Stabilization of Networked Control Systems With Random Delays

Luan, Xiaoli; Shi, Peng; Liu, Fei

doi:10.1109/tie.2010.2102322

Cited by 157 publications

(6 citation statements)

References 68 publications

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“…Nevertheless, the addition of the communication network leads to a series of challenging problems such as network delay, insufficient bandwidth, ineffective connections, and so on, which may degrade the performance of the system or cause system instability [4]. Recently, much effort has been made in examining stability, estimation, filtering, and control problems in NCS and many achievements have been reported, see [5,6] and references therein.…”

Section: Introductionmentioning

confidence: 99%

A delayed Takagi–Sugeno fuzzy control approach with uncertain measurements using an extended sliding mode observer

Aslam

Tiwari

Pandey

et al. 2023

Information Sciences

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Section: Introductionmentioning

confidence: 99%

A delayed Takagi–Sugeno fuzzy control approach with uncertain measurements using an extended sliding mode observer

Aslam

Tiwari

Pandey

et al. 2023

Information Sciences

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“…Researchers focus their work on studying the stabil-ity of LinearbNetworked ControlbSystems (LNCS), see for exampleb [4],b [5], [6] and the referencesbtherein. Nonlinear Networked Control Systems (NNCS) methods that study nonlinear systems were extensionsbof somebtechniques thatbwere proposed to controlbLNCS under suitablebconditions andbassumptions.…”

Section: Introductionmentioning

confidence: 99%

Resilient Observer-Based H _∞ Control of Uncertain Nonlinear Networked Control Systems

Saif

2021

IEEE Access

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This paper considers the resilient H ∞ dynamic control of nonlinear uncertain systems over a network assuming random communication packet dropouts, a subject which is seldom considered in the current literature for such uncertain systems. The uncertainties in the system and the controller are real, time-varying and norm bounded. Bernoulli distribution with white sequence is used to model the random packet losses with assumed conditions on the probabilitybdistribution. The resilient controllerbdesigned isban observer-basedbdynamic. The resulted closed-loopbsystem is exponentiallybmean squarebstable andbthe H ∞ performance is lessbthan a prescribed levelbγ for allbadmissible uncertainties. Newbsufficient conditionsbfor thebexistence of suchba controllerbare presented and provedbbased onbthe linearbmatrixbinequalities (LMIs)bapproach. A numericalbexample is presentedbto demonstrate and show thebeffectiveness of thebdeveloped theory.

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“…One of the main drawbacks in remote formation control is the bandwidth limitation of the communication network [10]. Other common shortcomings are time-varying delays [11,12], packet dropouts [13,14], packet disorder [13,15], and network bandwidth constraints [16,17]. These problems are especially important in the case under study, where the remote controller has to send and receive information about multiple sensor and actuator wireless nodes.…”

Section: Introductionmentioning

confidence: 99%

Self-Triggered Formation Control of Nonholonomic Robots

Santos

Espinosa

Martinez-Rey

et al. 2019

Sensors

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In this paper, we report the design of an aperiodic remote formation controller applied to nonholonomic robots tracking nonlinear, trajectories using an external positioning sensor network. Our main objective is to reduce wireless communication with external sensors and robots while guaranteeing formation stability. Unlike most previous work in the field of aperiodic control, we design a self-triggered controller that only updates the control signal according to the variation of a Lyapunov function, without taking the measurement error into account. The controller is responsible for scheduling measurement requests to the sensor network and for computing and sending control signals to the robots. We design two triggering mechanisms: centralized, taking into account the formation state and decentralized, considering the individual state of each unit. We present a statistical analysis of simulation results, showing that our control solution significantly reduces the need for communication in comparison with periodic implementations, while preserving the desired tracking performance. To validate the proposal, we also perform experimental tests with robots remotely controlled by a mini PC through an IEEE 802.11g wireless network, in which robots pose is detected by a set of camera sensors connected to the same wireless network.

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Stabilization of Networked Control Systems With Random Delays

Cited by 157 publications

References 68 publications

A delayed Takagi–Sugeno fuzzy control approach with uncertain measurements using an extended sliding mode observer

A delayed Takagi–Sugeno fuzzy control approach with uncertain measurements using an extended sliding mode observer

Resilient Observer-Based H _∞ Control of Uncertain Nonlinear Networked Control Systems

Self-Triggered Formation Control of Nonholonomic Robots

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Stabilization of Networked Control Systems With Random Delays

Cited by 157 publications

References 68 publications

A delayed Takagi–Sugeno fuzzy control approach with uncertain measurements using an extended sliding mode observer

A delayed Takagi–Sugeno fuzzy control approach with uncertain measurements using an extended sliding mode observer

Resilient Observer-Based H ∞ Control of Uncertain Nonlinear Networked Control Systems

Self-Triggered Formation Control of Nonholonomic Robots

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Resilient Observer-Based H _∞ Control of Uncertain Nonlinear Networked Control Systems