A Fuzzy-Kalman filtering strategy for state estimation

This thesis considers the combination of Fuzzy logic and Kalman Filtering that have traditionally been considered to be radically different. The former is considered heuristic and the latter statistical. In this thesis a philosophical justification for their combination is presented. Kalman Filtering is revised to enable the incorporation of fuzzy logic in its formulation. This formulation is subsequently referred to as the Revised-Kalman Filter. Heuristic membership functions are then used in the Revised-Kalman Filter to substitute for the system and measurement covariance matrices to form a fuzzy rendition of the Kalman Filter. The Fuzzy Kalman Filter formulation is further revised according to a concept referred to as the “Parallel Distributed Compensation” to allow for further heuristic adjustment of the corrective gain. This formulation is referred to as the Parallel Distributed Compensated-Fuzzy Kalman Filter. Simulated implementations of the above filters reveal that a tuned Kalman Filter provides the best performance. However, if conditions change, the Kalman filter’s performance degrades and a better performance is obtained from the two versions of the Fuzzy Kalman Filters

Advanced Mathematics and Computational Applications in Control Systems Engineering

Control system engineering is a multidisciplinary discipline that applies automatic control theory to design systems with desired behaviors in control environments. Automatic control theory has played a vital role in the advancement of engineering and science. It has become an essential and integral part of modern industrial and manufacturing processes. Today, the requirements for control precision have increased, and real systems have become more complex. In control engineering and all other engineering disciplines, the impact of advanced mathematical and computational methods is rapidly increasing. Advanced mathematical methods are needed because real-world control systems need to comply with several conditions related to product quality and safety constraints that have to be taken into account in the problem formulation. Conversely, the increment in mathematical complexity has an impact on the computational aspects related to numerical simulation and practical implementation of the algorithms, where a balance must also be maintained between implementation costs and the performance of the control system. This book is a comprehensive set of articles reflecting recent advances in developing and applying advanced mathematics and computational applications in control system engineering

DEVELOPMENT OF NONLINEAR CONTROL SCHEMES FOR ELECTRIC POWER SYSTEM STABILIZATION

Power system stabilizers and other controllers are employed to damp oscillations in power systems, thereby guaranteeing satisfactory dynamic performance following major network disturbances. However, the parameters of these controllers are often tuned based on the power system linearized model which generally is a function of the system operating point or state. These controllers suffer from poor performance when the system state changes. The aim of the research work reported in this Thesis is to develop nonlinear synchronous generator excitation control schemes with control laws for providing improved transient stability when the system is subjected to wide parameter variations due to network disturbances. The study employed fourth-and third-order models of a single-machine-connected-to-an-infinite-bus system to design two nonlinear sliding mode control laws (CLs) and one finite-time homogeneous control law (CL), which were constructed based on a well-chosen output function of the system. The parameters of the control laws were properly selected and/or tuned to give desirable dynamic characteristics using well established linear control methods. Justifications for the selection of the fourth-and third-order synchronous generator models to design the aforesaid controllers are presented. Dynamic simulations of the system under the action of the control laws were carried out using MATLAB®/SIMULINK. In order to test the performance of the laws, several simulation studies were performed when the voltage magnitude (V) of the infinite bus and the transmission line reactance (XE) of the system changed due to an applied three-phase symmetrical fault at the infinite bus and generator terminals. Results obtained from these studies show that the dynamic characteristics of the system being investigated have improved significantly, in terms of the rotor angle and rotor speed first peak, damping of low-frequency mechanical oscillations in rotor angle following fault clearance, and settling times of key stability indicators (rotor angle and rotor speed). For instance, for application of each of 5-cycle, 7-cycle, and 9-cycle fault at the infinite bus, the system rotor angle settled to its stable steady values within 1 - 2.2s with minimal control effort that varied between -5pu and 5pu before settling at the prefault value of 1.5603pu in 4.32s (CL1), in 1.92s (CL2), and in 3.32s (CL3). Whereas, CL3, which is a contribution to the improvement of the existing general higher-order sliding mode control structure for synchronous excitation control, was able to make the system withstand greater fault duration than CL1, CL2, which has a new positive parameter (called the dilation gain) incorporated into it, furnished the system with the greatest fault-retaining capability. In practice, the implementation of the three control laws can be carried out in a static exciter configuration with a very fast response

Nonlinear optimal control and its application to a two-wheeled robot

This research studies two advanced nonlinear optimal control techniques, i.e., the freezing control and the iteration scheme, and their associated applications, such as a single inverted pendulum (IP) on a cart system and a two-wheeled robot (TWR) system. These techniques are applied to stabilise the highly unstable nonlinear systems in the vertical upright position when facing different initial pitch angles. Different linear optimal controllers (linear quadratic regulator and linear quadratic Gaussian) and nonlinear optimal controllers are designed and applied to the models for concurrent control of all state variables. The controlled systems are tested in simulation and the best performing control design is eventually implemented on a robot prototype built with an educational kit – the LEGO EV3, after practical factors such as motor voltage limitation, gyro sensor drift and model uncertainties have been considered, analysed and dealt with. Simulations and experiments on the TWR robot prototype demonstrate the superiority of the nonlinear freezing optimal control technique, showing larger operation ranges of the robot pitch angle and better response performances (i.e., shorter rise time, less overshoot and reduced settling time) than the linear optimal control methods. In particular, a novel mixing method to create a new nonlinear model (Model AB) from two different models on the same physical prototype with an increased controllable region of the TWR system is introduced, for the first time, for the calculations of optimal feedback gains for the system. Significantly, the utilisation of this mixed model, combined with the nonlinear freezing controller, achieves true global control of the TWR, even from an initial pitch angle of 90° (i.e., the horizontal position), when a motor with a saturated voltage of 48V and nominal torque of 298 mNm is adopted in simulation tests. This is wider than the angle achievable from the primary model (Model A) and any other single feedback control method on TWR reported in the literature. Robustness tests when introducing model uncertainties by adding mass and height on the TWR also illustrate excellent control performances from the nonlinear optimal control in both simulations and hardware implementations

Fault detection in trajectory tracking of wheeled mobile robots

The problem of fault detection in nonlinear systems with application to trajectory tracking of nonholonomic wheeled mobile robots (WMRs) is addressed in this thesis. For the considered application, a nonholonomic wheeled mobile robot--having nonlinear kinematics--is required to follow a predefined smooth trajectory (in the absence of obstacles in the environment). This goal has to be accomplished despite the presence of faults that may occur in two of its major subsystems which are vital for navigation, namely the driving subsystem and the steering subsystem. These faults are assumed to be caused by actuator faults in either of these two subsystems. The problem addressed here is to detect the presence of faults and to determine the subsystem which has been affected by these faults. Toward this end, two different fault detection approaches are proposed and investigated. The first approach is based on system identification through Extended Kalman Filters (EKF) whereas the second one is based on system identification via artificial neural networks. In the former approach a novel method for residual generation is proposed while in the latter by utilizing the neural network's formal stability properties the desired performance can be guaranteed. Each of the proposed fault detection methods is studied subject to two different kinds of controllers (namely a dynamic linear controller and a dynamic feedback linearization based controller) and two different types of actuator faults (namely the Loss-of-Effectiveness fault and Locked-In-Place fault). In this way, the impact of the controller strategy on the fault detection approach is also investigated and evaluated

Non-silicon Microfabricated Nanostructured Chemical Sensors For Electric Nose Application

A systematic investigation has been performed for Electric Nose , a system that can identify gas samples and detect their concentrations by combining sensor array and data processing technologies. Non-silicon based microfabricatition has been developed for micro-electro-mechanical-system (MEMS) based gas sensors. Novel sensors have been designed, fabricated and tested. Nanocrystalline semiconductor metal oxide (SMO) materials include SnO2, WO3 and In2O3 have been studied for gas sensing applications. Different doping material such as copper, silver, platinum and indium are studied in order to achieve better selectivity for different targeting toxic gases including hydrogen, carbon monoxide, hydrogen sulfide etc. Fundamental issues like sensitivity, selectivity, stability, temperature influence, humidity influence, thermal characterization, drifting problem etc. of SMO gas sensors have been intensively investigated. A novel approach to improve temperature stability of SMO (including tin oxide) gas sensors by applying a temperature feedback control circuit has been developed. The feedback temperature controller that is compatible with MEMS sensor fabrication has been invented and applied to gas sensor array system. Significant improvement of stability has been achieved compared to SMO gas sensors without temperature compensation under the same ambient conditions. Single walled carbon nanotube (SWNT) has been studied to improve SnO2 gas sensing property in terms of sensitivity, response time and recovery time. Three times of better sensitivity has been achieved experimentally. The feasibility of using TSK Fuzzy neural network algorithm for Electric Nose has been exploited during the research. A training process of using TSK Fuzzy neural network with input/output pairs from individual gas sensor cell has been developed. This will make electric nose smart enough to measure gas concentrations in a gas mixture. The model has been proven valid by gas experimental results conducted

Systemidentifikation und Reglersynthese für örtlich verteilte Prozesse durch adaptive Takagi-Sugeno Fuzzy Systeme am Beispiel des Raumklimaverhaltens

Eine wichtige Aufgabe der „präventiven Konservierung“ ist die Stabilisierung des Raumklimas, insbesondere der relativen Luftfeuchte. Die betreffenden Raumklimagrößen unterliegen dabei einer signifikanten örtlichen Verteilung, die im Rahmen der Raumklimaregelung berücksichtigt werden muss. Durch Nutzung von Sensornetzwerken und Verwendung mobiler Aktuatoren kann das Raumklima als örtlich verteilter Prozess betrachtet werden. Bei den resultierenden Modellgleichungen handelt es sich um nichtlineare partielle Differentialgleichungssysteme, welche im Allgemeinen numerisch iterativ gelöst werden müssen, was mit erheblichem Rechen- und Zeitaufwand verbunden ist. In der vorliegenden Arbeit wird daher ein zweistufiger Ansatz zur Modellreduktion für örtlich verteilte nichtlineare Prozesse vorgestellt. Zunächst wird mit Hilfe von Finiten-Differenzen Methoden eine örtliche Diskretisierung durchgeführt. Anschließend wird die Theorie der Takagi-Sugeno Fuzzy Systeme auf die nichtlinearen Gleichungssysteme übertragen. Das Verfahren wird zunächst theoretisch eingeführt und im Anschluss auf das Raumklimaverhalten übertragen.One of the most important and challenging goals of preventive conservation is the protecting of cultural assets from unfavorable climate conditions during storage and exhibition. The longevity of these assets is best ensured by keeping the relative humidity within a suitable range. Modern approaches for modelling and controlling view indoor air conditions as lumped parameter systems, an assumption which has led to unsatisfying results for preventive conservation purposes. A long run of indoor climate measurements thus carried out for the current research, yielded the insight that some important physical values, especially relative humidity, are significantly influenced by spatial distribution. This insight led to the focus in this thesis on modelling and control of nonlinear distributed parameter systems. Since the calculation of spatial distributed systems is imperative for the preservation of cultural assets, it is advantageous to be able to accomplish these calculations quickly. A common approach to such calculations has been to first formulate a general flow problem and then solve it with Computation Fluid Dynamics (CFD). However, because a flow problem is described by a set of nonlinear partial differential equations, only numerical solutions can usually be found, e.g. in CFD. This is desirable in the sense that these numerical solutions are very detailed, but they are not widely used for controller synthesis because the process of arriving at them is very time consuming and complicated.For this reason, a reduced approach capable of simplifying controller design without neglecting the spatial distribution is developed in this thesis. First of all, a spatial discretization is performed via finite-difference methods. The set of partial differential equations is thus reduced to a set of ordinary differential equations. Subsequently, the derived nonlinear equations are approximated by a Takagi-Sugeno Fuzzy approach. In contrast to lumped parameter systems, there is a need for model reduction in distributed parameter systems, where the number of subsystems would otherwise increase exponentially. As shown in the following, this model reduction is accomplished through introducing the Hadamard-Product. Methods for controller design are then given, as well as system identification approaches. For the examined case of controlling indoor air conditions, system identification methods proved mandatory, since there is no way of deriving model parameters in real world applications. After these theoretical approaches are elucidated, they are applied to the indoor air conditions and compared to the afore-mentioned currently used methods. It is thus demonstrated that spatial distributed systems are far more beneficial for preventive conservation and can be simplified while improving accuracy for the purpose of controlling indoor climate conditions and related applications.Die vorliegende Arbeit befasst sich mit der Modellbildung und Regelung nichtlinearer örtlich verteilter Prozesse. Als beispielhafte Anwendung wird die Regelung des Raumklimas im Rahmen der Präventiven Konservierung betrachtet. Die Präventive Konservierung umfasst dabei vorbeugende Maßnahmen zum Schutz von Kulturgütern. Eine wichtige Aufgabe ist hierbei die Stabilisierung des Raumklimas, insbesondere der relativen Luftfeuchtigkeit, in einem stationär akzeptablen Bereich. Zudem sind die kurzfristigen Schwankungen der Klimagrößen auf ein Minimum zu reduzieren. Die Betrachtung des Raumklimaverhaltens als konzentriert-parametrisches System reicht dabei zur Erfüllung der Anforderungen der Präventiven Konservierung nicht aus. Aus diesem Grund wird in dieser Arbeit ein Ansatz zur örtlich verteilten Betrachtung der Klimagrößen entwickelt, der sowohl die Modellbildung als auch die Regelung umfasst. Das Verhalten des Raumklimas bildet dabei ein strömungstechnisches Problem der Fluiddynamik. Dieses lässt sich durch ein System nichtlinearer partieller Differentialgleichungen beschreiben. Die Lösung solcher Strömungsprobleme erfolgt üblicherweise über numerische Methoden, wie den bekannten CFD-Simulationen. Nachteilig wirkt sich dabei der hohe rechentechnische Aufwand aus, was CFD-Simulationen zur Synthese von Reglern ungeeignet macht. Durch örtliche Diskretisierung mit Hilfe von Finite-Differenzen Methoden werden die partiellen Differentialgleichungen durch ördinäre Differentialgleichungen approximiert. Anschließend wird das hierdurch entstandene nichtlineare dynamische Gleichungssystem durch Methoden der Takagi-Sugeno Fuzzy Theorie beschrieben. Hierbei tritt für den Fall örtlich verteilter Systeme die Notwendigkeit der Modellreduktion auf, welche durch die Einführung des sogenannten Hadamard-Produktes gelöst wird. In dieser Arbeit werden sowohl Methoden zur Reglersynthese als auch Methoden zur datengetriebenen Modellbildung behandelt. Die datengetriebene Modellbildung ist dabei für eine Anwendung des Ansatzes im Rahmen einer Raumklimaregelung notwendig, da ein analytischer Ansatz für diesen Fall nicht praktikabel umsetzbar ist. Die entwickelten Ansätze werden zunächst theoretisch hergeleitet und an einem eindimensionalen Fallbeispiel verifiziert. Anschließend werden sie auf das Raumklimaverhalten übertragen. Es werden Ergebnisse zur datengetriebenen Modellbildung sowie zur Regelung des Raumklimas anhand von Untersuchungen eines kulturell genutzten Raumes gezeigt und mit gängigen Methoden zur Regelung des Raumklimas verglichen. Die Ergebnisse zeigen dabei, dass die örtlich verteilte Betrachtung deutliche Vorteile bringt

Design and Development of Advanced Control strategies for Power Quality Enhancement at Distribution Level

In recent times, power quality (PQ) issues such as current and voltage harmonics, voltage sag/swell, voltage unbalances have become the important causes for malfunctioning and degradation of the quality of power. Poor power quality severely affects on electrical equipment and finally results in significant economic losses. Hence, installation of the custom power devices to improve the power quality issues becomes an important consideration. Therefore, this thesis considers the enhancement of power quality for power distribution systems by utilizing unified power quality conditioner (UPQC). An UPQC can adequately handle several power quality problems such as load current harmonics, supply voltage distortions, voltage sags/swells and voltage unbalance. Therefore, the main focus behind this thesis is to develop advanced control strategies that improve the compensation capability of the UPQC so that power quality issues of distribution network are efficiently improved. Firstly, the current harmonics are considered and are compensated by using the shunt active power filter (SAPF). Therefore, two control strategies such as Hysteresis current control (HCC) and Sliding Mode Control (SMC) based control algorithms are implemented to compensate current harmonics in the power distribution network. Furthermore, both the current control techniques utilize the Coulon oscillator based PLL (CO-PLL) for extraction of positive sequence signal from the supply voltage and generate the three-phase reference currents by employing PI-controller based DC-link voltage regulation. The performances of both current control techniques for SAPF are evaluated under different source voltage conditions such as balanced, unbalanced and non-sinusoidal. The SAPF effectively compensates currents harmonic, however, it is unable to compensate voltage related problems. To overcome this drawback, this thesis considers the UPQC, which comprises with shunt APF and series APF, can be utilized to compensate both current and voltage related problems. The research on UPQC is carried out progressively by considering different advanced control strategies. Each progress in the research enhances the compensation capabilities of the previous UPQC control system. The simulation and realtime Opal-RT studies are carried out to verify the operating performance of each design concept of UPQC. At first, operating principle and design of UPQC is presented and then a novel control algorithm is introduced with the aid of nonlinear DC-link voltage controller such as nonlinear variable gain fuzzy (NVGF) controller and nonlinear sliding mode controller (NLSMC) with modified synchronous reference frame (SRF) control strategy for improvement of both current and voltage compensation performance of the UPQC. However, existence of large settling time in dc voltage leads to poor dynamic performance of NVGF control technique and hence current harmonics, voltage distortions and voltage disturbance such as voltage sag/swell as well as voltage unbalance compensation capability of this technique is not quite effective in comparison to the NLSMC technique. Moreover, NLSMC is very sensitive to model mismatch and noise. It is quite sluggish in rejecting long drifting grid disturbances. Hence, a suitable control strategy has to be developed in UPQC, which has improved DC-link voltage regulation as well as tracking performance through load and grid perturbations. To overcome this drawback a resistive optimization technique (ROT) incorporated with enhanced phase-locked loop (EPLL) based NVGF hysteresis control strategy and an optimum active power (OAP) technique combined with enhanced phase-locked loop (EPLL) based fuzzy sliding mode (FSM) pulse-width modulation (PWM) control strategy for UPQC have been discussed. ROT-NVGF and OAP-FSMC based UPQC control strategies are adaptive as well as robust and able to mitigate the PQ problems satisfactorily during all dynamic conditions of power system perturbation. However, performances of these controllers are not effective when there is a variation occurring either in the nonlinear load parameter or supply voltage parameter. Thus, UPQC may not be able to compensate PQ problems satisfactorily. Considering aforesaid problems, this thesis proposes a command generator tracker (CGT) based direct adaptive control (DAC) applied to a three-phase three-wire UPQC to improve the current and voltage harmonics, sag/swell and voltage unbalance in the power system distribution network. CGT is a model reference control law for a linear timeinvariant system with known coefficients and is formulated for the generation of reference signal for both shunt and series inverter. The main advantage of the proposed control algorithm is that no online extraction is needed to perceive the UPQC parameters. Moreover, IV the adaptive control law is designed to track a linear reference model to reduce the tracking error between model reference output and measured signal to be controlled. Additionally, this proposed algorithm adaptively regulates the DC-link capacitor voltage without utilizing additional controller circuit. As a result, the proposed algorithm provides more robustness, flexibility and adaptability in all operating conditions of the power system network. At last, model reference robust adaptive control (MRRAC) technique is proposed for single phase UPQC system. This control strategy is designed with the purpose of achieving high stability, high disturbance rejection and high level of harmonics cancellation. From simulation results, it is not only found to be robust against PI-controller, but also satisfactory THD results have been achieved in UPQC system. This has motivated to develop a prototype experimental set up in the Laboratory using FPGA (Field Programmable Gate Array) based NI (National Instruments) cRIO-9014. From both the simulation and experimentation, it is observed that the proposed MRRAC approach to design a UPQC system is found to be more effective as compared to the conventional PI-controller

Commande par mode glissant de paliers magnétiques actifs économes en énergie : une approche sans modèle

Abstract : Over the past three decades, various fields have witnessed a successful application of active magnetic bearing (AMB) systems. Their favorable features include supporting high-speed rotation, low power consumption, and rotor dynamics control. Although their losses are much lower than roller bearings, these losses could limit the operation in some applications such as flywheel energy storage systems and vacuum applications. Many researchers focused their efforts on boosting magnetic bearings energy efficiency via minimizing currents supplied to electromagnetic coils either by a software solution or a hardware solution. According to a previous study, we adopt the hardware solution in this thesis. More specifically, we investigate developing an efficient and yet simple control scheme for regulating a permanent magnet-biased active magnetic bearing system. The control objective here is to suppress the rotor vibrations and reduce the corresponding control currents as possible throughout a wide operating range. Although adopting the hardware approach could achieve an energy-efficient AMB, employing an advanced control scheme could achieve a further reduction in power consumption. Many advanced control techniques have been proposed in the literature to achieve a satisfactory performance. However, the complexity of the majority of control schemes and the potential requirement of powerful platform could discourage their application in practice. The motivation behind this work is to improve the closed-loop performance without the need to do model identification and following the conventional procedure for developing a model-based controller. Here, we propose applying the hybridization concept to exploit the classical PID control and some nonlinear control tools such as first- and second-order sliding mode control, high gain observer, backstepping, and adaptive techniques to develop efficient and practical control schemes. All developed control schemes in this thesis are digitally implemented and validated on the eZdsp F2812 control board. Therefore, the applicability of the proposed model-free techniques for practical application is demonstrated. Furthermore, some of the proposed control schemes successfully achieve a good compromise between the objectives of rotor vibration attenuation and control currents minimization over a wide operating range.Résumé: Au cours des trois dernières décennies, divers domaines ont connu une application réussie des systèmes de paliers magnétiques actifs (PMA). Leurs caractéristiques favorables comprennent une capacité de rotation à grande vitesse, une faible consommation d'énergie, et le contrôle de la dynamique du rotor. Bien que leurs pertes soient beaucoup plus basses que les roulements à rouleaux, ces pertes pourraient limiter l'opération dans certaines applications telles que les systèmes de stockage d'énergie à volant d'inertie et les applications sous vide. De nombreux chercheurs ont concentré leurs efforts sur le renforcement de l'efficacité énergétique des paliers magnétiques par la minimisation des courants fournis aux bobines électromagnétiques soit par une solution logicielle, soit par une solution matérielle. Selon une étude précédente, nous adoptons la solution matérielle dans cette thèse. Plus précisément, nous étudions le développement d'un système de contrôle efficace et simple pour réguler un système de palier magnétique actif à aimant permanent polarisé. L'objectif de contrôle ici est de supprimer les vibrations du rotor et de réduire les courants de commande correspondants autant que possible tout au long d'une large plage de fonctionnement. Bien que l'adoption de l'approche matérielle pourrait atteindre un PMA économe en énergie, un système de contrôle avancé pourrait parvenir à une réduction supplémentaire de la consommation d'énergie. De nombreuses techniques de contrôle avancées ont été proposées dans la littérature pour obtenir une performance satisfaisante. Cependant, la complexité de la majorité des systèmes de contrôle et l'exigence potentielle d’une plate-forme puissante pourrait décourager leur application dans la pratique. La motivation derrière ce travail est d'améliorer les performances en boucle fermée, sans la nécessité de procéder à l'identification du modèle et en suivant la procédure classique pour développer un contrôleur basé sur un modèle. Ici, nous proposons l'application du concept d'hybridation pour exploiter le contrôle PID classique et certains outils de contrôle non linéaires tels que contrôle par mode glissement du premier et du second ordre, observateur à grand gain, backstepping et techniques adaptatives pour développer des systèmes de contrôle efficaces et pratiques. Tous les systèmes de contrôle développés dans cette thèse sont numériquement mis en oeuvre et évaluées sur la carte de contrôle eZdsp F2812. Par conséquent, l'applicabilité des techniques de modèle libre proposé pour l'application pratique est démontrée. En outre, certains des régimes de contrôle proposés ont réalisé avec succès un bon compromis entre les objectifs au rotor d’atténuation des vibrations et la minimisation des courants de commande sur une grande plage de fonctionnement