Publicações

Filtrar por tipo:

Ordenar por ano:

Adaptive gain-scheduling control for continuous-time systems with polytopic uncertainties: An LMI-based approach

Víctor C. da S. Campos, Anh-Tu Nguyen, Reinaldo Martínez Palhares
Artigos de periódico Automatica, vol. 133, November 2021.

Abstract

We develop a new adaptive gain-scheduling control scheme for continuous-time linear systems with polytopic uncertainties. The gain-scheduled control law is proposed as a convex sum of a fixed set of controller gains, exploiting the polytopic representation of the system uncertainty, which is not possible with classical robust control results in the literature. To realize this scheme, an adaptation law is proposed to adaptively provide the tuning parameter for the gain-scheduling implementation. The admissible domain of the stabilizing control feedback gains, defined by the fixed set of controller gains, can be determined offline by solving a set of linear matrix inequality constraints over a scalar line search. Using Lyapunov-based arguments, the proposed design conditions and the adaptation law ensure that all closed-loop signals are bounded. In particular, if the uncertain parameters are not time-varying, then the system states asymptotically converge to the origin. Theoretical arguments and appropriate numerical illustrations are provided to demonstrate the effectiveness of the proposed control scheme.

Takagi-Sugeno fuzzy observer design for nonlinear descriptor systems with unmeasured premise variables and unknown inputs

Anh-Tu Nguyen, Víctor C. da S. Campos, Thierry-Marie Guerra, Juntao Pan, Wenbo Xie
Artigos de periódico International Journal of Robust and Nonlinear Control (aceito para publicação)

Abstract

This article presents a new observer design framework for a class of nonlinear descriptor systems with unknown but bounded inputs. In the presence of unmeasured nonlinearities, that is, premise variables, designing nonlinear observers is known as particularly challenging. To solve this problem, we rewrite the nonlinear descriptor system in the form of a Takagi–Sugeno (TS) fuzzy model with nonlinear consequents. This model reformulation enables an effective use of the differential mean value theorem to deal with the mismatching terms involved in the estimation error dynamics. These nonlinear terms, issued from the unmeasured nonlinearities of the descriptor system, cause a major technical difficulty for TS fuzzy-model-based observer design. The descriptor form is treated through a singular redundancy representation. For observer design, we introduce into the Luenberger-like observer structure a virtual variable aiming at estimating the one-step ahead state. This variable introduction allows for free-structure decision variables involved in the observer design to further reduce the conservatism. Using Lyapunov-based arguments, the observer design is reformulated as an optimization problem under linear matrix inequalities with a single line search parameter. The estimation error bounds of both the state and the unknown input can be minimized by means of a guaranteed ℓ∞-gain performance level. The interests of the new ℓ∞ TS fuzzy observer design are clearly illustrated with two physically motivated examples.

H∞ control of event-triggered quasi-LPV systems based on an exact discretization approach - A linear matrix inequality approach

Víctor C. da S. Campos, Luciano Frezzatto, Tiago G. Oliveira, Víctor Estrada-Manzo, Márcio F. Braga
Artigos de periódico Journal of the Franklin Institute (aceito para publicação)

Abstract

This paper presents an H∞ event-triggered state-feedback controller design for continuous-time nonlinear systems via convex optimization techniques. The proposal is based on an exact discretization and its quasi-linear parameter varying representation. Thus, two sets of design conditions in terms of linear matrix inequalities by means of both parameter-dependent and quadratic Lyapunov functions are proposed. The proposed conditions also provide an estimate to system’s domain of attraction and an extra set of conditions is presented for a guaranteed minimum time between events. Well-known examples are employed to illustrate the effectiveness of the proposal.

An auxiliary system discretization approach tp Takagi-Sugeno fuzzy models

Víctor C. da S. Campos, Márcio F. Braga, Luciano Frezzatto
Artigos de periódico Fuzzy Sets and Systems (aceito para publicação)

Abstract

This paper proposes a new procedure for discretizing nonlinear systems described by Takagi-Sugeno fuzzy models. The discretization procedure consists of obtaining a linear auxiliary system that approximates the Takagi-Sugeno model over a sampling instant. By discretizing this auxiliary system, a norm bounded uncertain linear discrete-time system is found, which is capable of representing the fuzzy model. This auxiliary system, as well as the norm bounded uncertainty, is found by solving an optimization problem with Linear Matrix Inequality (LMI) constraints. To illustrate the discretization procedure, a constant state observer is synthesized based on simple LMI conditions and then applied to a real nonlinear Chua's circuit. Additionally, a state-feedback controller based on our discretization approach is synthesized and we obtain larger maximum sampling periods than other tested strategies from the literature.

Estimação de Estados de uma Câmara Termoeletricamente Controlada utilizando Projetos de Filtros H∞

Bárbara J. de Oliveira, Víctor C. S. Campos, Márcio F. Braga
Artigos de congresso XXIII Congresso Brasileiro de Automática (CBA2020)

Resumo

O objetivo deste trabalho é apresentar e comparar duas estratégias de filtros para estimação de estados aplicados em uma Câmara Termoeletricamente Controlada (CTC). A CTC é composta por cinco sensores digitais de temperatura que representam os estados do sistema. A aplicação dos métodos é executada em duas etapas. Na primeira etapa, os filtros são implementados de forma off-line no software MATLAB R2018a, a partir dos dados reais do sistema. Enquanto, na segunda etapa, os filtros são aplicados em tempo real no sistema físico. São apresentados dois teoremas para a obtenção dos parâmetros dos filtros robustos tendo como base o lema de Finsler e o bounded real lemma, utilizando a norma H∞ como critério de desempenho, uma vez que emprega-se um modelo politópico incerto para descrever a dinâmica da CTC. O problema de filtragem ótima para o sistema é resolvido por meio de Desigualdades Matriciais Lineares. Os resultados obtidos pelos dois métodos são comparados graficamente e por meio da métrica do Erro Quadrático Médio.

Novel Gaussian State Estimator based on H2 Norm and Steady-State Variance

Alesi A. de Paula, Víctor C. S. Campos, Guilherme Vianna Raffo, Bruno Otávio Soares Teixeira
Artigos de congresso XXIII Congresso Brasileiro de Automática (CBA2020)

Resumo

This paper proposes a novel state estimator for discrete-time linear systems with Gaussian noise. The proposed algorithm is a fixed-gain filter, whose observer structure is more general than Kalman one for linear time-invariant systems. Therefore, the steady-state variance of the estimation error is minimized. For white noise stochastic processes, this performance criterion is reduced to the square H2 norm of a given linear time-invariant system. Then, the proposed algorithm is called observer H2 filter (OH2F). This is the standard Wiener-Hopf or Kalman-Bucy filtering problem. As the Kalman predictor and Kalman filter are well-known solutions for such a problem, they are revisited.

Backstepping com Aproximação Adaptativa e Redução de Complexidade para um Sistema de Rotor Duplo

Fernanda R. Macedo, Leonardo A. B. Tôrres, Víctor C. S. Campos
Artigos de congresso XXIII Congresso Brasileiro de Automática (CBA2020)

Resumo

Neste artigo, é proposta uma nova abordagem de aproximação adaptativa baseada na técnica de backstepping para o controle do ângulo de arfagem (modo de operação SISO) de um sistema eletromecânico conhecido como Twin-Rotor MIMO System -- TRMS. Aproximadores universais na lei de controle são usados para estimar a parte desconhecida da dinâmica, usando modelos nebulosos Takagi-Sugeno (TS). De modo a se reduzir a complexidade no projeto do controlador por backstepping, filtros de comando são utilizados para evitar o cálculo explícito das derivadas temporais das ações de controle virtuais. Uma modificação de zona morta, desligando a lei de adaptação na região em que não se pode garantir a convergência da função de Lyapunov, é utilizada de modo a evitar o problema de deriva dos parâmetros. A eficácia do projeto do controlador é investigada por meio de simulações numéricas, enfatizando-se a redução no número de parâmetros a serem estimados.

Proposta de Sistema Aumentado para Controle Preditivo Baseado em Modelo de Inverso Trifásico com Filtro LC

Felipe R. A. Deus, Víctor C. S. Campos, Gabriel A. Fogli
Artigos de congresso XXIII Congresso Brasileiro de Automática (CBA2020)

Resumo

O uso de inversor com filtro de saída LC permite a geração de tensões senoidais com baixa distorção harmônica, adequada para sistemas de fonte de alimentação ininterrupta. No entanto, o projeto do controlador se torna mais difícil para sistemas deste tipo. Este artigo apresenta a formulação de um esquema de controle preditivo, projetado no referencial síncrono, para a tensão de um conversor de dois níveis. Para o projeto do controlador o modelo em espaço de estados é aumentado considerando que a referência e o erro integral também são estados do sistema. Assim sendo, o controlador usa o modelo para prever, em cada intervalo de amostragem, o comportamento da tensão de saída e das correntes no indutor para um horizonte de predição finito. Em seguida, uma função de custo quadrática, sujeita as restrições do problema, é otimizada gerando os sinais que são comparados com uma onda portadora originando o PWM senoidal para as chaves semicondutoras. A estratégia proposta é demonstrada em detalhes e validada com simulações para diferentes cenários de carga.

Analytical Upper Bound for the Error on the Discretization of Uncertain Linear Systems by using the Tensor Product Model Transformation

Víctor C. da S. Campos, Márcio F. Braga, Luciano Frezzatto
Artigos de periódico Acta Polytechnica Hungarica, Volume 17, Issue 6, 2020, Pages 61-74

Abstract

This work provides analytical upper bounds on the discretization error of uncertain linear systems. The Tensor Product Model Transformation is used to approximate the derived discretized system,with a reduced number of vertices. Digital state feedback controllers are then designed for the discretized system, for comparison to other available works in the current literature.

Improved Discretization Method for Uncertain Linear Systems: A Descriptor System Based Apprach

Márcio F. Braga, Víctor C. S. Campos, Luciano Frezzatto
Artigos de congresso 2019 IEEE 58th Conference on Decision and Control (CDC)

Resumo

This paper investigates an alternative approach for the discretization of uncertain time-invariant continuous-time linear systems which allows to employ higher sampling times. The approach consists in creating an artificial discrete-time descriptor system whose discretization error behaves similarly to the one obtained with double the sampling rate of the original system. The resulting discrete-time descriptor model is compounded of homogeneous polynomially parameter-dependent matrices and additive norm bounded terms related to the discretization residual error. A new linear matrix inequality condition is proposed for the synthesis of a robust digital state feedback control law that certifies the closed-loop stability of the hybrid system. Numerical examples are presented to illustrate how larger sampling times can be used in the proposed method when compared to other works in the literature.

Fuzzy Control Systems: Past, Present and Future

Anh-Tu Nguyen, Tadanari Taniguchi, Luka Eciolaza, Víctor Campos, Reinaldo Palhares, Michio Sugeno
Artigos de periódico IEEE Computational Inteligence Magazine, Volume 14, Issue 1, 2019, Pages 56-68

Abstract

More than 40 years after fuzzy logic control appeared as an effective tool to deal with complex processes, the research on fuzzy control systems has constantly evolved. Mamdani fuzzy control was originally introduced as a model-free control approach based on expert's experience and knowledge. Due to the lack of a systematic framework to study Mamdani fuzzy systems, we have witnessed growing interest in fuzzy model-based approaches with Takagi-Sugeno fuzzy systems and singleton-type fuzzy systems (also called piecewise multiaffine systems) over the past decades. This paper reviews the key features of the three above types of fuzzy systems. Through these features, we point out the historical rationale for each type of fuzzy systems and its current research mainstreams. However, the focus is put on fuzzy model-based approaches developed via Lyapunov stability theorem and linear matrix inequality (LMI) formulations. Finally, our personal viewpoint on the perspectives and challenges of the future fuzzy control research is discussed.

Simultaneous Estimation of State and Unknown Input With l∞ Guarantee on Error-Bounds for Fuzzy Descriptor Systems

Anh-Tu Nguyen, Thierry-Marie Guerra, Víctor Campos
Artigos de periódico IEEE Control Systems Letters, Volume 3, Issue 4, 2019, Pages 1020-1025

Abstract

This letter proposes a new l∞ observer design for fuzzy descriptor systems with unknown inputs. The descriptor form is treated using a singular redundancy system representation. To keep the consistency of the resulting fuzzy observer structure, we make use of a virtual variable playing the role of the one-step ahead state estimate. As a result, the observer gain can be constructed with free-structure decision variables to reduce the design conservatism. Using a membership-function-dependent Lyapunov function, the observer design is reformulated as a convex optimization problem with a single line search parameter. In particular, the error bounds of both the state and the unknown input estimations can be minimized through the guaranteed l∞ performance level. The effectiveness of our result is demonstrated with a challenging real-world application on robot manipulators.

Estimação de estados utilizando Observador Takagi-Sugeno e Filtro de Partículas - Uma aplicação para controle termoelétrico não linear

Letícia Vianna, Víctor C. S. Campos, Mateus Giesbrecht, Márcio Feliciano Braga
Artigos de congresso Anais do 14º Simpósio Brasileiro de Automação Inteligente (SBAI), 2019. Ouro Preto

Resumo

O objetivo deste trabalho é apresentar e comparar dois métodos de estimação de estado, realizados off-line, que são aplicados em uma câmara termeletricamente controlada, que consiste de uma câmara equipada com cinco sensores digitais de temperatura e um atuador de resfriamento/aquecimento composto de módulos Peltier. Os estados do sistema consistem nas temperaturas medidas pelos cinco sensores digitais de temperatura. Neste trabalho, os métodos escolhidos para estimar os estados foram o Filtro de Partículas e um Observador Fuzzy Takagi- Sugeno projetado com condições baseadas em desigualdades matriciais lineares. Uma comparação entre as duas abordagens de estimativa de estado é realizada e ilustrada pelos resultados obtidos e é apresentada no artigo.

Identificação de sistemas empregando técnica de otimização multiobjetivo para seleção de estrutura e parâmetros de modelo do tipo FBO-Volterra aplicada à modelagem de uma câmara termoelétrica

Alisson Marden Fonseca Pereira, Víctor C. S. Campos, Márcio Feliciano Braga
Artigos de congresso Anais do 14º Simpósio Brasileiro de Automação Inteligente (SBAI), 2019. Ouro Preto

Resumo

Este trabalho tem como objetivo fazer a modelagem de um sistema termoelétrico, usando as series de Volterra em conjunto com as Funções de Base Ortonormal (FBO). Neste trabalho, emprega-se otimização multiobjetivo para obter o polo ótimo da FBO e reduzir o número de parâmetros necessários para a identificação do modelo. O algoritmo utilizado é da classe dos Multiobjective Evolutionary Algorithms (MOEA) e o sistema utilizado para ilustrar a aplicação da técnica é uma câmara térmica com temperatura variada por meio de módulos Peltier.

Implementação de um método de detecção de ataques à Indústria 4.0

Paulo Ricardo de Freitas, Víctor C. S. Campos
Artigos de congresso XXIII Congresso Brasileiro de Automática (CBA), João Pessoa - PB, Setembro 2018

Resumo

As Indústrias 4.0 caracterizam uma revolução tecnológica nas infraestruturas críticas. A crescente necessidade de conectividade e acesso a informação rompe com os padrões dos modelos de sistemas supervisórios anteriores. O aumento da utilização dos sistemas ciberfísicos possibilitam grandes melhorias no controle de processos industriais. Por outro lado, a interconectividade está relacionada à redução da segurança, o que deixa as infraestruturas vulneráveis a ataques digitais. Esse trabalho apresenta um método para detecção de ataques utilizando um estimador de estados com erro quadrático mínimo.

Controle preditivo explícito aplicado à uma câmara termoeletricamente controlada

Victor de Pinho Lopes Miranda, Jean Rodrigo dos Santos, Renan Fernandes Bastos, Víctor Costa da Silva Campos
Artigos de congresso XXIII Congresso Brasileiro de Automática (CBA), João Pessoa - PB, Setembro 2018

Resumo

Este trabalho apresenta a aplicação de uma lei de controle preditiva explícita em um sistema térmico real. É apresentada uma estratégia de sistema aumentado para garantir erro em estado estacionário nulo para uma entrada em degrau, além das características construtivas do sistema considerado. Por fim, comparam-se os resultados obtidos pelo controlador em simulação e no sistema real.

Tensor Product Model Transformation Simplification of Takagi - Sugeno Control and Estimation Laws - An Application to a Thermoelectric Controlled Chamber

Alisson Marden Fonseca Pereira, Letícia Maria Sathler Viana, Natália Augusto Keles, Víctor Costa da Silva Campos
Artigos de periódico Acta Polytechnica Hungarica, Volume 15, Issue 3, 2018, Pages 13-29

Abstract

This paper presents a novel application of the Tensor Product Model Transformation: the approximation of fuzzy control and estimation laws. In order to illustrate this application, a thermoelectric controlled chamber was built using peltier coolers and an H Bridge. By using 5 digital temperature sensors, a Takagi-Sugeno discrete time fuzzy model of the system was found with system identification techniques. A control and an estimation law were designed using state of the art LMI conditions for fuzzy systems. By making use of the Tensor Product Model Transformation, these control and estimation laws were approximated/simplified and implemented on a microcontroller. The results obtained from these simplified laws show that this is a viable option and allows the use of cheap microcontrollers in cases where it would not be able to implement the control and estimation laws.

A Tensor Product Model Transformation Approach to the Discretization of Uncertain Linear Systems

Víctor Costa da Silva Campos, Letícia Maria Sathler Viana, Márcio Feliciano Braga
Artigos de periódico Acta Polytechnica Hungarica, Volume 15, Issue 3, 2018, Pages 31-43

Abstract

Most of the discretization approaches for uncertain linear systems make use of the series representation of the matrix exponential function and truncate the summation after a certain order. This usually leads to discrete-time uncertain polytopic models described by polynomial matrices with multiple indexes, which usually means that the higher the order used in the approximation, the higher the number of linear matrix inequalities (LMI) needed. This work, instead, proposes an approach based on a grid of the possible values for the matrix exponential function and an application of the tensor product model transformation technique to find a suitable polytopic model. Numerical examples are presented to illustrate the advantages and the applicability of the proposed technique.

LMI-Based Stability Analysis for Piecewise Multi-affine Systems

Anh-Tu Nguyen, Michio Sugeno, Víctor Campos, Michel Dambrine
Artigos de periódico IEEE Transactions on Fuzzy Systems, Volume 25, Issue 3, June 2017, Pages 707-174

Abstract

This paper provides a computational method to study the asymptotic stability of piecewise multi-affine (PMA) systems. Such systems stem from a class of fuzzy systems with singleton consequents and can be used to approximate any smooth nonlinear system with arbitrary accuracy. Based on the choice of piecewise Lyapunov functions, stability conditions are expressed as a feasibility test of a convex optimization with linear matrix inequality constraints. The basic idea behind these conditions is to exploit the parametric expressions of PMA systems by means of Finsler's lemma. Numerical examples are given to point out the effectiveness of the proposed method.

Improved Takagi-Sugeno fuzzy output tracking control for nonlinear networked control systems

Tiago G. Oliveira, Reinaldo M. Palhares, Víctor C. S. Campos, Pedro S. Queiroz, Eduardo N. Gonçalves
Artigos de periódico Journal of the Franklin Institute, Volume 354, Issue 16, November 2017, Pages 7280-7305

Abstract

This paper deals with the output tracking control problem for nonlinear networked control systems (NCSs) described by Takagi-Sugeno (T-S) fuzzy models. Due to the existence of inherent constraints in NCS as communication time-delays and limitation of data transmission capacity, a recent event-triggered scheme proposed in the literature is implemented to reduce the bandwidth utilization. On the other hand, the communication time-delay imposes an asynchronously operation between the proposed T-S fuzzy controller and the T-S fuzzy system handled via new LMI based conditions. Furthermore, a synchronous model operation is also proposed in this paper which allows to design a linear controller which is much simpler to implement. The main results are derived following the selection of an appropriate fuzzy Lyapunov Krasovskii Functional (LKF) together with alternative integral inequalities which lead to less conservative conditions when compared to recent results in the literature. An example illustrates the effectiveness of the proposed output tracking control for NCSs fuzzy models.

Improved Takagi-Sugeno fuzzy output tracking control for nonlinear networked control systems

Daniel Leite, Reinaldo M. Palhares, Víctor C. S. Campos, Fernando Gomide
Artigos de periódico IEEE Transactions on Fuzzy Systems, Volume 23, Issue 4, August 2015, Pages 923-938

Abstract

Unknown nonstationary processes require modeling and control design to be done in real time using streams of data collected from the process. The purpose is to stabilize the closed-loop system under changes of the operating conditions and process parameters. This paper introduces a model-based evolving granular fuzzy control approach as a step toward the development of a general framework for online modeling and control of unknown nonstationary processes with no human intervention. An incremental learning algorithm is introduced to develop and adapt the structure and parameters of the process model and controller based on information extracted from uncertain data streams. State feedback control laws and closed-loop stability are obtained from the solution of relaxed linear matrix inequalities derived from a fuzzy Lyapunov function. Bounded control inputs are also taken into account in the control system design. We explain the role of fuzzy granular data and the use of parallel distributed compensation. Fuzzy granular computation provides a way to handle data uncertainty and facilitates incorporation of domain knowledge. Although the evolving granular approach is oriented to control systems whose dynamics is complex and unknown, for expositional clarity, we consider online modeling and stabilization of the well-known Lorenz chaos as an illustrative example.

Revisiting the TP Model Transformation: Interpolation and Rule Reduction

Víctor Costa da Silva Campos, Leonardo Antônio Borges Tôrres, Reinaldo Martinez Palhares
Artigos de periódico Asian Journal of Control, Volume 17, Issue 2, March 2015, Pages 392-401

Abstract

The tensor‐product (TP) model transformation is a numerical technique that finds a convex representation, akin to a Takagi‐Sugeno (TS) fuzzy model, from a given linear parameter varying (LPV) model of a system. It samples the LPV model over a limited domain, which allows the use of the higher order singular value decomposition (HOSVD) and convex transformations that leads to the TS representation of the LPV model. In this paper, we discuss different strategies that could be used on the sampling step of the TP model transformation (which in turn lead to different membership function properties of a TS fuzzy model). Additionally, this paper discusses how the other steps could be used to reduce the number of rules of a given TS fuzzy model. In cases where nonzero singular values were discarded in the rule reduction, we also show how to obtain an uncertain model that covers the original.

On delay-dependent stability conditions for Takagi-Sugeno fuzzy systems

Fernando O. Souza, Víctor C. S. Campos, Reinaldo M. Palhares
Artigos de periódico Journal of the Franklin Institute, Volume 351, Issue 7, July 2014, Pages 3707-3718

Abstract

This paper presents new less conservative stability analysis conditions for Takagi–Sugeno fuzzy systems subject to interval time-varying delay. The methodology is based on the direct Lyapunov method allied with an appropriate Lyapunov–Krasovskii functional choice and the use of the integral inequalities, Finsler lemma, Newton–Leibniz formula manipulations and convex combination properties. Particularly, the main result differs from previous ones since the positiveness of the Lyapunov–Krasovskii functional is guaranteed by new relaxed conditions. Two examples illustrate the effectiveness of the proposed methodology.

New Stability Conditions Based on Piecewise Fuzzy Lyapunov Functions and Tensor Product Transformations

Víctor C. S. Campos, Fernando O. Souza, Leonardo A. B. Tôrres, Reinaldo M. Palhares
Artigos de periódico IEEE Transactions on Fuzzy Systems, Volume 21, Issue 4, August 2013, Pages 748-760

Abstract

Improvements of recent stability conditions for continuous-time Takagi-Sugeno (T-S) fuzzy systems are proposed. The key idea is to bring together the so-called local transformations of membership functions and new piecewise fuzzy Lyapunov functions. By relying on these special local transformations, the associated linear matrix inequalities that are used to prove the system's stability can be relaxed without increasing the number of conditions. In addition, to enhance the usefulness of the proposed methodology, one can choose between two different sets of conditions characterized by independence or dependence on known bounds of the membership functions time derivatives. A standard example is presented to illustrate that the proposed method is able to provide substantial improvements in some cases.

Adaptive complementary filtering algorithm for mobile robot localization

Armando Alves Neto, Douglas Guimarães Macharet, Víctor Costa da Silva Campos, Mario Fernando Montenegro Campos
Artigos de periódico Journal of the Brazilian Computer Society, Volume 15, Issue 3, September 2009, Pages 19-31

Abstract

As a mobile robot navigates through an indoor environment, the condition of the floor is of low (or no) relevance to its decisions. In an outdoor environment, however, terrain characteristics play a major role on the robot's motion. Without an adequate assessment of terrain conditions and irregularities, the robot will be prone to major failures, since the environment conditions may greatly vary. As such, it may assume any orientation about the three axes of its reference frame, which leads to a full six degrees of freedom configuration. The added three degrees of freedom have a major bearing on position and velocity estimation due to higher time complexity of classical techniques such as Kalman filters and particle filters. This article presents an algorithm for localization of mobile robots based on the complementary filtering technique to estimate the localization and orientation, through the fusion of data from IMU, GPS and compass. The main advantages are the low complexity of implementation and the high quality of the results for the case of navigation in outdoor environments (uneven terrain). The results obtained through this system are compared positively with those obtained using more complex and time consuming classic techniques.

Módulos didáticos para o ensino de análise e controle de sistemas dinâmicos

Natália A. Keles, Marina A. Silva, Víctor C. S. Campos, Márcio F. Braga
Artigos de congresso XIII Simpósio Brasileiro de Automação Inteligente (SBAI), Porto Alegre - RS, Outubro 2017, Páginas 1893-1898

Resumo

Este artigo apresenta a elaboração e desenvolvimento de um módulo didático experimental, dinâmico, incerto e de baixo custo, direcionado às disciplinas de modelagem e controle de sistemas dinâmicos. O modelo proposto ́e de fácil uso e com vasta aplicabilidade, podendo ser utilizado para compreender diversos conceitos, como estabilidade, linearidade, sistemas de fase não mínima e de fase mínima, abordagens nos domínios do tempo e da frequência, entre outros. Além disso, o módulo possibilita aos alunos dos cursos de Engenharia Elétrica e de Controle e Automação realizar a modelagem em espaço de estados de um sistema de baixo custo e com diferentes configurações de estados e saídas. Em níveis mais avançados, também lhes permite projetar controladores para o módulo que funcionem independentemente do comportamento escolhido para o sistema, isto é, estável ou instável.

A comparison of different upper-bound inequalities for the membership functions derivative

Víctor Costa da Silva Campos, Anh-Tu Nguyen, Reinaldo Martinez Palhares
Artigos de congresso IFAC-PapersOnLine, Volume 50, Issue 1, July 2017, Pages 3001-3006

Abstract

When using fuzzy Lyapunov functions for continuous-time Takagi-Sugeno fuzzy systems, it is common to have to deal with the membership functions’ time derivative. Several upper-bound inequalities have been proposed in the literature in order to deal with these derivatives in a Linear Matrix Inequality setting. In this article, we extend and compare some of these inequalities in the context of generating the largest estimate of the domain of attraction while synthesizing non-PDC control laws.

LMI-based adaptive control for uncertain polytopic systems

Víctor Costa da Silva Campos, Anh-Tu Nguyen, Reinaldo Martinez Palhares
Artigos de congresso 2016 IEEE 55th Conference on Decision and Control (CDC), December 2016, Pages 3222-3227

Abstract

When using fuzzy Lyapunov functions for continuous-time Takagi-Sugeno fuzzy systems, it is common to have to deal with the membership functions’ time derivative. Several upper-bound inequalities have been proposed in the literature in order to deal with these derivatives in a Linear Matrix Inequality setting. In this article, we extend and compare some of these inequalities in the context of generating the largest estimate of the domain of attraction while synthesizing non-PDC control laws.

Output Tracking Control for Networked Control Systems

Tiago G. de Oliveira, Reinaldo M. Palhares, Víctor C. S. Campos
Artigos de congresso 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2016), Volume 1, Pages 255-260

Abstract

This paper aims to compare alternative time delay relaxations for a class of nonlinear systems controlled via network and described by Takagi-Sugeno fuzzy models. In this regard, three alternatives were proposed and compared with a very recent relaxation proposed in the literature. Basically, the changes are made at two strategic points. The first point is the Lyapunov functional proposed and the second one is related to the introduction of different integral inequalities conditions. A numerical example of a network-based fuzzy tracking control systems is presented to highligth the advantages of the alternatives relaxations.

H∞ disturbance rejection for continuous-time Takagi-Sugeno models based on nested convex sums

R. Márquez, V. Campos, T. M. Guerra, R. Palhares, A. Kruszewski, M. Bernal
Artigos de congresso 23eme Rencontres Francophones sur la Logique Floue et ses Applications (LFA 2014), 2014, Cargèse.

Abstract

This paper is concerned with controller design for H-infinity disturbance rejection in continuous-time Takagi-Sugeno models. The control law belongs to a more general class than the well-known parallel distributed compensation: it is based on a recent approach which employs progressively more complex nested convex sums while preserving the use of a quadratic Lyapunov function. The results thus obtained are parameter-dependent linear matrix inequalities which allow logarithmic search of feasible solutions. Examples are provided to illustrate the aforementioned contributions.

Using information on membership function shapes in asymptotically exact triangulation approaches

Víctor C. S. Campos, Leonardo A. B. Tôrres, Reinaldo M. Palhares
Artigos de congresso 2012 IEEE 51st Conference on Decision and Control (CDC), December 2012, Pages 6205-6210

Abstract

Many Takagi-Sugeno (TS) synthesis and analysis conditions can be expressed as positive/negative definiteness conditions of fuzzy summations. In this regard, several sufficient conditions have been proposed in the literature that are asymptotically exact (i.e. necessary and sufficient as their number tends to infinity). However, since these conditions do not take the membership function shapes into account (aside from the fact that they add up to one and are greater than zero), the exactness of these conditions is only true when the membership functions can assume any possible combination of values inside the standard simplex. By making use of the membership functions shapes, in this paper we propose a triangulation (or simplicial partition) based approach that generates asymptotically exact conditions for fuzzy summations with a possibly smaller growing rate of added simplices per iteration than that observed in recently published algorithms. The set of conditions are Linear Matrix Inequalities (LMIs), for which efficient numerical routines are available.

Controle fuzzy por modelo de referência aplicado a um caça militar a jato

Víctor Costa da Silva Campos, Leonardo Antônio Borges Tôrres, Reinaldo Martinez Palhares
Artigos de congresso X Simpósio Brasileiro de Automação Inteligente (SBAI), São João del-Rei, Setembro 2011, Páginas 600-605

Resumo

Este artigo apresenta o uso de uma técnica de controle fuzzy por modelo de referência, baseada em resultados de LMIs recentes na literatura, aplicada ao modelo longitudinal de um caça militar a jato. Para poder aplicar tal técnica, este trabalho também faz uso da técnica de transformação do modelo via produto tensorial para modelar a aeronave como um sistema fuzzy. Resultados das simulações são apresentados ao final do artigo.

Localização de robôs móveis em terrenos irregulares

Douglas G. Macharet, Mario F. M. Campos, Armando A. Neto, Víctor C. da S. Campos
Artigos de congresso IX Simpósio Brasileiro de Automação Inteligente (SBAI), Brasília, 2009

Resumo

Uma premissa fundamental para que um robô móvel consiga executar suas tarefas é que ele possua conhecimento de sua localização. Portanto, este artigo aborda o cálculo da atitude de robôs móveis navegando em ambientes que possuem terrenos irregulares. A partir das informações provindas de diferentes sensores e utilizando-se o UKF para o cálculo da atitude foi possível obter bons resultados para a localização em ambientes externos.

Computer vision based monte carlo localization for autonomous vehicles

Douglas G. Macharet, Armando A. Neto, Víctor C. da S. Campos, Mario F. M. Campos
Artigos de congresso IX Simpósio Brasileiro de Automação Inteligente (SBAI), Brasília, 2009

Abstract

A robot’s knowledge of its location is a fundamental information on mobile robotics, allowing greater autonomy in decision-making problems. Thus, this paper proposes a technique for localization of Unmanned Aerial Vehicles based on Computer Vision sensing and using the Monte Carlo Localization method. Only natural landmarks already present in the environment are used, avoiding the need for manual insertion of recognizable landmarks. For the identification of landmarks the Scale Invariant Feature Transform algorithm (SIFT) is used. We present results from a model of a small autonomous aerial vehicle in a nonstructured environment.

Mobile robot localization in outdoor environments using complementary filtering

Douglas Guimarães Macharet, Armando Alves Neto, Víctor Costa da Silva Campos, Mario Fernando Montenegro Campos
Artigos de congresso COBEM 2009 - ABCM Symposium Series in Mechatronics, Volume 4, Pages 758-767

Abstract

As a mobile robot navigates through an indoor environment, the condition of the floor is of low (or no) relevance to its decisions, because it does not expect to find holes, rocks or other severe imperfections. In an outdoor environment, terrain characteristics play a major role on the robot’s motion. Without an adequate assessment of terrain conditions and irregularities, the robot will be prone to major failures, as an external environment is typically unstructured and pavement conditions may greatly vary. Since the assumption of horizontal flat support areas is no longer valid, a mobile robot pose needs to be fully described in the three dimensional space. As such, it may assume any orientation about the three axes of its reference frame, which leads to a full six degrees of freedom configuration. The added three degrees of freedom have a major bearing on position and velocity estimation due to higher time complexity of classical techniques such as Kalman filters and particle filters. Therefore, one challenge is the identification of good models for the robotic system, which includes sensors and actuators, but that are also fast to initialize and to compute. One interesting approach that fits these requirements is the complementary filtering, which allows the summation of reliable signals in different frequency bandwidths, resulting in more accurate values in the time domain. This technique has been successfully applied to estimate the three-dimensional orientation of mobile robots, with the major advantages of having low computational cost, faster dynamic responses and simple adjustment of the parameters of the algorithm. However, the technique is basically used to calculate the angles of orientation, not taking into account signals that measure the position of the robot. This article presents a localization system for mobile robots based on the complementary filtering technique to estimate the localization and orientation, through the fusion of data from IMU, GPS and compass. The main advantages are the low complexity of implementation and the high quality of the results for the case of navigation in outdoor environments (uneven terrain). The results obtained through this system are compared positively with those obtained using more complex and time consuming classic techniques.

Um arcabouço para utilização de robôs móveis na coleta eficiente de dados em redes de sensores sem fio

Marcelo Borghetti Soares, Vilar Fiuza da Camara Neto, Dimas Abreu Dutra, Víctor Costa da Silva Campos, Mario Fernando Montenegro Campos
Artigos de congresso VIII Simpósio Brasileiro de Automação Inteligente (SBAI), Florianópolis, 2007

Resumo

O objetivo deste artigo é mostrar um arcabouço desenvolvido para utilização de robôs móveis na coleta eficiente de dados em uma rede de nós sensores. Esse arcabouço é composto, basicamente, de três partes principais: i) protocolo de comunicação empregado entre o robô e os nós sensores espalhados no ambiente para transferir os dados coletados, ii) localização baseada em Transformada de Hough e Filtro de Kalman e iii) controle aplicado a um robô não holonômico utilizando um método baseado em campos de potencial para mover o robô em direção aos sensores. Simulações e experimentos são mostrados visando validar a metodologia proposta.

Hybrid mobile robot navigational strategy for efficient data collection in sparsely deployed sensor networks

Marcelo B. Soares, Mario F. M. Campos, Dimas A. Dutra, Victor C. da S. Campos, Guilherme A. S. Pereira
Artigos de congresso International Conference on Intelligent Robots and Systems (IROS), 2007, San Diego, USA, Pages 2833-2838

Abstract

We propose and implement a hybrid navigational strategy for mobile robots for data collection tasks in sparsely deployed sensor networks. Our approach presents an alternative to the routing algorithms used in wireless sensor networks which focus on the minimization of energy consumption of each node which is mainly due to data transmission. The method has two layers: i) Reactive Layer in which the data collected from a sensor node is modelled as a potential function whose gradient attracts the robot and ii) Planning Layer, that dictates the action the robot must take to collect sensor data. Results from both simulation and real world experiments showing the performance of the proposed methodology are shown, compared and discussed.