Partial and total actuator faults accommodation for input-affine nonlinear process plants.

Area of Science:

• Control Engineering
• Nonlinear Systems
• Adaptive Control

Background:

• Actuator failures and external disturbances pose significant challenges in controlling nonlinear systems.
• Existing fault-tolerant control strategies often require complex fault detection and diagnosis (FDD) units.
• Model Reference Adaptive System (MRAS) structures offer a framework for adaptive control but require enhancements for fault tolerance.

Purpose of the Study:

• To propose a novel fault-tolerant control system for input-affine nonlinear plants.
• To enhance the robustness of Model Reference Adaptive System (MRAS) based controllers against actuator failures and external disturbances.
• To develop a control strategy that does not necessitate a separate Fault Detection and Diagnosis (FDD) unit.

Main Methods:

• Modification of the conventional Model Reference Adaptive System (MRAS) control law.
• Augmentation of the MRAS structure with two compensating terms.
• One term designed to eliminate nonlinear dynamics, the other to compensate for actuator faults and disturbances.
• Evaluation of the proposed control scheme on a Continuous Stirred Tank Reactor (CSTR) system.

Main Results:

• The proposed control system effectively accommodates both partial and total actuator failures.
• The system demonstrates robustness against bounded external disturbances.
• The modified MRAS structure successfully compensates for nonlinear dynamics and fault effects.
• The absence of an FDD unit simplifies the control architecture.
• Satisfactory performance was achieved in simulations using a CSTR model.

Conclusions:

• The developed fault-tolerant control system based on a modified MRAS structure provides a robust and effective solution for nonlinear plants.
• The proposed methodology successfully handles actuator failures and external disturbances without requiring an FDD unit.
• The enhanced MRAS structure exhibits good robustness against parameter variations, making it suitable for real-world applications.