Reinaldo Martínez Palhares

Federal University of Minas Gerais | UFMG · Departamento de Engenharia Eletrônica (DELT)

This paper describes a novel passivity/dissipativity based approach for fault tolerant control (FTC) of nonlinear systems by means of fault hiding, i.e., by inserting reconfiguration blocks (RBs) between the plant and controller to mitigate the fault effects. The proposed approach is used to design a new kind of RB, called passivation block (PB), w...

This paper investigates the problem of event-triggered gain-scheduling control of nonlinear systems. The considered class of nonlinear systems is such that an equivalent local polytopic model is obtained. By following the co-design approach, it is performed the simultaneous design of the dynamic event-triggering mechanism (ETM) and the gain-schedul...

A method to design plug-and-play distributed controllers for large-scale nonlinear systems represented by interconnected Takagi-Sugeno fuzzy models with nonlinear consequent is presented in this paper. From the combination of techniques to use multiple fuzzy summations and to explore the chordal decomposition of the interconnection graph associated...

This paper introduces a novel delay-dependent condition for static output-feedback control of Takagi–Sugeno (TS) fuzzy models with time-varying delay. A distinctive feature of the proposed approach is the local asymptotic stability of the origin of the closed-loop system, unlike other works in the literature. This ensures the correct operation of t...

This paper concerns the dynamic event-triggered gain-scheduling control of discrete-time nonlinear systems represented by quasi-linear parameter-varying (quasi-LPV) models. A novel dynamic triggering mechanism is proposed to cancel out the influence of asynchronous parameters induced by the eventbased sampling. This new mechanism allows to derive c...

This paper presents a novel secure-control framework against sensor deception attacks. The vulnerability of cyber-physical systems with respect to sensor deceptive attacks makes that all sensor measurements are not reliable until the system security is assured by an attack detection module. Most of the active attack detection strategies require som...

The control of complex nonlinear systems (such as autonomous vehicles) usually requires models which might be unavailable or inaccurate. In this paper, a novel data-driven Model Predictive Control (MPC) framework is proposed based on a data-driven approach to learn Takagi–Sugeno (TS) fuzzy models for nonlinear systems. To address the data TS modeli...

This paper addresses the dynamic periodic event-triggered control for local stabilization of nonlinear networked control systems with communication delays. Based on a polytopic quasi-linear parameter-varying (quasi-LPV) model of the nonlinear plant and the Lyapunov-Krasovskii stability theory, a local stability analysis condition is established. Th...

The design of State Feedback (SF) and Static Output Feedback (SOF) controllers for nonlinear discrete-time systems subject to time-varying parameters is discussed in the context of Difference-Algebraic Representations (DAR) and parameter-dependent Lyapunov functions applied to obtain convex conditions in the form of Linear Matrix Inequalities (LMI)...

The increasing application of power converter systems based on semiconductor devices such as Insulated-Gate Bipolar Transistors (IGBTs) has motivated the investigation of strategies for their prognostics and health management. However, physicsbased degradation modelling for semiconductors is usually complex and depends on uncertain parameters, whic...

This paper addresses the problem of state and unknown inputs (UIs) estimation for nonlinear systems with arbitrary relative degree with respect to the UIs. For this purpose, a novel nonlinear unknown input observer (UIO) is proposed, which is able to decouple the UIs by using the derivatives of the output signal. The error dynamics is attained by a...

This paper introduces a novel local synthesis condition for gain-scheduling static output-feedback control of discrete-time linear parameter varying (LPV) systems under actuator saturation and state constraints. The proposed condition is formulated as a set of parameter-dependent linear matrix inequalities that are incorporated into a convex optimi...

To solve the state feedback stabilization problem for a class of T-S fuzzy systems, a new stability synthesis method is raised to further relax the conservatism existing in the analysis process. First, a series of nonlinear polynomials are used to approximate the system membership functions. And satisfied approximation results can be obtained. Then...

This article proposes a data-stream-driven event-triggered control strategy using evolving fuzzy models learned by granulation of input-output samples of non-linear systems with unknown time-varying dynamics. The evolving fuzzy model is obtained online from a data stream ensuring data coverage based on the principle of justifiable granularity and c...

This paper proposes the design of a robust Takagi-Sugeno (T–S) fuzzy reconfiguration block for systems with unmeasured premise variables. The reconfiguration block is composed of a virtual sensor and a virtual actuator whose design is obtained by means of new conditions based on Linear Matrix Inequalities (LMIs) with guaranteed H-infinity performan...

This paper presents a novel approach for designing reconfiguration blocks for fault hiding of linear systems subject to actuator faults based on the passivity/dissipativity theory. For this purpose, the concept of passivation block is used to design virtual actuators (VAs) which guarantee that the faulty plant achieves the desired passivity indices...

Although cerebral stroke is a important public worldwide health problem with more than 43 million global cases reported recently, more than 90% of metabolic risk factors are controllable. Therefore, early treatment can take advantage of a fast and low-cost diagnosis to minimize the disease’s sequels. The use Machine Learning (ML) techniques can pro...

This article deals with the problem of designing nonlinear distributed control laws for continuous-time networked nonlinear heterogeneous systems with bounded sector nonlinear interconnections. The networked system is a combination of interconnected Takagi-Sugeno (TS) fuzzy systems with nonlinear consequent subject to state and control input constr...

This paper presents a new approach to design static output feedback (SOF) controllers for constrained Takagi-Sugeno fuzzy systems with nonlinear consequents. The proposed SOF fuzzy control framework is established via the absolute stability theory with appropriate sector-bounded properties of the local state and input nonlinearities. Moreover, both...

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...

The traditional Interacting Multiple Model (IMM) filters usually consider that the Transition Probability Matrix (TPM) is known, however, when the IMM is associated with time-varying or inaccurate transition probabilities the estimation of system states may not be predicted adequately. The main methodological contribution of this paper is an approa...

This paper investigates dynamic periodic event-triggered gain-scheduling control co-design for nonlinear systems subject to disturbances. The considered class of nonlinear systems is such that an equivalent polytopic quasi-LPV model is obtained. Based on the co-design approach, gain-scheduled control law and dynamic event-triggering mechanism (ETM)...

This paper investigates the problem of stability and state-feedback control design for linear parameter-varying systems with time-varying delays. The uncertain parameters are assumed to belong to a polytope with bounded known variation rates. The new conditions are based on the Lyapunov theory and are expressed through Linear Matrix Inequalities. A...

This paper addresses the use of data-driven evolving techniques applied to fault prognostics. In such problems, accurate predictions of multiple steps ahead are essential for the Remaining Useful Life (RUL) estimation of a given asset. The fault prognostics' solutions must be able to model the typical nonlinear behavior of the degradation processes...

We present a method for incremental modeling and time-varying control of unknown nonlinear systems. The method combines elements of evolving intelligence, granular machine learning, and multi-variable control. We propose a State-Space Fuzzy-set-Based evolving Modeling (SS-FBeM) approach. The resulting fuzzy model is structurally and parametrically...

This paper is concerned with the static output-feedback secure control problem for Cyber-physical linear parameter varying systems under Denial of Service (DoS) attacks. A scenario where the number of consecutive DoS attacks is bounded is considered. A packet-based output control method for the design of gain-scheduling output-feedback controllers...

This work deals with the design of fuzzy controllers for stabilization of continuous-time nonlinear systems subject to L2 disturbances, which are represented by nonlinear Takagi-Sugeno fuzzy models, i.e., Takagi-Sugeno fuzzy models with nonlinear consequents. A nonquadratic Lyapunov function is used to derive sufficient design conditions based on l...

This paper presents new synthesis conditions for gain-scheduling static output-feedback control of discrete-time linear systems with time-varying parameters. A feature of the proposed condition, unlike most approaches in the literature, is that no structural constraints on the output matrix are imposed, that is, the proposed approach is able to han...

We present a method for incremental modeling and time-varying control of unknown nonlinear systems. The method combines elements of evolving intelligence, granular machine learning, and multi-variable control. We propose a State-Space Fuzzy-set-Based evolving Modeling (SS-FBeM) approach. The resulting fuzzy model is structurally and parametrically...

This paper addresses the use of data-driven evolving techniques applied to fault prognostics in Li-ion batteries. In such problems, accurate predictions of multiple steps ahead are essential for the Remaining Useful Life (RUL) estimation of a given asset. The fault prognostics’ solutions must be able to model the typical nonlinear behavior of the d...

This paper deals with the problem of sampled-data gain-scheduling control design for affine quasi-LPV systems. As the control implementation is based on sample-data and its update occurs only at specific sampling instants, the state-dependent scheduling functions of the controller are piecewise continuous. This characteristic causes a mismatch betw...

This paper addresses the local stabilization problem of nonlinear systems described by Difference‐Algebraic Representations (DAR). A novel set of sufficient Linear Matrix Inequalities (LMI) conditions are developed to design gain‐scheduled state feedback controllers. The proposed approach uses parameter‐dependent Lyapunov functions and new auxiliar...

Este artigo apresenta uma nova estratégia de controle preditivo robusto baseado em modelo de horizonte finito aplicado a sistemas lineares com saltos Markovianos. Considera-se ruído aditivo e incertezas nas matrizes do sistema bem como restrições são impostas aos estados e entradas de controle em termos do segundo momento. Como principal contribuiç...

This study addresses the gain-scheduled control problem for discrete-time delayed non-linear parameter-varying (NLPV) and linear parameter-varying (LPV) systems. First, by constructing the parameter-dependent Lyapunov–Krasovskii functional and employing multiple auxiliary functions, delay-dependent reciprocally convex inequality, and selecting a su...

This paper presents new stability and stabilisation conditions in the form of linear matrix inequalities for discrete-time Takagi-Sugeno fuzzy systems; they are derived considering a class of non-quadratic Lyapunov functions with multi-parametric non-monotonic terms, which significantly enhances the feasibility set of current state-of-the-art resul...

Robust stabilization of a class of uncertain nonlinear systems through a sampled‐data control law is considered in this work. Based on the forward discrete‐time Euler approximation, conditions in the form of linear matrix inequalities are provided to synthesize a discrete controller that guarantees the states to be asymptotically driven to the orig...

This paper is concerned with a new control method for path tracking of autonomous ground vehicles. We exploit the fuzzy model-based control framework to deal with the time-varying feature of the vehicle speed and the highly uncertain behaviors of the tire-road forces involved in the nonlinear vehicle dynamics. To avoid using costly vehicle sensors...

This paper proposes a novel Error Based Evolving Takagi-Sugeno Fuzzy Model (EBeTS) and a new data-driven approach to fault prognostics based on that fuzzy model. The proposed evolving Takagi-Sugeno (TS) model is useful for fault prognostics when the degradation phenomena exhibit nonlinear and time-varying dynamics because the model can represent th...

This paper addresses the problem of dissipativity-based fault tolerant control (FTC) based on fault hiding approach. In particular, a static reconfiguration block (RB) is used for reconfiguration of faulty systems. Such block performs a loop transformation by inserting series, feedback, and feedforward gains to a system including plant, sensor or a...

This paper presents a two-phase hybrid prognostics approach; in the first phase, the model's parameters are estimated using available training data in the least squares sense using the Levenberg-Marquardt algorithm. The second phase consists of using a particle filter to update the knowledge acquired so far and to predict future states of the syste...

This paper presents a new control method for path tracking of autonomous vehicles. Takagi-Sugeno fuzzy control is used to handle the time-varying vehicle speed and the uncertain tire-road forces involved in the nonlinear vehicle dynamics. To avoid using costly vehicle sensors while keeping a simple control structure, a new fuzzy static output feedb...

This paper presents new stabilization conditions for discrete‐time linear parameter‐varying systems in the form of linear matrix inequalities. The use of Lyapunov functions with dependence on delayed scheduling parameters is introduced. In addition, a lifted condition based on a Lyapunov function with dependence on delayed scheduling parameters, co...

This paper introduces a new Takagi–Sugeno (TS) reconfiguration block structure for control reconfiguration of nonlinear systems with sensor and actuator faults represented by TS models and provides conditions for the existence of such blocks that ensures the stability recovery by fault hiding. The proposed reconfiguration block structure consists o...

This paper presents a robust Fault-Tolerant Control (FTC) methodology for the design of virtual sensors and virtual actuators for discrete-time Linear Parameter Varying (LPV) systems. Conditions based on Linear Matrix Inequalities (LMIs) are proposed for the synthesis of a reconfiguration block composed of a virtual actuator and a virtual sensor, g...

This paper presents new conditions for stability analysis, static output-feedback and state-feedback control design for discrete-time linear parameter-varying systems. The proposed methodology is based on the combination of quadratic “Lyapunov-like” terms such that individually each one is not necessarily monotonically decreasing along the state tr...

This paper presents a strategy to compute a suboptimal solution to the finite-horizon linear-quadratic control problem for Markov jump linear parameter-varying systems. The system parameters depend not only on a Markov chain but also on linear parameter-varying elements that take values in convex polytopic sets. The suboptimal approach represents a...

This paper addresses the local stabilization of constrained nonlinear systems with input saturation described by Takagi-Sugeno fuzzy models with nonlinear consequents. To reduce the design conservativeness, we propose a new delayed multiple-parameterization control approach based on a nonquadratic Lyapunov function with multiple delayed fuzzy summa...

This paper addresses the problem of dissipativity-based fault tolerant control (FTC) based on fault hiding approach. In particular, a static reconfiguration block (RB) is used for reconfiguration of faulty systems. Such block performs a loop transformation by inserting series, feedback, and feedforward gains to a system including plant, sensor or a...

This paper presents a two-phase hybrid prognostics approach; in the first phase, the model’s parameters are estimated using available training data in the least squares sense using the Levenberg-Marquardt algorithm. The second phase consists of using a particle filter to update the knowledge acquired so far and to predict future states of the syste...

Artificial intelligence has played an important role in industrial community over the last decades. Benefited from the recent progress in data acquisition and high-performance computing, artificial intelligence technology has gained a great development, and plenty of industrial products have been built with intelligent abilities. Artificial intelli...

This work presents a novel static virtual actuator structure for fault tolerant control of linear systems under actuator faults conditions. Sufficient conditions for the existence of such static VAs that ensures the stability recovery by fault hiding of systems with input saturation are provided. The proposed methodology makes easier the applicatio...

This work deals with the robust eigenvalue assignment problem for periodic discrete-time systems with polytopic uncertainties. By employing a sampled state-feedback control law, a suitable time-invariant reformulation describing a period ahead dynamics associated with the uncertain periodic system is obtained. The obtained results are based on a sp...

In this work, a procedure for data abstraction and knowledge formation based on evolving granular systems is introduced. With the use of ellipsoidal information granules, an optimal granularity allocation approach for real-time data processing based on fuzzy sets is developed in order to obtain interpretable representations. From the real-time data...

Neste artigo aborda-se o problema de síntese de leis de controle descentralizadas para sistemas interconectados a tempo contínuo com não-lineares setoriais e sujeitos a restrições nos estados e na entrada de controle. Obtém-se condições suficientes que levam em conta restrições no estado e no controle descritas na forma de Desigualdades Matriciais...

This paper deals with the stabilization problem of continuous-time nonlinear descriptor systems. The methodological contribution is to propose a state transformation based on a canonical controllable form, originally proposed for linear descriptor systems, such that a feedback linearizable nonlinear descriptor model can be achieved and, consequentl...

A registration process generally uses two images at a time-the source S and target T images. The goal is to compute a spatial transformation between corresponding structures in S and T. If u is a function that represents a geometric deformation or displacement field to be performed on image S towards T, then the transformation function h at pixel p...

Dealing with uncertain data requires effective methods to properly describe their real meaning in terms of a trade-off between interpretability and generality on the process of knowledge formation based on data abstraction. This paper proposes an online granulation process based on Evolving Ellipsoidal Fuzzy Information Granules (EEFIG) and the Pri...

This paper presents a new method to design non-parallel distributed compensation (non-PDC) laws for Takagi- Sugeno fuzzy systems with local nonlinear models subject to actuator saturation. Based on specific congruence transformations, the local stabilization conditions are derived using Lyapunov stability theorem. The local design framework is esta...

This study is concerned with the problem of designing a robust model predictive control (MPC) for a class of uncertain discrete-time Markov jump linear systems. The main contribution is a set of linear matrix inequality (LMI) conditions obtained under new control policies for the unconstrained as well as the constrained MPC when uncertainties are p...

This paper is concerned with the reduction of conservatism on stabilization conditions of discrete-time Takagi-Sugeno fuzzy models via delayed nonquadratic Lyapunov functions, a fruitful approach just recently appeared in the literature which, despite its benefits, dramatically increases the number of linear matrix inequalities needed to synthesize...

This paper deals with the stabilization problem of continuous-time nonlinear descriptor systems. The methodological contribution is to propose a state transformation based on a canonical controllable form, originally proposed for linear descriptor systems, such that a feedback linearizable nonlinear descriptor model can be achieved and, consequentl...

This paper is concerned to present design conditions for state-derivative feedback control for Takagi-Sugeno fuzzy descriptor models. The main contribution is to derive a PDC control law without the requirement to rewrite the fuzzy model to fit in some specific format. We propose sufficient conditions as Linear Matrices Inequalities with or without...

MATLAB codes.

This paper describes a simulator for the three-tank system process named Sim3Tanks. This process presents a hybrid and nonlinear behavior and it is subject to different kinds of perturbations, faults, and noises. Sim3Tanks was developed in the MATLAB/Simulink environment and can be used via graphical user interface, Simulink block diagram, and comm...

This study presents an approach for fault detection and classification in a DC drive system. The fault is detected by a classical Luenberger observer. After the fault detection, the fault classification is started. The fault classification, the main contribution of this paper, is based on a representation which combines the Subctrative Clustering a...

This work is concerned with the reduction of conservatism in nonquadratic stabilization conditions of discrete-time nonlinear systems described by Takagi-Sugeno fuzzy models based on the non-PDC control law. In general, in the literature, less conservative conditions are obtained increasing the number of linear matrix inequalities (LMIs) to be solv...

This paper proposes a data-based approach for fault prognosis. The proposed method uses an information granulation technique based on fuzzy forms to represent a machine’s wear time series; then the granules are modeled with the least squares support vector machines (LSSVM) which parameters are optimized by the Nelder–Mead simplex algorithm. The app...

This study presents an approach for fault detection and classification in a DC drive system. The fault is detected by a classical Luenberger observer. After the fault detection, the fault classification is started. The fault classification, the main contribution of this paper, is based on a representation which combines the Subctrative Clustering a...

The Interacting Multiple Model (IMM) filter is a recognized method for adaptive estimation of states which is often necessary to characterize the behavior of dynamic systems with multiple mode operation. The traditional IMM filter adopts the measurement set to update the information about the active models. However, when this approach is adopted fo...

This paper proposes an improved fault prognostic approach based on a modified particle filter with a built-in differential evolution characteristic. The main methodological contribution of this study is to handle the problem of sample impoverishment faced by particle filters when only a few particles are resampled. This is done by incorporating mod...

The papers in this special issue examine the technology and applications supported by health monitoring management systems supported by complex mechatronic systems.