An RLS-based Adaptive-gain SMO for Deadbeat Predictive Speed Control
ID:67 View Protection:ATTENDEE Updated Time:2025-11-04 15:23:53 Hits:331 Oral Presentation

Start Time:2025-11-09 09:03(Asia/Shanghai)

Duration:1min

Session:P Poster presentation » P77.Electric Machine Design and Control

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Abstract
In the deadbeat speed control system of an interior permanent magnet synchronous motor (IPMSM),introducing a sliding mode observer (SMO) can reduce the cost of torque sensors and mitigate sensor noise. However, the use of switching functions inevitably induces chattering. Although decreasing the sliding mode gain alleviates chattering, it also compromises response speed. To address this trade-off, this paper proposes an recursive least squares (RLS)-based adaptive-gain SMO. Unlike conventional adaptive SMOs, the proposed method employs an RLS-based adaptive gain to anticipate the evolution of estimation errors and adjust accordingly, thereby accommodating unknown sudden load disturbances while keeping the chattering at a level comparable to that of a fixed small-gain SMO. The effectiveness and superior performance of the proposed method are validated on a 2.3-kW IPMSM control platform.
Keywords
PMSM,SMO,recursive least squares,Deadbeat Predictive Speed Control
Speaker
Ruiqi Li
Southwest Jiaotong University

Submission Author
瑞奇 李 southwestjiaotong university
德青 黄 西南交通大学
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Important Date
  • Conference Date

    Nov 07

    2025

    to

    Nov 09

    2025

  • Oct 30 2025

    Draft paper submission deadline

  • Nov 10 2025

    Registration deadline

Sponsored By
IEEE西南交通大学IAS学生分会
Organized By
西南交通大学电气工程学院
SPACI车网关系研究室
四川大学电力系统稳定与高压直流输电研究团队