Event-Triggered SMC for Networked Markov Jumping Systems With Channel Fading and Applications: Genetic Algorithm

Area of Science:

• Control Systems Engineering
• Networked Systems
• Stochastic Systems

Background:

• Networked systems face challenges like channel fading, affecting signal transmission reliability.
• Markov Jumping Systems (MJSs) exhibit state-dependent dynamics, requiring robust control strategies.
• Resource consumption is a critical concern in networked control systems.

Purpose of the Study:

• To develop an event-triggered sliding-mode control (SMC) for discrete-time MJSs with channel fading.
• To reduce resource usage in networked MJSs through an event-triggered protocol.
• To ensure the stability and performance of MJSs under uncertain network conditions.

Main Methods:

• Design of an event-triggered SMC law using a common sliding surface.
• Application of stochastic Lyapunov stability framework for stability analysis.
• Optimization using a genetic algorithm to minimize the sliding region.

Main Results:

• Sufficient conditions derived for mean-square stability of closed-loop MJSs.
• Demonstration of reaching the sliding region around the specified sliding surface.
• Validation of the proposed SMC method using the F-404 aircraft model.

Conclusions:

• The proposed event-triggered SMC effectively manages networked MJSs with channel fading.
• The genetic algorithm approach optimizes control performance by minimizing the convergence region.
• The method offers a resource-efficient and stable control solution for complex networked systems.