Observer-based Data-driven Sliding Mode Control for a Discrete-time Nonlinear Multiagent Systems
- Resource Type
- Conference
- Authors
- Yin, Caiyun; Lin, Guohuai; Chen, Guangdeng; Ma, Hui; Li, Hongyi
- Source
- 2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Data Driven Control and Learning Systems Conference (DDCLS), 2023 IEEE 12th. :467-472 May, 2023
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Learning systems
Sufficient conditions
Analytical models
Protocols
Consensus control
Stability analysis
Data models
Data-driven
Multiagent systems
Sliding mode control
- Language
- ISSN
- 2767-9861
In this work, an observer-based sliding mode control strategy is proposed for a discrete-time nonlinear multiagent systems (MASs) with unknown disturbance. Only some agents are capable of acquiring the reference trajectory, and the dynamic models of the agents are unknown. Unlike the traditional model-based consensus control protocol, this method is data-driven and solely dependent on the input/output (I/O) data of the agents. The stability of the proposed control strategy is ensured by theoretical analysis and the simulation outcomes ultimately validate the viability of the developed approach.