scholarly journals Application of a New Model Reference Adaptive Control Based on PID Control in CNC Machine Tools

Machines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 274
Author(s):  
Hongdong Gai ◽  
Xuewei Li ◽  
Fangrui Jiao ◽  
Xiang Cheng ◽  
Xianhai Yang ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Pid Control ◽  
Control Method ◽  
Model Reference Adaptive Control ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Model Reference ◽  
Loop Control ◽  
Model Reference Adaptive ◽  
Following Error

To improve the control performance of the CNC machine tool feed servo system with nonlinear disturbances, a model reference adaptive control (MRAC) based on PID control is proposed. The method is based on the traditional three-loop control, the output signal of the speed loop controller is used as the input signal of the model reference adaptive controller, and the adaptive law is derived on the basis of Lyapunov stability theory. To verify the effectiveness, this paper analyzed the method through simulation and experiment. Results showed that the following error caused by nonlinear friction was significantly reduced when the speed was reversed, and the influence of noise and mechanical resonance was effectively suppressed. The proposed control method in this paper improves the motion-control accuracy and anti-interference ability of the control system.

Model Reference Adaptive Control Based on KP Model for Magnetically Controlled Shape Memory Alloy Actuators

2017 ◽  
Vol 15 (1_suppl) ◽  
pp. 31-37 ◽  
Author(s):  
Miaolei Zhou ◽  
Yannan Zhang ◽  
Kun Ji ◽  
Dong Zhu
Keyword(s):  
Adaptive Control ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Control Method ◽  
Model Reference Adaptive Control ◽  
Positioning Accuracy ◽  
Model Reference ◽  
Hysteresis Nonlinearity ◽  
Adopted Model ◽  
Model Reference Adaptive

Introduction Magnetically controlled shape memory alloy (MSMA) actuators take advantages of their large deformation and high controllability. However, the intricate hysteresis nonlinearity often results in low positioning accuracy and slow actuator response. Methods In this paper, a modified Krasnosel'skii-Pokrovskii model was adopted to describe the complicated hysteresis phenomenon in the MSMA actuators. Adaptive recursive algorithm was employed to identify the density parameters of the adopted model. Subsequently, to further eliminate the hysteresis nonlinearity and improve the positioning accuracy, the model reference adaptive control method was proposed to optimize the model and inverse model compensation. Results The simulation experiments show that the model reference adaptive control adopted in the paper significantly improves the control precision of the actuators, with a maximum tracking error of 0.0072 mm. Conclusions The results prove that the model reference adaptive control method is efficient to eliminate hysteresis nonlinearity and achieves a higher positioning accuracy of the MSMA actuators.

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