Neural network compensator-based robust iterative learning control scheme for mobile robots nonlinear systems with disturbances and uncertain parameters.
Zhengquan ChenYandong HouRuirui HuangQianshuai ChengPublished in: Appl. Math. Comput. (2024)
Keyphrases
- control scheme
- nonlinear systems
- control law
- tracking error
- external disturbances
- controller design
- iterative learning
- adaptive neural control
- adaptive neural
- lyapunov function
- fuzzy controller
- mobile robot
- robust stability
- trajectory tracking
- neural controller
- closed loop
- proportional integral derivative
- neural network
- sliding mode control
- adaptive fuzzy
- nonlinear functions
- control strategy
- control system
- stability analysis
- linear matrix inequality
- dynamic model
- neural network controller
- adaptive control
- fault tolerant control
- visual servoing
- fuzzy control
- fuzzy systems
- sliding mode
- fuzzy inference system
- robot manipulators
- fuzzy neural network
- control theory
- fuzzy model
- pid controller
- pi controller
- autonomous robots
- control algorithm
- path planning
- real time
- genetic algorithm
- inverted pendulum
- dynamic environments
- learning rate
- robot control
- fuzzy logic controller
- motion planning
- feedback control
- fuzzy logic
- mathematical model
- dead zone
- multi robot
- optimal control