FeedNetBack - D05.04 - Design methodologies for event-based control systems

This is a Deliverable Report for the FeedNetBack project (www.feednetback.eu). Networked Control Systems (NCS) are systems in which the sensors or/and the actuators communicate with the controller through a network. Energy saving and robustness to unreliable channels are major challenges in networked control, notably in wireless scenarios. Energy efficiency and in particular asynchronous design methodologies are studied in this deliverable. The presence of a channel between the sensors measuring the plant and the controller generating the control inputs implies that the measurements should be quantized. As a preliminary step, the problem of finding a stabilizing policy with quantized measurements and bounded control inputs is considered. It is common to assume that the different nodes of a Network Control System use a periodic synchronized clock, this simplifies the model which may take into account some transmission delays. However, this assumption is strong and energy consuming. Indeed, the periodic sampling time is often chosen to ensure given performance in the worst case scenario, wasting energy when the system is running around its working point. To relax the assumption of synchronized nodes, the rest of the deliverable introduces two asynchronous design methodologies, event-based and self-triggered methodologies. The former consists in limiting the transmissions between the nodes when a given condition holds, or, in other words, when an event occurs. Not only this approach relaxes the assumption of synchronized nodes, but it also limits the transmissions which save energy. In the following, event-based approach is applied to a feedback control case and an estimation case. However, by its nature, event-based approach forces the communicating node to watch for the occurrence of the triggering event. This is relaxed in self-triggered approach where each node decides, at the end of an action (e.g. measuring, transmitting, controlling), when the next action will take place. In between these times, the node usually goes to down mode to save energy. In the last part of this deliverable, this approach is applied to a variable sample rate control and to the case of IEEE 802.15.4 protocol

Spectrum-efficient Architecture for Cognitive Wireless Sensor Networks

Projecte realitzat en col.laboració amb el centre Université Libre de BruxellesHoy en día existe la creencia de que en unos pocos años las actuales Redes Inalámbricas de Sensores estarán presentes en muchas aplicaciones. Mientras estas sigan actuando en la banda sin licencia de ISM 2,4GHz, tendrán que coexistir con otras exitosas tecnologías como Wi-Fi o Bluetooth. En consecuencia, resulta obvio asegurar que la banda en cuestión estará superpoblada en un futuro próximo. Sin embargo y gracias a las nuevas técnicas de Radio Cognitiva, que permitirán la aplicación de un eficiente Acceso al Espectro Dinámico, se conseguirá una distribución racional, dentro del espectro disponible en ese momento y lugar, de las comunicaciones inalámbricas que se estén llevando a cabo. Esta actuación permitirá acceder a frecuencias menos pobladas para poder transmitir con menos interferencias e incluso con menos pérdidas de propagación. A lo largo de este trabajo se va a presentar una arquitectura eficiente, espectralmente hablando, para Redes Inalámbricas de Sensores y Cognitivas. Este esquema desarrolla un protocolo de recolección de datos, para una red con topología de árbol, totalmente escalable y con finalidades genéricas. A través de las pruebas realizadas, podemos afirmar que nuestro esquema, sin alterar el ciclo normal de recolección de datos, puede detectar la presencia de otras Redes Inalámbricas de Sensores y, consecuentemente, migrar la red a nueva frecuencia mientras que todas estas operaciones están ocultas al usuario final. También es eficiente a nivel de energía, ya que no se realizan comprobaciones redundantes de la presencia de otras redes. De esta manera, nuestra propuesta asegura un mejor comportamiento en caso de la existencia de una Red Inalámbrica de Sensores externa, sin realizar operaciones complicadas ni añadiendo más tráfico a la red

Spectrum-efficient Architecture for Cognitive Wireless Sensor Networks

Projecte realitzat en col.laboració amb el centre Université Libre de BruxellesHoy en día existe la creencia de que en unos pocos años las actuales Redes Inalámbricas de Sensores estarán presentes en muchas aplicaciones. Mientras estas sigan actuando en la banda sin licencia de ISM 2,4GHz, tendrán que coexistir con otras exitosas tecnologías como Wi-Fi o Bluetooth. En consecuencia, resulta obvio asegurar que la banda en cuestión estará superpoblada en un futuro próximo. Sin embargo y gracias a las nuevas técnicas de Radio Cognitiva, que permitirán la aplicación de un eficiente Acceso al Espectro Dinámico, se conseguirá una distribución racional, dentro del espectro disponible en ese momento y lugar, de las comunicaciones inalámbricas que se estén llevando a cabo. Esta actuación permitirá acceder a frecuencias menos pobladas para poder transmitir con menos interferencias e incluso con menos pérdidas de propagación. A lo largo de este trabajo se va a presentar una arquitectura eficiente, espectralmente hablando, para Redes Inalámbricas de Sensores y Cognitivas. Este esquema desarrolla un protocolo de recolección de datos, para una red con topología de árbol, totalmente escalable y con finalidades genéricas. A través de las pruebas realizadas, podemos afirmar que nuestro esquema, sin alterar el ciclo normal de recolección de datos, puede detectar la presencia de otras Redes Inalámbricas de Sensores y, consecuentemente, migrar la red a nueva frecuencia mientras que todas estas operaciones están ocultas al usuario final. También es eficiente a nivel de energía, ya que no se realizan comprobaciones redundantes de la presencia de otras redes. De esta manera, nuestra propuesta asegura un mejor comportamiento en caso de la existencia de una Red Inalámbrica de Sensores externa, sin realizar operaciones complicadas ni añadiendo más tráfico a la red

Holistic Control for Cyber-Physical Systems

The Industrial Internet of Things (IIoT) are transforming industries through emerging technologies such as wireless networks, edge computing, and machine learning. However, IIoT technologies are not ready for control systems for industrial automation that demands control performance of physical processes, resiliency to both cyber and physical disturbances, and energy efficiency. To meet the challenges of IIoT-driven control, we propose holistic control as a cyber-physical system (CPS) approach to next-generation industrial automation systems. In contrast to traditional industrial automation systems where computing, communication, and control are managed in isolation, holistic control orchestrates the management of cyber platforms (networks and computing platforms) and physical plant control at run-time in an integrated architecture. Specifically, this dissertation research comprises the following primary components. Holistic wireless control: The core of holistic wireless control is a holistic controller comprising a plant controller and a network controller cooperating with each other. At run-time the holistic controller generates (1) control commands to the physical plant and (2) network reconfiguration commands to wireless networks based on both physical and network states. This part of dissertation research focused on the design and evaluation of holistic controllers exploiting a range of network reconfiguration strategies: (1) adapting transmission redundancy, (2) adapting sampling rates, (3) self-triggered control, and (4) dynamic transmission scheduling. Furthermore, we develop novel network reconfiguration protocols (NRP) as actuators to control network configurations in holistic control. Holistic edge control: This part of dissertation research explores edge computing as a multitier computing platform for holistic control. The proposed switching multi-tier control (SMC) dynamically switches controllers located on different computation platforms, thereby exploiting the trade-off between computation and communication in a multi-tier computing platform. We also design the stability switch between local and edge controllers under information loss from another perspective, based on co-design of edge and local controllers that are designed via a joint Lyapunov function. Real-time wireless cyber-physical simulators: To evaluate holistic control, we extend the Wireless Cyber-Physical Simulator (WCPS) to integrate simulated physical plants (in Simulink) with real wireless networks (WCPS-RT) and edge computing platforms (WCPS-EC). The real-time WCPS provides a holistic environment for CPS simulations that incorporate wireless dynamics that are challenging to simulate accurately, explore the impacts and trade-off of computation and communication of multi-tier platforms, and leverage simulation support for controllers and plants

Optimization and Communication in UAV Networks

UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques

Algorithms for energy-efficient adaptive wireless sensor networks

Mención Internacional en el título de doctorIn this thesis we focus on the development of energy-efficient adaptive algorithms for Wireless Sensor Networks. Its contributions can be arranged in two main lines. Firstly, we focus on the efficient management of energy resources in WSNs equipped with finite-size batteries and energy-harvesting devices. To that end, we propose a censoring scheme by which the nodes are able to decide if a message transmission is worthy or not given their energetic condition. In order to do so, we model the system using a Markov Decision Process and use this model to derive optimal policies. Later, these policies are analyzed in simplified scenarios in order to get insights of their features. Finally, using Stochastic Approximation, we develop low-complexity censoring algorithms that approximate the optimal policy, with less computational complexity and faster convergence speed than other approaches such as Q-learning. Secondly, we propose a novel diffusion scheme for adaptive distributed estimation in WSNs. This strategy, which we call Decoupled Adapt-then-Combine (D-ATC), is based on keeping an estimate that each node adapts using purely local information and then combines with the diffused estimations by other nodes in its neighborhood. Our strategy, which is specially suitable for heterogeneous networks, is theoretically analyzed using two different techniques: the classical procedure for transient analysis of adaptive systems and the energy conservation method. Later, as using different combination rules in the transient and steady-state regime is needed to obtain the best performance, we propose two adaptive rules to learn the combination coefficients that are useful for our diffusion strategy. Several experiments simulating both stationary estimation and tracking problems show that our method outperforms state-of-the-art techniques in relevant scenarios. Some of these simulations reveal the robustness of our scheme under node failures. Finally, we show that both approaches can be combined in a common setup: a WSN composed of harvesting nodes aiming to solve an adaptive distributed estimation problem. As a result, a censoring scheme is added on top of D-ATC. We show how our censoring approach helps to improve both steady-state and convergence performance of the diffusion scheme.La presente tesis se centra en el desarrollo de algoritmos adaptativos energéticamente eficientes para redes de sensores inalámbricos. Sus contribuciones se pueden englobar en dos líneas principales. Por un lado, estudiamos el problema de la gestión eficiente de recursos energéticos en redes de sensores equipadas con dispositivos de captación de energía y baterías finitas. Para ello, proponemos un esquema de censura mediante el cual, en un momento dado, un nodo es capaz de decidir si la transmisión de un mensaje merece la pena en las condiciones energéticas actuales. El sistema se modela mediante un Proceso de Decisión de Markov (Markov Decision Process, MDP) de horizonte infinito y dicho modelo nos sirve para derivar políticas óptimas de censura bajo ciertos supuestos. Después, analizamos estas políticas óptimas en escenarios simplificados para extraer intuiciones sobre las mismas. Por último, mediante técnicas de Aproximación Estocástica, desarrollamos algoritmos de censura de menor complejidad que aproximan estas políticas óptimas. Las numerosas simulaciones realizadas muestran que estas aproximaciones son competitivas, obteniendo una mayor tasa de convergencia y mejores prestaciones que otras técnicas del estado del arte como las basadas en Q-learning. Por otro lado, proponemos un nuevo esquema de difusión para estimación distribuida adaptativa. Esta estrategia, que denominamos Decoupled Adapt-then-Combine (D-ATC), se basa en mantener una estimación que cada nodo adapta con información puramente local y que posteriormente combina con las estimaciones difundidas por los demás nodos de la vecindad. Analizamos teóricamente nuestra estrategia, que es especialmente útil en redes heterogéneas, usando dos métodos diferentes: el método clásico para el análisis de régimen transitorio en sistemas adaptativos y el método de conservación de la energía. Posteriormente, y dado que para obtener el mejor rendimiento es necesario utilizar reglas de combinación diferentes en el transitorio y en régimen permanente, proponemos dos reglas adaptativas para el aprendizaje de los pesos de combinación para nuestra estrategia de difusión. La primera de ellas está basada en una aproximación de mínimos cuadrados (least-squares, LS); mientras que la segunda se basa en el algoritmo de proyecciones afines (Afifne Projection Algorithm, APA). Se han realizado numerosos experimentos tanto en escenarios estacionarios como de seguimiento que muestran cómo nuestra estrategia supera en prestaciones a otras aproximaciones del estado del arte. Algunas de estas simulaciones revelan además la robustez de nuestra estrategia ante errores en los nodos de la red. Por último, mostramos que estas dos aproximaciones son complementarias y las combinamos en mismo escenario: una red de sensores inalámbricos compuesta de nodos equipados con dispositivos de captación energética cuyo objetivo es resolver de manera distribuida y adaptativa un problema de estimación. Para ello, añadimos la capacidad de censurar mensajes a nuestro esquema D-ATC. Nuestras simulaciones muestran que la censura puede ser beneficiosa para mejorar tanto el rendimiento en régimen permanente como la tasa de convergencia en escenarios relevantes de estimación basada en difusión.This work was partially supported by the "Formación de Profesorado Universitario" fellowship from the Spanish Ministry of Education (FPU AP2010-5225).Programa Oficial de Doctorado en Multimedia y ComunicacionesPresidente: Santiago Zazo Bello.- Secretario: Miguel Lázaro Gredilla.- Vocal: Alexander Bertran