Online adaptive fuzzy neural identification and control of nonlinear dynamic systems
Autonomous robotic systems
Information Sciences—Informatics and Computer Science: An International Journal
A self-organizing feature map-driven approach to fuzzy approximate reasoning
Expert Systems with Applications: An International Journal
Gradient projection method and equality index in recurrent neural fuzzy network
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
Intelligent nonlinear friction compensation using friction observer and backstepping control
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Design of fuzzy neural network based control system for cement rotary kiln
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 2
The hybrid RFNN control for a PMSM drive electric scooter using rotor flux estimator
Advances in Fuzzy Systems
| Hi-index | 0.00 |
A supervisory fuzzy neural network (FNN) control system is designed to track periodic reference inputs in this study. The control system is composed of a permanent magnet (PM) synchronous servo motor drive with a supervisory FNN position controller. The supervisory FNN controller comprises a supervisory controller, which is designed to stabilize the system states around a defined bound region and an FNN sliding-mode controller, which combines the advantages of the sliding-mode control with robust characteristics and the FNN with online learning ability. The theoretical and stability analyses of the supervisory FNN controller are discussed in detail. Simulation and experimental results show that the proposed control system is robust with regard to plant parameter variations and external load disturbance. Moreover, the advantages of the proposed control system are indicated in comparison with the sliding-mode control system