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Model-Based Event-Triggered Sliding-Mode Control for Multi-Input Systems: Performance Analysis and Optimization

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

This article is concerned with the model-based event-triggered sliding-mode control (SMC) issue for multi-input systems, which is motivated by some existing results in a single-input case. A model-based event-triggered SMC scheme is first designed. In particular, a triggered condition is co-designed with SMC to achieve the reachability condition of a specified sliding surface. Thus, it can effectively mitigate the burden of data communication, and also eliminate the effect of the matched external disturbance and the model uncertainties in both system and input. For ensuring the stability of the model dynamics and the resulting sliding-mode dynamics simultaneously, an auxiliary disturbance input is introduced to the nominal model by compensating the switching term of the designed SMC law. Furthermore, the positive lower bound for the minimum interevent time is analyzed to ensure the feasibility of the proposed approach. To illustrate the proposed model-based event-triggered SMC approach from a practical viewpoint, two design problems to maximize the system robustness and performance are proposed, respectively. The nontrivial optimization problems are then solved by a genetic algorithm (GA). Finally, jet transport aircraft is utilized to demonstrate the effectiveness of the proposed results and algorithm.
Original languageEnglish
Pages (from-to)3902-3913
JournalIEEE Transactions on Cybernetics
Volume52
Issue number5
Online published23 Sept 2020
DOIs
Publication statusPublished - May 2022

Research Keywords

  • Computational modeling
  • Generators
  • Genetic algorithms
  • Sliding mode control
  • Optimization
  • Uncertainty
  • Stability analysis
  • Event-triggered mechanism
  • genetic algorithm (GA)
  • model-based networked control
  • sliding-mode control (SMC)
  • DESIGN

RGC Funding Information

  • RGC-funded

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