Title
Design a New Intelligent Control for a Class of Nonlinear Systems
Document Type
Conference Proceeding
Publication Date
10-1-2019
Publication Title
Proceedings - 2019 6th International Conference on Control, Instrumentation and Automation, ICCIA 2019
Keywords
Backstepping Method, Input Saturation Constraint, Nonlinear Systems, Radial Basis Function Neural Networks (RBFNN).
Abstract
© 2019 IEEE. This paper presents a new method based on computational intelligence for precise control of a class of nonlinear systems. In this method, the Radial Basis Function Neural Networks (RBFNN) is used to approximate the uncertain functions in the system dynamics. In addition, a constraint is considered on the input. The Backstepping method is used for improving the overall accuracy of the control process. To evaluate the performance of the proposed method, a single-link robot arm with nonlinear dynamics and input saturation constraint is investigated. The simulation results show the performance of the proposed method.
DOI
10.1109/ICCIA49288.2019.9030868
Recommended Citation
Tavoosi, Jafar and Mohammadi, Fazel. (2019). Design a New Intelligent Control for a Class of Nonlinear Systems. Proceedings - 2019 6th International Conference on Control, Instrumentation and Automation, ICCIA 2019.
https://scholar.uwindsor.ca/electricalengpub/26