Predictor-Based Periodic Event-Triggered Control for Dual-Rate Networked Control Systems With Disturbances

Networked control systems often face significant challenges when sensor sampling rates differ from actuator update frequencies. That uncertainty drove researchers to seek robust strategies for managing these dual-rate architectures under external interference. Prior research has shown that nonvanishing disturbances can severely degrade system stability in such environments. However, existing methods frequently struggle to maintain high performance during the intervals between slow sensor measurements. No prior work had resolved the difficulty of accurately estimating states while simultaneously minimizing network traffic. This gap motivated the development of advanced observers capable of operating effectively within intersample time windows. Previous approaches often lacked the necessary integration between state prediction and event-triggered communication protocols. Consequently, the field required a more cohesive framework to address these specific operational constraints.

The aim of this research is to design a robust control strategy for dual-rate networked systems facing nonvanishing disturbances. These systems typically suffer from performance degradation due to the mismatch between slow sensor sampling and fast actuator updates. The authors seek to address the challenge of maintaining accurate state estimation during the intervals between sensor measurements. This motivation drove them to develop an output predictor-based observer capable of functioning within intersample time windows. They also intend to propose an active anti-disturbance controller that updates at a fast rate to improve system reliability. Furthermore, the study aims to implement a periodic event-triggered mechanism to optimize communication network usage. The researchers want to ensure that the control method is easily applicable to digital platforms. Finally, they intend to verify the effectiveness of their proposed design through practical speed control simulations.

The researchers developed a discrete-time control architecture specifically designed for dual-rate environments. Their review approach involved constructing a predictor-based observer to estimate internal variables during slow sensor sampling intervals. They formulated an active anti-disturbance controller that operates at a fast rate to ensure consistent performance. The team designed a periodic event-triggered mechanism to regulate data transmission across the communication network. They utilized prediction techniques to generate packets containing both current and future control inputs. This design allows the system to maintain stability even when network resources are limited. The authors validated their approach through numerical simulations of a practical speed control application. This methodology ensures that the proposed framework remains computationally feasible for digital implementation.

The study demonstrates that the proposed predictor-based observer accurately estimates system states and disturbances during intersample intervals. Key findings from the literature suggest that the active anti-disturbance controller effectively achieves desirable performance despite nonvanishing disturbances. The periodic event-triggered mechanism successfully determines data transmission, reducing unnecessary network traffic. Simulation results of a practical speed control system confirm the effectiveness of the proposed control method. The authors report that the discrete-time form facilitates easy implementation on digital platforms. Their analysis shows that the integration of prediction techniques allows for high-frequency actuator updates. The results indicate that the system maintains robust disturbance rejection capabilities throughout the operation. The findings highlight the successful coordination between slow-rate sensing and fast-rate control inputs.

The authors propose a novel framework that successfully bridges the gap between slow-rate sensing and fast-rate actuation. Their synthesis indicates that the predictor-based observer effectively mitigates the impact of nonvanishing disturbances. The study demonstrates that the periodic event-triggered mechanism significantly reduces communication load without sacrificing control precision. These findings imply that digital platforms can achieve superior disturbance rejection through the integration of predictive data packets. The researchers suggest that their discrete-time approach offers a practical solution for real-world implementation in industrial settings. Synthesis of the results confirms that the proposed controller maintains desirable performance levels despite the inherent limitations of dual-rate systems. The authors conclude that their method provides a robust alternative to traditional control schemes in networked environments. This work highlights the potential for improved efficiency in complex systems through strategic data transmission and state estimation.