Fault-Tolerant H-Infinity Stabilization for Networked Cascade Control Systems With Novel Adaptive Event-Triggered Mechanism

Networked cascade control systems (NCCS) are susceptible to performance degradation from network-induced delays, communication constraints, and component failures. To address these interconnected challenges, this paper develops an integrated fault-tolerant H-infinity control framework for discrete-time nonlinear NCCS. A key contribution is a novel, disturbance-aware adaptive event-triggered mechanism (AETM) that uniquely incorporates measurable external disturbances into its triggering logic. This design dynamically reduces communication frequency while preserving performance. Furthermore, a unified co-design of the controller parameters and the AETM’s weighting matrix is established, while stability is rigorously substantiated through theoretical analysis. Simulation results for a boiler control system validate the proposed method’s effectiveness, demonstrating significant improvements in both system robustness and communication efficiency. Note to Practitioners—This study proposes an adaptive event-triggered mechanism for networked cascade control systems, which holds broad applicability in industrial processes such as boiler power generation and chemical processing. Unlike conventional static approaches, the proposed AETM dynamically adjusts communication frequency in response to measurable external disturbances, thereby optimizing resource utilization while ensuring system stability under network-induced delays, bandwidth constraints, and equipment failures. For industrial applications, the AETM significantly reduces communication overhead—our simulation on a boiler system demonstrated a 49.02% reduction in bandwidth usage compared to traditional event-triggered mechanisms, representing a 28.77% improvement over existing adaptive methods. When integrated with fault-tolerant H-infinity control, the framework maintains reliable control performance during actuator failures or disturbance spikes, enhancing operational efficiency in resource-constrained industrial environments.