High efficiency sensorless fault tolerant control of permanent magnet assisted synchronous reluctance motor

In the last decades, the development trends of high efficiency and compact electric drives on the motor side focused on Permanent Magnet Synchronous Machines (PMSMs) equipped with magnets based on the rare-earth elements. The permanent magnet components, however, dramatically impact the overall bill of materials of motor construction. This aspect has become even more critical due to the price instability of the rare-earth elements. This is why the Permanent Magnet Assisted Synchronous Reluctance Motor (PMaSynRM) concept was brought to the spotlight as it gives comparable torque density and similar efficiencies as PMSM although at a lower price accredited for the use of magnets built with ferrite composites. Despite these advantages, PMaSynRM drive design is much more challenging because of nonlinear inductances resulting from deep cross saturation effects. It is also true for multi-phase PMSM motors that have gained a lot of attention as they proportionally split power by the increased number of phases. Furthermore, they offer fault-tolerant operation while one or more phases are down due to machine, inverter, or sensor fault. The number of phases further increases the overall complexity for modeling and control design. It is clear then that a combination of multi-phase with PMaSynRM concept brings potential benefits but confronts standard modeling methods and drive development techniques. This Thesis consists of detailed modeling, control design, and implementation of a five-phase PMaSynRM drive for normal healthy and open phase fault-tolerant applications. Special emphasis is put on motor modeling that comprises saturation and space harmonics together with axial asymmetry introduced by rotor skewing. Control strategies focused on high efficiency are developed and the position estimation based on the observer technique is derived. The proposed models are validated through Finite Element Analysis (FEA) and experimental campaign. The results show the effectiveness of the elaborated algorithms and methods that are viable for further industrialization in PMaSynRM drives with fault-tolerant capabilities.En últimas décadas, las tendencias de desarrollo de accionamientos eléctricos compactos y de alta eficiencia en el lado del motor se centraron en las maquinas síncronas de imanes permanentes (PMSM) equipadas con imanes basados en elementos de tierras raras. Sin embargo, los componentes de imán permanente impactan dramáticamente en el coste de construcción del motor. Este aspecto se ha vuelto aún más crítico debido a la inestabilidad de precios de los elementos de tierras raras. Esta es la razón por la que el concepto de motor de reluctancia síncrona asistido por imán permanente (PMaSynRM) se ha tomado en consideración, ya que ofrece una densidad de par comparable y eficiencias similares a las de PMSM, aunque a un precio más bajo acreditado para el uso de imanes construidos con compuestos de ferritas. A pesar de drive PMaSynRM resulta muy complejo debido a las inductancias no lineales que resultan de los efectos de saturación cruzada profunda. Esto también es cierto para los motores PMSM polifásicos que han ganado mucha atención en los últimos años, en los que se divide proporcionalmente la potencia por el mayor número de fases. Además, ofrecen operación tolerante a fallas mientras una o más fases están inactivas debido a fallas en la máquina, el inversor o el sensor. Sin embargo, el número de fases aumenta aún más la complejidad general del diseño de modelado y control. Está claro entonces que una combinación de multifase con el concepto PMaSynRM tiene beneficios potenciales, pero dificulta los métodos de modelado estándar y las técnicas de desarrollo del sistema de accionamiento. Esta tesis consiste en el modelado detallado, el diseño de control y la implementación de un drive PMaSynRM de cinco fases para aplicaciones normales en buen estado y tolerantes a fallas de fase abierta. Se pone especial énfasis en el modelado del motor que comprende la saturación y los armónicos espaciales junto con la asimetría axial introducida por la inclinación del rotor. Se desarrollan estrategias de control enfocadas a la alta eficiencia y se deriva la estimación de posición basada en la técnica del observador. Los modelos propuestos se validan mediante Análisis de Elementos Finitos (FEA) y resultados experimentales. Los resultados muestran la efectividad de los algoritmos y métodos elaborados, que resultan viables para la industrialización de unidades PMaSynRM con capacidades tolerantes a fallas.Postprint (published version

A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version

Advances in gain-scheduling and fault tolerant control techniques

This thesis presents some contributions to the state-of-the-art of the fields of gain-scheduling and fault tolerant control (FTC). In the area of gain-scheduling, the connections between the linear parameter varying (LPV) and Takagi-Sugeno (TS) paradigms are analyzed, showing that the methods for the automated generation of models by nonlinear embedding and by sector nonlinearity, developed for one class of systems, can be easily extended to deal with the other class. Then, two measures, based on the notions of overboundedness and region of attraction estimates, are proposed in order to compare different models and choose which one can be considered the best one. Later, the problem of designing state-feedback controllers for LPV systems has been considered, providing two main contributions. First, robust LPV controllers that can guarantee some desired performances when applied to uncertain LPV systems are designed, by using a double-layer polytopic description that takes into account both the variability due to the varying parameter vector and the uncertainty. Then, the idea of designing the controller in such a way that the required performances are scheduled by the varying parameters is explored, which provides an elegant way to vary online the behavior of the closed-loop system. In both cases, the problem reduces to finding a solution to a finite number of linear matrix inequalities (LMIs), which can be done efficiently using the available solvers. In the area of fault tolerant control, the thesis first shows that the aforementioned double-layer polytopic framework can be used for FTC, in such a way that different strategies (passive, active and hybrid) are obtained depending on the amount of available information. Later, an FTC strategy for LPV systems that involves a reconfigured reference model and virtual actuators is developed. It is shown that by including the saturations in the reference model equations, it is possible to design a model reference FTC system that automatically retunes the reference states whenever the system is affected by saturation nonlinearities. In this way, a graceful performance degradation in presence of actuator saturations is incorporated in an elegant way. Finally, the problem of FTC of unstable LPV systems subject to actuator saturations is considered. In this case, the design of the virtual actuator is performed in such a way that the convergence of the state trajectory to zero is assured despite the saturations and the appearance of faults. Also, it is shown that it is possible to obtain some guarantees about the tolerated delay between the fault occurrence and its isolation, and that the nominal controller can be designed so as to maximize the tolerated delay.Aquesta tesi presenta diverses contribucions a l'estat de l'art del control per planificació del guany i del control tolerant a fallades (FTC). Pel que fa al control per planificació del guany, s'analitzen les connexions entre els paradigmes dels sistemes lineals a paràmetres variants en el temps (LPV) i de Takagi-Sugeno (TS). Es demostra que els mètodes per a la generació automàtica de models mitjançant encastament no lineal i mitjançant no linealitat sectorial, desenvolupats per una classe de sistemes, es poden estendre fàcilment per fer-los servir amb l'altra classe. Es proposen dues mesures basades en les nocions de sobrefitació i d'estimació de la regió d'atracció, per tal de comparar diferents models i triar quin d'ells pot ser considerat el millor. Després, es considera el problema de dissenyar controladors per realimentació d'estat per a sistemes LPV, proporcionant dues contribucions principals. En primer lloc, fent servir una descripció amb doble capa politòpica que té en compte tant la variabilitat deguda al vector de paràmetres variants i la deguda a la incertesa, es dissenyen controladors LPV robustos que puguin garantir unes especificacions desitjades quan s'apliquen a sistemes LPV incerts. En segon lloc, s'explora la idea de dissenyar el controlador de tal manera que les especificacions requerides siguin programades pels paràmetres variants. Això proporciona una manera elegant de variar en línia el comportament del sistema en llaç tancat. En tots dos casos, el problema es redueix a trobar una solució d'un nombre finit de desigualtats matricials lineals (LMIs), que es poden resoldre fent servir algorismes numèrics disponibles i molt eficients. En l'àrea del control tolerant a fallades, primerament la tesi mostra que la descripció amb doble capa politòpica abans esmentada es pot utilitzar per fer FTC, de tal manera que, en funció de la quantitat d'informació disponible, s'obtenen diferents estratègies (passiva, activa i híbrida). Després, es desenvolupa una estratègia de FTC per a sistemes LPV que fa servir un model de referència reconfigurat combinat amb la tècnica d'actuadors virtuals. Es mostra que mitjançant la inclusió de les saturacions en les equacions del model de referència, és possible dissenyar un sistema de control tolerant a fallades que resintonitza automàticament els estats de referència cada vegada que el sistema es veu afectat per les no linealitats de la saturació en els actuadors. D'aquesta manera s'incorpora una degradació elegant de les especificacions en presència de saturacions d'actuadors. Finalment, es considera el problema de FTC per sistemes LPV inestables afectats per saturacions d'actuadors. En aquest cas, es porta a terme el disseny de l'actuador virtual de tal manera que la convergència a zero de la trajectòria d'estat està assegurada tot i les saturacions i l'aparició de fallades. A més, es mostra que és possible obtenir garanties sobre el retard tolerat entre l'aparició d'una fallada i el seu aïllament, i que el controlador nominal es pot dissenyar maximitzant el retard tolerat

Field weakening and sensorless control solutions for synchronous machines applied to electric vehicles.

184 p.La polución es uno de los mayores problemas en los países industrializados. Por ello, la electrificación del transporte por carretera está en pleno auge, favoreciendo la investigación y el desarrollo industrial. El desarrollo de sistemas de propulsión eficientes, fiables, compactos y económicos juega un papel fundamental para la introducción del vehículo eléctrico en el mercado.Las máquinas síncronas de imanes permanentes son, a día de hoy la tecnología más empleada en vehículos eléctricos e híbridos por sus características. Sin embargo, al depender del uso de tierras raras, se están investigando alternativas a este tipo de máquina, tales como las máquinas de reluctancia síncrona asistidas por imanes. Para este tipo de máquinas síncronas es necesario desarrollar estrategias de control eficientes y robustas. Las desviaciones de parámetros son comunes en estas máquinas debido a la saturación magnética y a otra serie de factores, tales como tolerancias de fabricación, dependencias en función de la temperatura de operación o envejecimiento. Las técnicas de control convencionales, especialmente las estrategias de debilitamiento de campo dependen, en general, del conocimiento previo de dichos parámetros. Si no son lo suficientemente robustos, pueden producir problemas de control en las regiones de debilitamiento de campo y debilitamiento de campo profundo. En este sentido, esta tesis presenta dos nuevas estrategias de control de debilitamiento de campo híbridas basadas en LUTs y reguladores VCT.Por otro lado, otro requisito indispensable para la industria de la automoción es la detección de faltas y la tolerancia a fallos. En este sentido, se presenta una nueva estrategia de control sensorless basada en una estructura PLL/HFI híbrida que permite al vehículo continuar operando de forma pseudo-óptima ante roturas en el sensor de posición y velocidad de la máquina eléctrica. En esta tesis, ambas propuestas se validan experimentalmente en un sistema de propulsión real para vehículo eléctrico que cuenta con una máquina de reluctancia síncrona asistidas por imanes de 51 kW

Active fault-tolerant anti-input saturation control of a cross-domain robot based on a human decision search algorithm and RBFNN

This article presents a cross-domain robot (CDR) that experiences drive efficiency degradation when operating on water surfaces, similar to drive faults. Moreover, the CDR mathematical model has uncertain parameters and non-negligible water resistance. To solve these problems, a radial basis function neural network (RBFNN)-based active fault-tolerant control (AFTC) algorithm is proposed for the robot both on land and water surfaces. The proposed algorithm consists of a fast non-singular terminal sliding mode controller (NTSMC) and an RBFNN. The RBFNN is used to estimate the impact of drive faults, water resistance, and model parameter uncertainty on the robot and the output value compensates the controller. Additionally, an anti-input saturation control algorithm is designed to prevent driver saturation. To optimize the controller parameters, a human decision search algorithm (HDSA) is proposed, which mimics the decision-making process of a crowd. Simulation results demonstrate the effectiveness of the proposed control methods

Neural network observer based LPV fault tolerant control of a flying-wing aircraft

For the problem of fault tolerant trajectory tracking control for a large Flying-Wing (FW) aircraft with Linear Parameter-Varying (LPV) model, a gain scheduled H ∞ controller is designed by dynamic output feedback. Robust synthesis of this gain scheduled H ∞ control is carried out by an affine Parameter Dependent Lyapunov Function (PDLF). The problem of trajectory tracking control for the LPV plant is transformed into solving an infinite number of linear matrix inequalities by the PDLF design, and the linear matrix inequalities are solved by convex optimization techniques. To overcome model uncertainties due to linearization and external disturbances, a radial basis function neural network disturbance observer is proposed, and to estimate actuator faults, an LPV fault estimator is designed. Furthermore, a composite controller is proposed to realize fault tolerant trajectory tracking control, which combines the LPV control with the fault estimator and disturbance observer, as well as an active-set based control allocation to avoiding actuator saturation. The approach is tested by simulation of two scenarios that show responses of the altitude, speed and heading angle to (i) unknown disturbances and (ii) actuator faults. The results show that the proposed neural network observer based LPV control has better performances for both disturbance rejecting and fault-tolerant trajectory tracking

PEMFC performance improvement through oxygen starvation prevention, modeling, and diagnosis of hydrogen leakage

Catalyst degradation results in emerging pinholes in Proton Exchange Membrane Fuel Cells (PEMFCs) and subsequently hydrogen leakage. Oxygen starvation resulting from hydrogen leaks is one of the primary life-limiting factors in PEMFCs. Voltage reduces as a result of oxygen starvation, and the cell performance deteriorates. Starved PEMFCs also work as a hydrogen pump, increasing the amount of hydrogen on the cathode side, resulting in hydrogen emissions. Therefore, it is important to delay the occurrence of oxygen starvation within the Membrane Electrode Assembly (MEA) while simultaneously be able to diagnose the hydrogen crossover through the pinholes. In this work, first, we focus on catalyst configuration as a novel method to prevent oxygen starvation and catalyst degradation. It is hypothesized that the redistribution of the platinum catalyst can increase the maximum current density and prevent oxygen starvation and catalyst degradation. Therefore, a multi-objective optimization problem is defined to maximize fuel cell efficiency and to prevent oxygen starvation in the PEMFC. Results indicate that the maximum current density rises about eight percent, while the maximum PEMFC power density increases by twelve percent. In the next step, a previously developed pseudo two-dimensional model is used to simulate fuel cell behavior in the normal and the starvation mode. This model is developed further to capture the effect of the hydrogen pumping phenomenon and to measure the amount of hydrogen in the outlet of the cathode channel. The results obtained from the model are compared with the experimental data, and validation shows that the proposed model is fast and precise. Next, Machine Learning (ML) estimators are used to first detect whether there is a hydrogen crossover in the fuel cell and second to capture the amount of hydrogen cross over. K Nearest Neighbour (KNN) and Artificial Neural Network (ANN) estimators are chosen for leakage detection and classification. Eventually, a pair of ANN classifier-regressor is chosen to first isolate leaky PEMFCs and then quantify the amount of leakage. The classifier and regressor are both trained on the datasets that are generated by the pseudo two-dimensional model. Different performance indexes are evaluated to assure that the model is not underfitting/overfitting. This ML diagnosis algorithm can be employed as an onboard diagnosis system that can be used to detect and possibly prevent cell reversal failures

Interaction Motion Control on Tri-finger Pneumatic Grasper using Variable Convergence Rate Prescribed Performance Impedance Control with Pressure-based Force Estimator

Pneumatic robot is a fluid dynamic based robot system which possesses immense uncertainties and nonlinearities over its electrical driven counterpart. Requirement for dynamic motion handling further challenged the implemented control system on both aspects of interaction and compliance control. This study especially set to counter the unstable and inadaptable proportional motions of pneumatic robot grasper towards its environment through the employment of Variable Convergence Rate Prescribed Performance Impedance Control (VPPIC) with pressure-based force estimation (PFE). Impedance control was derived for a single finger of Tri-finger Pneumatic Grasper (TPG) robot, with improvement being subsequently made to the controller’s output by appropriation of formulated finite-time prescribed performance control. Produced responses from exerted pressure of the maneuvered pneumatic piston were then recorded via derived PEE with adherence to both dynamics and geometry of the designated finger. Validation of the proposed method was proceeded on both circumstances of human hand as a blockage and ping-pong ball as methodical representation of a fragile object. Developed findings confirmed relatively uniform force sensing ability for both proposed PEE and load sensor as equipped to the robot’s fingertip with respect to the experimented thrusting and holding of a human hand. Sensing capacity of the estimator has also advanced beyond the fingertip to enclose its finger in entirety. Whereas stable interaction control at negligible oscillation has been exhibited from VPPIC against the standard impedance control towards gentle and compression-free handling of fragile objects. Overall positional tracking of the finger, thus, justified VPPIC as a robust mechanism for smooth operation amid and succeed direct object interaction, notwithstanding its transcendence beyond boundaries of the prescribed performance constraint

Integrated fault-tolerant control approach for linear time-delay systems using a dynamic event-triggered mechanism

In this study, a novel integrated fault estimation (FE) and fault-tolerant control (FTC) design approach is developed for a system with time-varying delays and additive fault based on a dynamic event-triggered communication mechanism. The traditional static event-triggered mechanism is modified by adding an internal dynamic variable to increase the inter-event interval and decrease the amount of data transmission. Then, a dynamical observer is designed to estimate both the system state and the unknown fault signal simultaneously. A fault estimation-based FTC approach is then given to remove the effects generated by unknown actuator faults, which guarantees that the faulty closed-loop systems are asymptotical stable with a disturbance attenuation level γ. By theory analysis, the Zeno phenomenon is excluded in this study. Finally, a real aircraft engine example is provided to illustrate the feasibility of the proposed integrated FE and FTC method