Critical Review and Progress of Adaptive Controller Design for Robot Arms

2016 ◽  
pp. 3-12
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Critical Review ◽  
Controller Design ◽  
Adaptive Controller ◽  
Robot Arms

Adaptive Control of Pulse Width Modulation Voltage-Source Rectifier with Disturbance Signals

2013 ◽  
Vol 385-386 ◽  
pp. 977-980
Author(s):  
Bao Bin Liu
Keyword(s):  
Pulse Width ◽  
Pulse Width Modulation ◽  
Controller Design ◽  
Adaptive Controller ◽  
Voltage Source ◽  
Robust Controller ◽  
Reference Velocity ◽  
Velocity Tracking ◽  
Modulation Voltage ◽  
Robust Controller Design

A nonlinear adaptive controller is proposed for the design of pulse width modulation voltage-source rectifier with disturbance signals of harmonics to achieve reference velocity tracking. The procedure of the robust controller design is developed via improved backstepping method. With the proposed controller, PWM voltage-source rectifiers can guarantee accuracy of output voltage tracking. Global asymptotic stability of the closed-loop system has been proved. The simulation results demonstrate effectiveness of the presented method.

Robust self-tuning regressive adaptive controller design for a DC–DC BUCK converter

Measurement ◽  
2021 ◽  
Vol 174 ◽  
pp. 109071
Author(s):  
S. Morteza Ghamari ◽  
Hasan Mollaee ◽  
Fatemeh Khavari
Keyword(s):  
Controller Design ◽  
Adaptive Controller ◽  
Buck Converter ◽  
Self Tuning

Backstepping Based Adaptive Control of Magnetic Levitation System

2013 ◽  
Vol 341-342 ◽  
pp. 945-948 ◽  
Author(s):  
Wei Zhou ◽  
Bao Bin Liu
Keyword(s):  
Parameter Uncertainty ◽  
Closed Loop ◽  
Controller Design ◽  
Magnetic Levitation ◽  
Adaptive Controller ◽  
Closed Loop System ◽  
Actual System ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
Control Accuracy

In view of parameter uncertainty in the magnetic levitation system, the adaptive controller design problem is investigated for the system. Nonlinear adaptive controller based on backstepping is proposed for the design of the actual system with parameter uncertainty. The controller can estimate the uncertainty parameter online so as to improve control accuracy. Theoretical analysis shows that the closed-loop system is stable regardless of parameter uncertainty. Simulation results demonstrate the effectiveness of the presented method.

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