Abstract
An adaptive fuzzy neural network (FNN) control scheme is proposed for a marine vessel with time-varying constraints, guaranteed transient response and unknown dynamics. A series of continuous constraint functions are introduced to shape the motion of a marine vessel. To deal with the constraint problems and transient response problems, an asymmetric time-varying barrier Lyapunov function is designed to ensure that the system states are upper bounded by the considered constraint functions. FNNs are constructed to identify the unknown dynamics. Considering existing approximation errors when FNNs approximating the unknown dynamics, an adaptive term is designed to compensate the approximation errors in order to obtain accurate control. Via Lyapunov stability theory, it has been proved that all the states in the closed-loop system are uniformly bounded ultimately without violating the corresponding prescribed constraint region. Two comparative simulations are carried out to verify the effectiveness of the proposed control.
| Original language | English |
|---|---|
| Pages (from-to) | 1448-1455 |
| Number of pages | 8 |
| Journal | IET Control Theory and Applications |
| Volume | 12 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - 1 Jul 2018 |
Keywords
- neurocontrollers
- transient response
- stability
- adaptive control
- Lyapunov methods
- time-varying systems
- closed loop systems
- fuzzy neural nets
- fuzzy control
- marine vehicles
- control system synthesis
- approximation theory
- time-varying constraints
- adaptive fuzzy neural network control scheme
- marine vessel
- guaranteed transient response
- unknown dynamics
- continuous constraint functions
- constraint problems
- transient response problems
- asymmetric time-varying barrier Lyapunov function
- approximation errors
- adaptive term
- adaptive fuzzy control
- constraint functions
- FNN
- system states
- Lyapunov stability theory
- closed-loop system
- prescribed constraint region