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  • 标题:Gain Adaptation in Sliding Mode Control Using Model Predictive Control and Disturbance Compensation with Application to Actuators
  • 本地全文:下载
  • 作者:Benedikt Haus ; Paolo Mercorelli ; Harald Aschemann
  • 期刊名称:Information
  • 电子版ISSN:2078-2489
  • 出版年度:2019
  • 卷号:10
  • 期号:5
  • 页码:182-200
  • DOI:10.3390/info10050182
  • 出版社:MDPI Publishing
  • 摘要:In this contribution, a gain adaptation for sliding mode control (SMC) is proposed that uses both linear model predictive control (LMPC) and an estimator-based disturbance compensation. Its application is demonstrated with an electromagnetic actuator. The SMC is based on a second-order model of the electric actuator, a direct current (DC) drive, where the current dynamics and the dynamics of the motor angular velocity are addressed. The error dynamics of the SMC are stabilized by a moving horizon MPC and a Kalman filter (KF) that estimates a lumped disturbance variable. In the application under consideration, this lumped disturbance variable accounts for nonlinear friction as well as model uncertainty. Simulation results point out the benefits regarding a reduction of chattering and a high control accuracy.
  • 关键词:sliding mode control; model predictive control; adaptive control; disturbance estimation; actuators sliding mode control ; model predictive control ; adaptive control ; disturbance estimation ; actuators
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