Optimal Sensor Placement for Output Estimation Using an Artificial Bee Colony Algorithm with Pre-filter
R. P. P. F. Goetz, Y. Dwaraga, N. van de Wouw, T. Oomen, M. M. J. van de Wal, B. Sharif, H. J. Zwart
Abstract
Sensor placement for maximizing the estimation performance of the Kalman filter is an NP-hard optimization problem. Furthermore, its feasible set grows combinatorially with the candidate locations and the number of sensors. In this paper, we study this sensor placement problem for a 3D thermoelastic system modelled as a discrete-time linear stochastic model. We use the Novel Binary Artificial Bee Colony (NBABC) algorithm with a Gramian-based pre-filter to reduce the computational complexity. Our results show the efficiency and the fast convergence of the proposed approach.
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