Periodic event‐triggered cooperative control of multiple non‐holonomic wheeled mobile robots

Chen, Xia; Hao, Fei; Ma, Bolin

doi:10.1049/iet-cta.2016.0960

Cited by 43 publications

(30 citation statements)

References 42 publications

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“…We design a self-triggering condition assuming that the full state information is available at the measurement instants. Unlike most previous aperiodic control published works [18,21,27,29], we propose a self-triggering condition that triggers the controller taking into account the variation of the Lyapunov function and not the measurement error.…”

Section: Lyapunov Based Self-triggering Control Proposalmentioning

confidence: 99%

“…Aperiodic control techniques employ information about the system state to decide when the control action must be updated. The main aperiodic control techniques are event-triggered (ETC) [18,19,20,21,22,23,24,25] and self-triggered control (STC) [26,27,28,29,30,31,32]. In ETC, the triggering mechanism is based on the constant measurement of the plant state.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Lyapunov Based Self-triggering Control Proposalmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Self-Triggered Formation Control of Nonholonomic Robots

Santos

Espinosa

Martinez-Rey

et al. 2019

Sensors

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show abstract

“…This is mainly because a multi‐agent system has many advantages over single agent on work efficiency, load capacity, detection range, robustness, and so on. Among these research studies, formation control of multi‐robot systems has attracted great interest for its potential applications in military, industry, agriculture, and other fields, such as military reconnaissance, oceanic search and rescue, forest monitoring, agricultural sowing, and so on [6–8].…”

Section: Introductionmentioning

confidence: 99%

Distributed regular polygon formation control and obstacle avoidance for non‐holonomic wheeled mobile robots with directed communication topology

Wang

Zhang

et al. 2020

IET Control Theory & Applications

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“…The main features of NCSs are low cost, high reliability, ease of maintenance and expansion [1–3]. Meanwhile numerous special issues on NCSs have been concerned by many researchers, inspired by wide applications of NCSs in cooperative vehicles [4, 5], sensor networks [6, 7], multi‐agent systems [8, 9] and so on. In NCSs, the imperfect communication channels can introduce various constraints and uncertainties, for instance, packet dropouts [10, 11], time delays [12, 13], fading [14, 15], limited data rates [16, 17] and quantisation [18, 19] etc.…”

Section: Introductionmentioning

confidence: 99%