Fixed-time Stabilization with a Prescribed Constant Settling Time by Static Feedback for Delay-Free and Input Delay Systems

A static non-linear homogeneous feedback for a fixed-time stabilization of a linear time-invariant (LTI) system is designed in such a way that the settling time is assigned exactly to a prescribed constant for all nonzero initial conditions. The constant convergence time is achieved due to a dependence of the feedback gain of the initial state of the system. The robustness of the closed-loop system with respect to measurement noises and exogenous perturbations is studied using the concept of Input-to-State Stability (ISS). Both delay-free and input delay systems are studied. Theoretical results are illustrated by numerical simulations

Distributed estimation design for LTI systems: a linear quadratic approach

This paper deals with the problem of distributedly estimate the state of a plant through a network of interconnected agents. Each of these agents must perform a real-time monitoring of the plant state, counting on the measurements of local plant outputs and on the exchange of information with neighbouring agents. The paper introduces a distributed LQ-based design that is applied to a distributed observer structure based on a multi-hop subspace decomposition. Stability and optimality conditions are derived and tested in simulation. Finally, the design method presented allows the user, through the tune of two scalar parameters, to modify the observer gains according to their experience about the plant

Algebraic robust control of a closed circuit heating-cooling system with a heat exchanger and internal loop delays

This study demonstrates the use of a simple algebraic controller design for a cooling-heating plant with a through-flow air-water heat exchanger that evinces long internal delays with respect to the robustness to plant model uncertainties and variable ambient temperature conditions during the season. The advantage of the proposed design method consists in that the delays are not approximated but fully considered. Moreover, the reduction of sensitivity to model parameters’ variations yields the better applicability regardless modeling errors or environmental fluctuations. The infinite-dimensional mathematical model of the plant has been obtained by using anisochronic modeling principles. The key tool for the design is the ring special of quasipolynomial meromorphic functions (RQM). The Two-Feedback-Controllers (TFC) rather than the simple negative control feedback loop is utilized, which enables to solve the reference tracking and disturbance rejection independently and more efficiently. The eventual controller is then tuned such that robust stability and robust performance requirements are fulfilled. The tuning procedure is supported by a performance optimization idea. Since the originally obtained controller is of the infinite-dimensional nature, a possible way how to substitute it by a simplified finite-dimensional one is proposed for engineering practice. The functionality of both the controllers is compared and verified by simulations as well as by real measurements which prove a very good performance. © 2016 Elsevier LtdEuropean Regional Development Fund under the project CEBIA-Tech Instrumentation [CZ.1.05/2.1.00/19.0376

Adaptive Systems: History, Techniques, Problems, and Perspectives

We survey some of the rich history of control over the past century with a focus on the major milestones in adaptive systems. We review classic methods and examples in adaptive linear systems for both control and observation/identification. The focus is on linear plants to facilitate understanding, but we also provide the tools necessary for many classes of nonlinear systems. We discuss practical issues encountered in making these systems stable and robust with respect to additive and multiplicative uncertainties. We discuss various perspectives on adaptive systems and their role in various fields. Finally, we present some of the ongoing research and expose problems in the field of adaptive control

Modeling and Control of Reluctance Actuators

Los actuadores de reluctancia son dispositivos que se caracterizan por una elevada densidad de fuerza, buena eficiencia, gran tolerancia frente a fallos y un coste reducido. Estas características hacen que estén siendo considerados como una alternativa muy prometedora frente a otro tipo de actuadores electromagnéticos en ciertas aplicaciones que requieren gran velocidad y precisión. Por otro lado, los actuadores de reluctancia también son la solución ideal para algunos dispositivos electromecánicos que requieren unas prestaciones modestas, lo cual es debido principalmente a que son compactos, tienen un bajo coste y consumen relativamente poco. En concreto, los relés electromecánicos y las válvulas de solenoide son dispositivos cuya operación está basada en la fuerza creada por un pequeño actuador de reluctancia.A pesar de sus ventajas, los actuadores de reluctancia son sistemas complejos cuya dinámica es no lineal. Una de sus características más distintivas es que la fuerza magnética que provoca el movimiento es siempre de atracción y, además, depende fuertemente de la posición de la armadura. Básicamente, el comportamiento de esta fuerza es lo que explica que dispositivos como los relés y las electroválvulas sufran fuertes impactos y desgaste cada vez que son activados. Adicionalmente, algunos fenómenos electromagnéticos como la histéresis magnética o las corrientes inducidas hacen que el modelado dinámico de los actuadores de reluctancia sea bastante complejo. El trabajo realizado en esta tesis doctoral está enfocado en estudiar las posibilidades que ofrecen estos actuadores y, en concreto, en analizar el comportamiento dinámico y proponer algoritmos de estimación y control para relés electromecánicos y válvulas de solenoide.El primer objetivo de la investigación es el desarrollo de modelos dinámicos para actuadores de reluctancia, es decir, modelos de orden reducido que puedan ser utilizados para realizar simulaciones transitorias lo más precisas posibles con un bajo coste computacional. Para ello, lo primero que se ha estudiado es el comportamiento electromagnético de estos sistemas. El método de modelado más usado en la tesis es el de los circuitos magnéticos equivalentes (MEC, por sus siglas en inglés). No obstante, también se han realizado algunas simulaciones con modelos de elementos _nitos, en concreto para validar las aproximaciones del método MEC o para calcular la reluctancia del entrehierro. Se han estudiado los principales fenómenos electromagnéticos que aparecen en los actuadores de reluctancia, lo que ha llevado a la obtención de expresiones analíticas para modelar la dispersión de flujo, las corrientes inducidas y la saturación e histéresis magnéticas. Por otra parte, la expresión de la fuerza magnética que produce el movimiento se ha obtenido mediante un balance energético del sistema.El movimiento de la armadura también se ha estudiado en la tesis. Dado que los actuadores de reluctancia tienen generalmente un recorrido físicamente acotado, se han propuesto dos técnicas diferentes que permiten modelar los límites del movimiento y los rebotes de la armadura. Una vez estudiado el movimiento, el modelo mecánico se ha combinado con las ecuaciones electromagnéticas para poder analizar el comportamiento dinámico del actuador en su conjunto. Se han desarrollado cinco modelos dinámicos distintos, desde el más sencillo posible hasta uno que incluye todos los fenómenos electromagnéticos citados con anterioridad, y posteriormente se han comparado teniendo en cuenta su precisión y coste computacional.Las medidas experimentales son fundamentales a la hora de analizar y caracterizar cualquier sistema dinámico. Por ello, otro de los objetivos de la tesis ha sido la evaluación de distintas técnicas de medida que pudieran ayudar a mejorar la comprensión sobre el comportamiento dinámico de los actuadores de reluctancia y, en caso de que fuera posible, formar parte de un bucle de control realimentado. En este sentido, se ha intentado grabar el movimiento de uno de los dispositivos estudiados mediante tres instrumentos ópticos distintos. Los resultados indican que, a pesar de que en ciertas situaciones sí sería posible medir la trayectoria del dispositivo durante su movimiento, ninguno de los instrumentos podría aplicarse en la práctica por su baja flexibilidad y alto coste. Por este motivo, también se ha explorado el uso de otras variables que puedan ser medidas mucho más fácilmente.Otra parte importante de la investigación ha estado centrada en técnicas de estimación. Se han desarrollado dos algoritmos que son capaces de estimar, en tiempo real, el flujo magnético, la resistencia y la inductancia de un actuador dado. Los algoritmos utilizan únicamente medidas de tensión y corriente, lo cual representa una clara ventaja ya que no se necesita utilizar sensores o equipamiento añadido. Las prestaciones de ambos estimadores han sido analizadas mediante simulación y experimentos reales. El problema de estimar la posición de la armadura también se ha abordado en la tesis. En concreto, se ha prestado especial atención en resaltar los efectos que la histéresis magnética produce en la estimación, algo que no había sido estudiado con anterioridad.Finalmente, se han propuesto distintas técnicas de control para actuadores de reluctancia. En concreto, el objetivo principal es lograr que estos sigan un movimiento con aterrizaje suave, es decir, un movimiento que no dé lugar a impactos o rebotes. Como un primer paso, se han estudiado las propiedades básicas de los sistemas de control, es decir, la estabilidad, controlabilidad y observabilidad. Después se ha explorado la técnica de linealización por realimentación como un posible método para diseñar un bucle de control realimentado para la trayectoria de la armadura. Los resultados obtenidos demuestran que el control por realimentación es capaz de controlar el movimiento con gran precisión, siempre y cuando haya disponibles medidas o estimaciones precisas de la posición en tiempo real. Como esta situación es difícil que se dé en la práctica, se ha estudiado el uso de técnicas de control óptimo en bucle abierto para aquellos casos en los que la posición de la armadura no se pueda obtener. En particular, se han obtenido distintas soluciones tiempo óptimo y de energía óptima para un actuador nominal y, posteriormente, se ha analizado su robustez utilizando un método de Montecarlo.Como alternativa a los métodos clásicos, se ha estudiado la aplicabilidad de los métodos Run-to-Run (R2R) en actuadores de relutancia. Estas técnicas están diseñadas específicamente para sistemas que realizan un proceso repetitivo y, por lo tanto, son idóneas para dispositivos como los relés y las válvulas. En concreto, los métodos R2R implícitos se basan en la idea de construir una función que evalúe el desempeño del sistema al final de cada repetición. De esta forma, es posible mejorar el comportamiento dinámico del actuador a lo largo de las repeticiones utilizando un algoritmo de búsqueda.Las posibilidades para diseñar un controlador R2R son prácticamente infinitas, así que en la tesis se dan consejos prácticos sobre cómo elegir y parametrizar la señal de entrada, cómo usar las medidas disponibles para evaluar el comportamiento del sistema o cómo comparar distintos algoritmos de búsqueda. Los experimentos realizados demuestran que el algoritmo R2R diseñado es capaz de mejorar enormemente el comportamiento de un relé electromecánico y que, después de unos pocos ciclos, ,los resultados son incluso mejores que con cualquier estrategia presente en la literatura.Reluctance actuators are characterized by having a high force density, good efficiency, high fault tolerance and reduced cost. These features make them a promising alternative to other electromagnetic actuators for high-speed and high-precision applications. In addition, reluctance actuators are also ideal for small switch-type devices that require a modest performance because of their compactness, low cost, reduced mass and low energy dissipation. In particular, electromechanical switches and solenoid valves are devices whose operation is based on the force created by a small reluctance actuator. Despite their advantages, reluctance actuators are systems with highly nonlinear dynamics. One of their most distinctive features is that the magnetic force that produces the motion is always attractive and varies greatly with the position of the armature. In essence, the nature of this force explains why switch-type devices like relays and valves are subject to strong impacts and wear each time they are operated. In addition to that, electromagnetic phenomena such as magnetic hysteresis and eddy currents make the dynamic modeling of reluctance actuators even more difficult. The work of this thesis aims to investigate the capabilities of reluctance actuators and, in particular, to analyze the dynamic behavior and propose estimation and control algorithms for electromechanical switches and solenoid valves. The first objective of the investigation is the development of control-oriented dynamical models for reluctance actuators, i.e., low-order models that can be used to perform accurate transient simulations with low computational requirements. For that, the electromagnetic behavior of these systems is firstly studied. The magnetic equivalent circuit (MEC) methodology is selected as the primary modeling technique. Simulations from finite element models are also used for some specific purposes, e.g., to verify the assumptions of the MEC approach or to calculate the reluctance of the air gap. Then, the main electromagnetic phenomena that occur in reluctance actuators are studied. Analytic expressions are derived to model magnetic saturation, hysteresis, flux fringing and eddy currents, and an energy balance is used to obtain the expression for the magnetic force that produces the motion. After that, the motion of the armature is incorporated to the analysis. Given that reluctance actuators usually have a limited range of motion, two different techniques are proposed to model the limits of the armature stroke and the bouncing phenomenon. Then, the electromagnetic equations and the mechanical models are combined to describe the overall dynamic behavior of the actuator. Five different dynamical models are presented, ranging from a computationally inexpensive structure to a comprehensive model that includes saturation, hysteresis, eddy currents and flux fringing. The models are compared in terms of accuracy and computational requirements. Measurements play an important role in the analysis and characterization of dynamical systems. Thus, another objective of this thesis is the evaluation of different measurement methodologies that may improve the understanding of the dynamic behavior of reluctance actuators and, if possible, be used as part of a feedback controller. In this regard, three optical instruments are explored in order to record the motion of switch-type actuators. The results show that, even though in some cases it is possible to measure the position of several components of the device, none of the instruments could be applied in a practical situation due to their low flexibility and high cost. For that reason, other variables that are much more easily obtainable are also explored. Another significant part of the research is devoted to estimation in reluctance actuators. Two different algorithms are proposed to estimate the magnetic flux, the resistance and the inductance of the device, both of which can be implemented in real time. The algorithms rely only on measurements of the coil voltage and current, which represents a clear advantage because no additional hardware is required. Simulation and experiments are presented to show the performance of the estimators. Furthermore, the estimation of the armature position is also investigated in this work. In particular, special focus is put on highlighting the effects of magnetic hysteresis on the performance of different estimation approaches. Control strategies are then proposed to achieve soft landing in reluctance actuators, i.e., a controlled motion without impacts or bounces. As a first step, the basic properties of control systems theory---stability, controllability and stability---are investigated for a nominal actuator. Then, feedback linearization is explored as a method to design a trajectory tracking controller for the armature position. The obtained results show that soft landing can be accomplished by means of feedback control provided that accurate measurements or estimates of the position are available. Since this situation is rare in practice, open-loop optimal control is proposed as an alternative technique when the position is not accessible. Different time-optimal and energy-optimal solutions are derived for a nominal actuator and then compared in terms of robustness using a Monte Carlo analysis. Finally, Run-to-Run (R2R) control is explored as another method that may be used to improve the performance of reluctance actuators. These techniques are specifically designed for systems that perform a repetitive operation and, hence, they are very well suited to being applied to switch-type devices. In particular, implicit R2R methods are based on the idea of building a function that evaluates the performance of the system at the end of each repetition. In this way, the dynamic behavior of the actuator can be gradually improved along the repetitions by conducting a black-box search. Considering that the possibilities to design a R2R controller are almost endless, practical advice is given on how to select and parameterize the input profile, how to use measurements to evaluate the system performance and how to compare different search algorithms. The performed experiments show that the designed R2R controller is able to improve greatly the behavior of a switch-type device and that, after a few cycles, it outperforms other methodologies in the literature.<br /

DISTRIBUTED ESTIMATION AND STABILITY OF EVOLUTIONARY GAME DYNAMICS WITH APPLICATIONS TO STUDY OF ANIMAL MOTION

In this dissertation, we consider three problems: in the first we investigate distributed state estimation of linear time-invariant (LTI) plants; in the second we study optimal remote state estimation of Markov processes; while in the third we examine stability of evolutionary game dynamics in large populations. Problem 1: Consider that an autonomous LTI plant is given and that each member of a network of LTI observers accesses a portion of the output of the plant. The dissemination of information within the network is dictated by a pre-specified directed graph in which each vertex represents an observer. This work proposes a distributed estimation scheme that is a natural generalization of consensus in which each observer computes its own state estimate using only the portion of the output vector accessible to it and the state estimates of other observers that are available to it, according to the graph. Unlike straightforward high-order solutions in which each observer broadcasts its measurements throughout the network, the average size of the state of each observer in the proposed scheme does not exceed the order of the plant plus one. We determine necessary and sufficient conditions for the existence of a parameter choice for which the proposed scheme attains asymptotic omniscience of the state of the plant at all observers. The conditions reduce to certain detectability requirements that imply that if omniscience is not possible under the proposed scheme then it is not viable under any other scheme -- including higher order LTI, nonlinear, and time-varying ones -- subject to the same graph. We apply the proposed scheme to distributed tracking of a group of water buffaloes. Problem 2: Consider a two-block remote estimation framework in which a sensing unit accesses the full state of a Markov process and decides whether to transmit information about the state to a remotely located estimator given that each transmission incurs a communication cost. The estimator finds the best state estimate of the process using the information received from the sensing unit. The main purpose of this work is to design transmission policies and estimation rules that dictate decision making of the sensing unit and estimator, respectively, and that are optimal for a cost functional which combines the expectation of squared estimation error and communication costs. Our main results establish the existence of transmission policies and estimation rules that are jointly optimal, and propose an iterative procedure to find ones. Our convergence analysis shows that the sequence of sub-optimal solutions generated by the proposed procedure has a convergent subsequence, and the limit of any convergent subsequence is a person-by-person optimal solution. We apply the proposed scheme to remote estimation of location of a water buffalo. Problem 3: We investigate an energy conservation and dissipation (passivity) aspect of evolutionary dynamics in evolutionary game theory. We define a notion of passivity for evolutionary dynamics, and describe conditions under which dynamics exhibit passivity. For dynamics that are defined on a finite-dimensional state space, we show that the conditions can be characterized in connection with state-space realizations of the dynamics. In addition, we establish stability of passive dynamics in terms of dissipation of stored energy defined by passivity, and present stability results in population games. We provide implications of stability for various passive dynamics both analytically and by means of numerical simulations

Robust Observation and Control of Complex Networks

The problem of understanding when individual actions of interacting agents display to a coordinated collective behavior has receiving a considerable attention in many research fields. Especially in control engineering, distributed applications in cooperative environments are achieving resounding success, due to the large number of relevant applications, such as formation control, attitude synchronization tasks and cooperative applications in large-scale systems. Although those problems have been extensively studied in Literature, themost of classic approaches use to consider the unrealistic scenario in which networks always consist of identical, linear, time-invariant entities. It’s clear that this assumption strongly approximates the effective behavior of a network. In fact agents can be subjected to parameter uncertainties, unmodeled dynamics or simply characterized by proper nonlinear dynamics. Therefore, motivated by those practical problems, the present Thesis proposes various approaches for dealing with the problem of observation and control in both the framework of multi-agents and complex interconnected systems. The main contributions of this Thesis consist on the development of several algorithms based on concepts of discontinuous slidingmode control. This techniques can be employed for solving in finite-time problems of robust state estimation and consensus-based synchronization in network of heterogenous nonlinear systems subjected to unknown but bounded disturbances and sudden topological changes. Both directed and undirected topologies have been taken into account. It is worth to mention also the extension of the consensus problem to networks of agents governed by a class parabolic partial differential equation, for which, for the first time, a boundary-based robust local interaction protocol has been presented

Robust Observation and Control of Complex Networks

The problem of understanding when individual actions of interacting agents display to a coordinated collective behavior has receiving a considerable attention in many research fields. Especially in control engineering, distributed applications in cooperative environments are achieving resounding success, due to the large number of relevant applications, such as formation control, attitude synchronization tasks and cooperative applications in large-scale systems. Although those problems have been extensively studied in Literature, themost of classic approaches use to consider the unrealistic scenario in which networks always consist of identical, linear, time-invariant entities. It’s clear that this assumption strongly approximates the effective behavior of a network. In fact agents can be subjected to parameter uncertainties, unmodeled dynamics or simply characterized by proper nonlinear dynamics. Therefore, motivated by those practical problems, the present Thesis proposes various approaches for dealing with the problem of observation and control in both the framework of multi-agents and complex interconnected systems. The main contributions of this Thesis consist on the development of several algorithms based on concepts of discontinuous slidingmode control. This techniques can be employed for solving in finite-time problems of robust state estimation and consensus-based synchronization in network of heterogenous nonlinear systems subjected to unknown but bounded disturbances and sudden topological changes. Both directed and undirected topologies have been taken into account. It is worth to mention also the extension of the consensus problem to networks of agents governed by a class parabolic partial differential equation, for which, for the first time, a boundary-based robust local interaction protocol has been presented