On State-Constrained Containment Control for Nonlinear Multiagent Systems Using Event-Triggered Input
Southwest University · Texas A&M University at Qatar · +2 more institutions
Abstract
The neural-approximation-based adaptive nonlinear containment control issue for multiagent systems with full-state constraints is studied by invoking the backstepping approach. First, the barrier Lyapunov functions are established to deal with the state constraining issue in the multiple leaders/followers control scenarios. Then, by introducing the first-order filter, the system communication burden is substantially reduced. Moreover, the event-triggered controller is constructed by utilizing the switching-based mechanism so that the system security, control accuracy, resource consumption, and imposed state constraints are neatly balanced. We prove the output of each follower can converge to the desired hull…
Citation impact
- FWCI
- 38.35
- Percentile
- 100%
- References
- 35
Authors
5Topics & keywords
- Backstepping
- Control theory (sociology)
- Computer science
- Controller (irrigation)
- Nonlinear system
- State (computer science)
- Bounded function
- Lyapunov function
- Decent work and economic growth