing at a spectacular rate in recent years. The energy cost and the dependence on fossil fuels can be reduced by improving the efficiency of photovoltaic energy production. The performance of a solar radiation conversion system is affected by a tilt angle with the horizontal plane. Thus, the photovoltaic array needs to be tilted at the correct angle to maximize the performance of the system. In this paper, we found the optimum tilt angle and applied for Barcelona, Spain, located at latitude 41o 22' 56'' North and longitude 2o 6'56'' East. The optimal tilt angle for Winter (December, January, February) is 56.46 and the optimum tilt angle for Spring (March, April, May Ls 2 .11°and the optimum tilt angle for Summer(Jun, July, August Ls 13.76° and the optimum tilt angle for Autumn (September, 2ctober, November Ls 8.1 °. finally, the annual optimum tilt angle for our latitude Ls 36.87°, ZLth thLs optimal slope angle, maximum monthly and annual solar radiation is calculated. In this way, we can increase the energy generation when achieved to maximum solar radiation. With this process, we were able to increase 10.54% of energy.Peer ReviewedPostprint (author's final draft

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A Monomer-to-Trimer Transition of the Human Mitochondrial Transcription Termination Factor (mTERF) Is Associated with a Loss of in Vitro Activity

The human mitochondrial transcription termination factor (mTERF) is a nuclear-encoded 39-kDa protein that recognizes a mtDNA segment within the mitochondrial tRNALeu(UUR) gene immediately adjacent to and downstream of the 16 S rRNA gene. Binding of mTERF to this site promotes termination of rDNA transcription. Despite the fact that mTERF binds DNA as a monomer, the presence in its sequence of three leucine-zipper motifs suggested the possibility of mTERF establishing intermolecular interactions with proteins of the same or different type. When a mitochondrial lysate from HeLa cells was submitted to gel filtration chromatography, mTERF was eluted in two peaks, as detected by immunoblotting. The first peak, which varied in proportion between 30 and 50%, appeared at the position expected from the molecular mass of the monomer (41 ± 2 kDa), and the gel filtration fractions that contained it exhibited DNA binding activity. Most interestingly, the material in this peak had a strong stimulating activity on in vitro transcription of the mitochondrial rDNA. The second peak eluted at a position corresponding to an estimated molecular mass of 111 ± 5 kDa. No mTERF DNA binding activity could be detected in the corresponding gel filtration fractions. Therefore, we propose that mTERF exists in mitochondria in two forms, an active monomer and an inactive large size complex. The estimated molecular weight of this complex and the fact that purified mTERF can be eluted from a gel filtration column as a complex of the same molecular weight strongly suggest that this inactive complex is a homotrimer of mTERF

Robust optimization based energy dispatch in smart grids considering demand uncertainty

In this study we discuss the application of robust optimization to the problem of economic energy dispatch in smart grids. Robust optimization based MPC strategies for tackling uncertain load demands are developed. Unexpected additive disturbances are modelled by defining an affine dependence between the control inputs and the uncertain load demands. The developed strategies were applied to a hybrid power system connected to an electrical power grid. Furthermore, to demonstrate the superiority of the standard Economic MPC over the MPC tracking, a comparison (e.g average daily cost) between the standard MPC tracking, the standard Economic MPC, and the integration of both in one-layer and two-layer approaches was carried out. The goal of this research is to design a controller based on Economic MPC strategies, that tackles uncertainties, in order to minimise economic costs and guarantee service reliability of the system.Postprint (author's final draft

Economic MPC with periodic terminal constraints of nonlinear differential-algebraic-equation systems: Application to drinking water networks

© 2026 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 worksIn this paper, an Economic Model Predictive Control (EMPC) strategy with periodic terminal constraints is addressed for nonlinear differential-algebraic-equation systems with an application to Drinking Water Networks (DWNs). DWNs have some periodic behaviours because of the daily seasonality of water demands and electrical energy price. The periodic terminal constraint and economic terminal cost are implemented in the EMPC controller design for the purpose of achieving convergence. The feasibility of the proposed EMPC strategy when disturbances are considered is guaranteed by means of soft constraints implemented by using slack variables. Finally, the comparison results in a case study of the D-Town water network is provided by applying the EMPC strategy with or without periodic terminal constraints.Accepted versio

Model predictive control based on LPV models with parameter-varying delays

© 2019 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 a Model Predictive Control (MPC) strategy based on Linear Parameter Varying (LPV) models with varying delays affecting states and inputs. The proposed control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. Moreover, the solution of the optimization problem associated with the MPC design is achieved by solving a series of Quadratic Programming (QP) problem at each time instant. This iterative approach reduces the computational burden compared to the solution of a non-linear optimization problem. A pasteurization plant system is used as a case study to demonstrate the effectiveness of the proposed approach.Peer ReviewedPostprint (author's final draft

Wasting Democracy, Fueling Dissent:Refuse-Derived Fuels in Can Sant Joan (Catalonia)

The cement industry is one of the most energy intensive in the world, contributing significantly to global greenhouse gas emissions. The use of refuse-derived fuels (RDF) in cement kilns is increasingly portrayed as a sustainable solution to reduce emissions while dealing with different types of waste. Nevertheless, the use of RDF in cement plants is contested by communities around the world, who are facing immediate environmental impacts. In this article, we examine the burgeoning movement against waste incineration in cement kilns legitimized as energy recovery. We start by revisiting the environmental justice literature, which laid the groundwork for the contemporary anti-RDF movement. Then, in order to highlight the energy dimension of RDF we focus on two energy-related concepts: energy justice and energy democracy. Through the case study of Can Sant Joan (Catalonia), we assess the suitability and usefulness of these concepts with the local movement against waste incineration. Our analysis suggests that the movement against RDF use can be further energized and strengthened by expanding into the realm of energy democracy. Both the anti-RDF and the energy democracy movement share a focus on the local scale, have similar typology of stakeholders involved, and favor a strong bottom-up approach while paying attention to unequal power relations. We also observe that these movements can mutually benefit from being better integrated with one another. Finally, we propose that a potential alliance between the Plataforma Antiincineració de Montcada i Reixac (PAMiR) and the Xarxa per la Sobirania Energètica (Xse) in Catalonia, can mobilize fruitful internal tensions toward a more inclusive and democratic future

Output-feedback model predictive control of a pasteurization pilot plant based on an LPV model

In order to optimize the trade-off between components life and energy consumption, the integration of a system health management and control modules is required. This paper proposes the integration of model predictive control (MPC) with a fatigue estimation approach that minimizes the damage of the components of a pasteurization plant. The fatigue estimation is assessed with the rainflow counting algorithm. Using data from this algorithm, a simplified model that characterizes the health of the system is developed and integrated with MPC. The MPC controller objective is modified by adding an extra criterion that takes into account the accumulated damage. But, a steady-state offset is created by adding this extra criterion. Finally, by including an integral action in the MPC controller, the steady-state error for regulation purpose is eliminated. The proposed control scheme is validated in simulation using a simulator of a utility-scale pasteurization plant.Peer ReviewedPostprint (author's final draft

Economic health-aware LPV-MPC based on system reliability assessment for water transport network

This paper proposes a health-aware control approach for drinking water transport networks. This approach is based on an economic model predictive control (MPC) that considers an additional goal with the aim of extending the components and system reliability. The components and system reliability are incorporated into the MPC model using a Linear Parameter Varying (LPV) modeling approach. The MPC controller uses additionally an economic objective function that determines the optimal filling/emptying sequence of the tanks considering that electricity price varies between day and night and that the demand also follows a 24-h repetitive pattern. The proposed LPV-MPC control approach allows considering the model nonlinearities by embedding them in the parameters. The values of these varying parameters are updated at each iteration taking into account the new values of the scheduling variables. In this way, the optimization problem associated with the MPC problem is solved by means of Quadratic Programming (QP) to avoid the use of nonlinear programming. This iterative approach reduces the computational load compared to the solution of a nonlinear optimization problem. A case study based on the Barcelona water transport network is used for assessing the proposed approach performance.Peer ReviewedPostprint (published version