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Chapter 1
Preliminary Notions and State of the Art 1
1.1. Overview
Basically, co-design needs to share, compare, and gather the knowledge and perspectives brought by the stakeholders involved in the design process. Indeed, the design of safe networked control systems involves many basic methodologies and technologies. The essential methodologies involved here are feedback control, real-time scheduling, fault detection and isolation (FDI), filtering and identification, networking protocols, and QoS metrics: each of them relies on theoretic concepts and specific domains of applied mathematics such as optimization and information theory. On the other hand, these concepts are implemented via various technologies and devices, for example, involving mechanical or chemical engineering, continuous and digital electronics and software engineering.
These basic domains are explained in existing literature; hence, this chapter is not meant to give an exhaustive overview of all the methodologies and technologies used further in the book. This book is also not meant to provide an exhaustive state of the art nor to be a definitive treatise on the open topic of safe NCS; it is aimed at recording and disseminating the experience gathered by the authors during the joint SAFENECS academic research project. The team brought together people from different horizons, with basic backgrounds in control or computer science, and expertise in various domains and technologies such as digital control design, modeling of dynamic systems, real-time scheduling, identification, and diagnosis. Fault-tolerant control (FTC), networking protocols, quality of service (QoS) analysis in networks, and model-based software development, among others.
Besides the knowledge provided by basic education in control and computer science, it appears that some topics that are useful in the joint design of control systems over networks are too specific, or too new and not disseminated enough, to be currently a part of basic education in control or industrial computing. So the next sections provide additional knowledge about such topics and will be useful in what follows.
Section 1.2 gives preliminary notions about real-time scheduling as well as some popular real-time scheduling policies. A particular focus is given on the so-called (m, k)-firm scheduling policy, which is, in particular, the groundwork for the control/networking co-design methodology that is developed in Chapter 5. Then, section 1.3 provides basic considerations and describes the current solutions for control-aware computing, i.e. providing computing architecture designs able to improve the quality of control of the system. One very appealing solution for the control of computing and networking resources subject to variable and/or badly known operating conditions uses a feedback-scheduling loop, whose basic design and implementation are described in section 1.4. Finally, section 1.5 provides a brief state of the art about fault diagnosis in control systems subject to network-induced effects.
1.2. Preliminary notions on real-time scheduling
When taking into account the implementation aspect of the control applications, one of the fundamental problems is to ensure timely execution of the tasks and transmission of messages related to control loops, e.g. transmission of a sampling data from a sensor to a controller, execution of the control task on a multitasking operating system (OS), sending the command from the controller to the actuator.
Control applications are typical real-time applications. The execution of a task or transmission of data is under time constraint (often under deadline constraint) in order to ensure the reactivity of the system and thus guarantee the stability and desired control performance. Real-time scheduling theory has been developed for studying how to effectively schedule the access to a shared resource of the concurrent tasks (through scheduling algorithm development) and to guarantee that the designed system can meet time constraints (through schedulability analysis).
This section is not intended to give a comprehensive review of the real-time scheduling theory, but rather provides the necessary basic background to facilitate the understanding of the remaining chapters of this book. Readers interested in more detail may refer to [LIU 00], and also to [LEU 04] for a broader view on scheduling.
The notion of priority is commonly used to order access to the shared resources such as a processor in multitask systems and a communication channel in networks. In the following, except in case of necessity, we will always use the term task which may represent either a task execution on a processor or a packet/message transmitted on a network channel.
A classic periodic task model is proposed by Liu and Layland [LIU 73]. Each periodic task of priority i, denoted by τi, is characterized by its worst-case execution time (WCET) Ci, its period Ti with which its execution is requested, and its relative deadline Di. The problem is how to schedule a set of n independent periodic tasks Γ = {τ 1, τ2,…, τn} on one processor to ensure that the deadline of each instance is met (i.e. executed before the deadline). This is called hard real-time guarantee. In priority-based scheduling, it is usual to use the value i = 1 for the highest priority and larger integer of i for lower priority. During the execution of a task instance of priority i, if a higher priority one arrives, two ...
