Disturbance-observer-based event-triggered control for multi-agent systems with input saturation

Zhou, Qi; Chen, Guangdeng; Lu, Renquan; Bai, Weiwei

doi:10.1360/ssi-2019-0105

Cited by 64 publications

(4 citation statements)

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“…Step 1. Considering equations (7), (29), (30) and (32), differentiating 1 1 1 χ z ζ   with respect to time yields…”

Section: Remarkmentioning

confidence: 99%

“…Design the control function 1 α and the updated law of 1, W s as follows: (29), (30) and (32), and differentiating…”

Section: Remarkmentioning

confidence: 99%

“…The nonlinear disturbance observer (NDO) technique is recognized as an effective way to suppress external disturbances and the approximate errors of approximators due to its simple structure and implementation, and various NDO-based adaptive control approaches have been investigated for uncertain nonlinear systems subjected to external disturbances to enhance the robustness of controllers [27][28][29][30][31][32]. In [33][34][35], two adaptive controllers were proposed for a for a class of single-input single-output and multiple-input multiple-output uncertain nonlinear systems respectively, where the NDO was introduced to estimate and compensate the compounded disturbance.…”

Section: Introductionmentioning

confidence: 99%

“… and its filter signal 1 n α  are obtained. Considering (1), (9), (29),(30) and(32), and differentiating n…”

mentioning

confidence: 99%

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Adaptive anti-disturbance control for a class of unknown pure feedback switched nonlinear systems

Chen

2021

Preprint

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In this study, an adaptive anti-disturbance control scheme is investigated for a class of unknown pure feedback switched nonlinear systems subjected to immeasurable states and external disturbances. Radial basis function neural networks (RBFNNs) are employed to identify the switched unknown nonlinearities, and a Butterworth low-pass filter is adopted to remove the algebraic loop problem. Subsequently, a novel switched neural state observer and a novel switched disturbance are presented via the coupled design method to estimate the immeasurable states and compounded disturbances. Then, an improved adaptive control strategy for the studied problem is designed with the help of a filtering method to eliminate the “explosion of complexity” problem, and certain compensating signals are set up to compensate for the filter errors, where switched updated laws are constructed to lessen the conservativeness caused by adoption of a common updated law for all subsystems. By utilizing the Lyapunov stability theorem, the developed control scheme can guarantee that all signals in the closed-loop system are bounded under a class of switching signals with the average dwell time (ADT), while the tracking error can converge to a small neighbourhood of origin. Finally, simulation results are provided to demonstrate the effectiveness of the presented approach.

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“…Step 1. Considering equations (7), (29), (30) and (32), differentiating 1 1 1 χ z ζ   with respect to time yields…”

Section: Remarkmentioning

confidence: 99%

“…Design the control function 1 α and the updated law of 1, W s as follows: (29), (30) and (32), and differentiating…”

Section: Remarkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“… and its filter signal 1 n α  are obtained. Considering (1), (9), (29),(30) and(32), and differentiating n…”

mentioning

confidence: 99%

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Adaptive anti-disturbance control for a class of unknown pure feedback switched nonlinear systems

Chen

2021

Preprint

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Event‐triggered adaptive tracking control for high‐order multi‐agent systems with unknown control directions

Xue

Ahn

et al. 2021

Intl J Robust & Nonlinear

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In this article, an event‐triggered adaptive control strategy is presented for nonlinear pure‐feedback multi‐agent systems, and the problem of the unknown control gain is also considered. In contrast to most of the existing results, each agent's control item is a power exponential function, and this problem is handled by utilizing the “adding a power integrator" technique. Based on the Nussbaum gain technique, a control scheme is presented to handle the problem concerning unknown control gains. The tracking differentiator is used to eliminate the problem of “explosion of complexity” in the backstepping method. Furthermore, an event‐triggered control strategy is designed to reduce the communication burden and the computational cost. It is proved via the Lyapunov stability method that the consensus tracking errors can converge to a small neighborhood of the origin and all signals of the closed‐loop systems are semi‐globally uniformly ultimately bounded. Finally, some simulation results are proposed to verify the effectiveness of the theoretical results.

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Sensor fault estimation and fault tolerant control for IT2 fuzzy system via sliding mode approach

Sun

Kang

2021

Intl J Robust & Nonlinear

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The point of this article is the sensor fault estimation and fault‐tolerant controller design for IT2 fuzzy systems via sliding mode approach. In order to estimate accurately the system states and sensor faults, a novel proportional and derivative sliding mode observer is introduced, which provide more design freedom and eliminate the effects of sensor faults. By splitting the operating domain and estimating the membership functions, a set of relaxation stability conditions subject to the information of membership functions and system states are obtained. Then, a sliding mode controller in form of IT2 fuzzy model is designed to stabilize the closed‐loop systems. An example of bolt‐tightening tool model is considered to demonstrate the validity of the proposed results.

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Disturbance-observer-based event-triggered control for multi-agent systems with input saturation

Cited by 64 publications

References 0 publications

Adaptive anti-disturbance control for a class of unknown pure feedback switched nonlinear systems

Adaptive anti-disturbance control for a class of unknown pure feedback switched nonlinear systems

Event‐triggered adaptive tracking control for high‐order multi‐agent systems with unknown control directions

Sensor fault estimation and fault tolerant control for IT2 fuzzy system via sliding mode approach

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