Programming of the merger process for small foundries

Frente a vários desafios no âmbito de competitividade mundial, a indústria de fundição de metais ferrosos busca medidas de redução de custos de seus processos internos. Neste trabalho, através do estudo de um modelo matemático relacionado à otimização de processos produtivos, busca-se auxiliar as empresas nas tomadas de decisão tático-operacional e, consequentemente, obter redução de custos de produção. Este estudo visa a minimização da função custo através da minimização das penalidades – entendidas como variáveis – envolvidas no processo, para melhor atendimento da carteira de pedidos. Estas variáveis são referentes a atrasos e antecipações de fusões de ligas, bem como preparação do forno. O modelo desenvolvido para empresas de pequeno porte é um modelo de programação linear estruturada multiperíodo inteira mista, resolvida através de programação em MatLab. Nas condições apresentadas, o modelo se mostrou satisfatório quanto a possibilidade de redução de custos em função de uma melhor programação das fusões, chegando a obter até 91% de redução de custo total na programação em um dos cenários estudados, o que não podia ser verificado anteriormente através de uma programação manual.Faced with several challenges in the context of global competitiveness, the ferrous metal smelting industry seeks measures to reduce the costs of its internal processes. In this work, through the study of a mathematical model related to the optimization of productive processes, it is sought to help the companies in tactical-operational decision making and, consequently, to obtain reduction of production costs. This study aims at minimizing the cost function by minimizing the penalties involved in the process, to better serve the order book. These penalties refer to delays and anticipations of alloy mergers as well as penalties for furnace preparation. The model developed for small businesses is a multiperiod structured linear programming mixed, solved through programming in MatLab. The model proved to be satisfactory in terms of meeting the proposed objectives, reducing the total cost of the programming (this cost refers to the predefined value for the conditions of: keeping items in stock, delaying items in manufacturing, switching between different alloys in sequential loads). According to the simulations of conditions, up to 91% of the total cost reduction was obtained, which could not be verified previously through manual programming.Fil: Faria, Larissa. Instituto de Educação Tecnológica,; BrasilFil: Rubio Scola, Ignacio Eduardo Jesus. Instituto Nacional de Tecnologia Industrial. Gerencia Operativa Regional. Subgerencia Regional Centro. Departamento de Ingenieria de Productos Industriales Region Centro.; Argentina. Universidad Nacional de Rosario; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pereira Leite Nunes, Aline. Instituto de Educação Tecnológica,; Brasi

Robust Local Stabilization of Discrete-Time Systems with Time-Varying State Delay and Saturating Actuators

The robust local stabilization of uncertain discrete-time systems with time-varying state delayed and subject to saturating actuators is investigated in this work. A convex optimization method is proposed to compute robust state feedback control law such that the uncertain closed-loop is locally asymptotically stable if the initial condition belongs to an estimate of the region of attraction for the origin. The proposed procedure allows computing estimates of the region of attraction through the intersection of ellipsoidal sets in an augmented space, reducing the conservatism of the estimates found in the literature. Also, the conditions can handle the amount of delay variation between two consecutive samples, which is new in the literature for the discrete-time case. Although the given synthesis conditions are delay dependent, the proposed control law is delay independent, yielding to easier real time implementations. A convex procedure is proposed to maximize the size of the set of safe initial conditions. Numerical examples are provided to illustrate the effectiveness of our approach and also to compare it with other conditions in the literature.Fil: Silva, J. V. V.. Centro Federal de Educação Tecnológica de Minas Gerais; BrasilFil: Silva, L. F. P.. Centro Federal de Educação Tecnológica de Minas Gerais; BrasilFil: Rubio Scola, Ignacio Eduardo Jesus. Cefetmg/ufjs;Fil: Leite, V. J. S.. Cefetmg/ufjs

Optimizing Kalman optimal observer for state affine systems by input selection

In this paper, a new algorithm to build an optimal input for state reconstruction in the class of state-affine systems is proposed, in the sense that it enhances the performances of a Kalman-like observer, as well as it guarantees the system observability. The approach relies on the fact that for a state-affine system, as soon as the input is defined as a function of time, Kalman filtering theory can be applied. In fact, it is first highlighted how an appropriate choice of the system input can improve the Kalman filtering performance in this case. It is then emphasized how this input selection amounts to a control problem, which can be solved by an appropriate optimization algorithm. Finally, the algorithm is applied to a case of fault detection in a pipeline as an illustrative example, with some simulation results showing the observer performance improvement with the proposed input.Fil: Rubio Scola, Ignacio Eduardo Jesus. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Besancon, Gildas. Université Grenoble Alpes; FranciaFil: Georges, Didier. Université Grenoble Alpes; Franci

Affordable control platform with MPC application

This paper presents a control platform developed to interface with various hardware, allowing the design and rapid implementation even of advanced controllers, both on academic and industrial systems. The code of the controllers is written in the open-source Python language, facilitating the translation of code usually written in commercial software. The proposed platform can use from Arduinos to Programmable Logic Computers (PLCs). Beyond the research and tests on industrial facilities, the simplicity of the proposed platform allows its use also for educational and training purposes. Therefore, the proposed platform can help students focus on system analysis and control theory instead of hardware interfacing issues, while using low cost hardware. Developed in a client-server scheme, the platform can run in affordable computers while taking advantage of high-level mathematical and graphical tools available in Python language, allowing rapid implementation of advanced controllers. The use of this platform is illustrated with an implementation of a model predictive control (MPC) of a level control in a laboratory-scale process. A PLC is used to take the level measures, to dispatch control signals, and also for interlocking secure tasks. The controller runs on a Raspberry Pi computer that communicates with the PLC through an ethernet link.Fil: Álan C. E SOUSA. Centro Federal de Educação Tecnológica de Minas Gerais; BrasilFil: Valter Júnior de Souza Leite. Cefetmg/ufjs;Fil: Rubio Scola, Ignacio Eduardo Jesus. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentin

Evolving granular control with high-gain observers for feedback linearizable nonlinear systems

Feedback linearization control is a simple and effective strategy whenever a faithful model of the system and its states are available. Feedback linearization may suffer from the mismatches between the model used in the design and the actual system due to e.g. uncertain parameter values, parasitic dynamics, or because of the impossibility to measure some states of the system. To aleviate such an issue, we suggest a novel robust adaptive control approach using the evolving participatory learning algorithm together with a high-gain observer. The robust evolving granular high-gain observers (RegHGO) controller is suitable to control nonlinear systems that can be input-output linearized by feedback. The approach is robust to modeling mismatches and does not require full state availability because, once the system is in a suitable canonical form, a high gain observer can be constructed to supply the state information required for control. The usefulness and efficacy of the approach is shown using a fan and plate system, and an DC motor driven angular arm-position control. The fan and plate evaluates the controller in a regulation process, and the angular arm position control evaluates reference tracking perfromance. In both cases, time-varying parameter uncertainties disturb the closed-loop control system. Both, qualitative and quantitative performance evaluation of the RegHGO controller are done. Additionally, we compare the performance of the RegHGO controller with well-established methods such as exact feedback linearization with high-gain state observer and extensions. The results show that robust evolving granular control with high-gain observers achieves better performance than its counterparts.Fil: Bento, Anderson. Universidade Federal de Minas Gerais; BrasilFil: Oliveira, Lucas. Universidade Federal de Minas Gerais; BrasilFil: Rubio Scola, Ignacio Eduardo Jesus. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: de Souza Leite, Valter Junior. Universidade Federal de Minas Gerais; BrasilFil: Gomide, Fernando. Universidade Estadual de Campinas; Brasi

A Robust Control Strategy With Perturbation Estimation for the Parrot Mambo Platform

This article addresses theoretical and practical challenges associated with a commercially available and ready-to-fly small-scale unmanned aircraft system (UAS) developed by Parrot SA: the Mambo quad rotorcraft. The dynamic model and the structure of the controller running onboard the UAS autopilot are not disclosed by its manufacturers. For this reason, a novel robust controller for discrete-time systems under time delays and input saturation is first developed for this platform. Then, three fundamental estimation and control challenges are addressed. The first challenge is the system identification of the X and Y translational dynamics of the UAS. To accomplish this goal, input-output data pairs are collected from different UAS platforms during real-time experimental flights. A group of dynamic models are identified from the data pairs through an extended least-squares algorithm. The obtained models are similar in nature but exhibit parametrical variations due to uncertainties in the fabrication process and different levels of wear and tear. Using a time-varying modeling approach, the second challenge addresses the development of a robust controller, which guarantees the stability of all the identified dynamic models. The third challenge addresses the development of a nonlinear controller enhanced with a perturbation estimation, which can reject, from the nominal model, the effects of model uncertainties and perturbations. These theoretical developments are presented in the form of two original theorems. The proposed strategies are ultimately validated in a set of real-time experiments, demonstrating their effectiveness and applicability.Fil: Rubio Scola, Ignacio Eduardo Jesus. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Reyes, Gabriel Alexis Guijarro. New Mexico State University.; Estados UnidosFil: Carrillo, Luis Rodolfo Garcia. New Mexico State University.; Estados UnidosFil: Hespanha, Joao Pedro. University of California; Estados UnidosFil: Burlion, Laurent. State University of New Jersey; Estados Unido