Dual-Power Fault Estimator-Based Event-Triggered Tracking Strategy for Nonlinear Servo Systems

Abstract

In this paper, the tracking control problem for nonlinear servo systems with gap nonlinearity under intermittent faults is investigated. Firstly, for intermittent faults (IFs), a dynamic threshold-based fault detection mechanism is designed to detect IFs occurrence and disappearance in real time, and a double-power-function fixed-time fault estimator is proposed to achieve fast and accurate fault magnitude estimation. Secondly, a novel fault-compensating tracking control strategy is developed by integrating fault diagnosis with controller design, which guarantees global boundedness of all closed-loop signals under intermittent faults. Thirdly, a dynamic memory event-triggered control scheme is proposed, which integrates historical error information through external auxiliary variables to regulate data transmission. This approach achieves longer trigger intervals than memoryless mechanisms while ensuring system stability and avoiding the Zeno effect. Finally, simulation and experimental results confirm the effectiveness of the proposed algorithm. Note to Practitioners—Nonlinear servosystems with gear backlash often face intermittent actuator faults in industrial automation, which can compromise tracking accuracy and increase network load due to redundant data transmission. This paper provides a practical control strategy integrating dynamic memory event-triggered control and fast fault estimation. Practitioners can apply the proposed approach to improve reliability and efficiency: the dual-power fixed-time fault estimator quickly reconstructs fault magnitude, while the DMETS incorporates historical error data to extend inter-event intervals and reduce communication. Representative parameter values and tuning considerations are provided in the simulation and semi-physical experiments. The method is applicable to robotics, precision machining, and aerospace servo systems.