ELM Based Adaptive Backstepping Control of Hybrid Conveying Mechanism With Mismatched Disturbances
- Resource Type
- Conference
- Authors
- Yuan, Wei; Wang, Yao; Gao, Guoqin
- Source
- IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society Industrial Electronics Society, IECON 2019 - 45th Annual Conference of the IEEE. 1:6255-6260 Oct, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Backstepping
Disturbance observers
Trajectory tracking
Lyapunov methods
Adaptive control
Force
Stability analysis
Mismatched disturbances
hybrid conveying mechanism
adaptive backstepping control
extreme learning machine
trajectory tracking
- Language
- ISSN
- 2577-1647
An extreme learning machine based adaptive backstepping control law is proposed for the problem of trajectory tracking control of hybrid conveying mechanism with mismatched disturbances. In order to eliminate matched and mismatched disturbances in different channels, two extreme learning machine disturbance observers are used to estimate and compensate disturbances in system. According to the stability of Lyapunov function, control law and adaptive law are designed to realize the trajectory tracking control of the hybrid conveying mechanism. The simulation results show that the proposed control law has good trajectory tracking accuracy and robustness under the condition of mismatched disturbances.