Robust Distributed Average Tracking for Double-Integrator Agents Without Velocity Measurements Under Event-Triggered Communication

This article focuses on an event-triggered mechanism to solve the distributed average tracking problem for double-integrator agents without velocity measurements. In some practical applications, velocity measurements may be unavailable due to technology and space limitations, and it is also usually less accurate and more expensive to implement. Before deriving the event-triggered approach, we first present a base algorithm without using velocity measurements, which sets the stage for the development of the event-triggered algorithm. The base algorithm has an advantage over the existing related works in the sense that there is no global information requirement for parameter design. Building on the base algorithm, we present an event-triggered algorithm that further removes the continuous communication requirement and is free of Zeno behavior. It is suitable for practical implementation, since in reality, the bandwidth of the communication network and power capacity are usually constrained. The event-triggered algorithm overcomes some practical limitations, such as the unbounded growth of the adaptive gain and requirement of additional internal dynamics, by constructing a new triggering strategy. In addition, a continuous nonlinear function is used to approximate the signum function to reduce the chattering phenomenon in reality. Numerical simulations are provided to illustrate the obtained results.

Automated summary

This article introduces an event-triggered mechanism to solve the distributed average tracking problem for double-integrator agents without velocity measurements. By removing the continuous communication requirement and Zeno behavior, the algorithm is suitable for practical implementation.