Facultad Regional San Francisco
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Item Modeling of a Continuous Stirred Tank Reactor and Controller Design Using LMI Approaches(Wiley, 2025-01-07) Cappelletti, Carlos Alberto; Pipino , Hugo; Bernardi, Emanuel; Adam, Eduardo J.The design of non-linear control systems remains a challenge today, therefore through this work a procedure to obtain a vertex-reduced multi-model representation, without loss of convexity, is proposed as a suitable solution. That is, a novel approach which considers all parameter variations around the Continuous Stirred Tank Reactor (CSTR) system operating region is developed, resulting in a unique polytopic representation. After that, based on the linear matrix inequalities approach, a control scheme is developed to compute the optimal matrix gains, while the operating, states and inputs, constraints are satisfied and the stability conditions are ensured. Finally, the realistic simulation results highlight the model representation effectiveness in capturing the CSTR dynamic behavior in the operating region, despite parameter variations, allowing the optimal control law design, overcoming the non-linear system nature, to achieve the desired closed-loop system performance.Item Caracterización y calibración de unidades de medición inercial de bajo costo(edUTecNe, 2024-10) Jaime, Ibrahim; Beck Ferrero, Federico Augusto; Miretti, Marco; Bernardi, EmanuelConsiderando que la agricultura es una de las bases fundamentales de nuestra economía, su modernización resulta crucial para mejorar el rendimiento. La incorporación de tecnologías avanzadas permite una mejor gestión de los recursos, mayor precisión en las labores y una reducción significativa de los tiempos de trabajo. Además, estas tecnologías contribuyen a disminuir el impacto ambiental y a reducir la frecuencia de accidentes laborales. Con el objetivo de contribuir a la tecnificación de los procesos agro-industriales, desde el grupo de investigación de control aplicado y sistemas embebidos se inició el desarrollo de un vehículo autónomo multipropósito, para la evaluación de estrategias de navegación y control. Un componente fundamental para el seguimiento de trayectorias de manera autónoma es el sistema de adquisición de datos sobre la actitud del vehículo, en cada instante. Esto es, para determinar la orientación del mismo se utiliza una unidad de medición inercial (IMU), la cuál está compuesta por tres tipos de sensores: magnetómetro, giroscopio y acelerómetro. Dichos sensores son del tipo microelectromecánico y brindan mediciones de campo magnético, aceleración y velocidad angular. Las unidades de bajo costo comerciales cuentan con nueve grados de libertad, ya que poseen tres sensores de cada tipo, apropiadamente dispuestos. En el presente trabajo se presentarán las técnicas empleadas para la caracterización y calibración de IMU's de bajo costo. Dicho proceso es fundamental para su correcto funcionamiento debido a las perturbaciones que los sensores reciben por parte del entorno y también por el movimiento y vibraciones del vehículo en movimiento. Esto es, se realizará la caracterización de los sensores empleando el método varianza de Allan. Dicha información será utilizada tanto en el desarrollo del algoritmo de control como también en la determinación del período de recalibración del sensor, para asegurar un correcto funcionamiento.Item Fault-tolerant predictive control based on linear parameter varying scheme for industrial processes(2021-12-01) Bernardi, Emanuel; Adam, Eduardo J.Background: Process safety is a major concern in the researchers community, both in the past and today. However, the hardware complexity and the involved non-linear dynamics of industrial processes could lead to unsatisfactory behavior of traditional control methods. Methods: To cope with these issues, this paper presents a model-based strategy for fault tolerance in non-lin- ear chemical processes. Specifically, an observer-based fault detection and diagnosis scheme was imple- mented, which generates early and detailed fault information. Therefore, this valuable data was used to compensate the effects induced by actuator and sensor faults throughout the use of an integrated optimiza- tion-based identification and model predictive control technique, which allowed to track a reference even in the presence of faults. Significant Findings: This method reinforces the inherent robustness against faults of linear parameter varying predictive controllers. Moreover, the observers convergence and the controller stability were guaranteed in terms of linear matrix inequalities problems. A simulation based on a typical chemical industrial process, the highly non-linear continuous stirred tank reactor shows that the proposed method can achieve satisfactory performance in fault tolerance.Item Observer-based fault detection and diagnosis strategy for industrial processes(2020-07-30) Bernardi, Emanuel; Adam, Eduardo J.This study presents the design of a fault detection and diagnosis (FDD) scheme, composed from a bank of two types of observers, applied to linear parameter varying (LPV) systems. The first one uses a combination of reduced-order LPV observers to detect, isolate and estimate actuators faults, and the second one consists of a set of full-order LPV unknown input observers (UIO) to detect, isolate and estimate sensors faults. The observers’ design, convergence and its stability conditions are guaranteed in terms of linear matrix inequalities (LMI). Therefore, the main purpose of this work is to provide a novelty model-based observers’ technique to detect and diagnose faults upon non-linear systems. Simulation results, based on two typical chemical industrial processes, are given to illustrate and discuss the implementation and performance of such an approach.Item Fault-tolerant energy management for an industrial microgrid: A compact optimization method(2021-01-10) Bernardi, Emanuel; Morato, Marcelo M.; Costa Mendes, Paulo R.; Adam, Eduardo J.; Normey-Rico, Julio E.This work presents an optimization-based control method for the fault-tolerant energy management task of an industrial energy microgrid, based on a sugarcane power plant. The studied microgrid has several renewable energy sources, such as photovoltaic panels, wind turbines and biomass power generation, being subject to different operational constraints and load demands. The proposed management policy guarantees that these demands are met at every sampling instant, despite eventual faults. This law is derived from the solution of an optimization problem that combines the formalism of a Moving Horizon Estimation (MHE) scheme (to estimate faults) and a Model Predictive Control (MPC) loop (for fault-tolerant control goals); it chooses which energy source to use, seeking maximal profit and increased sustainability. The predictive controller part of the scheme is based on a linear time-varying model of the process, which is scheduled with respect to the fault estimation brought up by the MHE. Via numerical simulations, it is demonstrated that the proposed method, when com- pared to other MPC strategies, exhibits enhanced performances.Item Infraestructura para el desarrollo de laboratorios remotos(2022-06-15) Miretti, Marco; Bernardi, EmanuelEl presente trabajo se fundamenta en la enseñanza a través de experiencias remotas. El mismo plantea el desarrollo de una infraestructura de aprendizaje a distancia mediante la construcción de laboratorios remotos de forma versátil, escalable y asequible, al apoyarse en la democratización de la tecnología. Si bien la propuesta es aplicable a un sinnúmero de ramas de la ciencia, con el fin de proveer un prototipo funcional, éste se implementó para la enseñanza de sistemas de control. En consecuencia, éste consiste en la construcción de un sistema dinámico, típico del área. Además, cuenta con una interfaz de programación de aplicación (API) que permite a los estudiantes desarrollar sus propios algoritmos de control, utilizando lenguajes de alto nivel, como son Python y GNU Octave, prescindiendo de competencias afines a los sistemas embebidos y a las redes de comunicación.Item A qLPV Nonlinear Model Predictive Control with Moving Horizon Estimation(2021-10-15) Morato, Marcelo M.; Bernardi, Emanuel; Stojanović, VladimirThis paper presents a Model Predictive Control (MPC) algorithm for Nonlinear systems represented through quasiLinear Parameter Varying (qLPV) embeddings. Input-to-state stability is ensured through parameter-dependent terminal ingredients, computed offline via Linear Matrix Inequalities. The online operation comprises three consecutive Quadratic Programs (QPs) and, thus, is computationally efficient and able to run in real-time for a variety of applications. These QPs stand for the control optimization (MPC) and a Moving-Horizon Estimation (MHE) scheme that predicts the behaviour of the scheduling parameters along the future horizon. The method is practical and simple to implement. Its effectiveness is assessed through a benchmark example (a CSTR system).Item Full-order Output Observer Applied to a Linear Parameter Varying System with Unknown Input(IEEE, 2020-12-01) Bernardi, Emanuel; Pipino, Hugo; Adam, Eduardo J.This short work presents the outline of a set of full-order observers, applied to linear parameter varying systems with unknown input. In particular, this approach is used to constructs a strategy to detect and diagnose sensor faults on industrial processes. The observers’ design and its stability conditions are guaranteed in terms of a linear matrix inequalities framework. As a consequence, the main purpose of this paper is to provide a model-based observers’ technique, to detect, isolate and diagnose sensor faults upon non-linear systems. At last, two numerical simulations of typical chemical industrial processes are given to illustrate its implementation and performance.Item Nonlinear Fault-tolerant Model Predictive Control Strategy for Industrial Processes(IEEE, 2020-10-28) Bernardi, Emanuel; Adam, Eduardo J.This short paper presents a strategy to tolerate the income of additive faults in nonlinear chemical processes. For that, an observed-based fault detection and diagnosis scheme is implemented to generate an early and detailed fault information. Then, this valuable knowledge is used to compensate the effects induced by actuators and sensors faults throughout the use of an integrated optimization-based estimation and model predictive control scheme, which allows to track a reference even in presence of faults. A simulation based on a typical chemical industrial process, the highly non-linear continuous stirred tank reactor, is addressed to illustrate the design process and the performance of such approach.Item Fault-tolerant Model Predictive Control Strategy Applied to Industrial Processes(IEEE, 2019-09-20) Bernardi, Emanuel; Cappelletti, Carlos Alberto; Adam, Eduardo J.This paper presents a strategy to address the income of actuators faults using a model-based predictive controller scheme, which allows to track a reference even in the presence of actuator faults. The proposed fault-tolerant control system adopts a model predictive control technique to design a reconfigurable fault-tolerant controller and a reduce-order observer to achieve the fault detection and diagnosis function. Simulation results, based on two typical chemical industries processes, are given to illustrate the use and performance of such approach.