Resilience-oriented control and communication framework for cyber-physical microgrids

Climate change drives the energy supply transition from traditional fossil fuel-based power generation to renewable energy resources. This transition has been widely recognised as one of the most significant developing pathways promoting the decarbonisation process toward a zero-carbon and sustainable society. Rapidly developing renewables gradually dominate energy systems and promote the current energy supply system towards decentralisation and digitisation. The manifestation of decentralisation is at massive dispatchable energy resources, while the digitisation features strong cohesion and coherence between electrical power technologies and information and communication technologies (ICT). Massive dispatchable physical devices and cyber components are interdependent and coupled tightly as a cyber-physical energy supply system, while this cyber-physical energy supply system currently faces an increase of extreme weather (e.g., earthquake, flooding) and cyber-contingencies (e.g., cyberattacks) in the frequency, intensity, and duration. Hence, one major challenge is to find an appropriate cyber-physical solution to accommodate increasing renewables while enhancing power supply resilience. The main focus of this thesis is to blend centralised and decentralised frameworks to propose a collaboratively centralised-and-decentralised resilient control framework for energy systems i.e., networked microgrids (MGs) that can operate optimally in the normal condition while can mitigate simultaneous cyber-physical contingencies in the extreme condition. To achieve this, we investigate the concept of "cyber-physical resilience" including four phases, namely prevention/upgrade, resistance, adaption/mitigation, and recovery. Throughout these stages, we tackle different cyber-physical challenges under the concept of microgrid ranging from a centralised-to-decentralised transitional control framework coping with cyber-physical out of service, a cyber-resilient distributed control methodology for networked MGs, a UAV assisted post-contingency cyber-physical service restoration, to a fast-convergent distributed dynamic state estimation algorithm for a class of interconnected systems.Open Acces

Cyber-Physical Co-Design of Wireless Control Systems

Wireless sensor-actuator network (WSAN) technology is gaining rapid adoption in process industries because of its advantages in lowering deployment and maintenance cost in challenging environments. While early success of industrial WSANs has been recognized, significant potential remains in exploring WSANs as unified networks for industrial plants. This thesis research explores a cyber-physical co-design approach to design wireless control systems. To enable holistic studies of wireless control systems, we have developed the Wireless Cyber-Physical Simulator (WCPS), an integrated co-simulation environment that integrates Simulink and our implementation of WSANs based on the industrial WirelessHART standard. We further develop novel WSAN protocols tailored for advanced control designs for networked control systems. WCPS now works as the first simulator that features both linear and nonlinear physical plant models, state-of-art WirelessHART protocol stack, and realistic wireless network characteristics. A realistic wireless structural control study sheds light on the challenges of WSC and the limitations of a traditional structural control approach under realistic wireless conditions. Systematic emergency control results demonstrate that our real-time emergency communication approach enables timely emergency handling, while allowing regular feedback control loops to effectively share resources in WSANs during normal operations. A co-joint study of wireless routing and control highlights the importance of the co-design approach of wireless networks and control

Predictive control for packet dropouts in wireless networked control systems

A predictive PID controller is presented to achieve stability in wireless networked control systems, where the communication is subject to data packet dropouts in both communication routes: sensor to control and control to actuator transmission. The control strategy is based on General Predictive Control (GPC). A Kalman filter and a consecutive dropouts compensator algorithm have been added to the control scheme. The purpose of the algorithm is to develop an estimation and control system that maintains information of the sensor packets and the control actions. Several experiments using the TrueTime network simulator are provided to demonstrate the algorithm and its effectiveness

PID controller design and tuning in networked control systems

Networked control systems (NCS) are distributed real-time computing and control systems with sensors, actuators and controllers that communicate over a shared medium. The distributed nature of NCS and issues related to the shared communication medium pose significant challenges for control design, as the control system no longer follows the rules of classical control theory. The main problems that are not well covered by the traditional control theory are varying time-delays due to communication and computation, and packet losses. During recent years, the control design of NCS and varying time-delay systems has been extensively researched. This investment has provided us with new results on stability. Often the proposed methods and solutions are far too complex for industrial use, especially if wireless automation applications are considered. The algorithms are computationally heavy, possibly requiring complete information from say, a network of hundreds or thousands of nodes. In the wireless case this is not feasible. The above justifies the use and research of simple controller structures and algorithms for NCS. Despite the growing interest towards more advanced control algorithms, the Proportional-Integral-Derivative (PID) controller still has a dominant status in the industry. Nevertheless, using PID for NCS has not been thoroughly investigated, especially with regard to controller tuning. This thesis proposes several PID tuning methods, which provide robustness against the challenges of NCS, namely varying time-delays (jitter) and packet loss. The doctoral thesis consists of a summary and eight publications that focus on the PID controller design, tuning and experimentation in NCS. The thesis includes a literature review of recent stability and control design results in NCS, a summary of publications and the original publications. The control design methods applied in the publications are also reviewed. In the thesis, several new methods for PID tuning in NCS are proposed. To make the methods usable, a PID tuning tool that implements one of the tuning methods is also developed. In order to verify the results of control design with real processes, the thesis suggests using the MoCoNet platform developed at the Helsinki University of Technology, Finland. The platform provides the tools for remote laboratory experiments in NCS settings. The results of the thesis indicate that the PID controller is well suited for NCS provided that the properties of the integrated communication and control system are taken into account in the tuning phase

Control over the Cloud : Offloading, Elastic Computing, and Predictive Control

The thesis studies the use of cloud native software and platforms to implement critical closed loop control. It considers technologies that provide low latency and reliable wireless communication, in terms of edge clouds and massive MIMO, but also approaches industrial IoT and the services of a distributed cloud, as an extension of commercial-of-the-shelf software and systems.First, the thesis defines the cloud control challenge, as control over the cloud and controller offloading. This is followed by a demonstration of closed loop control, using MPC, running on a testbed representing the distributed cloud.The testbed is implemented using an IoT device, clouds, next generation wireless technology, and a distributed execution platform. Platform details are provided and feasibility of the approach is shown. Evaluation includes relocating an on-line MPC to various locations in the distributed cloud. Offloaded control is examined next, through further evaluation of cloud native software and frameworks. This is followed by three controller designs, tailored for use with the cloud. The first controller solves MPC problems in parallel, to implement a variable horizon controller. The second is a hierarchical design, in which rate switching is used to implement constrained control, with a local and a remote mode. The third design focuses on reliability. Here, the MPC problem is extended to include recovery paths that represent a fallback mode. This is used by a control client if it experiences connectivity issues.An implementation is detailed and examined.In the final part of the thesis, the focus is on latency and congestion. A cloud control client can experience long and variable delays, from network and computations, and used services can become overloaded. These problems are approached by using predicted control inputs, dynamically adjusting the control frequency, and using horizontal scaling of the cloud service. Several examples are shown through simulation and on real clouds, including admitting control clients into a cluster that becomes temporarily overloaded

Data analytics for stochastic control and prognostics in cyber-physical systems

In this dissertation, several novel cyber fault diagnosis and prognosis and defense methodologies for cyber-physical systems have been proposed. First, a novel routing scheme for wireless mesh network is proposed. An effective capacity estimation for P2P and E2E path is designed to guarantee the vital transmission safety. This scheme can ensure a high quality of service (QoS) under imperfect network condition, even cyber attacks. Then, the imperfection, uncertainties, and dynamics in the cyberspace are considered both in system model and controller design. A PDF identifier is proposed to capture the time-varying delays and its distribution. With the modification of traditional stochastic optimal control using PDF of delays, the assumption of full knowledge of network imperfection in priori is relaxed. This proposed controller is considered a novel resilience control strategy for cyber fault diagnosis and prognosis. After that, we turn to the development of a general framework for cyber fault diagnosis and prognosis schemes for CPSs wherein the cyberspace performance affect the physical system and vice versa. A novel cyber fault diagnosis scheme is proposed. It is capable of detecting cyber fault by monitoring the probability of delays. Also, the isolation of cyber and physical system fault is achieved with cooperating with the traditional observer based physical system fault detection. Next, a novel cyber fault prognosis scheme, which can detect and estimate cyber fault and its negative effects on system performance ahead of time, is proposed. Moreover, soft and hard cyber faults are isolated depending on whether potential threats on system stability is predicted. Finally, one-class SVM is employed to classify healthy and erroneous delays. Then, another cyber fault prognosis based on OCSVM is proposed --Abstract, page iv

Design and implementation of event-based multi-rate controllers for networked control systems

Tesis por compendio[ES] Con esta tesis se pretende dar solución a algunos de los problemas más habituales que aparecen en los Sistemas de control basados en red (NCS) como son los retardos variables en el tiempo, las pérdidas y el desorden de paquetes, y la restricción de ancho de banda y de recursos computacionales y energéticos de los dispositivos que forman parte del sistema de control. Para ello se ha planteado la integración de técnicas de control multifrecuencial, de control basado en paquetes, de control basado en predictor y de control basado en eventos. Los diseños de control realizados se han simulado utilizando Matlab-Simulink y Truetime, se ha analizado su estabilidad mediante LMIs y QFT, y se han validado experimentalmente en un péndulo invertido, un robot cartesiano 3D y en robots móviles de bajo coste. El artículo 1 aborda el control basado en eventos, el cual minimiza el ancho de banda consumido en el NCS mediante un control basado en eventos periódicos y presenta un método para obtener sus parámetros óptimos para el sistema específico en que se utilice. Los artículos 2, 4 y 6 añaden el control basado en paquetes, así como el control multifrecuencia, que aborda problemas de falta de datos por bajo uso del sensor y los retardos, pérdidas y desórdenes de paquetes en la red. También afrontan, mediante tecnicas de predicción basadas en un filtro de Kalman multifrecuencia variable en el tiempo, los problemas de ruido y perturbaciones, así como la observación de los estados completos del sistema. El artículo 7 hace frente a un modelo no lineal que utiliza las anteriores soluciones junto con un filtro de Kalman extendido para presentar otro tipo de estructura para un vehículo autónomo que, gracias a la información futura obtenida mediante estas técnicas, puede realizar de forma remota tareas de alto nivel como es la toma de decisiones y la monitorización de variables. Los artículos 3 y 5, presentan una forma de obtener y analizar la respuesta en frecuencia de sistemas SISO multifrecuencia y estudian su comportamiento ante ciertas incertidumbres o problemas en la red haciendo uso de procedimientos QFT.[CA] Amb aquesta tesi es pretén donar solució a alguns dels problemes més habituals que apareixen als Sistemes de Control Basats en xarxa (NCS) com son els retards d'accés i transferència variables en el temps, les pèrdues y desordenament de paquets, i la restricció d'ampli de banda així com de recursos computacionals i energètics dels dispositius que foment part del sistema de control. Per tal de resoldre'ls s'ha plantejat la integració de tècniques de control multifreqüencial, de control basat en paquets, de control basat en predictor i de control basat en events. Els dissenys de control realitzats s'han simulat fent ús de Matlab-Simulink i de TrueTime, s'ha analitzat la seua estabilitat mitjançant LMIs i QFT, i s'han validat experimentalment en un pèndul invertit, un robot cartesià 3D i en robots mòbils de baix cost. L'article 1 aborda el control basat en events, el qual minimitza l'ampli de banda consumit a l'NCS mitjançant un control basat en events periòdics i presenta un mètode per a obtindré els seus paràmetres òptims per al sistema específic en el qual s'utilitza. Els articles 2, 4 i 6 afegeixen el control basat en paquets, així com el control multifreqüència, que aborda problemes de falta de dades per el baix us del sensor i els retards, pèrdues i desordre de paquets en la xarxa. També afronten, mitjançant tècniques de predicció basades en un filtre de Kalman multifreqüència variable en el temps. Els problemes de soroll i pertorbacions, així com la observació dels estats complets del sistema. L'article 7 fa referència a un model no lineal que utilitza les anteriors solucions junt a un filtre de Kalman estès per a presentar altre tipus d'estructura per a un vehicle autònom que, gracies a la informació futura obtinguda mitjançant aquestes tècniques, pot realitzar de manera remota tasques d'alt nivell com son la presa de decisions i la monitorització de variables. Els articles 3 y 5 presenten la manera d'obtindre i analitzar la resposta en frequencia de sistemes SISO multifreqüència i estudien el seu comportament front a certes incerteses o problemes en la xarxa fent us de procediments QFT.[EN] This thesis attempts to solve some of the most frequent issues that appear in Networked Control Systems (NCS), such as time-varying delays, packet losses and packet disorders and the bandwidth limitation. Other frequent problems are scarce computational and energy resources of the local system devices. Thus, it is proposed to integrate multirate control, packet-based control, predictor-based control and event-based control techniques. The control designs have been simulated using Matlab-Simulink and Truetime, the stability has been analysed by LMIs and QFT, and the experimental validation has been done on an inverted pendulum, a 3D cartesian robot and in low-cost mobile robots. Paper 1 addresses event-based control, which minimizes the bandwidth consumed in NCS through a periodic event-triggered control and presents a method to obtain the optimal parameters for the specific system used. Papers 2, 4 and 6 include packet-based control and multirate control, addressing problems such as network delays, packet dropouts and packet disorders, and the scarce data due to low sensor usage in order to save battery in sensing tasks and transmissions of the sensed data. Also addressed, is how despite the existence of measurement noise and disturbances, time-varying dual-rate Kalman filter based prediction techniques observe the complete state of the system. Paper 7 tackles a non-linear model that uses all the previous solutions together with an extended Kalman filter to present another type of structure for an autonomous vehicle that, due to future information obtained through these techniques, can remotely carry out high level tasks, such as decision making and monitoring of variables. Papers 3 and 5, present a method for obtaining and analyzing the SISO dual-rate frequency response and using QFT procedures to study its behavior when faced with specific uncertainties or network problems.This work was supported by the Spanish Ministerio de Economía y Competitividad under Grant referenced TEC2012-31506.Alcaina Acosta, JJ. (2020). Design and implementation of event-based multi-rate controllers for networked control systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/159884TESISCompendi

Qos-aware fine-grained power management in networked computing systems

Power is a major design concern of today\u27s networked computing systems, from low-power battery-powered mobile and embedded systems to high-power enterprise servers. Embedded systems are required to be power efficiency because most embedded systems are powered by battery with limited capacity. Similar concern of power expenditure rises as well in enterprise server environments due to cooling requirement, power delivery limit, electricity costs as well as environment pollutions. The power consumption in networked computing systems includes that on circuit board and that for communication. In the context of networked real-time systems, the power dissipation on wireless communication is more significant than that on circuit board. We focus on packet scheduling for wireless real-time systems with renewable energy resources. In such a scenario, it is required to transmit data with higher level of importance periodically. We formulate this packet scheduling problem as an NP-hard reward maximization problem with time and energy constraints. An optimal solution with pseudo polynomial time complexity is presented. In addition, we propose a sub-optimal solution with polynomial time complexity. Circuit board, especially processor, power consumption is still the major source of system power consumption. We provide a general-purposed, practical and comprehensive power management middleware for networked computing systems to manage circuit board power consumption thus to affect system-level power consumption. It has the functionalities of power and performance monitoring, power management (PM) policy selection and PM control, as well as energy efficiency analysis. This middleware includes an extensible PM policy library. We implemented a prototype of this middleware on Base Band Units (BBUs) with three PM policies enclosed. These policies have been validated on different platforms, such as enterprise servers, virtual environments and BBUs. In enterprise environments, the power dissipation on circuit board dominates. Regulation on computing resources on board has a significant impact on power consumption. Dynamic Voltage and Frequency Scaling (DVFS) is an effective technique to conserve energy consumption. We investigate system-level power management in order to avoid system failures due to power capacity overload or overheating. This management needs to control the power consumption in an accurate and responsive manner, which cannot be achieve by the existing black-box feedback control. Thus we present a model-predictive feedback controller to regulate processor frequency so that power budget can be satisfied without significant loss on performance. In addition to providing power guarantee alone, performance with respect to service-level agreements (SLAs) is required to be guaranteed as well. The proliferation of virtualization technology imposes new challenges on power management due to resource sharing. It is hard to achieve optimization in both power and performance on shared infrastructures due to system dynamics. We propose vPnP, a feedback control based coordination approach providing guarantee on application-level performance and underlying physical host power consumption in virtualized environments. This system can adapt gracefully to workload change. The preliminary results show its flexibility to achieve different levels of tradeoffs between power and performance as well as its robustness over a variety of workloads. It is desirable for improve energy efficiency of systems, such as BBUs, hosting soft-real time applications. We proposed a power management strategy for controlling delay and minimizing power consumption using DVFS. We use the Robbins-Monro (RM) stochastic approximation method to estimate delay quantile. We couple a fuzzy controller with the RM algorithm to scale CPU frequency that will maintain performance within the specified QoS

Decoding the `Nature Encoded\u27 Messages for Wireless Networked Control Systems

Because of low installation and reconfiguration cost wireless communication has been widely applied in networked control system (NCS). NCS is a control system which uses multi-purpose shared network as communication medium to connect spatially distributed components of control system including sensors, actuator, and controller. The integration of wireless communication in NCS is challenging due to channel unreliability such as fading, shadowing, interference, mobility and receiver thermal noise leading to packet corruption, packet dropout and packet transmission delay. In this dissertation, the study is focused on the design of wireless receiver in order to exploit the redundancy in the system state, which can be considered as a `nature encoding\u27 for the messages. Firstly, for systems with or without explicit channel coding, a decoding procedures based on Pearl\u27s Belief Propagation (BP), in a similar manner to Turbo processing in traditional data communication systems, is proposed to exploit the redundancy in the system state. Numerical simulations have demonstrated the validity of the proposed schemes, using a linear model of electric generator dynamic system. Secondly, we propose a quickest detection based scheme to detect error propagation, which may happen in the proposed decoding scheme when channel condition is bad. Then we combine this proposed error propagation detection scheme with the proposed BP based channel decoding and state estimation algorithm. The validity of the proposed schemes has been shown by numerical simulations. Finally, we propose to use MSE-based transfer chart to evaluate the performance of the proposed BP based channel decoding and state estimation scheme. We focus on two models to evaluate the performance of BP based sequential and iterative channel decoding and state estimation. The numerical results show that MSE-based transfer chart can provide much insight about the performance of the proposed channel decoding and state estimation scheme. In this dissertation, the study is focused on the design of wireless receiver in order to exploit the redundancy in the system state, which can be considered as a `nature encoding\u27 for the messages. Firstly, for systems with or without explicit channel coding, a decoding procedures based on Pearl\u27s Belief Propagation (BP), in a similar manner to Turbo processing in traditional data communication systems, is proposed to exploit the redundancy in the system state. Numerical simulations have demonstrated the validity of the proposed schemes, using a linear model of electric generator dynamic system. Secondly, we propose a quickest detection based scheme to detect error propagation, which may happen in the proposed decoding scheme when channel condition is bad. Then we combine this proposed error propagation detection scheme with the proposed BP based channel decoding and state estimation algorithm. The validity of the proposed schemes has been shown by numerical simulations. Finally, we propose to use MSE-based transfer chart to evaluate the performance of the proposed BP based channel decoding and state estimation scheme. We focus on two models to evaluate the performance of BP based sequential and iterative channel decoding and state estimation. The numerical results show that MSE-based transfer chart can provide much insight about the performance of the proposed channel decoding and state estimation scheme

A Novel Predictor Based Framework to Improve Mobility of High Speed Teleoperated Unmanned Ground Vehicles

Teleoperated Unmanned Ground Vehicles (UGVs) have been widely used in applications when driver safety, mission eciency or mission cost is a major concern. One major challenge with teleoperating a UGV is that communication delays can significantly affect the mobility performance of the vehicle and make teleoperated driving tasks very challenging especially at high speeds. In this dissertation, a predictor based framework with predictors in a new form and a blended architecture are developed to compensate effects of delays through signal prediction, thereby improving vehicle mobility performance. The novelty of the framework is that minimal information about the governing equations of the system is required to compensate delays and, thus, the prediction is robust to modeling errors. This dissertation first investigates a model-free solution and develops a predictor that does not require information about the vehicle dynamics or human operators' motion for prediction. Compared to the existing model-free methods, neither assumptions about the particular way the vehicle moves, nor knowledge about the noise characteristics that drive the existing predictive filters are needed. Its stability and performance are studied and a predictor design procedure is presented. Secondly, a blended architecture is developed to blend the outputs of the model-free predictor with those of a steering feedforward loop that relies on minimal information about vehicle lateral response. Better prediction accuracy is observed based on open-loop virtual testing with the blended architecture compared to using either the model-free predictors or the model-based feedforward loop alone. The mobility performance of teleoperated vehicles with delays and the predictor based framework are evaluated in this dissertation with human-in-the-loop experiments using both simulated and physical vehicles in teleoperation mode. Predictor based framework is shown to provide a statistically significant improvement in vehicle mobility and drivability in the experiments performed.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146026/1/zhengys_1.pd