Normas e estabilidade para modelos estocásticos cuja variação do controle e do estado aumentam a incerteza

Orientador: João Bosco Ribeiro do ValDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Essa dissertação de mestrado gira em torno da discussão sobre controle de sistemas incertos. Modelos matemáticos utilizados como base para o design de controladores automáticos são naturalmente uma representação aproximada do sistema real, o que, em conjunto com perturbações externas e dinâmica não modelada, gera incertezas a respeito dos sistemas estudados. Na literatura de controle, este tema vêm sendo discutido frequentemente, em particular nas sub-áreas de controle estocástico e controle robusto. Dentre as técnicas desenvolvidas dentro da teoria de controle estocástico, uma proposta recente se diferencia das demais por basear-se na idéia de que variações abruptas na política de controle possam acarretar em maiores incertezas a respeito do sistema. Matematicamente, essa noção é representada pelo uso de um ruído estocástico dependente do módulo da ação de controle, e a técnica foi apelidada de VCAI - acrônimo para variação do controle aumenta a incerteza. A definição da política de controle ótima correspondente, obtida por meio do método de programação dinâmica, mostra a existência de uma região ao redor do ponto de equilíbrio para a qual a política ótima é manter a ação de controle do equilíbrio inalterada, um resultado que parece particular à abordagem VCAI, mas que pode ser relacionado a políticas de gerenciamento cautelosas em áreas como economia e biologia. O problema de controle ótimo VCAI foi anteriormente resolvido ao adotar-se um critério de custo quadrático descontado e um horizonte de otimização infinito, e nessa dissertação nós utilizamos essa solução para atacar o problema de custo médio a longo prazo. Dada certa semelhança entre a estrutura do ruído estocástico na abordavem VCAI e modelos utilizados na teoria de controle robusto, discutimos ainda possíveis relações entre a abordagem proposta e controladores robustos. Discutimos ainda algumas possíveis aplicações do modelo propostoAbstract: This work discusses a new approach to the control of uncertain systems. Uncertain systems and their representation is a recurrent theme in control theory: approximate mathematical models, unmodeled dynamics and external disturbances are all sources of uncertainties in automated systems, and the topic has been extensively studied in the control literature, particularly within the stochastic and robust control research areas. Within the stochastic framework, a recent approach, named CVIU - control variation increases uncertainty, for short -, was recently proposed. The approach differs from previous models for assuming that a control action might actually increase the uncertainty about an unknown system, a notion represented by the use of stochastic noise depending on the absolute value of the control input. Moreover, the solution of the corresponding stochastic optimal control problem shows the existence of a region around the equilibrium point in which the optimal action is to keep the equilibrium control action unchanged. The CVIU control problem was previously solved by adopting a discounted quadratic cost formulation, and in this work we extend this previous result and study the corresponding long run average control problem. We also discuss possible relations between the CVIU approach and models from robust control theory, and present some potential applications of the theory presented hereMestradoAutomaçãoMestre em Engenharia Elétrica2016/02208-6, 2017/10340-4FAPES

Controller Design for Active Vibration Damping with Inertial Actuators

In the machining industry, there is a constant need to improve productivity while maintaining required dimensional tolerances and surface quality. The self-excited vibration called chatter is one of the main factors limiting machining productivity. Chatter produces unstable cutting conditions during machining and unstable forces will damage and shorten the life of the machine tool. It can also damage the cutting tool, machining components as well as produce a poor surface finish on the workpiece. Researchers have developed various chatter suppression techniques such as changing process parameters, spindle speeds, and using passive dampers. However, many of these methods are not very robust to changing dynamics in the machine tool due to changing machine positioning, cutting setups, etc. Active vibration damping with a force actuator is a robust method of adding damping by due to its bandwidth and variable controller gains. However, the commissioning of the controller design for the actuators is not trivial and requires significant manual tuning to reach optimal productivity. The research presented in this thesis aims to simplify and automate the controller design process for force actuators. A frequency domain, sensitivity based automatic controller tuning method for force actuators has been developed. This method uses the measured actuator dynamics and open-loop system dynamics to develop a prediction tool for closed-loop responses without needing to have the complete system model (model free). By monitoring the predicted closed-loop response of various virtually designed controllers, an optimal controller is found amongst the candidate parameter values. The stability of the system and actuator is monitored during the search to ensure that the system is stable throughout its bandwidth that the actuator does not become saturated. The controller is then experimentally tested to ensure that the predicted output is the same as the real output. In cases where the system has several vibration modes that are in counter-phase and close in frequency, the model-free approach does not perform well. A more complex model-based control law has also been developed and implemented. The method automatically identifies a transfer function model for the measured open-loop system dynamics and synthesizes mixed-sensitivity optimization based controller to damp out the modes in counter-phase. In order to verify that the model-based controllers can reduce vibration modes in counter-phase, a small-scale experimental setup was developed to mimic machine tools with vibration modes in counter-phase. A flexure was designed and fabricated. A shaker from Modal Shop is used as an active damping actuator to reduce the flexure’s vibration modes. It was concluded that while the model-based controller synthesis techniques were able to damp the vibration modes in counter phase, the flexure was too simplistic and the model-free controller was able to achieve similar results

A framework for optimal actuator/sensor selection in a control system

© 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group. When dealing with large-scale systems, manual selection of a subset of components (sensors/actuators), or equivalently identification of a favourable structure for the controller, that guarantees a certain closed-loop performance, is not very feasible. This paper is dedicated to the problem of concurrent optimal selection of actuators/sensors which can equivalently be considered as the structure identification for the controller. In the context of a multi-channel H 2 dynamic output feedback controller synthesis, we formulate and analyse a framework in which we incorporate two extra terms for penalising the number of actuators and sensors into the variational formulations of controller synthesis problems in order to induce a favourable controller structure. We then develop an explicit scheme as well as an iterative process for the purpose of dealing with the multi-objective problem of controller structure and control law co-design. It is also stressed that the immediate application of the proposed approach lies within the fault accommodation stage of a fault tolerant control scheme. By two numerical examples, we demonstrate the remarkable performance of the proposed approach

Novel frameworks for the design of fault-tolerant control using optimal sliding-mode control

Copyright © 2018 John Wiley & Sons, Ltd. This paper describes 2 schemes for a fault-tolerant control using a novel optimal sliding-mode control, which can also be employed as actuator redundancy management for overactuated uncertain linear systems. By using the effectiveness level of the actuators in the performance indexes, 2 schemes for redistributing the control effort among the remaining (redundant or nonfaulty) set of actuators are constructed based on an H2-based optimal sliding-mode control. In contrast to the current sliding-mode fault-tolerant control design methods, in these new schemes, the level of control effort required to maintain sliding is penalised. The proposed optimal sliding-mode fault-tolerant control design schemes are implemented in 2 stages. In the first stage, a state feedback gain is derived using an LMI-based scheme that can assign a number of the closed-loop eigenvalues to a known value whilst satisfying performance specifications. The sliding function matrix related to the particular state feedback derived in the first stage is obtained in the second stage. The difference between the 2 schemes proposed for the sliding-mode fault-tolerant control is that the second one includes a separate control allocation module, which makes it easier to apply actuator constraints to the problem. Moreover, it will be shown that, with the second scheme, we can deal with actuator faults or even failures without controller reconfiguration. We further discuss the advantages and disadvantages of the 2 schemes in more details. The effectiveness of the proposed schemes are illustrated with numerical examples

Model Order Reduction

An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This three-volume handbook covers methods as well as applications. This third volume focuses on applications in engineering, biomedical engineering, computational physics and computer science

Commande par mode glissant de paliers magnétiques actifs économes en énergie : une approche sans modèle

Abstract : Over the past three decades, various fields have witnessed a successful application of active magnetic bearing (AMB) systems. Their favorable features include supporting high-speed rotation, low power consumption, and rotor dynamics control. Although their losses are much lower than roller bearings, these losses could limit the operation in some applications such as flywheel energy storage systems and vacuum applications. Many researchers focused their efforts on boosting magnetic bearings energy efficiency via minimizing currents supplied to electromagnetic coils either by a software solution or a hardware solution. According to a previous study, we adopt the hardware solution in this thesis. More specifically, we investigate developing an efficient and yet simple control scheme for regulating a permanent magnet-biased active magnetic bearing system. The control objective here is to suppress the rotor vibrations and reduce the corresponding control currents as possible throughout a wide operating range. Although adopting the hardware approach could achieve an energy-efficient AMB, employing an advanced control scheme could achieve a further reduction in power consumption. Many advanced control techniques have been proposed in the literature to achieve a satisfactory performance. However, the complexity of the majority of control schemes and the potential requirement of powerful platform could discourage their application in practice. The motivation behind this work is to improve the closed-loop performance without the need to do model identification and following the conventional procedure for developing a model-based controller. Here, we propose applying the hybridization concept to exploit the classical PID control and some nonlinear control tools such as first- and second-order sliding mode control, high gain observer, backstepping, and adaptive techniques to develop efficient and practical control schemes. All developed control schemes in this thesis are digitally implemented and validated on the eZdsp F2812 control board. Therefore, the applicability of the proposed model-free techniques for practical application is demonstrated. Furthermore, some of the proposed control schemes successfully achieve a good compromise between the objectives of rotor vibration attenuation and control currents minimization over a wide operating range.Résumé: Au cours des trois dernières décennies, divers domaines ont connu une application réussie des systèmes de paliers magnétiques actifs (PMA). Leurs caractéristiques favorables comprennent une capacité de rotation à grande vitesse, une faible consommation d'énergie, et le contrôle de la dynamique du rotor. Bien que leurs pertes soient beaucoup plus basses que les roulements à rouleaux, ces pertes pourraient limiter l'opération dans certaines applications telles que les systèmes de stockage d'énergie à volant d'inertie et les applications sous vide. De nombreux chercheurs ont concentré leurs efforts sur le renforcement de l'efficacité énergétique des paliers magnétiques par la minimisation des courants fournis aux bobines électromagnétiques soit par une solution logicielle, soit par une solution matérielle. Selon une étude précédente, nous adoptons la solution matérielle dans cette thèse. Plus précisément, nous étudions le développement d'un système de contrôle efficace et simple pour réguler un système de palier magnétique actif à aimant permanent polarisé. L'objectif de contrôle ici est de supprimer les vibrations du rotor et de réduire les courants de commande correspondants autant que possible tout au long d'une large plage de fonctionnement. Bien que l'adoption de l'approche matérielle pourrait atteindre un PMA économe en énergie, un système de contrôle avancé pourrait parvenir à une réduction supplémentaire de la consommation d'énergie. De nombreuses techniques de contrôle avancées ont été proposées dans la littérature pour obtenir une performance satisfaisante. Cependant, la complexité de la majorité des systèmes de contrôle et l'exigence potentielle d’une plate-forme puissante pourrait décourager leur application dans la pratique. La motivation derrière ce travail est d'améliorer les performances en boucle fermée, sans la nécessité de procéder à l'identification du modèle et en suivant la procédure classique pour développer un contrôleur basé sur un modèle. Ici, nous proposons l'application du concept d'hybridation pour exploiter le contrôle PID classique et certains outils de contrôle non linéaires tels que contrôle par mode glissement du premier et du second ordre, observateur à grand gain, backstepping et techniques adaptatives pour développer des systèmes de contrôle efficaces et pratiques. Tous les systèmes de contrôle développés dans cette thèse sont numériquement mis en oeuvre et évaluées sur la carte de contrôle eZdsp F2812. Par conséquent, l'applicabilité des techniques de modèle libre proposé pour l'application pratique est démontrée. En outre, certains des régimes de contrôle proposés ont réalisé avec succès un bon compromis entre les objectifs au rotor d’atténuation des vibrations et la minimisation des courants de commande sur une grande plage de fonctionnement

System- and Data-Driven Methods and Algorithms

An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques

Integrating coupled simulation of surface water and groundwater with Artificial Intelligence

Surface water and groundwater, integral to the hydrological cycle, engage in complex hydraulic interactions and frequent transformations. Isolating surface water and groundwater systems in individual studies often fails to capture and analyse their interrelationships, limiting the comprehensive understanding of regional water resources. Additionally, conventional physics-based coupled models encounter challenges arising from the complexities and non-linearity of interactions, impeding their accuracy in simulation results. To address this challenge, this thesis proposes a novel framework that integrates artificial intelligence and physics-based coupled models to simulate variations in surface water and groundwater, establishing a foundation for integrated water resource management. Specifically, the study develops a boundary-coupled framework to model interactions between surface water and groundwater. In this framework, a data-driven deep learning model is employed to simulate surface water flow. Additionally, physics-based analytical models are used to describe groundwater movement in riparian zones, while simplifying river behaviour to a Dirichlet boundary condition to assimilate data from the surface water model. Subsequently, the simulated values from analytical solutions serve as the source data, while groundwater observation data is employed as the target data. A transfer learning model is then be utilized to learn the features of the source data and, in conjunction with the target dataset, facilitate the prediction and regression of groundwater. Finally, the framework is applied at the watershed scale to predict and model catchment-scale surface water flow and groundwater head. In this framework, the thesis assesses the influence of various input variables on surface water prediction, explores the effect of groundwater layer heterogeneity, and validates the effectiveness of the deep transfer learning approach, particularly in catchment-scale predictions. The main conclusions are as follows: 1. The selection of model inputs greatly influences accuracy. The PCA method effectively enhances the precision of the deep RNN model, especially in scenarios with numerous input variables. It achieves this by distilling essential information, categorizing original data into several comprehensive variables. 2. The two-layer structure significantly influences groundwater flow responses to hydrological events. During recharge events with a less permeable upper layer, lateral discharge to the river is hindered, directing more groundwater downward into the more permeable lower layer. Conversely, when the upper layer is more permeable, greater lateral flow into the river occurs, with less downward flow into the less permeable lower layer. During a flood event with a less permeable upper layer, river water predominantly infiltrates the more permeable lower layer initially, then flows upward into the upper layer, creating a vertical flow. The direction of this flow reverses during the recession period. However, this phenomenon is not evident when the upper layer is more permeable than the lower layer. 3. The transfer learning method can enhance the capacity of analytical solutions for heterogeneous aquifers. By integrating analytical knowledge with the neural network, the analytical solution-transfer learning method significantly improves hydraulic head prediction accuracy. Even for very sparse training data, the analytical solution-transfer learning method still performs more satisfactorily than the traditional deep learning method. 4. The analytical solution-transfer learning method is also effective at the catchment scale. The analytical solution-transfer learning method can obtain more accuracy and robust results than traditional deep learning methods with the same training dataset