Networked control systems (NCSs) have been one of the main research focuses in academia as well as in industry for many decades and have become a multidisciplinary area. With these growing research trends, it is important to consolidate the latest knowledge and information to keep up with the research needs. In this paper, the NCS and its different forms are introduced and discussed. The beginning of this paper discusses the history and evolution of NCSs. The next part of this paper focuses on different fields and research arenas such as networking technology, network delay, network resource allocation, scheduling, network security in real-time NCSs, integration of components on a network, fault tolerance, etc. A brief literature survey and possible future direction concerning each topic is included.

Networked Control System: Overview and Research Trends

Computer algebra systems are now ubiquitous in all areas of science and engineering. This highly successful textbook, widely regarded as the “bible of computer algebra”, gives a thorough introduction to the algorithmic basis of the mathematical engine in computer algebra systems. Designed to accompany oneor two-semester courses for advanced undergraduate or graduate students in computer science or mathematics, its comprehensiveness and reliability has also made it an essential reference for professionals in the area. Special features include: detailed study of algorithms including time analysis; implementation reports on several topics; complete proofs of the mathematical underpinnings; and a wide variety of applications (among others, in chemistry, coding theory, cryptography, computational logic, and the design of calendars and musical scales). A great deal of historical information and illustration enlivens the text. In this third edition, errors have been corrected and much of the Fast Euclidean Algorithm chapter has been renovated.

Modern computer algebra

This paper examines a class of real-time control systems in which each control task triggers its next release based on the value of the last sampled state. Prior work used simulations to demonstrate that self-triggered control systems can be remarkably robust to task delay. This paper derives bounds on a task's sampling period and deadline to quantify how robust the control system's performance will be to variations in these parameters. In particular we establish inequality constraints on a control task's period and deadline whose satisfaction ensures that the closed-loop system's induced L 2 gain lies below a specified performance threshold. The results apply to linear time-invariant systems driven by external disturbances whose magnitude is bounded by a linear function of the system state's norm. The plant is regulated by a full-information H infin controller. These results can serve as the basis for the design of soft real-time systems that guarantee closed-loop control system performance at levels traditionally seen in hard real-time systems.

Self-Triggered Feedback Control Systems With Finite-Gain ${\cal L}_{2}$ Stability

In this 25th year anniversary paper for the IEEE Real Time Systems Symposium, we review the key results in real-time scheduling theory and the historical events that led to the establishment of the current real-time computing infrastructure. We conclude this paper by looking at the challenges ahead of us.

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Real Time Scheduling Theory: A Historical Perspective

Event-triggered communication and H∞ control co-design for networked control systems

In this paper, we first identify the potential violations of control assumptions inherent in standard real-time scheduling approaches (because of the presence of jitters) that causes, degradation in control performance and may even lead to instability. We then develop practical approaches founded on control theory to deal with these violations. Our approach is based on the notion of compensations wherein controller parameters are adjusted at runtime for the presence of jitters. Through time and memory overhead analysis, and by elaborating on the implementation details, we characterize when offline and on-line compensations are feasible. Our experimental results confirm that our approach does compensate for the degraded control performance when EDF and FPS algorithms are used for scheduling the control tasks. Our compensation approach provides us another advantage that leads to better schedulability of control tasks. This derives from the potential to derive more flexible timing constraints, beyond periods and deadlines necessary to apply EDF and FPS. Overall, our approach provides guarantees offline that the control system will be stable at runtime-if temporal requirements are met at runtime-even when actual execution patterns are not known beforehand. With our approach, we can address the problems due to (a) sampling jitters, (b) varying delays between sampling and actuation, or (c) both-not addressable using traditional EDF and FPS based scheduling, or by previous real-time and control integration approaches.

/pdf/jitter-compensation-for-real-time-control-systems-2c1k5exwgy.pdf

Jitter compensation for real-time control systems

In many application areas, including control systems, careful management of system resources is key to providing the best application performance. Most traditional resource management techniques for real-time systems with multiple control loops are based on open-loop strategies that statically allocate a constant CPU share to each controller, independent of their current resource needs. This provides average control performance with minimal overhead but in general fails to provide the best performance possible within the available resources. We show that by using feedback to dynamically allocate resources to controllers as a function of the current state of their controlled systems, control performance can be significantly improved. We present an optimal resource allocation policy that maximizes control performance within the available resources and provide experimental results showing that the optimal policy 1) significantly increases control performance compared to traditional control system implementations (by more than 20% in our experiments), 2) maximizes control performance over other feedback-based policies, 3) saves resources when perturbations occur infrequently, and 4) incurs negligible overhead.

https://esaii.upc.edu/people/pmarti/RTSS2004.pdf

Optimal state feedback based resource allocation for resource-constrained control tasks

Closed-loop control systems are dynamic systems subject to perturbations. One of the main concerns of the control is to design controllers to correct or limit the deviation that transient perturbations cause in the controlled system response. The smaller and shorter the deviation, the better the achieved performance. However, such controllers have been traditionally implemented using fixed timing constraints (periods and deadlines). This precludes controllers to execute dynamically, accordingly to the system dynamics, which may lead to sub-optimal implementations: although higher execution rates may be preferable when reacting to perturbations in order to minimize the response deviations, they imply wastage of resources when the system is in equilibrium. In this paper we argue and demonstrate that the responsibility of maximizing the performance of closed-loop systems relies on both the controller designer and the scheduler. We show that the dynamic optimization of the quality of the controlled system response calls for (a) flexible control task timing constraints that deliver effective control performance; flexible constraints allow us to achieve faster reaction by adaptively choosing the controller sampling rate and completion time upon transient perturbations, (b) a quality-of-control (QoC) metric; it associates with each control task timing a quantitative value expressing control performance (in terms of the closed-loop system error), and (c) new scheduling approaches; their goal is to quickly react to perturbations by dynamically scheduling tasks based on the chosen control task execution parameters to maximize the QoC. This combination offers the possibility of taking scheduling decisions based on the control information for each control task invocation, rather than using fixed timing constraints with constant periods and deadlines.

/pdf/improving-quality-of-control-using-flexible-timing-4owawgdf02.pdf

Improving quality-of-control using flexible timing constraints: metric and scheduling

Bandwidth allocation techniques for control loops closed over communication networks are based on static strategies that ensure average control performance at the expense of permanently occupying the available bandwidth. We present a dynamic approach to bandwidth management in networked control systems that allows control loops to consume band-width according to the dynamics of the controlled process while attempting to optimize overall control performance. By augmenting the original state-space representation of each controlled process with a new state variable that describes the network dynamics, 1) the allocation of bandwidth lo control loops can he done locally at run-time according to the state of each controlled process without causing overload situations and 2) control laws can be designed to account for the variations in the assigned bandwidth preventing the unexpected control performance degradation and even destabilization that would otherwise occur. Experimental data shows that this approach improves control performance with respect to the static strategy and uses less bandwidth.

https://esaii.upc.edu/people/pmarti/IECON2004.pdf

A control approach to bandwidth management in networked control systems

In general, characteristics of classical control theory and properties of real-time scheduling algorithms may cause unexpected control system responses in the implementation of real-time computer-controlled systems. Revising realtime scheduling properties, we analyse which are the main timing problems that current scheduling algorithms may introduce in the execution of control loops. Next, we categorise those timing problems, that is, jitters on task-instances executions, in a control context. Afterwards, we show, by simulations, different types of control system performance degradation that these jitters may cause. Finally, we propose possible solutions that solves this degradation, based on irregular sampling discrete-time system models with varying time delays.

https://esaii.upc.edu/people/pmarti/ecc2001.pdf

Josep M. Fuertes

Papers

Jitter compensation for real-time control systems

Optimal state feedback based resource allocation for resource-constrained control tasks

Improving quality-of-control using flexible timing constraints: metric and scheduling

A control approach to bandwidth management in networked control systems

On real-time control tasks schedulability