Adaptive sampling rate control for networked systems based on statistical characteristics of packet disordering.

Area of Science:

• Control Engineering
• Networked Systems
• Stochastic Systems

Background:

• Networked control systems (NCSs) face challenges from packet disordering, transmission delays, and packet loss.
• Existing control schemes struggle to maintain stability and performance under these communication imperfections.

Purpose of the Study:

• To develop an adaptive sampling rate control scheme for NCSs that mitigates packet disordering.
• To ensure the stability of NCSs despite disordering, delay, and packet loss.
• To design a controller that adapts the sampling period for improved performance.

Main Methods:

• A novel sampling rate control algorithm is proposed, utilizing statistical characteristics of disordering entropy.
• The closed-loop NCS is modeled as an uncertain and stochastic system for controller design.
• Stochastic stability is analyzed using Linear Matrix Inequalities (LMIs).
• An adaptive tracking controller is developed to adjust the sampling period.

Main Results:

• The proposed scheme effectively addresses packet disordering in NCSs.
• Sufficient conditions for stochastic stability were derived using LMIs.
• The adaptive tracking controller successfully adjusts the sampling period.
• Experimental results validate the scheme's effectiveness and advantages.

Conclusions:

• The adaptive sampling rate control scheme offers a robust solution for NCSs with packet disordering.
• The methodology provides a framework for designing stable and reliable NCSs under adverse network conditions.
• The adaptive nature of the controller enhances tracking performance and system adaptability.