Model-based control for high-tech mechatronic systems

Motion systems are mechanical systems with actuators with the primary function to position a load. The actuator can be either hydraulic, pneumatic, or electric. The feedback controller is typically designed using frequency domain techniques, in particular via manual loop-shaping. In addition to the feedback controller, a feedforward controller is often implemented with acceleration, velocity, and friction feedforward for the reference signal. This chapter provides an overview of a systematic control design procedure for motion systems that has proven its use in industrial motion control practise. A step-by-step procedure is presented that gradually extends single-input single-output (SISO) loop-shaping to the multi-input multi-output (MIMO) situation. This step-by-step procedure consists of interaction analysis, decoupling, independent SISO design, sequential SISO design, and finally, norm-based MIMO design. Extreme ultraviolet is a key technology for next-generation lithography

Modal control of an oblique wing aircraft

A linear modal control algorithm is applied to the NASA Oblique Wing Research Aircraft (OWRA). The control law is evaluated using a detailed nonlinear flight simulation. It is shown that the modal control law attenuates the coupling and nonlinear aerodynamics of the oblique wing and remains stable during control saturation caused by large command inputs or large external disturbances. The technique controls each natural mode independently allowing single-input/single-output techniques to be applied to multiple-input/multiple-output systems

Design and analysis of genetic feedback architectures for synthetic biology

Synthetic Biology seeks to design and assemble novel biological systems with favourable properties. It allows us to comprehend and modify the fundamental mechanisms of life and holds significant promise in revolutionizing current technologies ranging from medicine and biomanufacturing to energy and environmental protection. Biological processes constitute remarkably complex dynamical systems operating impeccably well in messy and constantly changing environments. Their ability to do so is rooted in sophisticated molecular control architectures crafted by natural evolutionary innovation over billions of years. Such control architectures, often blended with human-engineering approaches, are the key to realizing efficient and reliable synthetic biological systems. Aiming to accelerate the development of the latter, the present thesis addresses some fundamental challenges in biomolecular systems and control design. We begin by elucidating biological mechanisms of temporal gradient computation, enabling cells to adjust their behaviour in response to anticipated environmental changes. Specifically, we introduce biomolecular motifs capable of functioning as highly tunable and accurate signal differentiators to input molecular signals around their nominal operation. We investigate strategies to deal with high-frequency input signal components which can be detrimental to the performance of most differentiators. We ascertain the occurrence of such motifs in natural regulatory networks and demonstrate the potential of synthetic experimental realizations. Our motifs can serve as reliable speed biosensors and can form the basis for derivative feedback control. Motivated by the pervasiveness of Proportional-Integral-Derivative (PID) controllers in modern technological applications, we present the realization of a PID controller via biomolecular reactions employing, among others, our differentiator motifs. This biomolecular architecture represents a PID control law with set point weighting and filtered derivative action, offering robust regulation of a single-output biological process with enhanced dynamic performance and low levels of stochastic noise. It is characterized by significant ease of tuning and can be of particular experimental interest in molecular programming applications. Finally, we investigate efficient regulation strategies for multi-output biological processes with internal coupling interactions, expanding previously established single-output control approaches. More specifically, we propose control schemes allowing for robust manipulation of the outputs in various ways, namely manipulation of their product/ratio, linear combinations of them as well as manipulation of each of the outputs independently. Our analysis is centered around two-output biological processes, yet the scalability of the proposed regulation strategies to processes with a higher number of outputs is highlighted. In parallel, their experimental implementability is explored in both in vivo and in vitro settings

Identification and Adaptive Control for High-performance AC Drive Systems.

High-performance AC machinery and drive systems can be found in a variety of applications ranging from motion control to vehicle propulsion. However, machine parameters can vary significantly with electrical frequency, flux levels, and temperature, degrading the performance of the drive system. While adaptive control techniques can be used to estimate machine parameters online, it is sometimes desirable to estimate certain parameters offline. Additionally, parameter identification and control are typically conflicting objectives with identification requiring plant inputs which are rich in harmonics, and control objectives often consisting of regulation to a constant set-point. In this dissertation, we present research which seeks to address these issues for high-performance AC machinery and drive systems. The first part of this dissertation concerns the offline identification of induction machine parameters. Specifically, we have developed a new technique for induction machine parameter identification which can easily be implemented using a voltage-source inverter. The proposed technique is based on fitting steady-state experimental data to the circular stator current locus in the stator flux linkage reference-frame for varying steady-state slip frequencies, and provides accurate estimates of the magnetic parameters, as well as the rotor resistance and core loss conductance. Experimental results for a 43 kW induction machine are provided which demonstrate the utility of the proposed technique by characterizing the machine over a wide range of flux levels, including magnetic saturation. The remainder of this dissertation concerns the development of generalizable design methodologies for Simultaneous Identification and Control (SIC) of overactuated systems via case studies with Permanent Magnet Synchronous Machines (PMSMs). Specifically, we present different approaches to the design of adaptive controllers for PMSMs which exploit overactuation to achieve identification and control objectives simultaneously. The first approach utilizes a disturbance decoupling control law to prevent the excitation input from perturbing the regulated output. The second approach uses a Lyapunov-based adaptive controller to constrain the states to the output error-zeroing manifold on which they are varied to provide excitation for parameter identification. Finally, a receding-horizon control allocation approach is presented which includes a metric for generating persistently exciting reference trajectories.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120862/1/davereed_1.pd

Using classical control theory for node buffer control of delay tolerant networks

Els satèl·lits no tenen un comportament autònom pel que fa a l'adquisició i transmissió de dades. En un entorn proper a la Terra amb pocs dispositius i connectivitat fiable, això no suposa una limitació pel que poden ser operats manualment gairebé en temps real. No obstant, amb major nombre de satèl·lits i en enentorns de Delay Tolerant Network (DTN), on la connectivitat és inestable i interrompuda amb llargues demores, cal confiar en l'automatització. En aquest aspecte, ja s'han realitzat estudis utilitzant el Reinforcement Learning per gestionar la memòria d'un node DTN amb resultats prometedors. Tot i així, aquests mètodes requereixen de molt temps de simulació i no són aptes per a ser implementats en els ordinadors de a bord. Es podria entendre, però, com un agent de control centralitzat amb resultats i xarxes neuronals delegades als satèl·lits. En aquest projecte, es presenta un enfocament més lleuger utilitzant Teoria de Control Clàssica modelant el node DTN com un sistema de cues on la taxa de transmissió s'ajusta automàticament per mantenir un estat concret de la memòria. En aquest aspecte, ja s'han realitzat estudis utilitzant el Reinforcement Learning per gestionar la memòria d'un node DTN amb resultats prometedors. No obstant això, aquests mètodes requereixen de molt temps de simulació i no són aptes per a ser implementats en els ordinadors de a bord. Es podrien entendre, però, com un agent de control centralitzat amb resultats i xarxes neuronals delegades als satèl·lits. En aquest projecte, es presenta un enfocament més lleuger utilitzant Teoria de Control Clàssica modelant el node DTN com un sistema de cues on la taxa de transmissió s'ajusta automàticament per mantenir un estat concret de la memòria.Los satélites carecen de un comportamiento autónomo con respecto a la adquisición y transmisión de datos. En un entorno cercano a la Tierra con pocos dispositivos y conectividad fiable, esto no supone una limitación por lo que pueden ser operados manualmente casi en tiempo real. Sin embargo, con mayor número de satélites en enentornos de Delay Tolerant Network (DTN), donde la conectividad es inestable e interrumpida con largas demoras, es necesario confiar en la automatización. En este aspecto, ya se han realizado estudios utilizando el Reinforcement Learning para gestionar la memoria de un nodo DTN con resultados prometedores. No obstante, estos métodos requieren de mucho tiempo de simulación y no son aptos para ser implementados en los ordenadores de a bordo. Se podrían entender, sin embargo, como un agente de control centralizado con resultados y redes neuronales delegadas a los satélites. En este proyecto, se presenta un enfoque más ligero utilizando Teoría de Control Clásica modelando el nodo DTN como un sistema de colas donde la tasa de transmisión se ajusta automáticamente para mantener un estado concreto de la memoria.Satellites lack autonomous behavior regarding data acquisition and transmission. In a near Earth environment with few spacecraft and reliable connectivity, this is not a limitation for which they can be almost real time and manually operated. However, in Delay/Disruption Tolerant Networks (DTN) environments where connectivity is unstable/disrupted with long delays and with greater number of spacecraft, it is necessary to rely on automation. Some approaches have already been made using Reinforcement Learning to manage DTN node buffers with promising results . However, this methods are highly computer intensive and are not suitable to be implemented in the on-board computers. They could, however, be understood as a centralized control agent with delegated results and Neural Net (NN) implementations. In this thesis, a lighter approach is presented using Classical Control Theory modeling the DTN node as a Queuing System using classical dynamics, where the transmission rate is autonomously adjusted to maintain a specific memory state

Multiobjective performance-based designs in fault estimation and isolation for discrete-time systems and its application to wind turbines

In this work, we develop a performance-based design of model-based observes and statistical-based decision mechanisms for achieving fault estimation and fault isolation in systems affected by unknown inputs and stochastic noises. First, through semidefinite programming, we design the observers considering different estimation performance indices as the covariance of the estimation errors, the fault tracking delays and the degree of decoupling from unknown inputs and from faults in other channels. Second, we perform a co-design of the observers and decision mechanisms for satisfying certain trade-off between different isolation performance indices: the false isolation rates, the isolation times and the minimum size of the isolable faults. Finally, we extend these results to a scheme based on a bank of observers for the case where multiple faults affect the system and isolability conditions are not verified. To show the effectiveness of the results, we apply these design strategies to a well-known benchmark of wind turbines which considers multiple faults and has explicit requirements over isolation times and false isolation rates

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

Wind Preview-Based Model Predictive Control of Multi-Rotor UAVs Using LiDAR

Autonomous outdoor operations of Unmanned Aerial Vehicles (UAVs), such as quadrotors, expose the aircraft to wind gusts causing a significant reduction in their position-holding performance. This vulnerability becomes more critical during the automated docking of these vehicles to outdoor charging stations. Utilising real-time wind preview information for the gust rejection control of UAVs has become more feasible due to the advancement of remote wind sensing technology such as LiDAR. This work proposes the use of a wind-preview-based Model Predictive Controller (MPC) to utilise remote wind measurements from a LiDAR for disturbance rejection. Here a ground-based LiDAR unit is used to predict the incoming wind disturbance at the takeoff and landing site of an autonomous quadrotor UAV. This preview information is then utilised by an MPC to provide the optimal compensation over the defined horizon. Simulations were conducted with LiDAR data gathered from field tests to verify the efficacy of the proposed system and to test the robustness of the wind-preview-based control. The results show a favourable improvement in the aircraft response to wind gusts with the addition of wind preview to the MPC; An 80% improvement in its position-holding performance combined with reduced rotational rates and peak rotational angles signifying a less aggressive approach to increased performance when compared with only feedback based MPC disturbance rejection. System robustness tests demonstrated a 1.75 s or 120% margin in the gust preview’s timing or strength respectively before adverse performance impact. The addition of wind-preview to an MPC has been shown to increase the gust rejection of UAVs over standard feedback-based MPC thus enabling their precision landing onto docking stations in the presence of wind gusts