Systems Structure and Control

The title of the book System, Structure and Control encompasses broad field of theory and applications of many different control approaches applied on different classes of dynamic systems. Output and state feedback control include among others robust control, optimal control or intelligent control methods such as fuzzy or neural network approach, dynamic systems are e.g. linear or nonlinear with or without time delay, fixed or uncertain, onedimensional or multidimensional. The applications cover all branches of human activities including any kind of industry, economics, biology, social sciences etc

Spatial Formation Control

In this thesis, we study robust spatial formation control from several aspects. First, we study robust adaptive attitude synchronization for a network of rigid body agents using various attitude error functions defined on SO(3). Our results are particularly useful for networks with large initial attitude difference. We devise an adaptive geometric approach to cope with situations where the inertia matrices are not available for measurement. We use the Frobenius norm as a measure for the difference between the actual values of inertia matrices and their estimated values, to construct the individual adaptive laws of the agents. Compared to the previous methods for synchronization on SO(3) such as those which are based on quaternions, our proposed approach does not contain any attitude representation ambiguity. As the final part of our studies from the attitude synchronization aspect, we analyze robustness to external disturbances and unmodeled dynamics, and propose a method to attenuate such effects. Simulation results illustrate the effectiveness of the proposed approach. In the next part of the thesis, we study the distributed localization of the extremum point of unknown quadratic functions representing various physical or artificial signal potential fields. It is assumed that the value of such functions can be measured at each instant. Using high pass filtering of the measured signals, a linear parametric model is obtained for system identification. For design purposes, we add a consensus term to modify the identification subsystem. Next, we analyze the exponential convergence of the proposed estimation scheme using algebraic graph theory. In addition, we derive a distributed identifiability condition and use it for the construction of distributed extremum seeking control laws. In particular, we show that for a network of connected agents, if each agent contains a portion of the dithering signals, it is still possible to drive the system states to the extremum point provided that the distributed identifiability condition is satisfied. In the final part of this research, several robust control problems for general linear time invariant multi-agent systems are studied. We consider the robust consensus problem in the presence of unknown Lipschitz nonlinearities and polytopic uncertainties in the model of each agent. Next, this problem is solved in the presence of external disturbances. A set of control laws is proposed for the network to attain the consensus task and under the zero initial condition, achieves the desired H-infinity performance. We show that by implementing the modified versions of these control laws, it is possible to perform two-time scales formation control

Control of power converter in modern power systems

A la portada consta el nom del programa interuniversitari: Joint Doctoral Programme in Electric Energy Systems [by the] Universidad de Málaga, Universidad de Sevilla, Universidad del País Vasco/Euskal Erriko Unibertsitatea i Universitat Politècnica de CatalunyaPower system is undergoing an unpreceded paradigm shift: from centralized to distributed generation. As the renewable-based generations and battery storage systems are increasingly displacing conventional generations, it becomes more and. more difficult to maintain the stability and reliability of the grid by using only conventional generations. The main reason for the degradation of grid stability is the rapid penetration of nonconventional sources. These new generations interface with the grids through power electronics converters which are conventionally designed to maximize conversion efficiency and resource utilization. Indeed, these power converters only focus on their internal operation despite the grid conditions, which often worsens the grid operation. To overcome such a drawback, the grid-forming concept has been proposed for power converters, aiming to redesign the control of the power converters to enforce more grid-friendly behaviours such as inertia response and power oscillation damping to name a few. Despite the rich literature, actual adaptation of grid-forming controller in real-world applications is still rare because incentives for renewable power plants to provide services based on such advanced grid-forming functions were at best scarce. In the last years, however, several system operators have imposed new requirements and markets for grid-supporting services. In addition, the existing grid-forming controllers require modification to low-level control firmware of a power converter, which is often unrealistic due to the control hardware limitations as well as necessary testing and certifications. To ensure a stable operation of a grid-forming converter under adverse operating conditions, a robust voltage sensorless current controller is developed in this PhD thesis. The proposed controller is able to handle most of the possible abnormal conditions of the grid such as impedance variations, unbalanced voltage; harmonics distortion. These abnormalities of the grid are mathematically represented using equivalent linear models such that they can be used for calculating the controller gains. Linear matrix inequality techniques are also used to facilitate parameter tuning. In fact, the performance and stability of the current control loop can be determined through only two tuning parameters instead of eight parameters for a controller of a similar structure. The existing grid-forming implementations are designed considering that the control firmware of the power converter can be upgraded at will. However, modifications of the control firmware are not straightforward and cost-effective at mass scale. To overcome such a limitation, an external synchronous controller is presented in this PhD thesis. The external synchronous controller uses measurements, which are either provided by the power converter or a dedicated measurement unit, to calculate the actual active and reactive power that should be injected by the power converters in a way that the power plant acts as an aggregated grid­forming converter. As a result, any conventional power converters can be utilized for providing grid-supporting services with minimal modification to the existing infrastructure. Power converters can provide even better performance than a synchronous generator if a proper control scheme is used. In this regard, the final chapter of this PhD thesis presents the multi-rotor virtual machine implementation for grid-forming converter to boost their damping performance to power oscillations. The multi-rotor virtual machine-controller implements several virtual rotors instead of only one rotor as in typical grid-forming strategies. Since each of the virtual rotors is tuned to target a specific critical mode, the damping participation to such a mode can be increased and adjusted individually. The controllers presented in this PhD thesis are validated through simulators and experiments in the framework of the H2020 FlexiTranstore project. The results are throughout analysed to assess the control performance as well as to highlight possible implications.A medida que las generaciones basadas en energías renovables y los sistemas de almacenamiento de baterías desplazan la generación convencional, se vuelve cada vez más difícil mantener la estabilidad y confiabilidad de la red. Estas nuevas generaciones interactúan con las redes a través de convertidores de electrónica de potencia que están diseñados tradicionalmente para maximizar la eficiencia de conversión y la utilización de recursos. Estos convertidores centran su funcionamiento interno independientemente de las condiciones de la red, lo que a menudo empeora el funcionamiento de la red. Para esto, se ha propuesto el concepto de convertidores de potencia formadores de red (grid-forming), con el objetivo de rediseñar el control de los convertidores de potencia para imponer comportamientos más favorables a la red, por ejemplo, la respuesta inercial y la amortiguación de oscilaciones de potencia. No en tanto, la adaptación real del controlador grid-forming en aplicaciones del mundo real todavía es escasa debido a los pocos incentivos para que las plantas de energía renovable proporcionen servicios basados en funciones de formación de red tan avanzadas. Aunque en los últimos años, operadores de sistemas han impuesto nuevos requisitos y mercados para servicios auxiliares, los controladores grid-forming existentes requieren cambios en el firmware de control de bajo nivel de un convertidor de potencia, algo poco realista debido a las limitaciones del hardware de control, así como a las pruebas y certificaciones necesarias. En esta tesis se desarrolla un controlador de corriente robusto, sin sensor de tensión, para garantizar el funcionamiento estable de un convertidor grid-forming en condiciones de operación adversas. Este controlador es capaz de manejar la mayoría de las condiciones anormales de red, como variaciones de impedancia, tensión desequilibrada y distorsión de armónicos. Estas anomalías de la red se representan matemáticamente mediante modelos lineales equivalentes, utilizados para calcular las ganancias del controlador. También, usando técnicas de desigualdad matricial lineal para facilitar el ajuste de parámetros. De hecho, el rendimiento y la estabilidad del bucle de control de la corriente pueden determinarse mediante sólo dos parámetros de sintonización. Las implementaciones de formación de red existentes están diseñadas considerando que el firmware de control del convertidor de potencia puede actualizarse a voluntad. Sin embargo, las modificaciones del firmware de control no son sencillas ni rentables a gran escala. Por tanto, esta tesis presenta un controlador síncrono externo que utiliza las mediciones proporcionadas por el convertidor de potencia o por una unidad de medición dedicada para calcular la potencia activa y reactiva real que deben inyectar los convertidores de potencia, de forma que la central eléctrica actúe como un convertidor grid-forming agregado. Como resultado, cualquier convertidor de potencia convencional puede utilizarse para proporcionar servicios de apoyo a la red con una modificación mínima de la infraestructura existente. Los convertidores de potencia pueden ofrecer mejor rendimiento que un generador síncrono utilizando un esquema de control adecuado. El último capítulo de esta tesis presenta la implementación de una máquina virtual multirrotor para que los convertidores de red aumenten su rendimiento de amortiguación de las oscilaciones de potencia. El controlador de la máquina virtual multirrotor implementa varios rotores virtuales en lugar de un solo rotor como en las estrategias típicas de grid-forming. Dado que cada uno de los rotores virtuales está sintonizado para dirigirse a un modo crítico específico, la participación de la amortiguación a dicho modo puede aumentarse y ajustarse individualmente. Los controladores presentados en esta tesis doctoral han sido validados mediante simulaciones y experimentos en el marco del proyecto H2020 FlexiTranstore.Postprint (published version

D04.05 - Feasibility mock-ups of feedback schedulers

Control and computation co-design deals with the interaction between feedback control laws design and their implementation on a real execution resource. Control design is often carried out in the framework of continuous time, or under the assumption of ideal sampling with equidistant intervals and known delays. Implementation on a real-time execution platform introduces many timing uncertainties and distortions to the ideal timing scheme, e.g. due to variable computation durations, complex preemption patterns between concurrent activities, uncertain network induced communication delays or occasional data loss. Analyzing, prototyping, simulating and guaranteeing the safety of complex control systems are very challenging topics. Models are needed for the mechatronic continuous system, for the discrete controllers and diagnosers, and for network behavior. Real-time properties (task response times) and the network Quality of Service (QoS) influence the controlled system properties (Quality of Control, QoC). To reach effective and safe systems it is not enough to provide theoretic control laws and leave programmers and real-time systems engineers just do their best to implement the controllers. This report first describes, through the detailed design of a quadrotor drone controller, the main features of {\sc Orccad}, an integrated development environment aimed to bridge the gap between advanced control design and real-time implementation. Besides control design and implementation, a real-time (hardware-in-the-loop) simulation has been designed to assess the control design with a simulated target rather than with the real plant. Using this HIL structure, several experiments using flexible real-time control features are reported, namely Kalman filters subject to data loss, control under (m,k)-firm constraints, control with varying sampling rates and feedback scheduling using the MPC approach

On real-time feedback control systems: Requirements, achievements and perspectives

International audienceThe present article is a position paper reviewing the main requirements and existing achievements of co-design approaches for real-time control and computing. This problem arises with the increasing complexity of modern computers which require more integrated methodologies, specifically suited to critical embedded systems. The general problem to be solved is the achievement of multi-objective goals (i.e. mixing stability, performance and dependability requirements) under constraints of limited execution resources (combining hardware and software components in CPUs and networks). It is expected that co-design approaches, handling the constraints arising from the control and real-time computing domains at early design time, can improve the overall e ectiveness of distributed real-time controllers

Stochastic Event-Based Control and Estimation

Digital controllers are traditionally implemented using periodic sampling, computation, and actuation events. As more control systems are implemented to share limited network and CPU bandwidth with other tasks, it is becoming increasingly attractive to use some form of event-based control instead, where precious events are used only when needed. Forms of event-based control have been used in practice for a very long time, but mostly in an ad-hoc way. Though optimal solutions to most event-based control problems are unknown, it should still be viable to compare performance between suggested approaches in a reasonable manner. This thesis investigates an event-based variation on the stochastic linear-quadratic (LQ) control problem, with a fixed cost per control event. The sporadic constraint of an enforced minimum inter-event time is introduced, yielding a mixed continuous-/discrete-time formulation. The quantitative trade-off between event rate and control performance is compared between periodic and sporadic control. Example problems for first-order plants are investigated, for a single control loop and for multiple loops closed over a shared medium. Path constraints are introduced to model and analyze higher-order event-based control systems. This component-based approach to stochastic hybrid systems allows to express continuous- and discrete-time dynamics, state and switching constraints, control laws, and stochastic disturbances in the same model. Sum-of-squares techniques are then used to find bounds on control objectives using convex semidefinite programming. The thesis also considers state estimation for discrete time linear stochastic systems from measurements with convex set uncertainty. The Bayesian observer is considered given log-concave process disturbances and measurement likelihoods. Strong log-concavity is introduced, and it is shown that the observer preserves log-concavity, and propagates strong log-concavity like inverse covariance in a Kalman filter. A recursive state estimator is developed for systems with both stochastic and set-bounded process and measurement noise terms. A time-varying linear filter gain is optimized using convex semidefinite programming and ellipsoidal over-approximation, given a relative weight on the two kinds of error