Fractional Order Synchronous Reluctance Motor: Analysis, Chaos Control and FPGA Implementation

Stability and stabilization analysis of fractional‐order linear time‐invariant (FO‐LTI) systems with different derivative orders is studied in this paper. First, by using an appropriate linear matrix function, a single‐order equivalent system for the given different‐order system is introduced by which a new stability condition is obtained that is easier to check in practice than the conditions known up to now. Then the stabilization problem of fractional‐order linear systems with different fractional orders via a dynamic output feedback controller with a predetermined order is investigated, utilizing the proposed stability criterion. The proposed stability and stabilization theorems are applicable to FO‐LTI systems with different fractional orders in one or both of 0 < α < 1 and 1 ≤ α < 2 intervals. Finally, some numerical examples are presented to confirm the obtained analytical results.

Section: B Stabilitymentioning

confidence: 77%

Section: Resultsmentioning

confidence: 99%

Section: A Equivalencymentioning

confidence: 99%

Section: Stabilizationmentioning

confidence: 99%

Section: Stabilizationmentioning

confidence: 99%

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FPGA implementation of extended Kalman filter for SOC estimation of lithium‐ion battery in electric vehicle

Duan

et al. 2019

A FPGA implementation for a model-based state of charge (SOC) estimation is described in this paper. A Thevenin equivalent circuit model is designed for SOC estimation. The extended Kalman filter (EKF) is designed to complete the SOC estimation, and the error is within 1 % . The FPGA is chosen to achieve realtime SOC estimation. A fast matrix method is proposed to improve the calculation speed of the EKF in FPGA because the EKF algorithm requires many matrix operations. In addition, the embedded system based on the FPGA with a system on a programmable chip (SOPC) technique is built using the Qsys platform in Quartus II. Based on the embedded system, an online testing platform is established to monitor the terminal voltage and load current of the experimental battery in real time; experimental results show that the online SOC estimation is successful. The measurement results show that the FPGA embedded scheme of the EKF allows for successful implementation of the SOC estimation with accuracy and speed. The fast matrix method requires 0.00007 s to implement the SOC estimation and is four times faster than the conventional matrix method.