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Gain Adaptation in Sliding Mode Control Using Model Predictive Control and Disturbance Compensation with Application to Actuators

Research output: Journal contributions › Journal articles › Research › peer-review

Standard

Gain Adaptation in Sliding Mode Control Using Model Predictive Control and Disturbance Compensation with Application to Actuators. / Haus, Benedikt; Mercorelli, Paolo; Aschemann, Harald.
In: Information, Vol. 10, No. 5, 182, 25.05.2019.

Research output: Journal contributions › Journal articles › Research › peer-review

Harvard

Haus, B, Mercorelli, P & Aschemann, H 2019, 'Gain Adaptation in Sliding Mode Control Using Model Predictive Control and Disturbance Compensation with Application to Actuators', Information, vol. 10, no. 5, 182. https://doi.org/10.3390/info10050182

APA

Haus, B., Mercorelli, P., & Aschemann, H. (2019). Gain Adaptation in Sliding Mode Control Using Model Predictive Control and Disturbance Compensation with Application to Actuators. Information, 10(5), Article 182. https://doi.org/10.3390/info10050182

Vancouver

Haus B, Mercorelli P, Aschemann H. Gain Adaptation in Sliding Mode Control Using Model Predictive Control and Disturbance Compensation with Application to Actuators. Information. 2019 May 25;10(5):182. doi: 10.3390/info10050182

Bibtex

@article{2740e8e3222846cb92feddd9cd6ae648,
title = "Gain Adaptation in Sliding Mode Control Using Model Predictive Control and Disturbance Compensation with Application to Actuators",
abstract = "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.",
keywords = "sliding mode control, model predictive control, adaptive control, disturbance estimation, actuators, Engineering",
author = "Benedikt Haus and Paolo Mercorelli and Harald Aschemann",
note = "Publisher Copyright: {\textcopyright} 2019 by the authors.",
year = "2019",
month = may,
day = "25",
doi = "10.3390/info10050182",
language = "English",
volume = "10",
journal = "Information",
issn = "2078-2489",
publisher = "MDPI AG",
number = "5",

}

RIS

TY - JOUR

T1 - Gain Adaptation in Sliding Mode Control Using Model Predictive Control and Disturbance Compensation with Application to Actuators

AU - Haus, Benedikt

AU - Mercorelli, Paolo

AU - Aschemann, Harald

N1 - Publisher Copyright: © 2019 by the authors.

PY - 2019/5/25

Y1 - 2019/5/25

N2 - 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.

AB - 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.

KW - sliding mode control

KW - model predictive control

KW - adaptive control

KW - disturbance estimation

KW - actuators

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85069883761&partnerID=8YFLogxK

U2 - 10.3390/info10050182

DO - 10.3390/info10050182

M3 - Journal articles

VL - 10

JO - Information

JF - Information

SN - 2078-2489

IS - 5

M1 - 182

ER -

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Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

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