Distributed Fuzzy Adaptive Control for Heterogeneous Nonlinear Multiagent Systems with Similar Composite Structure

A distributed fuzzy adaptive control with similar parameters is constructed for a class of heterogeneous multiagent systems. Unlike many existing works, the dimensions of each multiagent dynamic system are considered to be nonidentical in this paper. Firstly, similar properties for different dimensions of multiagent systems are introduced, and some similar parameters among multiagent systems are also proposed. Secondly, a distributed fuzzy adaptive control on the basis of similar parameters is designed for the consensus of leader-follower multiagent systems. Following the graph theory and Lyapunov stability approach, it is concluded that UUB (uniformly ultimately bounded) of all signals in the closed-loop system can be guaranteed, and the consensus tacking error converges to a small compact zero set. Finally, a simulation example with different dimensions is provided to illustrate the effectiveness of the proposed method.

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Distributed type‐2 fuzzy adaptive control for heterogeneous nonlinear multiagent systems

Asian Journal of Control ◽

10.1002/asjc.2566 ◽

2021 ◽

Author(s):

Bo Qin ◽

Yongqing Fan ◽

Tiantian Xiao ◽

Zhen Li

Keyword(s):

Adaptive Control ◽

Multiagent Systems ◽

Fuzzy Adaptive Control ◽

Fuzzy Adaptive

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Event-Triggered Adaptive Control

Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems ◽

10.1115/dscc2015-9724 ◽

2015 ◽

Author(s):

Ali Albattat ◽

Benjamin C. Gruenwald ◽

Tansel Yucelen

Keyword(s):

Adaptive Control ◽

Lyapunov Stability ◽

Data Exchange ◽

Closed Loop ◽

Closed Loop System ◽

Control Approach ◽

Event Triggering ◽

Control Methodology ◽

Tools And Methods ◽

Event Triggered

In this paper, we present a new adaptive control methodology that allows a desirable command performance while the proposed controller exchanges data with the physical system through a real-time network. Specifically, we utilize tools and methods from event-triggering control theory to schedule data exchange dependent upon errors exceeding user-defined thresholds and show the boundedness of the overall closed-loop system using Lyapunov stability. An illustrative numerical example is provided to demonstrate the efficacy of the proposed adaptive control approach.

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Fuzzy adaptive control system of a non-stationary plant with closed-loop passive identifier

Resource-efficient Technologies ◽

10.1016/j.reffit.2015.07.001 ◽

2015 ◽

Vol 1 (1) ◽

pp. 10-18 ◽

Cited By ~ 6

Author(s):

Flavio Manenti ◽

Francesco Rossi ◽

Alexey G. Goryunov ◽

Valeriy F. Dyadik ◽

Kirill A. Kozin ◽

...

Keyword(s):

Adaptive Control ◽

Control System ◽

Closed Loop ◽

Adaptive Control System ◽

Fuzzy Adaptive Control ◽

Stationary Plant ◽

Fuzzy Adaptive

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Logic-Based Switching Adaptive Control of DC-DC Buck Converter

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.229-231.2209 ◽

2012 ◽

Vol 229-231 ◽

pp. 2209-2212

Author(s):

Bao Bin Liu ◽

Wei Zhou

Keyword(s):

Adaptive Control ◽

Closed Loop ◽

Buck Converter ◽

Uncertain Parameters ◽

Small Signal ◽

Closed Loop System ◽

Unknown Parameters ◽

Signal Model ◽

Small Signal Model ◽

Control Scheme

Logic-based switching adaptive control scheme is proposed for the model of DC-DC buck converter in presence of uncertain parameters and power supply disturbance. All uncertain parameters and the disturbance are estimated together through constructing Lyapunov function. And a switching mechanism is used to ensure global asymptotic stability of the closed-loop system. The results of simulation show that even if there are multiple unknown parameters in the small-signal model, the control system of DC-DC buck converter can estimate unknown parameters quickly and accurately.

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