EMMD-Prony approach for dynamic validation of simulation models

Model validation and updating is critical to model credibility growth. In order to assess model credibility quantitatively and locate model error precisely, a new dynamic validation method based on extremum field mean mode decomposition（EMMD） and the Prony method is proposed in this paper. Firstly, complex dynamic responses from models and real systems are processed into stationary components by EMMD. These components always have definite physical meanings which can be the evidence about rough model error location. Secondly, the Prony method is applied to identify the features of each EMMD component. Amplitude similarity, frequency similarity, damping similarity and phase similarity are defined to describe the similarity of dynamic responses.Then quantitative validation metrics are obtained based on the improved entropy weight and energy proportion. Precise model error location is realized based on the physical meanings of these features. The application of this method in aircraft controller design provides evidence about its feasibility and usability.

Using the Prony Analysis for Assessing Servo Drive Control

The Prony Analysis is already used in different fields of science and industries. The described new approach intends assessing the performance of Servo Drive Control. The basic approach is, that two important dynamic parameters of closed loop behavior, damping and frequency, are estimated by the Prony method. Hence analyzing a control loop in this way leads to a statement concerning the quality of control and allows comparing different parameter sets. The paper presents results achieved by using this method on a test rig.

An Application of Prony’s Sum of Exponentials Method to Pharmacokinetic Data Analysis

We discuss the basic concept of compartmental modelling in pharmacokinetics and demonstrate that all the solutions admitted by multi-compartment models of classical pharmacokinetics are expressed as linear combinations of exponential functions of time.This lends itself to data analysis that depends on fitting exponential functions to finite size sets.A mathematical method developed a long time ago to deal with this type of problem is called Prony’s method.We discuss the usefulness of this method in pharmacokinetic modeling and apply it to a particular data set obtained for the drug mibefradil.In spite of the method’s power in dealing with well-behaved data sets,we indicate the existence of severe limitations since real concentration curves coming from pharmacokinetic data are seldom purely exponential.

A voltage resonance-based single-ended online fault location algorithm for DC distribution networks

A novel single-ended online fault location algorithm is investigated for DC distribution networks. The proposed algorithm calculates the fault distance based on the characteristics of the voltage resonance. The Prony's method is introduced to extract the characteristics. A novel method is proposed to solve the pseudo dual-root problem in the calculation process. The multiple data windows are adopted to enhance the robustness of the proposed algorithm. An index is proposed to evaluate the accuracy and validity of the results derived from the various data windows. The performances of the proposed algorithm in different fault scenarios were evaluated using the PSCAD/EMTDC simulations. The results show that the algorithm can locate the faults with transient resistance using the 1.6 ms data of the DC-side voltage after a fault inception and offers a good precision.