Online Neuro-Fuzzy Controller: Design for Robust Stability

• Main Authors: Everthon De Souza Oliveira, Ricardo H. C. Takahashi, Walmir Matos Caminhas
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Adaptive control; fuzzy control; ONFC; robust stability
• Online Access: https://ieeexplore.ieee.org/document/9239264/

The Online Neuro-Fuzzy Controller (ONFC) is a fuzzy-based adaptive control that uses a very simple structure and can control nonlinear, time-varying and uncertain systems. Its efficiency and low computational cost allowed applications in several industrial plants successfully. However, none of the previous works on the ONFC provided a design procedure endowed with formal guarantees of robust closed-loop stability. In this paper, some conditions for ONFC robust stability, considering system polytopic uncertainties, are presented using the Lyapunov method. A new adaptation rule is proposed that dynamically varies the adaptation gain and incorporates the dead-zone technique to ensure robustness to the noise measurement. A reference model is also introduced, in order to allow a direct specification of the closed-loop dynamics. Simulation results show that the new design conditions present good performance in the control of several types of systems.