Diego Rivelino Espinoza-Trejo

An Observer-Based Diagnosis Scheme for Single and Simultaneous Open-Switch Faults in Induction Motor Drives

In this paper, the detection and isolation of open-switch faults in induction motor (IM) drives are addressed from a model-based perspective. Residuals are synthesized by using nonlinear observers followed from a directional characterization. First, it is observed that the IM model can be written in a recurrent decoupled structure by taking the stator currents and mechanical velocity as outputs. In this way, residuals can be insensitive to load torque and operating conditions, and simultaneous faults can be addressed. A pulsewidth modulation three-phase inverter is studied as power actuator for the IM. Hence, in order to isolate faults related to the six switching devices, a directional residual evaluation in the -frame is employed. Hence, three residuals are constructed to isolate the faulty switches. The ideas presented in this paper are validated experimentally in a test bench of 1-hp IM under single and simultaneous faults.

Voltage-Oriented Input–Output Linearization Controller as Maximum Power Point Tracking Technique for Photovoltaic Systems

This paper presents a robust input-output linearization controller as maximum power point tracking (MPPT) technique in a photovoltaic (PV) buck dc-dc converter with applications to dc microgrids, solar vehicles, or stand-alone systems. Due to the control structure proposed in this paper, the MPPT control system is able to track very fast irradiance changes. Meanwhile, the internal stability of the overall closed-loop system is guaranteed for different load scenarios. A sector condition is only required for the load current, which is satisfied for most of the current PV applications. In turn, this condition implies the robustness against oscillations in the dc bus voltage. Finally, the MPPT control system is validated through experimental results, where the closed-loop performance is evaluated under abrupt irradiance and set-point changes, parametric uncertainty, and dc bus load variations.

An Advisory Protocol for Rapid- and Slow-Acting Insulin Therapy Based on a Run-to-Run Methodology

BACKGROUND Emerging technology, such as an artificial pancreatic beta-cell, is not likely to be affordable to people who live in developing nations in the next 20-30 years. However, multiple-daily injection (MDI) therapy can be improved using similar advanced control algorithms designed for continuous glucose monitoring and continuous insulin infusion pumps. METHODS A simulation study of run-to-run control was developed for MDI therapy. Rapid- and slow-acting insulins were used in the protocol, which uses pre- and postprandial glucose measurements. The key information for the synthesis of the control algorithm is the subject insulin sensitivity that is calculated for two cases: (a) when the subjects glycemia and insulin dosing information is known (sensitivity response) and (b) when there is no previous information about the subjects response to the insulin protocol. In the latter case, this information needs to be estimated recursively using online data. After the sensitivity is recalculated, the run-to-run correction scheme is updated, obtaining an adaptive MDI therapy. The robustness of the advisory algorithm was evaluated by constant random parameter variations and superimposing sinusoidal oscillations on glucose-insulin model parameters to simulate intra-individual variability of the glucoregulatory system. RESULTS Optimal glycemic control has been achieved for both cases (a and b) despite variable meals (15% variation in carbohydrate content and 15-min variation in timing) and parametric variations in the glucose-insulin model. In Case (b), no profound hypoglycemic (<60 mg/dL) or hyperglycemic (>180 mg/dL) events were observed on average during all evaluations. CONCLUSIONS This work shows that the run-to-run framework for insulin updating can be successfully extended to an adaptive MDI protocol. These results motivate the practical implementation of this scheme in portable units such as personal digital assistants or smartphones.

Increasing security in an artificial pancreas: diagnosis of actuator faults

The current and incoming technology for the treatment of type 1 diabetes mellitus (T1DM) suggests that the concept of an artificial pancreas is a feasible goal [1]. Many engineering areas have key roles in the development of such system since they are involved in every part of the process (monitoring, dosing algorithms and delivering). Control engineering has presented many advances in the dosing strategies and some research groups are developing their own prototypes and plan to test them in a small-scale clinical set of trials [2]. As any other automated system, an artificial pancreas is susceptible to faults, hence the study of their possible effects and corrective solutions becomes an important topic in health care systems. In this sense, this paper addresses model-based fault diagnosis for an artificial pancreas, which consists of a continuous glucose monitor, a portable insulin pump and a glucose control strategy. Specifically, this work is focused on sub- and over-dosing scenarios caused by the malfunction of the insulin delivering device. The T1DM mathematical model developed in [3] is employed to design the fault diagnosis algorithm and its performance is evaluated in a virtual environment, where the patient inter-variability and the meal carbohydrate content variations can be simulated.

A Model-Based Strategy for Interturn Short-Circuit Fault Diagnosis in PMSM

A model-based method for interturn short-circuit fault detection and isolation in permanent magnet synchronous machines (PMSMs) is proposed in this paper. The fault detection is realized based on a residual current vector (RCV) generated by the difference between the measured stator currents and the stator currents estimated by a state observer. In order to avoid false alarms due to possible undesired perturbations, the sequence decomposition of the RCV is performed by employing different reference-frames. Thus, the proposed RCV allows the correct detection of interturn short-circuit faults and quantification of the fault severity in any faulty stator-phase winding. Moreover, since the back-EMF generated by the magnets is proportional to the rotor shaft speed, the electrical angular speed is estimated through the stator voltages measurement, without using a speed sensor. Simulation results from the three-phase PMSM dynamic model that allows considering the interturn short-circuit fault in any stator phase-windings are presented. The proposed method is validated using a three-phase PMSM prototype with modified stator windings. The robustness and the reliability of the proposal was tested for several interturn fault conditions under transient conditions including different disturbances.

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.

Actuator fault tolerant control for an artificial pancreas

With advances in continuous glucose sensors and portable insulin pumps, the concept of an artificial pancreas is now feasible. However, due to continuous operation, the actuator in this system could fail in some degree. In this sense, this paper addresses model-based fault diagnosis using a glucose-insulin model developed by Hovorka et al. (2004), and extended with an interstitial compartment to reproduce subcutaneous glucose measurements. First, a nominal feedback controller is designed following a pole-placement technique and internal model principle. In addition, a feedforward action is included to compensate fast glucose excursions due to meals. For fault diagnosis purposes, meals are considered as partially known perturbations in the system, so their information is appended into the glucose-insulin model as an exosystem with nominal initial conditions. A nonlinear PI observer is then designed using the extended glucose-insulin model to generate a dedicated residual for fault diagnosis. After fault detection and identification, the controller gain is modified in order to compensate the effect of the fault. These ideas are validated in simulation under a closed-loop configuration, and fault conditions of sub and over-dosing in the insulin pump.

Active fault tolerant scheme for variable speed drives under actuator and sensor faults

In this paper, an active fault tolerant control (AFTC) architecture is suggested for nonlinear systems, where actuator and sensor faults are addressed. The nonlinear structure is specially suited to describe some electric motors, and the ideas here developed can be applied to design more reliable variable speed drives. The AFTC scheme departs from a nominal control law previously designed. The fault diagnosis and isolation (FDI) structure is carried out in two stages. First, a fault condition is detected, and next a fault isolation and identification is performed. Hence, according to the FDI structure, the control algorithm can follow four scenarios: (i) operate in open-loop, (ii) replace missing/erroneous sensors by virtual ones, (iii) adjust the references for a faulty actuator, and (iv) reconfigure the control law. The application to a DC motor in parallel configuration is illustrated, and the evaluation is carried experimentally in a 2 HP test-bed.

Robust FDI Scheme in Power Actuators for Induction Motor

Abstract In this paper a robust model-based FDI scheme for actuator faults in induction motor (IM) drives is presented. A voltage source inverter is studied as power actuator for the induction motor. Residuals are synthesized by applying a differential geometry approach. In order to obtain a robust observer-based FDI scheme a bank of PI-observers is used, which according to the fault time profile allows to identify the faults. Departing from the results in Espinoza et al. [2008], the diagnosability and decoupling conditions for actuator faults are satisfied in the IM model. In this way, residuals are decoupled from the load torque and operating conditions, and simultaneous faults can be addressed. Hence, in order to isolate faults related to switching devices, it is suggested a directional residual evaluation. Hence 3 residuals are constructed to isolate the faulty switches. The ideas presented in the paper are verified experimentally in a test-bench of 1 HP induction motor under single and simultaneous faults.

Model-based Fault Detection and Isolation in a MPPT BOOST converter for photovoltaic systems

In this paper an observer-based fault diagnosis system is proposed for a Maximum Power Point Tracker (MPPT) BOOST converter in photovoltaic (PV) systems. Open- and Short-circuit switch faults can be diagnosed by the Fault Detection and Isolation (FDI) algorithm suggested in this study. A decoupled subsystem from the load and PV currents is obtained for residual generation, which is guaranteed at the price of 2 measurements, namely, PV current and load voltage. Hence, the FDI system is insensitive to load changes and sudden irradiance drops. According to observability properties of this subsystem, the fault detection time can be assigned arbitrarily. In addition, operation of the FDI system in open- and closed-loop has been evaluated through a prototype of 350 W. Only the most common measurements employed into the Maximum Power Point searching techniques are required in the proposed FDI system. Finally, as an important result, the proposed FDI system can be applied over the most common PV applications due to the residual generation system is decoupled from load conditions.