Contrôle avancé des convertisseurs de puissance multi-niveaux pour applications sur réseaux faibles

139 p.El advenimiento progresivo de las microrredes que incorporan fuentes de energía renovable está dando lugar a un nuevo paradigma de distribución de la electricidad. Este nuevo planteamiento sirve de interfaz entre consumidores no controlados y fuentes intermitentes, implicando desafíos adicionales en materia de conversión, almacenamiento y gestión de la energía.Los convertidores de potencia se adaptan en consecuencia, en particular con el desarrollo de los convertidores multinivel, que integrando los mismos componentes que sus predecesores y un control más complejo, soportan potencias más altas y aseguran una mejor calidad de la energía.Debido al carácter híbrido de los convertidores de potencia, su control se divide comúnmente en dos partes: por un lado, el control de los objetivos continuos vinculados a la función principal de los convertidores de servir de interfaz, y, por otro, el control discreto de los interruptores de potencia, conocido con el nombre de modulación.En este contexto, las exigencias crecientes en términos de eficiencia, fiabilidad, versatilidad y rendimiento hacen necesaria una mejora de la inteligencia de la estructura de control. Para cumplir conestos requisitos, se propone tratar mediante un solo controlador ambas problemáticas, la vinculada a la función de interfaz de los convertidores y la relacionada con su naturaleza discreta. Esta decisión implica incorporar la no-linealidad de los convertidores de potencia en el controlador, lo que equivale a suprimir el bloque de modulación, que constituye la solución tradicional para linealizar el comportamiento interno de los convertidores. Se adopta un planteamiento de Control Predictivo basado en Modelos (MPC) para abordar la no-linealidad y la gran diversidad de objetivos de control que acompañan a los convertidores de potencia.El algoritmo desarrollado combina teoría de grafos ¿con algoritmos de Dijkstra, A* y otros¿ con un modelo de estado especial para sistemas conmutados al objeto de proporcionar una herramienta potente y universal, capaz de manipular simultáneamente el carácter cuantificado de los interruptores de potencia y el continuo de las entidades interconectadas por el convertidor. Se han obtenido resultados sobre la estabilidad y la controlabilidad de los modelos de estado conmutados aplicados al caso particular de los convertidores de potencia.El controlador así desarrollado y descrito se ha examinado en simulación frente a varios casos y aplicaciones: inversor aislado o conectado a la red, rectificador y convertidor bidireccional. Se ha empleado la misma estructura de control para tres topologías de convertidor multinivel: Neutral-Point Clamped, Flying Capacitor y Cascaded H-Bridge. Al objeto de adaptarse a los cambios citados, lo único que varía en el controlador es el modelo del convertidor adoptado para la predicción, así como la función de coste, que traduce los requisitos de control en un problema de optimización a solucionar por el algoritmo. Un cambio de topología resulta en una modificación del modelo interno, sin impacto sobre la función de coste, mientras que variaciones de esta función son suficientes para adaptarse a la aplicación.Los resultados muestran que el controlador logra actuar directamente sobre los interruptores de potencia en función de diversos requisitos. Los desempeños de la estructura de control propuesta son similares a los de las numerosas estructuras dedicadas a cada uno de los casos estudiados, excepto en el caso de operación en modo rectificador, en el que la versatilidad y rapidez de control obtenidos son particularmente interesantes.En definitiva, el controlador planteado puede emplearse para diferentes aplicaciones, topologías, objetivos y limitaciones. Si bien las estructuras de control lineal tradicionales han de modificarse, a menudo en profundidad, para afrontar diferentes modos de operación o requisitos de control, dichas alteraciones no tienen ningún impacto sobre la arquitectura del controlador MPC obtenido, lo que pone de manifiesto su versatilidad, así como su universalidad, también demostrada por su capacidad para adaptarse a diferentes convertidores de potencia sin modificaciones importantes. Finalmente, la solución propuesta elude por completo la complejidad de la modulación, ofreciendo simplicidad y flexibilidad al diseño del control

Robust stabilisation of multivariable systems: A super-optimisation approach

The work aims to derive extended robust stability results for the case of unstructured uncertainty models of multivariable systems. More specifically, throughout the thesis, additive and coprime unstructured perturbation models are considered. Refined robust stabilisation problems of MIMO systems are defined and maximally robust controllers are synthesised in a state-space form. Unstructured perturbations which destabilise the feedback system for every optimal (maximally robust) controller are identified on the boundary of the optimal ball, i.e. the set of all admissible perturbations with norm equal to the maximum robust stability radius. Boundary perturbations are termed "uniformly destabilising" if they destabilise the closed-loop system for every optimal controller and it is shown that they all share a common characteristic, i.e. a projection of magnitude equal to the maximal robust stability radius, along a fixed direction defined by a pair of maximising vectors (scaled Schmidt pair) of a Hankel operator related to the problem. By imposing a directionality constraint it is shown that it is possible to increase the robust stability radius in every other direction by a subset of all optimal controllers. In order to solve this problem, super-optimisation techniques are developed. Independently a natural extension of Hankel norm approximations, the so-called super­ optimisation problem is posed and solved explicitly for the case of one-block problems in a state-space setting. It is thus shown that a subset of all maximally robust controllers, namely the class of super-optimal controllers, stabilises all perturbed plants within an extended stability radius 11,*(b), subject to a directionality constraint. In addition, the work is related to robust stabilisation subject to structured perturbations. The notions of structured robust stabilisation problem, and structured set approximation are defined in connection with the maximised set of permissible perturbations. It is further shown that µ*(J) can serve as an upper bound the structured robust stabilisation problem. The effect of µ*(J) as an upper bound depends on the compatibility between the two structures, the true structure and the artificial structure of the extended permissible set. [Look inside the thesis' abstract for an exact version of formulas and equations

Communication-constrained feedback stability and Multi-agent System consensusability in Networked Control Systems

With the advances in wireless communication, the topic of Networked Control Systems (NCSs) has become an interesting research subject. Moreover, the advantages they offer convinced companies to implement and use data networks for remote industrial control and process automation. Data networks prove to be very efficient for controlling distributed systems, which would otherwise require complex wiring connections on large or inaccessible areas. In addition, they are easier to maintain and more cost efficient. Unfortunately, stability and performance control is always going to be affected by network and communication issues, such as band-limited channels, quantization errors, sampling, delays, packet dropouts or system architecture. The first part of this research aims to study the effects of both input and output quantization on an NCS. Both input and output quantization errors are going to be modeled as sector bounded multiplicative uncertainties, the main goal being the minimization of the quantization density, while maintaining feedback stability. Modeling quantization errors as uncertainties allows for robust optimal control strategies to be applied in order to study the accepted uncertainty levels, which are directly related to the quantization levels. A new feedback law is proposed that will improve closed-loop system stability by increasing the upper bound of allowed uncertainty, and thus allowing the use of a coarser quantizer. Another aspect of NCS deals with coordination of the independent agents within a Multi-agent System (MAS). This research addresses the consensus problem for a set of discrete-time agents communicating through a network with directed information flow. It examines the combined effect of agent dynamics and network topology on agents\u27 consensusability. Given a particular consensus protocol, a sufficient condition is given for agents to be consensusable. This condition requires the eigenvalues of the digraph modeling the network topology to be outer bounded by a fan-shaped area determined by the Mahler measure of the agents\u27 dynamics matrix

Stability Analysis and Design of Digital Compensators for Networked Control Systems

Networked Control Systems (NCSs) are distributed control systems where sensors, actuators, and controllers are interconnected by communication networks, e.g. LAN, WAN, CAN, Internet. Use of digital networks are advantageous due to less cost, ease in installation and/or ready availability. These are widely used in automobiles, manufacturing plants, aircrafts, spacecrafts, robotics and smart grids. Due to the involvement of network in such systems, the closed-loop system performance may degrade due to network delays and packet losses. Since delays are involved in NCS, predictor based compensators are useful to improve control performance of such systems. Moreover, the digital communication network demands implementation of digital compensators. First, the thesis studies stability analysis of NCSs with uncertain time-varying delays. For this configuration, both the controller and actuators are assumed as event-driven (i.e. the delays are fractional type). The NCS with uncertain delays and packet losses are represented as systems in polytopic form as well as with norm-bounded uncertainties. The closed-loop system stability is guaranteed using quadratic Lyapunov function in terms of LMIs. For given controller gain the maximum tolerable delay calculated and the resultant stability regions of the system is explored in the parameter plane of control gain and maximum tolerable delay. The stability region is found to be almost same for both the methods for the case of lower order systems (an integrator plant), whereas for higher order systems (second order example system), the obtained stability region is more for the case of polytopic approach than the norm-bounded one. This motivates to use the polytopic modeling approach in remaining of the thesis. Next, design of digital Smith Predictor (SP) to improve the performance of NCS with bounded uncertain delays and packet losses in both the forward and feedback channels is con-sidered. For implementing a digital SP, it is essential that the controller is implemented with constant sampling interval so that predictor model is certain and therefore the controller is required to be time-driven one (sensor-to-controller channel uncertainties are integer type). On the other hand, the actuator is considered to be event-driven since it introduces lesser delay compared to the time-driven case. Thereby, the controller-to-actuator channel delays are fractional type. The system with uncertain delay parameters (packet losses as uncertain integer delays) are modeled in polytopic form. For this system, Lyapunov stability criterion has been presented in terms of LMIs to explore the closed-loop system stability. Finally, the proposed analysis is verified with numerical studies and using TrueTime simulation en- vironment. It is observed that the digital SP improves the stability performance of the NCS considerably compared to without predictor. However, the choice of predictor delay affects the system performance considerably. Further, an additional filter is used along with conventional digital SP to improve the system response and disturbance rejection property of the controller. For this configurations, both the controller and actuators are assumed to be time-driven. The NCS with random but bounded delays and packet losses introduced by the network is modeled as a switched system and LMI based iterative algorithm is used for designing the controller. A LAN-based experimental setup is developed to validate the above theoretical findings.The plant is an op-amp based emulated integrator plant.The plant is interfaced with a computer using data acquisition card. Another computer is used as the digital controller and the two computers are connected via LAN using UDP communication protocol. The effectiveness of the proposed controller design method is verified with this LAN-based experi- mental setup. Three controller configurations (i.e. without and with digital SP as well as the digital SP with filter) are considered for comparison of their guaranteed cost performance. It is shown that the digital SP with filter improves the performance of NCS than with and without simple digital SP based NCS configurations. Finally, design of digital predictor based robust H1 control for NCSs is made in such a way that the effect of randomness in network delays and packet losses on the closed-loop system dynamics is reduced. For the purpose, the predictor delay is chosen as a fixed one whereas variation of random delays in the system are modeled as disturbances. Then quadratic H1 design criterion in the form of LMIs is invoked so that the network jitter effect is minimized. The efficacy of the proposed configurations are validated with the developed LAN based NCS setup. It is seen that the designed controllers effectively regularize the system dynamics from random variations of the network delays and packet losses

A vision-based optical character recognition system for real-time identification of tractors in a port container terminal

Automation has been seen as a promising solution to increase the productivity of modern sea port container terminals. The potential of increase in throughput, work efficiency and reduction of labor cost have lured stick holders to strive for the introduction of automation in the overall terminal operation. A specific container handling process that is readily amenable to automation is the deployment and control of gantry cranes in the container yard of a container terminal where typical operations of truck identification, loading and unloading containers, and job management are primarily performed manually in a typical terminal. To facilitate the overall automation of the gantry crane operation, we devised an approach for the real-time identification of tractors through the recognition of the corresponding number plates that are located on top of the tractor cabin. With this crucial piece of information, remote or automated yard operations can then be performed. A machine vision-based system is introduced whereby these number plates are read and identified in real-time while the tractors are operating in the terminal. In this paper, we present the design and implementation of the system and highlight the major difficulties encountered including the recognition of character information printed on the number plates due to poor image integrity. Working solutions are proposed to address these problems which are incorporated in the overall identification system.postprin

Active vibration control of civil engineering structures

This thesis is in the area of active vibration control of Civil Engineering structures subject to earthquake loading. Existing structural control methods and technologies including passive, active, semi-active and hybrid control are first introduced. An extensive analysis of a frame-pendulum model is developed and analysed to investigate under what conditions effective energy dissipation is achieved in Tuned Mass Damper systems and the limitation of these devices under stiffness degradation when the structure enters the inelastic region. Linear Quadratic Gaussian and H-infinity active control schemes are designed, simulated and assessed for buildings, modelled as lumped parameter systems, including base and actuator dynamics. Various aspects of the designs are extensively evaluated using multiple criteria and loading conditions and validated in large-scale benchmark problems under practical limitations and implementation constraints. A novel design method is proposed for minimising peak responses of regulated signals via a deadbeat parametrisation of all stabilising controllers in discrete-time. The method incorporates constraints on the magnitude and rate of the control signal and is solved via efficient Linear Programming methods. It is argued that this type of optimisation is more relevant for structural control, as failure occurs when maximum member displacements are exceeded. The problem of stiffness matrix estimation from experimental data is formulated as an optimisation problem and solved under various conditions (positive definiteness, tridiagonal structure) via an alternating convex projection scheme. Both static and dynamic loading is considered. The method is finally incorporated in an adaptive control scheme involving the redesign in real-time of an LQR (Linear Quadratic Regulator) active vibration controller. It is shown that the method is successful in recovering the stability and performance properties of the nominal design under conditions of significant uncertainty in the stiffness parameters

Job shop scheduling with artificial immune systems

The job shop scheduling is complex due to the dynamic environment. When the information of the jobs and machines are pre-defined and no unexpected events occur, the job shop is static. However, the real scheduling environment is always dynamic due to the constantly changing information and different uncertainties. This study discusses this complex job shop scheduling environment, and applies the AIS theory and switching strategy that changes the sequencing approach to the dispatching approach by taking into account the system status to solve this problem. AIS is a biological inspired computational paradigm that simulates the mechanisms of the biological immune system. Therefore, AIS presents appealing features of immune system that make AIS unique from other evolutionary intelligent algorithm, such as self-learning, long-lasting memory, cross reactive response, discrimination of self from non-self, fault tolerance, and strong adaptability to the environment. These features of AIS are successfully used in this study to solve the job shop scheduling problem. When the job shop environment is static, sequencing approach based on the clonal selection theory and immune network theory of AIS is applied. This approach achieves great performance, especially for small size problems in terms of computation time. The feature of long-lasting memory is demonstrated to be able to accelerate the convergence rate of the algorithm and reduce the computation time. When some unexpected events occasionally arrive at the job shop and disrupt the static environment, an extended deterministic dendritic cell algorithm (DCA) based on the DCA theory of AIS is proposed to arrange the rescheduling process to balance the efficiency and stability of the system. When the disturbances continuously occur, such as the continuous jobs arrival, the sequencing approach is changed to the dispatching approach that involves the priority dispatching rules (PDRs). The immune network theory of AIS is applied to propose an idiotypic network model of PDRs to arrange the application of various dispatching rules. The experiments show that the proposed network model presents strong adaptability to the dynamic job shop scheduling environment.postprin