Abstract:
This project deals with fault-tolerant control (FTC) for nonlinear systems using an observer-
based estimation strategy. A complete framework is developed by combining Takagi-Sugeno
fuzzy modeling with fast iterative k-step observers for real-time actuator fault estimation and
compensation. Centralized and distributed observers are designed for both single-agent and
multi-agent systems, with stability ensured using Lyapunov theory and Linear Matrix Inequal-
ities. The method is applied to differential drive mobile robots, maintaining trajectory tracking
despite actuator faults. The control architecture is implemented in ROS and tested in a re-
alistic robotic simulation. Results confirm the method’s reliability and practical applicability.
This work advances robust and adaptive control strategies for autonomous systems under fault
conditions.
