Dynamic boundary layer super‐twisting sliding mode control algorithm based on RBF neural networks for a class of leader‐follower multi‐agent systems
From MaRDI portal
Publication:6117658
DOI10.1002/RNC.7073OpenAlexW4388313917MaRDI QIDQ6117658
Unnamed Author, Unnamed Author, Chao Jia
Publication date: 20 March 2024
Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/rnc.7073
RBF neural networkdynamic boundary layersuper-twisting sliding mode controlleader-follower multi-agent system
Hierarchical systems (93A13) Variable structure systems (93B12) Multi-agent systems (93A16) Consensus (93D50)
Cites Work
- SMC design for robust \(H^{\infty}\) control of uncertain stochastic delay systems
- Passivity-based sliding mode control of uncertain singular time-delay systems
- Event-triggered sliding mode based consensus tracking in second order heterogeneous nonlinear multi-agent systems
- Finite-time consensus of neutrally stable multi-agent systems in the presence of input saturation
- Distributed adaptive fixed-time consensus tracking for second-order multi-agent systems using modified terminal sliding mode
- Distributed control gains design for consensus in multi-agent systems with second-order nonlinear dynamics
- Distributed consensus control for multi-agent systems using terminal sliding mode and Chebyshev neural networks
- Sliding Mode Control of Switched Stochastic Hybrid Systems
- Finite-Time Consensus for Leader-Following Second-Order Multi-Agent Networks
- Leaderless output consensus of multi‐agent systems with distinct relative degrees under switching directed topologies
- Finite-time consensus tracking for multi-agent systems with inherent uncertainties and disturbances
- SMC for Discrete-Time Nonlinear Semi-Markovian Switching Systems With Partly Unknown Semi-Markov Kernel
- Sliding mode control for multi‐agent systems under stochastic communication protocol
- Distributed consensus for multi‐agent systems via adaptive sliding mode control
This page was built for publication: Dynamic boundary layer super‐twisting sliding mode control algorithm based on RBF neural networks for a class of leader‐follower multi‐agent systems
