A direct approach to adaptive controller design and its application to inverted pendulum tracking

Author(s):  
S.C. Ge ◽  
C.C. Hang ◽  
T. Zhang
2013 ◽  
Vol 385-386 ◽  
pp. 977-980
Author(s):  
Bao Bin Liu

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.


Measurement ◽  
2021 ◽  
Vol 174 ◽  
pp. 109071
Author(s):  
S. Morteza Ghamari ◽  
Hasan Mollaee ◽  
Fatemeh Khavari

2014 ◽  
Vol 71 (1) ◽  
Author(s):  
Hazem I. Ali

In this paper the design of robust stabilizing state feedback controller for inverted pendulum system is presented. The Ant Colony Optimization (ACO) method is used to tune the state feedback gains subject to different proposed cost functions comprise of H-infinity constraints and time domain specifications. The steady state and dynamic characteristics of the proposed controller are investigated by simulations and experiments. The results show the effectiveness of the proposed controller which offers a satisfactory robustness and a desirable time response specifications. Finally, the robustness of the controller is tested in the presence of system uncertainties and disturbance.


2013 ◽  
Vol 341-342 ◽  
pp. 945-948 ◽  
Author(s):  
Wei Zhou ◽  
Bao Bin Liu

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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