Embedding Kalman techniques in the one-shot task model when non-uniform samples are corrupted by noise

The performance of several closed-loop systems whose controllers concurrently execute in a multitasking realtime system may be deteriorated due to timing uncertainties in tasks´executions, problem known as scheduling jitters. Recently, the one-shot task model, that combines irregular sampling, a predictor observer, and strictly periodic actuation, was presented in order to remove the negative effects of jitters. However, its successful application required noise-free samples. In this paper we extend the one-shot task model to the case of noisy measurements. In particular, we embed a Kalman filter into the model taking into account that the available measurements are not periodic. This poses the problem of adapting the standard discrete-time Kalman filter to the case under study, and decide when to apply the prediction and the correction phase. Two different strategies are presented, and their control performance and computation demand are analyzed through real experiments.Peer ReviewedPostprint (published version

Sensor-Based Model Driven Control Strategy for Precision Irrigation

Improving the efficiency of the agricultural irrigation systems substantially contributes to sustainable water management. This improvement can be achieved through an automated irrigation system that includes a real-time control strategy based on the water, soil, and crop relationship. This paper presents a model driven control strategy applied to an irrigation system, in order to make an efficient use of water for large crop fields, that is, applying the correct amount of water in the correct place at the right moment. The proposed model uses a predictive algorithm that senses soil moisture and weather variables, to determine optimal amount of water required by the crop. This proposed approach is evaluated against a traditional irrigation system based on the empirical definition of time periods and against a basic soil moisture control system. Results indicate that the use of a model predictive control in an irrigation system achieves a higher efficiency and significantly reduce the water consumption

An Embedded Software Development Framework for Internet of Things Devices

Internet of things (IoT) devices are mostly ubiquitous in this day and age, and it is hard to imagine a life without them, especially in the productive sectors (industry, agriculture, and automotive) and in our daily life activities (consumer electronics, home automation, and intelligent buildings). The high demand for these devices has created significant competition to provide them at the best price, at the right time, and with the best features. The trend in which these devices have increased their product features has resulted in their embedded software being more complex, leading to extended development and testing times. Consequently, as the types of advanced IoT products keep diversifying, the field maintenance of all the different models deployed grows more complicated. This paper proposes an embedded software development framework for IoT devices independent of the microcontroller architecture, the compiler, and the development environment. This framework allows having a common software baseline between different projects, which shortens the learning curve, development time, and module validation while allowing code reuse for embedded software professionals. A proof-of-concept evaluation is also presented to demonstrate the efficiency and reliability of the obtained embedded software code for a simple but representative IoT application

Resource and performance trade-offs in real-time embedded control systems

The use of computer controlled systems has increased dramatically in our daily life. Microprocessors are embedded in most of the daily- used devices. Due to cost constraints, many of these devices that run control applications are designed under processing power, space, weight, and energy constraints, i.e., with limited resources. Moreover, the embedded control systems market demands new capabilities to these devices or improvements in the existing ones without increasing the resource demands. Enabling devices with real-time technology is a promising step toward achieving cost-effective embedded control systems. Recent results of real-time systems theory provide methods and policies for an efficient use of the computational resources. At the same time, control systems theory is starting to offer controllers with varying computational load. By combining both disciplines, it is theoretically feasible to design resource-constrained embedded control systems capable of trading-off control performance and resource utilization. This thesis focuses on the practical feasibility of this new generation of embedded control systems. To this extend, two issues are addressed: 1) the effective implementation of control loops using real-time technology and 2) the evaluation of resource/performance- aware policies that can be applied to a set of control loops that concurrently execute on a microprocessor. A control task generally consists of three main activities: input, control algorithm computation, and output. The timing of the input and output actions is critical to the performance of the controller. The implementation of these operations can be conducted within the real- time task body or using hardware functions. The former introduces considerable amounts of jitters while the latter forces delays. This thesis presents a novel task model as a computational abstraction for implementing control loops that is shown to remove the endemic problems caused by jitters and delays. This model is synchronized at the output instants rather than at the input instants. This has been shown to provide interesting properties. From the scheduling point of view, the new task model can be seamlessly integrated into existing scheduling theory and practice, while improving task set schedulability. From a control perspective, the task model absorbs jitters because it allows irregular sampling by incorporating predictors, and improves reactiveness in front of perturbations. In addition, Kalman techniques have been also investigated to deal with the case of noisy measurements. The effective implementation of simple control algorithms making use of this new task model does not guarantee the feasibility of implementing state-of-the-art resource/performance-aware policies. These policies, which can be roughly divided into feedback scheduling and event-driven control, have been mainly treated from a theoretical point of view while practical aspects have been omitted. Conversely to the initial problem targeted by these policies, that is, to minimize or keep resource requirements to meet the tight cost constraints related with mass production and strong industrial competition, research advances seem to require sophisticated procedures that may impair a cost-effective implementation. This thesis presents a performance evaluation framework that permits to assess these policies in terms of the potential benefits offered by the theory as well as the pay-off in terms of complexity and overhead. The framework design is the result of a taxonomical analysis of the related state-of-the-art. Among other specifications, the framework, which is composed by a simulation and an experimental platform, supports both event/time triggered paradigms, allows different sort of control and optimization algorithms, and flexibly evaluates control performance and resource utilization.El uso de sistemas controlados por computadora ha incrementado dramáticamente en nuestra vida cotidiana. En la mayor parte de los dispositivos que usamos diariamente encontramos microprocesadores. Debido a restricciones de coste muchos de estos dispositivos ejecutan aplicaciones de control diseñadas bajo restricciones de potencia, espacio, peso y energía, esto es, con recursos limitados. Además, el mercado de sistemas de control embebido demanda nuevas capacidades a estos dispositivos o mejoras en los dispositivos ya existentes sin incrementar las demandas de recursos. Incluir en estos dispositivos tecnología de tiempo real es un prometedor paso para conseguir sistemas de control embebido de bajo coste. Resultados recientes en sistemas de tiempo real proporcionan métodos y políticas para un uso eficiente de los recursos. Al mismo tiempo, los sistemas de control empiezan a ofrecer controladores con carga computacional variable. Al combinar estas dos disciplinas, es teóricamente posible diseñar sistemas de control embebido con recursos restringidos capaces de balancear el rendimiento de control y la utilización de recursos. El objetivo de esta tesis es determinar la viabilidad de la implementación práctica de esta nueva generación de sistemas de control embebidos. En este sentido, dos problemas principales son abordados: 1) la efectiva implementación de lazos de control usando tecnología de tiempo real, y 2) la evaluación de políticas de mejoras en recursos y rendimiento que pueden ser aplicados a un conjunto de lazos de control que se ejecutan concurrentemente en un microprocesador. Una tarea de control consiste generalmente en tres actividades principales: entrada, cómputo del algoritmo de control y salida. El tiempo en el que se ejecutan las acciones de entrada y salida es crítico con respecto al rendimiento del controlador. La implementación de estas operaciones puede ser ejecutada dentro del cuerpo de la tarea de tiempo real o a través de funciones hardware como interrupciones. La primera opción introduce una considerable cantidad de jitters (variaciones), mientras que la segunda introduce retardos. Esta tesis presenta un nuevo modelo de tareaspara la implementación de lazos de control que es capaz de eliminar los problemas endémicos causados por los jitters y los retardos. En este modelo la sincronización se realiza en los instantes de salida, en lugar de los instantes de entrada. Esto ha demostrado tener propiedades interesantes. Desde el punto de vista de planificación de tareas, el nuevo modelo puede ser integrado en forma directa a la teoría y práctica de planificación de tareas, mejorando la capacidad de planificación. Desde una perspectiva de control, el modelo de tareas absorbe los jitters al permitir muestreos irregulares mediante el uso de predictores, y además mejora la capacidad de reacción del sistema frente a perturbaciones. Adicionalmente, técnicas basadas en filtros de Kalman han sido también investigadas para tratar situaciones en que se tengan mediciones con ruido. La efectiva implementación de algoritmos simples de control haciendo uso de este nuevo modelo de tarea no garantiza la factibilidad de implementar políticas más avanzadas, aparecidas recientemente en el estado del arte, para mejorar el rendimiento del control y el uso eficiente de recursos. Estas políticas, que pueden ser divididas en planificación con retroalimentación (feedback scheduling) y control guiado por eventos (event-driven control), han sido principalmente abordadas desde una perspectiva teórica mientras los aspectos prácticos usualmente son omitidos. Contrariamente al problema inicial al que se enfocan estas políticas, que es minimizar o mantener los requerimientos de uso de recursos para lograr las restricciones de coste debidas a la producción en masa y a la fuerte competencia industrial, los avances en las investigaciones parecen requerir procedimientos sofisticados que van en detrimento de una implementación de bajo coste. Esta tesis presenta una plataforma de evaluación de rendimiento que permite valorar estas políticas en términos de los beneficios potenciales ofrecidos por la teoría, además de valorar los costes en términos de complejidad y uso adicional de recursos. El diseño de la plataforma es el resultado de un análisis taxonómico de distintos métodos que forman parte del estado del arte. Entre otras especificaciones, la plataforma, que está compuesta por una plataforma de simulación y una experimental, soporta tanto los paradigmas basados en tiempo como los basados en eventos, permite la implementación de distintos algoritmos de optimización y control, y es capaz de evaluar tanto el rendimiento de control como el uso de recursos

On the timing of discrete events in event-driven control systems

Abstract. This paper presents an analysis method to determine offline at what intervals have to be taken the samples for various types of eventdriven control systems.

Minimizing control cost in resource-constrained control systems: from Feedback scheduling to event-driven control

This paper evaluates approaches aimed at minimizing aggregated control cost of a set of controllers that concurrently execute sharing limited computing resources. The evaluation focuses on feedback scheduling and event-driven control methods. The performance results drive the analysis to explore self-triggered controllers in the context of minimizing control cost when given a fixed amount of computing resources. This leads to the formulation of an optimization problem, that for given example, is numerically solved. The solution helps understanding the behavior of self-triggered controllers.Peer Reviewe