An H∞ Output Tracking Control Approach to Sampled-Data Control for Nonlinear Networked Control Systems

In this article, we study the problem of H<sub>&#x221E;</sub> output tracking control and analyze the stability of nonlinear networked control systems with dynamic quantization, variable sampling intervals and communication delays. To improve the bandwidth utilization, an event-trigg...

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Main Authors: Gaofeng Peng, Ke Peng
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9157857/
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spelling doaj-42078c786c33422b83e0e60826ae6b3c2021-03-30T04:51:47ZengIEEEIEEE Access2169-35362020-01-01814364414365310.1109/ACCESS.2020.30142109157857An H&#x221E; Output Tracking Control Approach to Sampled-Data Control for Nonlinear Networked Control SystemsGaofeng Peng0https://orcid.org/0000-0002-0214-2227Ke Peng1College of Information Science and Engineering, Changsha Normal University, Changsha, ChinaCollege of Engineering and Design, Hunan Normal University, Changsha, ChinaIn this article, we study the problem of H<sub>&#x221E;</sub> output tracking control and analyze the stability of nonlinear networked control systems with dynamic quantization, variable sampling intervals and communication delays. To improve the bandwidth utilization, an event-triggered mechanism is introduced in network control systems. Different from traditional periodic sampling control, the event trigger control adopted in this study is only controlled when the current sampling signal meets the triggering conditions, which can effectively reduce resource waste in network control systems by ensuring system control performance. By adopting input-delay and parallel distributed compensation (PDC) techniques, we establish an augment tracking model based on the Takagi-Sugeno (T-S) fuzzy model, in which the sampling interval of the sampler and the signal transmission delay are transformed into the refreshing interval of a zero-order holder (ZOH). Furthermore, we use the applicable lyapunov-krasovski-based approach to derive conditions expressed in linear matrix inequalities (LMIs), helping the problem to be accurately solved using the LMI toolbox in Matlab. Examples are given to illustrate the effectiveness of our results, especially the good tracking effect of the designed fuzzy controller.https://ieeexplore.ieee.org/document/9157857/H∞ output tracking controlLyapunov–Krasovskii methodnonlinear networked control systemsT-S fuzzy model
collection DOAJ
language English
format Article
sources DOAJ
author Gaofeng Peng
Ke Peng
spellingShingle Gaofeng Peng
Ke Peng
An H&#x221E; Output Tracking Control Approach to Sampled-Data Control for Nonlinear Networked Control Systems
IEEE Access
H∞ output tracking control
Lyapunov–Krasovskii method
nonlinear networked control systems
T-S fuzzy model
author_facet Gaofeng Peng
Ke Peng
author_sort Gaofeng Peng
title An H&#x221E; Output Tracking Control Approach to Sampled-Data Control for Nonlinear Networked Control Systems
title_short An H&#x221E; Output Tracking Control Approach to Sampled-Data Control for Nonlinear Networked Control Systems
title_full An H&#x221E; Output Tracking Control Approach to Sampled-Data Control for Nonlinear Networked Control Systems
title_fullStr An H&#x221E; Output Tracking Control Approach to Sampled-Data Control for Nonlinear Networked Control Systems
title_full_unstemmed An H&#x221E; Output Tracking Control Approach to Sampled-Data Control for Nonlinear Networked Control Systems
title_sort h&#x221e; output tracking control approach to sampled-data control for nonlinear networked control systems
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description In this article, we study the problem of H<sub>&#x221E;</sub> output tracking control and analyze the stability of nonlinear networked control systems with dynamic quantization, variable sampling intervals and communication delays. To improve the bandwidth utilization, an event-triggered mechanism is introduced in network control systems. Different from traditional periodic sampling control, the event trigger control adopted in this study is only controlled when the current sampling signal meets the triggering conditions, which can effectively reduce resource waste in network control systems by ensuring system control performance. By adopting input-delay and parallel distributed compensation (PDC) techniques, we establish an augment tracking model based on the Takagi-Sugeno (T-S) fuzzy model, in which the sampling interval of the sampler and the signal transmission delay are transformed into the refreshing interval of a zero-order holder (ZOH). Furthermore, we use the applicable lyapunov-krasovski-based approach to derive conditions expressed in linear matrix inequalities (LMIs), helping the problem to be accurately solved using the LMI toolbox in Matlab. Examples are given to illustrate the effectiveness of our results, especially the good tracking effect of the designed fuzzy controller.
topic H∞ output tracking control
Lyapunov–Krasovskii method
nonlinear networked control systems
T-S fuzzy model
url https://ieeexplore.ieee.org/document/9157857/
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