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    Data driven approach for performance assessment of linear and nonlinear Kalman filters
    A new technique is developed for assessing the performance of linear and nonlinear Kalman filter based state estimators. The proposed metric will indicate the performance of these state estimators which will be primarily influenced by: (i) difference between the model dynamics and process dynamics and, (ii) various approximations of the nonlinear plant dynamics used in nonlinear Kalman filters. Currently, there exists no such quantification method to analyze the performance of linear and nonlinear Kalman filters, a key requirement for improvement and a practical benchmark for comparison of these state estimation algorithms. The proposed technique uses the generalized Hurst exponent of the prediction errors (difference in measured output and a posteriori estimates) obtained from the state estimators to quantify the performance. This technique could be implemented on-line as it requires only plant operating data and the predicted outputs (from the linear and nonlinear Kalman filters) to assess the performance. Several simulation studies demonstrate the applicability of the proposed performance metric to both linear and non-linear Kalman filters. © 2014 American Automatic Control Council.
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    Publication
    On-line performance monitoring of PEM fuel cell using a fast EIS approach
    The Polymer Electrolyte Membrane Fuel Cell is a widely researched fuel cell, and a highly potential candidate for alternate power generation. However, technical issues such as membrane flooding and drying prevent its deployment in many applications. Electrochemical Impedance Spectroscopy (EIS) is a very powerful technique that is used to isolate flooding and drying of the fuel cell from operating data. Such information about the state of operation of the cell is critical to deciding necessary control actions to maintain the health and performance of the cell. However, the time taken in obtaining measurements in EIS can be large enough to allow the cell to flood or dry beyond irreparable damage, rendering it a mere postmortem technique. Moreover, after long durations of perturbation, the cell takes a considerable amount of time to return to its regular operation. A new technique is proposed that uses the concept of EIS, but is computationally faster and gives results comparable with those of traditional EIS. This technique is based on perturbing the cell with a small chirp signal containing large number of frequencies instead of series of small sinusoids at different frequencies. Simulation results on isolation of flooding and drying based on Fast EIS are illustrated and future work directions are indicated.