Wavelet Dual Function-Link Fuzzy Brain Emotional Learning System Design for System Identification and Trajectory Tracking of Nonlinear Systems
- Resource Type
- Conference
- Authors
- Huynh, Tuan-Tu; Lin, Chih-Min
- Source
- 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference on. :1653-1657 Oct, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Orbits
Learning systems
Trajectory
Time-varying systems
Artificial neural networks
System identification
Nonlinear systems
Wavelet function
function-link network
fuzzy brain emotional learning system
time-varying system
chaotic trajectory
- Language
- ISSN
- 2577-1655
This paper proposes a new efficient identification system for nonlinear systems. The proposed wavelet dual function-link fuzzy brain emotional learning system (WDFLFBELS) is used as an identifier to identify the system and to track the trajectory of nonlinear systems. The WDFLFBELS consists of three sub-structures and a fuzzy inference system. The sub-structures include a prefrontal cortex, an amygdala, and a new dual function-link network, then it can efficiently reduce the identification and tracking errors, and obtain good performance. The gradient descent technique is used to find the adaptive laws to online tune the parameters of the system effectively. Simulation studies for identifying a time-varying system and tracking a chaotic trajectory are performed to validate the effectiveness and superiority of the proposed method.