A Quadratic Boundedness Approach to Event‐Triggered Nonfragile Model Predictive Fault‐Tolerant Control for IT2 T‐S Fuzzy Systems

ABSTRACT This study provides a new static output feedback model predictive fault‐tolerant regulation strategy for a class of nonlinear dynamics described by interval type‐2 Takagi‐Sugeno fuzzy models with embedded process constraints, that aims at achieving robustness against nonvanishing bounded disturbances and actuator faults. To ameliorate network transmission burden and reduce energy consumption of the fault‐tolerant regulation scheme, an event‐triggered control approach is incorporated. Additionally, a nonfragile controller architecture is implemented to maintain resilience against potential gain perturbations. Within this fuzzy control framework, leveraging quadratic boundedness techniques enables converting the controller design into a convex optimization problem that complies with the specified process constraints. In turn, sufficient conditions for the solvability of the aforementioned optimization problem are established, accompanied by the derivation of explicit controller gain matrices. Moreover, our approach ensures recursive feasibility and quadratic stability of the closed‐loop dynamics under less conservative conditions, even when subject to actuator faults and nonvanishing bounded disturbances. The efficacy and advantages of the developed controller are validated through two illustrative examples.