Event-Triggered Tracking Control for Adaptive Anti-Disturbance Problem in Systems with Multiple Constraints and Unknown Disturbances
Aimed at the objective of anti-disturbance and reducing data transmission, this article discusses a novel dynamic neural network (DNN) modeling-based anti-disturbance control for a system under the framework of an event trigger. In order to describe dynamical characteristics of irregular disturbance...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/25/1/43 |
| _version_ | 1827626182733987840 |
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| author | Hong Shen Qin Wang Yang Yi |
| author_facet | Hong Shen Qin Wang Yang Yi |
| author_sort | Hong Shen |
| collection | DOAJ |
| description | Aimed at the objective of anti-disturbance and reducing data transmission, this article discusses a novel dynamic neural network (DNN) modeling-based anti-disturbance control for a system under the framework of an event trigger. In order to describe dynamical characteristics of irregular disturbances, exogenous DNN disturbance models with different excitation functions are firstly introduced. A novel disturbance observer-based adaptive regulation (DOBAR) method is then proposed, which can capture the dynamics of unknown disturbance. By integrating the augmented triggering condition and the convex optimization method, an effective anti-disturbance controller is then found to guarantee the system stability and the convergence of the output. Meanwhile, both the augmented state and the system output are constrained within given regions. Moreover, the Zeno phenomenon existing in event-triggered mechanisms is also successfully avoided. Simulation results for the A4D aircraft models are shown to verify the availability of the algorithm. |
| first_indexed | 2024-03-09T12:50:14Z |
| format | Article |
| id | doaj.art-a9df815847754873ae14f3f4cbf9f3e9 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T12:50:14Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-a9df815847754873ae14f3f4cbf9f3e92023-11-30T22:07:26ZengMDPI AGEntropy1099-43002022-12-012514310.3390/e25010043Event-Triggered Tracking Control for Adaptive Anti-Disturbance Problem in Systems with Multiple Constraints and Unknown DisturbancesHong Shen0Qin Wang1Yang Yi2College of Business, Yangzhou University, Yangzhou 225127, ChinaCollege of Information Engineering, Yangzhou University, Yangzhou 225127, ChinaCollege of Information Engineering, Yangzhou University, Yangzhou 225127, ChinaAimed at the objective of anti-disturbance and reducing data transmission, this article discusses a novel dynamic neural network (DNN) modeling-based anti-disturbance control for a system under the framework of an event trigger. In order to describe dynamical characteristics of irregular disturbances, exogenous DNN disturbance models with different excitation functions are firstly introduced. A novel disturbance observer-based adaptive regulation (DOBAR) method is then proposed, which can capture the dynamics of unknown disturbance. By integrating the augmented triggering condition and the convex optimization method, an effective anti-disturbance controller is then found to guarantee the system stability and the convergence of the output. Meanwhile, both the augmented state and the system output are constrained within given regions. Moreover, the Zeno phenomenon existing in event-triggered mechanisms is also successfully avoided. Simulation results for the A4D aircraft models are shown to verify the availability of the algorithm.https://www.mdpi.com/1099-4300/25/1/43dynamic neural networks (DNNs)event-triggered controlanti-disturbance controladaptive controlsaturation constraintoutput constraint |
| spellingShingle | Hong Shen Qin Wang Yang Yi Event-Triggered Tracking Control for Adaptive Anti-Disturbance Problem in Systems with Multiple Constraints and Unknown Disturbances Entropy dynamic neural networks (DNNs) event-triggered control anti-disturbance control adaptive control saturation constraint output constraint |
| title | Event-Triggered Tracking Control for Adaptive Anti-Disturbance Problem in Systems with Multiple Constraints and Unknown Disturbances |
| title_full | Event-Triggered Tracking Control for Adaptive Anti-Disturbance Problem in Systems with Multiple Constraints and Unknown Disturbances |
| title_fullStr | Event-Triggered Tracking Control for Adaptive Anti-Disturbance Problem in Systems with Multiple Constraints and Unknown Disturbances |
| title_full_unstemmed | Event-Triggered Tracking Control for Adaptive Anti-Disturbance Problem in Systems with Multiple Constraints and Unknown Disturbances |
| title_short | Event-Triggered Tracking Control for Adaptive Anti-Disturbance Problem in Systems with Multiple Constraints and Unknown Disturbances |
| title_sort | event triggered tracking control for adaptive anti disturbance problem in systems with multiple constraints and unknown disturbances |
| topic | dynamic neural networks (DNNs) event-triggered control anti-disturbance control adaptive control saturation constraint output constraint |
| url | https://www.mdpi.com/1099-4300/25/1/43 |
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