Distributed estimation and control over mobile sensor networks with jointly connected topology: Event-triggered...

Area of Science:

• Control Systems Engineering
• Robotics and Automation
• Networked Systems

Background:

• Mobile sensor networks (MSNs) face challenges in distributed tracking control.
• Existing event-triggered methods often require target state information, limiting applicability.
• Jointly connected topologies (JCT) allow for dynamic, non-permanently connected communication graphs in MSNs.

Purpose of the Study:

• To develop novel distributed event-triggered tracking control schemes for MSNs.
• To address tracking control under jointly connected topologies (JCT) where connectivity is not guaranteed.
• To enable target state estimation and tracking without prior knowledge of the target's states.

Main Methods:

• Development of two event-triggered algorithms for linear and Lipschitz nonlinear MSNs.
• Utilizing an event-triggered approach to minimize continuous information exchange between sensor nodes.
• Employing the Cauchy convergence criterion and a common Lyapunov function to establish stability and control conditions.

Main Results:

• Successful estimation and tracking of mobile targets using event-triggered control.
• Demonstrated effectiveness of the schemes under jointly connected topologies (JCT), including disconnected graphs.
• Validated algorithms for scenarios where target states are not available a priori.

Conclusions:

• The proposed event-triggered tracking control schemes are effective for MSNs with JCT.
• The methods provide a robust solution for target tracking even without target state information.
• The research contributes to efficient and practical distributed control in dynamic sensor networks.