Automation and Control Architecture for Hybrid Pipeline Robots

The aim of this research project, towards the automation of the Hybrid Pipeline Robot (HPR), is the development of a control architecture and strategy, based on reconfiguration of the control strategy for speed-controlled pipeline operations and self-recovering action, while performing energy and time management. The HPR is a turbine powered pipeline device where the flow energy is converted to mechanical energy for traction of the crawler vehicle. Thus, the device is flow dependent, compromising the autonomy, and the range of tasks it can perform. The control strategy proposes pipeline operations supervised by a speed control, while optimizing the energy, solved as a multi-objective optimization problem. The states of robot cruising and self recovering, are controlled by solving a neuro-dynamic programming algorithm for energy and time optimization, The robust operation of the robot includes a self-recovering state either after completion of the mission, or as a result of failures leading to the loss of the robot inside the pipeline, and to guaranteeing the HPR autonomy and operations even under adverse pipeline conditions Two of the proposed models, system identification and tracking system, based on Artificial Neural Networks, have been simulated with trial data. Despite the satisfactory results, it is necessary to measure a full set of robot’s parameters for simulating the complete control strategy. To solve the problem, an instrumentation system, consisting on a set of probes and a signal conditioning board, was designed and developed, customized for the HPR’s mechanical and environmental constraints. As a result, the contribution of this research project to the Hybrid Pipeline Robot is to add the capabilities of energy management, for improving the vehicle autonomy, increasing the distances the device can travel inside the pipelines; the speed control for broadening the range of operations; and the self-recovery capability for improving the reliability of the device in pipeline operations, lowering the risk of potential loss of the robot inside the pipeline, causing the degradation of pipeline performance. All that means the pipeline robot can target new market sectors that before were prohibitive

Nonlinear predictive restricted structure control

This thesis defines new developments in predictive restricted structure control for industrial applications. It begins by describing the augmented system for both state-space and polynomial model descriptions. These descriptions can contain the plant model, the disturbance model, and any additional essential model subsystems. It then describes the predictive restricted structure control solution for both linear and nonlinear systems in state-space form. The solution utilizes the recent development in nonlinear predictive generalized minimum variance by adding a general operator subsystem that defines nonlinear system along with the linear or the linear parameter varying output subsystem. The next contribution is the polynomial predictive restricted structure control algorithm for polynomial linear parameter varying model that may result from nonlinear equations or experimental data-driven model identification. This algorithm utilizes the generalised predictive control method to approximate and control nonlinear systems in the linear parameter varying system inputoutput transfer operator matrices. The solution is simple in unconstrained and constrained optimization solutions and required a small computing capacity. Four examples have been chosen to test the algorithms for different nonlinear characteristics. In the first three examples, state-space versions of the algorithm for the linear, the quasi-linear parameter varying and the state-dependent were employed to control the quadruple tank process, electronic throttle body, and the continuous stirred tank reactors. In the last example, the polynomial linear parameter varying restricted structure controller is used to control automotive variable camshaft timing system.This thesis defines new developments in predictive restricted structure control for industrial applications. It begins by describing the augmented system for both state-space and polynomial model descriptions. These descriptions can contain the plant model, the disturbance model, and any additional essential model subsystems. It then describes the predictive restricted structure control solution for both linear and nonlinear systems in state-space form. The solution utilizes the recent development in nonlinear predictive generalized minimum variance by adding a general operator subsystem that defines nonlinear system along with the linear or the linear parameter varying output subsystem. The next contribution is the polynomial predictive restricted structure control algorithm for polynomial linear parameter varying model that may result from nonlinear equations or experimental data-driven model identification. This algorithm utilizes the generalised predictive control method to approximate and control nonlinear systems in the linear parameter varying system inputoutput transfer operator matrices. The solution is simple in unconstrained and constrained optimization solutions and required a small computing capacity. Four examples have been chosen to test the algorithms for different nonlinear characteristics. In the first three examples, state-space versions of the algorithm for the linear, the quasi-linear parameter varying and the state-dependent were employed to control the quadruple tank process, electronic throttle body, and the continuous stirred tank reactors. In the last example, the polynomial linear parameter varying restricted structure controller is used to control automotive variable camshaft timing system

Correct-By-Construction Control Synthesis for Systems with Disturbance and Uncertainty

This dissertation focuses on correct-by-construction control synthesis for Cyber-Physical Systems (CPS) under model uncertainty and disturbance. CPSs are systems that interact with the physical world and perform complicated dynamic tasks where safety is often the overriding factor. Correct-by-construction control synthesis is a concept that provides formal performance guarantees to closed-loop systems by rigorous mathematic reasoning. Since CPSs interact with the environment, disturbance and modeling uncertainty are critical to the success of the control synthesis. Disturbance and uncertainty may come from a variety of sources, such as exogenous disturbance, the disturbance caused by co-existing controllers and modeling uncertainty. To better accommodate the different types of disturbance and uncertainty, the verification and control synthesis methods must be chosen accordingly. Four approaches are included in this dissertation. First, to deal with exogenous disturbance, a polar algorithm is developed to compute an avoidable set for obstacle avoidance. Second, a supervised learning based method is proposed to design a good student controller that has safety built-in and rarely triggers the intervention of the supervisory controller, thus targeting the design of the student controller. Third, to deal with the disturbance caused by co-existing controllers, a Lyapunov verification method is proposed to formally verify the safety of coexisting controllers while respecting the confidentiality requirement. Finally, a data-driven approach is proposed to deal with model uncertainty. A minimal robust control invariant set is computed for an uncertain dynamic system without a given model by first identifying the set of admissible models and then simultaneously computing the invariant set while selecting the optimal model. The proposed methods are applicable to many real-world applications and reflect the notion of using the structure of the system to achieve performance guarantees without being overly conservative.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145933/1/chenyx_1.pd

Fault Diagnosis and Performance Recovery Based on the Dynamic Safety Margin

The complexity of modern industrial processes makes high dependability an essential demand for reducing production loss, avoiding equipment damage, and increasing human safety. A more dependable system is a system that has the ability to: 1) detect faults as fast as possible; 2) diagnose them accurately; 3) recover the system to the nominal performance as much as possible. Therefore, a robust Fault Detection and Isolation (FDI) and a Fault Tolerant Control (FTC) system design have attained increased attention during the last decades. This thesis focuses on the design of a robust model-based FDI system and a performance recovery controller based on a new performance index called Dynamic Safety Margin (DSM). The DSM index is used to measure the distance between a predefined safety boundary in the state space and the system state trajectory as it evolves. The DSM concept, its computation methods, and its relationship to the state constraints are addressed. The DSM can be used in different control system applications; some of them are highlighted in this work. Controller design based on DSM is especially useful for safety-critical systems to maintain a predefined margin of safety during the transient and in the presence of large disturbances. As a result, the application of DSM to controller design and adaptation is discussed in particular for model predictive control (MPC) and PID controller. Moreover, an FDI scheme based on the analysis of the DSM is proposed. Since it is difficult to isolate different types of faults using a single model, a multi-model approach is employed in this FDI scheme. The proposed FDI scheme is not restricted to a special type of fault. In some faulty situations, recovering the system performance to the nominal one cannot be fulfilled. As a result, reducing the output performance is necessary in order to increase the system availability. A framework of FTC system is proposed that combines the proposed FDI and the controllers design based on DSM, in particular MPC, with accepted degraded performance in order to generate a reliable FTC system. The DSM concept and its applications are illustrated using simulation examples. Finally, these applications are implemented in real-time for an experimental two-tank system. The results demonstrate the fruitfulness of the introduced approaches

Dynamic Reactive Power Control of Isolated Power Systems

This dissertation presents dynamic reactive power control of isolated power systems. Isolated systems include MicroGrids in islanded mode, shipboard power systems operating offshore, or any other power system operating in islanded mode intentionally or due to a fault. Isolated power systems experience fast transients due to lack of an infinite bus capable of dictating the voltage and frequency reference. This dissertation only focuses on reactive control of islanded MicroGrids and AC/DC shipboard power systems. The problem is tackled using a Model Predictive Control (MPC) method, which uses a simplified model of the system to predict the voltage behavior of the system in future. The MPC method minimizes the voltage deviation of the predicted bus voltage; therefore, it is inherently robust and stable. In other words, this method can easily predict the behavior of the system and take necessary control actions to avoid instability. Further, this method is capable of reaching a smooth voltage profile and rejecting possible disturbances in the system. The studied MicroGrids in this dissertation integrate intermittent distributed energy resources such as wind and solar generators. These non-dispatchable sources add to the uncertainty of the system and make voltage and reactive control more challenging. The model predictive controller uses the capability of these sources and coordinates them dynamically to achieve the voltage goals of the controller. The MPC controller is implemented online in a closed control loop, which means it is self-correcting with the feedback it receives from the system

Model Predictive Control of Complex Systems including Fault Tolerance Capabilities: Application to Sewer Networks

El control en temps real de xarxes de clavegueram (RTC) desenvolupa un paper fonamental dins de la gestió dels recursos hídrics relacionats amb el cicle urbà de l'aigua i, en general, amb el seu cicle natural. Un adequat disseny de control per a xarxes de clavegueram evita impactes mediambientals negatius originats per inundacions i/o alta pol·lució producte de condicions meteorològiques xtremes. No obstant, s'ha de tenir en compte que aquestes xarxes, a més de la seva grandària i quantitat de variables i instrumentació, són sistemes rics en dinàmiques complexes i altament no lineals. Aquest fet, unit a les condicions atmosfèriques extremes, fan necessari utilitzar una estratègia de control capaç¸ de suportar totes aquestes condicions. En aquest sentit, dins del camp del (RTC) de xarxes de clavegueram es destaquen les estratègies de control predictiu basat en model (MPC), les quals són alternatives adequades per al control de configuracions multivariable i de gran escala, aplicades com estratègies de control global del sistema. A m´es, permeten optimitzar la resposta del sistema tenint en compte diversos índexs de rendiment (control multiobjectiu). Aquesta tesi s'enfoca en el disseny de controladors MPC per a xarxes de clavegueram considerant diverses metodologies de modelat. Addicionalment, analitza les situacions en les quals es presenten fallades als actuadors de la xarxa, proposant estratègies per a mantenir la resposta del sistema amb la menor degradació possible dels objectius de control, malgrat la presència de la fallada. En la primera part s'introdueixen els conceptes principals dels temes a tractar en la tesi: xarxes de clavegueram, MPC i tolerància a fallades. Seguidament, es presenta la tècnica de modelat utilitzada per a definir el model d'una xarxa de clavegueram. Finalment, es presenta i descriu el cas d'aplicació en la tesi: la xarxa de clavegueram de Barcelona (Espanya). La segona part es centra en dissenyar controladors MPC per al cas d'estudi. S'han considerat dos tipus de model de xarxa: (i) un model lineal, el qual aproxima els comportaments no lineals de la xarxa, donant origen a estratègies MPC lineals amb les seves conegudes avantatges de l'optimització convexa i escalabilitat; i (ii) un model híbrid, el qual inclou les dinàmiques de commutació més representatives d'una xarxa de clavegueram com són els sobreeixidors. En aquest últim cas es proposa una nova etodologia de modelat híbrid per a xarxes de clavegueram i es dissenyen estratègies de control predictives basades en aquests models (HMPC), les quals calculen lleis de control globalment òptimes. Addicionalment, es proposa una estratègia de relaxació del problema d'optimització discreta per a evitar els grans temps de còmput requerits per a calcular la llei de control HMPC. Finalment, la tercera part de la tesi s'encarrega d'estudiar les capacitats de tolerància a fallades en actuadors de llaços de control MPC. En el cas de xarxes de clavegueram, la tesi considera fallades en les comportes de derivació i de retenció d'aigües residuals. A més, es proposa un modelat híbrid per a fallades que faci que el problema d'optimització associat no perdi la seva convexitat. Així, es proposen dos estratègies de HMPC tolerant a fallades (FTMPC): l'estratègia activa, la qual utilitza les avantatges d'una arquitectura de control tolerant a fallades (FTC), i l'estratègia passiva, la qual només depèn de la robustesa intrínseca de les tècniques de control MPC. Com a extensió a l'estudi de tolerància a fallades, es proposa una avaluació d'admissibilitat per a configuracions d'actuadors en fallada agafant com a referència la degradació dels objectius de control. El m-etode, basat en satisfacció de restriccions, permet avaluar l'admissibilitat d'una configuració d'actuadors en fallada i, en cas de no ser admesa, evitaria el procés de resoldre un problema d'optimització amb un alt cost computacional. Paraules clau: control predictiu basat en model, sistemes de clavegueram, sistemes híbrids, MLD, control tolerant a fallades, satisfacció de restriccions.El control en tiempo real de redes de alcantarillado (RTC) desempeña un papel fundamental dentro de la gestión de los recursos hídricos relacionados con el ciclo urbano del agua y, en general, con su ciclo natural. Un adecuado diseño de control para de redes de alcantarillado evita impactos medioambientales negativos originados por inundaciones y/o alta polución producto de condiciones meteorológicas extremas. Sin embargo, se debe tener en cuenta que estas redes, además de su gran tamaño y cantidad de variables e instrumentación, son sistemas ricos en dinámicas complejas y altamente no lineales. Este hecho, unido a unas condiciones atmosféricas extremas, hace necesario utilizar una estrategia de control capaz de soportar todas estas condiciones. En este sentido, dentro del campo del RTC de redes de alcantarillado se destacan las estrategias de control predictivo basadas en modelo (MPC), las cuales son alternativas adecuadas para el control de configuraciones multivariable y de gran escala, aplicadas como estrategias de control global del sistema. Además, permiten optimizar el desempeño del sistema teniendo en cuenta diversos índices de rendimiento (control multiobjetivo). Esta tesis se enfoca en el diseño de controladores MPC para redes de alcantarillado considerando diversas metodologías de modelado. Adicionalmente, analiza las situaciones en las cuales se presentan fallos en los actuadores de la red, proponiendo estrategias para mantener el desempeño del sistema y evitando la degradación de los objetivos de control a pesar de la presencia del fallo. En la primera parte se introducen los conceptos principales de los temas a tratar en la tesis: redes de alcantarillado, MPC y tolerancia a fallos. Además, se presenta la técnica de modelado utilizada para definir el modelo de una red de alcantarillado. Finalmente, se presenta y describe el caso de aplicación considerado en la tesis: la red de alcantarillado de Barcelona (España). La segunda parte se centra en diseñar controladores MPC para el caso de estudio. Dos tipos de modelo de la red son considerados: (i) un modelo lineal, el cual aproxima los comportamientos no lineales de la red, dando origen a estrategias MPC lineales con sus conocidas ventajas de optimización convexa y escalabilidad; y (ii) un modelo híbrido, el cual incluye las dinámicas de conmutación más representativas de una red de alcantarillado como lo son los rebosaderos. En este último caso se propone una nueva metodología de modelado híbrido para redes de alcantarillado y se diseñan estrategias de control predictivas basadas en estos modelos (HMPC), las cuales calculan leyes de control globalmente óptimas. Adicionalmente se propone una estrategia de relajación del problema de optimización discreto para evitar los grandes tiempos de cálculo que pudieran ser requeridos al obtener la ley de control HMPC. Finalmente, la tercera parte de la tesis se ocupa de estudiar las capacidades de tolerancia a fallos en actuadores de lazos de control MPC. En el caso de redes de alcantarillado, la tesis considera fallos en las compuertas de derivación y de retención de aguas residuales. De igual manera, se propone un modelado híbrido para los fallos que haga que el problema de optimización asociado no pierda su convexidad. Así, se proponen dos estrategias de HMPC tolerante a fallos (FTMPC): la estrategia activa, la cual utiliza las ventajas de una arquitectura de control tolerante a fallos (FTC), y la estrategia pasiva, la cual sólo depende de la robustez intrínseca de las técnicas de control MPC. Como extensión al estudio de tolerancia a fallos, se propone una evaluación de admisibilidad para configuraciones de actuadores en fallo tomando como referencia la degradación de los objetivos de control. El método, basado en satisfacción de restricciones, permite evaluar la admisibilidad de una configuración de actuadores en fallo y, en caso de no ser admitida, evitaría el proceso de resolver un problema de optimización con un alto coste computacional. Palabras clave: control predictivo basado en modelo, sistemas de alcantarillado, sistemas híbridos, MLD, control tolerante a fallos, satisfacción de restricciones.Real time control (RTC) of sewer networks plays a fundamental role in the management of hydrological systems, both in the urban water cycle, as well as in the natural water cycle. An adequate design of control systems for sewer networks can prevent the negative impact on the environment that Combined Sewer Overflow (CSO) as well as preventing flooding within city limits when extreme weather conditions occur. However, sewer networks are large scale systems with many variables, complex dynamics and strong nonlinear behaviour. Any control strategy applied should be capable of handling these challenging requirements. Within the field of RTC of sewer networks for global network control, the Model Predictive Control (MPC) strategy stands out due to its ability to handle large scale, nonlinear and multivariable systems. Furthermore, this strategy allows performance optimization, taking into account several control objectives simultaneously. This thesis is devoted to the design of MPC controllers for sewer networks, as well as the complementary modelling methodologies. Furthermore, scenarios where actuator faults occur are specially considered and strategies to maintain performance or at least minimizing its degradation in presence of faults are proposed. In the first part of this thesis, the basic concepts are introduced: sewer networks, MPC and fault tolerant control. In addition, the modelling methodologies used to describe such systems are presented. Finally the case study of this thesis is described: the sewer network of the city of Barcelona (Spain). The second part of this thesis is centered on the design of MPC controllers for the proposed case study. Two types of models are considered: (i) a linear model whose corresponding MPC strategy is known for its advantages such as convexity of the optimization problem and existing pro of sofstability, and (ii) a hybrid model which allows the inclusion of state dependent hybrid dynamics such as weirs. In the latter case, a new hybrid modelling methodology is introduced and hybrid model predictive control (HMPC) strategies based on these models are designed. Furthermore, strategies to relax the optimization problem are introduced to reduce calculation time required for the HMPC control law. Finally, the third part of this thesis is devoted to study the fault tolerance capabilities of MPC controllers. Actuator faults in retention and redirection gates are considered. Additionally, hybrid modelling techniques are presented for faults which, in the linear case, can not be treated without loosing convexity of the related optimization problem. Two fault tolerant HMPC strategies are compared: the active strategy, which uses the information from a diagnosis system to maintain control performance, and the passive strategy which only relies on the intrinsic robustness of the MPC control law. As an extension to the study of fault tolerance, the admissibility of faulty actuator configurations is analyzed with regard to the degradation of control objectives. The method, which is based on constraint satisfaction, allows the admissibility evaluation of actuator fault configurations, which avoids the process of solving the optimization problem with its related high computational cost. Keywords: MPC, sewer networks, hybrid systems, MLD, fault tolerant control, constraints satisfaction

Nachweislich sichere Bewegungsplanung für autonome Fahrzeuge durch Echtzeitverifikation

This thesis introduces fail-safe motion planning as the first approach to guarantee legal safety of autonomous vehicles in arbitrary traffic situations. The proposed safety layer verifies whether intended trajectories comply with legal safety and provides fail-safe trajectories when intended trajectories result in safety-critical situations. The presented results indicate that the use of fail-safe motion planning can drastically reduce the number of traffic accidents.Die vorliegende Arbeit führt ein neuartiges Verifikationsverfahren ein, mit dessen Hilfe zum ersten Mal die verkehrsregelkonforme Sicherheit von autonomen Fahrzeugen gewährleistet werden kann. Das Verifikationsverfahren überprüft, ob geplante Trajektorien sicher sind und generiert Rückfalltrajektorien falls diese zu einer unsicheren Situation führen. Die Ergebnisse zeigen, dass die Verwendung des Verfahrens zu einer deutlichen Reduktion von Verkehrsunfällen führt