Control against faults of dynamical systems

Abstract

Modern industrial systems have become increasingly complex, making them more vulnerable to faults in critical components such as actuators and sensors. The objective of this thesis is to develop robust control strategies capable of managing faults in actuators and sensors while maintaining the stability and desired performance of complex systems, even in the presence of faults and external disturbances. To achieve this, the work combines advanced fault estimation techniques with robust fault-tolerant control (FTC) strategies designed for both linear and nonlinear systems. Specifically, for linear systems, Unknown Input Observers (UIO) and output feedback fault-tolerant controllers are developed, with their gain matrices obtained by optimizing a multi-objective function using a genetic algorithm. Similarly, for nonlinear systems, UIO and output feedback sliding mode faulttolerant controllers are designed. Stability is ensured through the use of Linear Matrix Inequalities (LMIs) based on Lyapunov functions. Additionally, the LMI region is employed to control the poles of the overall closed-loop system, allowing for greater flexibility in achieving desired performance levels. The proposed framework not only detects and isolates faults but also compensates for them to ensure smooth operation. Simulations involving systems such as wind turbines and DC motors demonstrate the effectiveness of these methods. This research contributes to safer and more efficient industrial processes