Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM
| Autor: | Junlong Fang, Yubo Liu, Kezhu Tan, Boyan Huang, Wenshuai He |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Lyapunov function
Control and Optimization Observer (quantum physics) Computer science 020209 energy Stability (learning theory) sliding mode observer Energy Engineering and Power Technology 02 engineering and technology lcsh:Technology law.invention symbols.namesake Robustness (computer science) Position (vector) Control theory law 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Engineering (miscellaneous) adaptive parameters estimation control lcsh:T Renewable Energy Sustainability and the Environment Rotor (electric) Estimation theory 020208 electrical & electronic engineering Filter (signal processing) interior permanent magnet synchronous motor super twisting algorithm parameter mismatch symbols Energy (miscellaneous) |
| Zdroj: | Energies; Volume 13; Issue 22; Pages: 5991 Energies, Vol 13, Iss 5991, p 5991 (2020) |
| ISSN: | 1996-1073 |
| DOI: | 10.3390/en13225991 |
| Popis: | To improve the observation accuracy and robustness of the sensorless control of an interior permanent magnet synchronous motor (IPMSM), a sliding mode observer based on the super twisting algorithm (STA-SMO) with adaptive parameters estimation control is proposed, as parameter mismatches are considered. First, the conventional sliding mode observer (CSMO) is analyzed. The conventional exponential approach law produces a large chattering phenomenon in the back EMF estimation, which causes a large observation error when filtering the chattering through the low-pass filter. Second, a high-order approach law of the super twisting algorithm is introduced to observe the rotor position and speed estimation, which uses the integral function to eliminate the chattering of the sliding mode. Third, an adaptive parameter estimation control (APEC) is presented to enhance the observation accuracy caused by parameter mismatches; the motor parameter adaptive law of the APEC is designed by Lyapunov’s stability law. Finally, the proposed method not only reduces both the chattering and the low-pass filter, but it also enhances accuracy and robustness against parameter mismatches, as discussed through simulations and experiments. |
| Databáze: | OpenAIRE |
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