There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Networked control systems (NCSs) are spatially distributed systems for which the communication between sensors, actuators, and controllers is supported by a shared communication network. We review several recent results on estimation, analysis, and controller synthesis for NCSs. The results surveyed address channel limitations in terms of packet-rates, sampling, network delay, and packet dropouts. The results are presented in a tutorial fashion, comparing alternative methodologies

/pdf/a-survey-of-recent-results-in-networked-control-systems-2vqnhq8czm.pdf

A Survey of Recent Results in Networked Control Systems

In this note, we revisit the problem of scheduling stabilizing control tasks on embedded processors. We start from the paradigm that a real-time scheduler could be regarded as a feedback controller that decides which task is executed at any given instant. This controller has for objective guaranteeing that (control unrelated) software tasks meet their deadlines and that stabilizing control tasks asymptotically stabilize the plant. We investigate a simple event-triggered scheduler based on this feedback paradigm and show how it leads to guaranteed performance thus relaxing the more traditional periodic execution requirements.

/pdf/event-triggered-real-time-scheduling-of-stabilizing-control-t1gebqsndp.pdf

Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks

First, we review some previous work on networked control systems (NCSs) and offer some improvements. Then, we summarize the fundamental issues in NCSs and examine them with different underlying network-scheduling protocols. We present NCS models with network-induced delay and analyze their stability using stability regions and a hybrid systems technique. Following that, we discuss methods to compensate network-induced delay and present experimental results over a physical network. Then, we model NCSs with packet dropout and multiple-packet transmission as asynchronous dynamical systems and analyze their stability. Finally, we present our conclusions.

Stability of networked control systems

https://hal.archives-ouvertes.fr/hal-00855159/document

Wirtinger-based integral inequality: Application to time-delay systems

Recent technological advances have enabled distributed control systems to be implemented via networks. This allows feedback control loops to be closed over a shared communication channel. Network-induced delays are inevitable, however, when transmitting digital data between control devices. This paper analyzes the stability of such networked control systems (NCS). We first review some previous work on this topic, offering some improvements. We analyze the influence of the sampling rate and network delay on system stability. We further study the stability of NCS using a hybrid system stability analysis technique.

Stability of networked control systems: explicit analysis of delay

Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems (NCSs). The insertion of the communication network in the feedback control loop makes the analysis and design of an NCS complex. Driving our research effort into NCSs is the point of view that the design of both the communication protocols and the interacting controlled system should not be treated as separate. In the co-design approach we propose, network issues such as bandwidth, quantization, survivability, reliability and message delay will be considered simultaneously with controlled system issues such as stability, performance, fault tolerance and adaptability. Thus, we study network scheduling when a set of NCSs are connected to the network and arbitrating for network bandwidth. We first define the basic concepts of network scheduling in NCSs. Then, we apply the rate monotonic scheduling algorithm to schedule a set of NCSs. We also formulate the optimal scheduling problem under both rate-monotonic-schedulability constraints and NCS-stability constraints, and give an example of how such optimization is carried out. Next, the assumptions of ideal transmission are relaxed: we study the above network scheduling problem with network-induced delay, packet dropouts, and multiple-packet transmissions taken into account.

Scheduling and feedback co-design for networked control systems

In this article, we are concerned with neural-nets which can learn to control systems in accordance with a guiding intent, and can also learn how to formulate that control strategy or intent. The overall task of systems control is viewed as being carried out by four components, these being the predictive monitoring net, the control action generator net, the objective function net and the optimization net. This approach and perspective are described and illustrated in this article. In our examples, we show that systems identification can indeed be achieved in the presence of noise and that optimal control can be formulated in a learning mode, by neural nets.

Neural-net computing and the intelligent control of systems

We provide a general framework for networked control systems (NCSs) and review previous theoretical results for NCS co-design. We present experimental studies of control and feedback scheduling of NCSs, consisting of dynamic system simulations for the control agents and environment and packet-level network simulations for the communications. To this end, we have extended the ns-2 release in order to simulate the transmissions of plants and controllers that are modeled by ODEs (solved via a linked package). Our results show the overall control and network performances achieved while modeling the individual control and network components. Major co-design issues, such as scalability and network heterogeneity, are explored.

S.M. Phillips

Papers

Stability of networked control systems

Stability of networked control systems: explicit analysis of delay

Scheduling and feedback co-design for networked control systems

Neural-net computing and the intelligent control of systems

Networked control system co-simulation for co-design