Robust Optimal Consensus State Estimator for a Piezoactive Distributed Parameter System

Abstract

This paper proposes a consensus state estimator for sensor networks of distributed parameter structures. A thin beam with clamped–clamped boundary conditions enhanced by piezoelectric sensors is considered, and individual observers are assigned for each of these sensors. The so-called estimation agents are then connected to one another in a network with certain directed topology, and consensus is enforced between the agents estimated output in observers dynamics. Observer gains are optimized using algebraic Riccati equations (AREs), and robustness to measurement disturbances is applied via H∞ design. The consensus state estimator is then numerically investigated for a sensor network of five agents. According to the results of the optimal and robust designs, the proposed consensus observer successfully estimates the modal system states in finite time, whereas the estimation output is resilient to measurement disturbances. Implementation of the consensus sensor network increases the robustness of the estimation, due to its inherent redundancy.