Networked Control System: Overview and Research Trends

Gupta, Rachana Ashok; Chow, Mo-Yuen

doi:10.1109/tie.2009.2035462

Cited by 990 publications

(435 citation statements)

References 76 publications

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“…This results in significantly smaller switching delays (especially in the case of multiple switches) at the cost of allowing corrupted packets to be retransmitted rather than being discarded as they would by a store-and-forward switch. Significant research is also being undertaken into methods by which network delays can be modelled and compensated for [15].…”

Section: B Ethernet Fieldbusmentioning

confidence: 99%

Introduction to Industrial Control Networks

Galloway

Hancke

2013

IEEE Commun. Surv. Tutorials

407

193

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Abstract-An industrial control network is a system of interconnected equipment used to monitor and control physical equipment in industrial environments. These networks differ quite significantly from traditional enterprise networks due to the specific requirements of their operation. Despite the functional differences between industrial and enterprise networks, a growing integration between the two has been observed. The technology in use in industrial networks is also beginning to display a greater reliance on Ethernet and web standards, especially at higher levels of the network architecture. This has resulted in a situation where engineers involved in the design and maintenance of control networks must be familiar with both traditional enterprise concerns, such as network security, as well as traditional industrial concerns such as determinism and response time. This paper highlights some of the differences between enterprise and industrial networks, presents a brief history of industrial networking, gives a high level explanation of some operations specific to industrial networks, provides an overview of the popular protocols in use and describes current research topics. The purpose of this paper is to serve as an introduction to industrial control networks, aimed specifically at those who have had minimal exposure to the field, but have some familiarity with conventional computer networks.

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Section: B Ethernet Fieldbusmentioning

confidence: 99%

Introduction to Industrial Control Networks

Galloway

Hancke

2013

IEEE Commun. Surv. Tutorials

407

193

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“…The scheduling law in (16) tries to maintain the no-delay, nominal control performance despite network delays.…”

Section: Gain Scheduling Multi-rate Pid Controllermentioning

confidence: 99%

“…Advantages such as cost reduction and easy maintenance have motivated a wide study about NCS in the last years (see, for instance, in [16], [48], [52]). Nevertheless, some drawbacks arise when using a shared link, being the fundamental one the existence of time-varying delays when transmitting information between devices (usually, from sensor to controller and from controller to actuator) [51], [47], [24], [7].…”

Section: Introductionmentioning

confidence: 99%

A non-uniform multi-rate control strategy for a Markov chain-driven Networked Control System

Cuenca

Ojha²,

Salt

et al. 2015

Information Sciences

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ElsevierCuenca Lacruz, ÁM.; Ojha, U.; Salt Llobregat, JJ.; Chow, M. (2015). AbstractIn this work, a non-uniform multi-rate control strategy is applied to a kind of Networked Control System (NCS) where a wireless path tracking control for an Unmanned Ground Vehicle (UGV) is carried out. The main aims of the proposed strategy are to face time-varying network-induced delays and to avoid packet disorder. A Markov chain-driven NCS scenario will be considered, where different network load situations, and consequently, different probability density functions for the network delay are assumed. In order to assure mean-square stability for the considered NCS, a decay-rate based sufficient condition is enunciated in terms of probabilistic Linear Matrix Inequalities (LMIs). Simulation results show better control performance, and more accurate path tracking, for the scheduled (delay-dependent) controller than for the non-scheduled one (i.e. the nominal controller when delays appear). Finally, the control strategy is validated on an experimental test-bed.

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“…The goal in this case, because of delays and packet loss induced by the presence of the network in the control loop [Tabuada, 2007;Gupta and Chow, 2010;Garcia and Antsaklis, 2013], is to avoid packets transmission if not necessary, both in the direct path (from the controller to the plant) and in the feedback path (from the sensor to the controller). To achieve this goal a model-based event-triggered MPC/ISM control scheme for nonlinear constrained continuous-time uncertain systems is discussed [Ferrara et al, 2014a].…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Model Predictive/Sliding Mode Control of Nonlinear Constrained Uncertain Systems

2015

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Abstract-This paper presents an overview of some hierarchical control schemes composed by a high level Model Predictive Control (MPC) and a low level Sliding Mode Control (SMC). The latter is realized by using the so-called Integral Sliding Mode (ISM) control approach and is meant to reject the matched disturbances affecting the plant, thus providing a system with reduced uncertainty for the MPC design. Both continuous and discrete-time solutions are discussed in the paper. Moreover, assuming the presence of a network in the control loop, a networked version of the control scheme is presented. It is a model-based event-triggered MPC/ISM control scheme aimed at minimizing the packets transmission. The input-to-state (practical) stability properties of the proposed approaches are also addressed in the paper.

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Networked Control System: Overview and Research Trends

Cited by 990 publications

References 76 publications

Introduction to Industrial Control Networks

Introduction to Industrial Control Networks

A non-uniform multi-rate control strategy for a Markov chain-driven Networked Control System

Hierarchical Model Predictive/Sliding Mode Control of Nonlinear Constrained Uncertain Systems

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