Hybrid fuzzy direct/indirect adaptive controller for uncertain nonlinear systems

abstract

• This paper describes a new approach to adaptive control of uncertain nonlinear systems. A fuzzy logic controller is used to combine both direct and indirect methods. Based on the fuzzy neural networks, the plant unknown nonlinear functions are estimated, and then combined to form the indirect control law. In parallel, another fuzzy neural network approximates the direct adaptive control. According to the modelling error and its derivatives, the fuzzy logic controller modulates between direct and indirect adaptive controllers. The global stability of the overall system is shown by constructing a Lyapunov function. The simulation results show that within this scheme, the control objectives can be achieved with a fast convergence and optimal control for different dynamic regimes.

authors

• Bouhali, Othmane

published proceedings

• TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL

author list (cited authors)

• Bibi, Y., Bouhali, O., & Bouktir, T.

citation count

• 2

complete list of authors

• Bibi, Youssouf||Bouhali, Omar||Bouktir, Tarek

publication date

• November 2020

publisher

• SAGE Publications  Publisher

published in

• Transactions of the Institute of Measurement and Control  Journal

keywords

• Direct Adaptive Control
• Fuzzy Neural Networks (fnn)
• Fuzzy Systems (fs)
• Hybrid Adaptive Control
• Indirect Adaptive Control
• Lyapanov Stability
• Optimal Control

Digital Object Identifier (DOI)

• 10.1177/0142331220939728

start page

• 3012

end page

• 3023

volume

• 42

issue

• 15

URL

• http://dx.doi.org/10.1177/0142331220939728