Trajectory Synthesis for Fisher Information Maximization.
Trajectory Synthesis for Fisher Information Maximization.
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DOI：
10.1109/tro.2014.2345918
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发表时间：
2014-12-05
期刊：
影响因子：
--
通讯作者：
Murphey TD
中科院分区：
文献类型：
--
作者：
Wilson AD;Schultz JA;Murphey TD
Estimation of model parameters in a dynamic system can be significantly improved with the choice of experimental trajectory. For general nonlinear dynamic systems, finding globally “best” trajectories is typically not feasible; however, given an initial estimate of the model parameters and an initial trajectory, we present a continuous-time optimization method that produces a locally optimal trajectory for parameter estimation in the presence of measurement noise. The optimization algorithm is formulated to find system trajectories that improve a norm on the Fisher information matrix (FIM). A double-pendulum cart apparatus is used to numerically and experimentally validate this technique. In simulation, the optimized trajectory increases the minimum eigenvalue of the FIM by three orders of magnitude, compared with the initial trajectory. Experimental results show that this optimized trajectory translates to an order-of-magnitude improvement in the parameter estimate error in practice.
