An experimental demonstration of a distributed and event-based state estimation algorithm

Abstract

A distributed state estimation algorithm that makes use of model-based predictions to reduce communication requirements in a networked control architecture is tested on an unstable system. A cube balancing on one of its edges serves as the test platform, and six rotating bodies on the cube's inner faces constitute the agents in the control network. Each agent carries a computational unit, which runs estimation and control algorithms, and is associated with local sensors and an actuator. Measurement data is shared among the agents over a broadcast network. Each agent maintains two estimates of the system state: the first reflecting the common knowledge in the network, and the second additionally including all local sensor information. An agent's sensor measurement is only broadcast if it deviates from the common estimate of that measurement by more than a specified threshold. Experimental results show that the number of communicated measurements required for stabilizing the system can be significantly reduced with this event-based communication protocol.