Elvia Palacios

Data fusion for multiple mechanical fault diagnosis in induction motors at variable operating conditions

In this paper, data fusion based on multi-class support vector machines (SVM) is presented to detect and isolate three mechanical faults in induction motors. First, we construct the feature vector by using signatures created from frequency-domain characteristics. These signatures are obtained from mechanical vibration and line currents measurements. Then, the feature vector is used to feed SVMs to classify different motor conditions (normal, misalignment, unbalanced and bearing fault). Different experiments using a three phase induction motor were performed under variable operational conditions (motor speeds and load torque scenarios) in order to acquire training and validation data. The identified optimal parameters of the SVMs are reported. The SVMs are studied with two types of kernel functions, the radial basis and the polynomial functions. Data acquisition, feature extraction and SVMs computation were implemented by using LabView programming language. The experimental results show the effectiveness of the proposed approach in diagnosing the studied mechanical faults at different speeds and load conditions. In these experimental tests, the worst-case accuracy of the proposed method was 97.1%.

Quantitative and Redundant Multi-variable Fault Diagnosis in Induction Motors

Abstract In this work, a quantitative multi-variable fault diagnosis algorithm is presented for three-phase induction motors based entirely on electrical measurements—supply voltages and line currents. Redundancy is added by employing two residual functions, which are constructed by the total supply power and Parks vector magnitude with the aim of visualizing the fault components in frequency sub-bands. A detailed analysis of the resulting frequency content in these residuals is carried out by assuming that the faults are affecting the line currents by a magnitude modulation effect in steady state. In addition, a complete analysis of the residuals robustness against stator asymmetries due to the manufacturing process of the induction motor is described. Next, using a multi-resolution wavelet decomposition of the residuals, the energy of these sub-bands is accurately computed and compared with a baseline condition to detect quantitatively a fault scenario. In this way, variable speed and load torque operating conditions could be monitored for the induction motor. Finally, simulation and experimental evaluations are carried out for an asymmetric rotor fault to show the applicability of the diagnosis scheme.

Interconnection and Damping Passivity-Based Control applied to a single-phase voltage source inverter

In this paper, a control expression for a single-phase inverter following the Interconnection and Damping Assignment Passivity Based Control (IDA-PBC) methodology is developed; this is achieved in a stationary framework using the single-phase d-q transformation. The proposed controller is designed exploiting the passivity properties of the averaged model of the circuit, while its evaluation is carried out in an experimental setting to examine its robustness properties with respect to load uncertainty and dynamic transient response. Both linear and nonlinear loads are considered in the experiments. The proposed controller is compared with another passive control expression obtained with the standard PBC approach under the same experimental operation.

Fault Accommodation Strategy for LTI Systems based on GIMC Structure: Additive Faults.

In this contribution a fault accommodation strategy is suggested for LTI systems. The faults and perturbations are considered as additive signals that modify the output measurement. The accommodation scheme is based on the generalized internal model control architecture recently proposed [17] for fault tolerant control. In order to improve the performance after a fault, the compensation is considered in two steps according with a fault detection and isolation algorithm. After a fault scenario is detected a general fault compensator is activated. Finally, once the fault is isolated a specific compensator is introduced. In this setup, multiple faults could be simultaneously treated since their effect is assumed to be additive.

Una Alternativa para Regular los Buses de CC en un Filtro Activo Paralelo con Inversor de 5 Niveles en Cascada

An alternative to regulate the DC bus capacitors voltage from shunt active power filter is presented in this paper. The power stage of shunt active power filter is a cascaded five-level inverter. This multilevel converter has two H power cells in series connection and each power cell has a capacitive link. With only one voltage measurement from one power cell, the control law proposed has to regulate the two DC link voltages. To accomplish the DC bus regulation and the current output tracking, PIs controllers are used on each control loop. In order to demonstrate and validate the effectiveness proposed in this work several mathematical analyses, simulations and experimental results are shown

A passivity-based approach for HIV-1 treatment scheduling

This paper explores the theoretical possibilities for applying a globally defined passivity-based control for a dynamical model of the HIV-1. This control law will define a treatment scheduling scheme for the anti-retroviral therapy. The controller structure is divided into two parts, the purpose of the first is to render passive the HIV-1 model while the second exploits the properties associated to passive systems to achieve the stability requirements. The presented control scheme guarantees that the objectives established by the highly active anti-retroviral therapy (HAART) are fulfilled. From a systems theoretic perspective, the presented result states a first attempt in solving the problem using passivity arguments since the controller exhibits a state-feedback structure and assumes knowledge of the parameters model. Nevertheless, considering the remarkable performances achieved in numerical simulations, the importance of the contribution lies in the establishment of solid bases for continuing the research under the considered approach.

Non-linear Observer for the Estimation of CD8 Count Under HIV-1 Infection

The problem of information (state) reconstruction from available measurements under HIV-1 infection will be addressed. First, the HIV-1 nonlinear model is recalled, and its dynamic properties are detailed. Next, a reduced nonlinear observer is constructed based on a linear coordinates transformation. The transformed system has now nonlinear terms that depend on the actual measurements. Simulation results are illustrated that show the convergence of the estimation despite initial conditions and initialization time. Moreover, the estimation robustness was also investigated through a random evaluation.

Path following through reference points for a car-like mobile robot

In this paper a solution for the problem of following paths defined by reference points for a car-like mobile robot is addressed. The proposed control law is a linearizing state feedback for the rotational kinematics of the mobile robot. The orientation error is defined in such a way that it remains in the interval greater than or equal minus one hundred eighty degrees and smaller than one hundred eighty degrees in order to avoid the unwinding phenomena. The efficiency of the proposed control strategy is verified through numerical simulations.

A Takagi-Sugeno Fuzzy Model of a Concentric-Tubes Heat Exchanger

In the present study we develop a Takagi-Sugeno (TS) fuzzy model of a concentric-tubes heat exchanger. The model is structured on fuzzy logic reasoning with sets of linguistic rules describing the dynamic characteristics of the thermal system. Using a system identification technique based on adaptive neural networks, the fuzzy rules are derived from experimental data of the flow rates and fluid temperatures in the heat exchanger. The accuracy of the resulting model is assessed by predicting the time-dependent response of the outlet hot- and cold-water temperatures under a step-change in the mass flow rate of the cold fluid. The results indicate that the TS fuzzy model is able to estimate the behavior of the physical system with very little predicting errors. Upon the basis of this empirical model, in the near future we will report on a control strategy for the regulation and tracking of the outlet temperatures in the heat exchanger.Copyright

A robust output-feedback treatment scheduling for HIV-1

Abstract In this paper an anti–retroviral supply treatment scheduling for a dynamical model of the HIV-1 is proposed. This therapy design problem is approached from an equilibrium point stabilization perspective by viewing the drug treatment as a control law. The main feature of the proposed controller is threefold, namely: It exploits the natural properties, for stabilization purposes, of the HIV-1 model leading to a quite simple structure. It is an output–feedback scheme in the sense that for achieving the desired stability properties it is not required neither feedback nor estimation of the unmeasurable state. It is robust against both parametric and structural uncertainties. The usefulness of the presented control scheme is illustrated via numerical simulations.