Sliding Mode Control with Observer for PMSM Based on Stribeck Friction Model

2014 ◽  
Author(s):  
Dong Chen ◽  
Fenxi Yao ◽  
Senchun Chai
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Friction Model ◽  
Mode Control

Backstepping sliding mode control of large telescope based on friction model

2017 ◽  
Vol 25 (10) ◽  
pp. 2620-2626
Author(s):  
郭鹏飞 GUO Peng-fei ◽  
邓永停 DENG Yong-ting ◽  
王 帅 WANG Shuai
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Friction Model ◽  
Large Telescope ◽  
Mode Control ◽  
Backstepping Sliding Mode Control

LuGre Friction Model Estimation of a Precision Table and Sliding Mode Control Design

2009 ◽  
Vol 147-149 ◽  
pp. 264-271
Author(s):  
Shiuh Jer Huang ◽  
Chun Ming Chiu ◽  
M.C. Huang
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Control Design ◽  
Friction Model ◽  
System Stability ◽  
Adaptive Sliding Mode Control ◽  
Model Based ◽  
Mode Control ◽  
Lugre Friction Model ◽  
Lugre Friction

Piezoelectric friction actuating mechanism is chosen to construct long traveling range sub-micro X-Y positioning table. LuGre friction model is employed to simulate the friction dynamics of this positioning mechanism. The optimization scheme of Matlab toolbox is adopted to search the optimal friction model parameters. However, this piezoelectric actuating system has obvious nonlinear and time-varying dead-zone offset control voltage due to the static friction and preload. The estimated LuGre dynamic model is still not accurate enough for model-based precision control design. Hence, the adaptive sliding mode control (SMC) with robust behavior is employed to design the nonlinear controller for this piezoelectric friction actuating mechanism. The Laypunov-like design strategy is adopted to achieve the system stability criterion. The dynamic experimental results of the proposed nonlinear controllers are compared with that of a model-based PID controller, too.

scholarly journals Theoretical Analysis of Friction Compensation Using Sliding Mode Control

2012 ◽  
Vol 229-231 ◽  
pp. 2385-2388 ◽  
Author(s):  
N.A. Rafan ◽  
Z. Jamaludin ◽  
T. Tjahjowidodo ◽  
L.S. Chey ◽  
T.H. Chiew
Keyword(s):  
Sliding Mode Control ◽  
Machine Tools ◽  
Pid Controller ◽  
Sliding Mode ◽  
Friction Model ◽  
Control Technique ◽  
Friction Compensation ◽  
Nonlinear Phenomenon ◽  
Tracking Accuracy ◽  
Mode Control

Friction is an undesired nonlinear phenomenon that reduces position and tracking accuracy in machine tools application. This paper focuses on development of control technique to compensate friction force at motion reversal of a drive system that generates quadrant glitch phenomenon thus improving tracking accuracy. Sliding Mode Control (SMC) is designed to compensate friction. The Generalized Maxwell-Slip (GMS) friction model is applied for numerical analysis. The performance of the controller is analysed based on the reduction in the quadrant glitches magnitude. The performance of the SMC controller is compared with the classical PID controller. Results show that SMC controller yields the smallest quadrant glitch magnitudes.

Azimuth Axis Servo System Integrated Control Based on Sliding-Mode Control

2011 ◽  
Vol 219-220 ◽  
pp. 556-559
Author(s):  
Shu Fang Wang ◽  
Jian Cheng Zhang ◽  
Hong Hong Guo
Keyword(s):  
Sliding Mode Control ◽  
Control Strategy ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Integrated Control ◽  
Servo System ◽  
Friction Model ◽  
Mode Control ◽  
Real Model ◽  
Simulation And Experiment

On the basis of LuGer friction model, an integrated sliding-mode control strategy is proposed to deal with servo system nonlinear and uncertain factors effectively. The control strategy includes two parts. One is nominal model without considering disturb and uncertain, the other is real model including disturb and uncertain. To one part, choose reasonable sliding surface and design controller law. To another part, PTSC algorithm and NNC algorithm combines together to optimize RBF neural network in order to acquire upper bound of uncertain. Simulation and experiment results show that proposed control strategy better servo system performance.

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