Event-triggered distributed predictive control for asynchronous coordination of multi-agent systems

Zou, Yuanyuan; Xu, Su Xiu; Li, Shaoyuan; Niu, Yugang; Li, Dewei

doi:10.1016/j.automatica.2018.10.019

Cited by 94 publications

(47 citation statements)

References 21 publications

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“…Let Assumptions 1-6 be valid. Consider that the system (25) with the event-driven optimal control policy ( 13) and the NN observer (26), the observer errorx, the estimated weight errorsW o andṼ o , and the total disturbance compensating error̃o are UUB if the NN weights and the disturbance compensation are updated by: Case 1: When an event is not triggered, for t ∈ [s j − 1 , s j ), we havėŴ…”

Section: Observer Designmentioning

confidence: 99%

“…In order to reduce communication and computational costs, various event-driven control mechanisms have been proposed. [23][24][25][26][27][28][29][30][31][32] Unlike in the time-driven control, the sampling of system states in the event-driven control depends on a trigger threshold. Guo et al 23 provided two different event-triggered strategies to solve the problem of feedback control in uncertain nonlinear systems.…”

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confidence: 99%

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Event‐driven adaptive near‐optimal tracking control of the robot in aircraft skin inspection

Wang

2021

Intl J Robust & Nonlinear

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In this article, we discuss a near-optimal tracking control problem (NOTCP) of robots used for inspecting aircraft skin with partially unknown systems, unmeasurable states, unknown disturbances, and unknown output delay. A novel observer based on an augmented neural network is designed to overcome the unknown disturbances, unknown output delay, and unknown internal states. An augmented system state, composed of the tracking error and reference system state, is proposed to introduce a new nonquadratic discounted performance function for the NOTCP. Due to the complexity in solving the Hamilton-Jacobi-Bellman equation, an online policy iteration is presented under the adaptive dynamic programming (ADP) framework. Unlike the traditional ADP, the event-driven algorithm updates the control input only when the event is triggered, which reduces the computational cost and transmission load. Both the control policy and the observer are updated according to the developed triggering condition. Convergence to a near-optimal control solution and the stability analysis of the proposed algorithm are shown through the Lyapunov candidate function for both the continuous and jump dynamics. The performance of the proposed algorithm is demonstrated by simulation. K E Y W O R D Sadaptive dynamic programming, augmented neural network observer, event driven, nonlinear partially unknown systems, online learning and control INTRODUCTIONWith the continuous advancement of new technologies, service robots have begun to enter into people's work and life to replace tedious, repetitive, and onerous tasks. 1 Among them, the climbing robots have attracted increasing attention as their applications are found in industry, 2 dangerous areas, 3 and domestic needs. 4 Damaged skins of aircrafts have led to a number of air crashes. Nevertheless, there are many shortcomings, such as high cost and low efficiency. An oversight of the staff is also a potential threat. Such circumstances motivate people to design robots for replacing/reducing human involvement. This article introduces a robot for inspecting skins of aircrafts. 5 In general, there always exist some problems in physical systems, for instance, unmeasurable system states, disturbances, and system uncertainties between mathematical models and practical systems. Such issues may lead to degrade the controlling performance. Hence, the designed controlling policy should be robust enough.

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Section: Observer Designmentioning

confidence: 99%

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confidence: 99%

Event‐driven adaptive near‐optimal tracking control of the robot in aircraft skin inspection

Wang

2021

Intl J Robust & Nonlinear

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“…To handle the consensus problem, various distributed control strategies have been proposed, including adaptive control [8], sliding mode control (SMC) [3, 6], predictive control [7, 9], robust

H_{\infty}

control [10], pinning control [11] and so on. In [8], the non‐linear heterogeneous MASs with unknown dynamics achieved robust tracking control by designing adaptive neural networks (NNs) tuning laws.…”

Section: Introductionmentioning

confidence: 99%

“…In [8], the non‐linear heterogeneous MASs with unknown dynamics achieved robust tracking control by designing adaptive neural networks (NNs) tuning laws. To reduce computation and energy consumption, Zou et al [9] designed a dynamic event‐triggering condition and solved the distributed predictive control problem for MASs with bounded disturbances. Li et al .…”

Section: Introductionmentioning

confidence: 99%

Adaptive non‐singular fast terminal sliding mode control for multi‐agent systems with unknown non‐linear dynamics

Niu

Chen

2020

IET Control Theory & Appl

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“…The NCSs have many merits such as low cost, reduced weight and power, and easy manipulation. Nevertheless, the implementation of communication networks between system components (e.g., sensors, controller and actuators) has largely raised the level of complexities in the analysis and synthesis of the overall NCSs mainly due to the inherent limited bandwidth [14], [29], [32], [42]. It is well recognized that if not properly handled, the network-induced phenomena could cause performance degradation of the overall NCSs.…”

Section: Introductionmentioning

confidence: 99%

Reliable Sliding Mode Control of Fast Sampling Singularly Perturbed Systems: A Redundant Channel Transmission Protocol Approach

Song

Niu

Lam

2019

IEEE Trans. Circuits Syst. I

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Event-triggered distributed predictive control for asynchronous coordination of multi-agent systems

Cited by 94 publications

References 21 publications

Event‐driven adaptive near‐optimal tracking control of the robot in aircraft skin inspection

Event‐driven adaptive near‐optimal tracking control of the robot in aircraft skin inspection

Adaptive non‐singular fast terminal sliding mode control for multi‐agent systems with unknown non‐linear dynamics

Reliable Sliding Mode Control of Fast Sampling Singularly Perturbed Systems: A Redundant Channel Transmission Protocol Approach

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