Lan J., Yu X., Mai V. T., Zhakiyev N., Yedilkhan D., Khani A., Mohammadzadeh A.
A Type-3 Fuzzy Actuator-Fault-Tolerant Control Strategy with Lyapunov Predictive Learning // International Journal of Computational Intelligence Systems. — 2026. — Vol. 19. — Article No. 156. — DOI: 10.1007/s44196-026-01255-6.

Abstract: This paper introduces an active fault-tolerant control (AFTC) strategy for detecting and eliminating actuator faults in nonlinear control systems. The proposed scheme consists of two subsystems: a main control system and a parallel dynamic virtual system. The main subsystem employs a Type-3 fuzzy logic system (FLS) for online identification of system uncertainties, a T3-FLS-based predictive controller, and a supplementary compensator. The virtual subsystem mirrors this structure, incorporating its own T3-FLS, predictive control, compensator, and fault detection mechanism. Fault detection is performed using two T3-FLS-based estimators, supported by a virtual sensor concept for reconstructing actuator signals. The method relies solely on measurable input–output data, eliminating the need for explicit system dynamics. Adaptive updating of the T3-FLS parameters is performed in real time based on feedback from the virtual structure. Stability is analytically proven using Lyapunov-based methods. The approach is validated on two applications: blood-glucose regulation in diabetes and inflation control in a dynamic economic model, demonstrating strong performance in fault detection and compensation.

Link / DOI: https://doi.org/10.1007/s44196-026-01255-6