Stable Robust Adaptive Control of Induction Motors with Unknown Parameters

2010 ◽  
Vol 6 (2) ◽  
pp. 145-149
Author(s):  
Ibrahim Fahad Jasim
Author(s):  
JIANPING CAI ◽  
LUJUAN SHEN ◽  
FUZHEN WU

We consider a class of uncertain non-linear systems preceded by unknown backlash-like hysteresis, which is modelled by a differential equation. We propose a new state feedback robust adaptive control scheme using a backstepping technique and properties of the differential equation. In this control scheme, we construct a new continuous function to design an estimator to estimate the unknown constant parameters and the unknown bound of a ‘disturbance-like’ term. The transient performance of the output tracking error can be guaranteed by the introduction of pre-estimates of the unknown parameters in our controller together with update laws. We do not require bounds on the ‘disturbance-like’ term or unknown system parameters in this scheme. The global stability of the closed-loop system can be proved.


2002 ◽  
Vol 35 (1) ◽  
pp. 67-72
Author(s):  
Haruo Suemitsu ◽  
Takami Matsuo ◽  
Wataru Matsuzaki ◽  
Kazushi Nakano

2016 ◽  
Vol 13 (03) ◽  
pp. 1650010 ◽  
Author(s):  
Zhengcai Cao ◽  
Longjie Yin ◽  
Yili Fu ◽  
Jian S. Dai

A significant amount of work has been reported in the area of vision-based stabilization of wheeled robots during the last decade. However, almost all the contributions have not considered the actuator dynamics in the controller design. Considering the unknown parameters of the robot kinematics and dynamics incorporating the actuator dynamics, this paper presents a vision-based robust adaptive controller for the stabilization of a wheeled humanoid robot by using the adaptive backstepping approach. For the controller design, the idea of backstepping is used and the adaptive control technique is applied to treat all parametric uncertainties. Moreover, to attenuate the effect of the external disturbances on control performance, smooth robust compensators are employed. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, simulation results are given to verify the effectiveness of the proposed controller.


2010 ◽  
Vol 6 (2) ◽  
pp. 145-149
Author(s):  
Ibrahim Jasim

This paper presents a new strategy for controlling induction motors with unknown parameters. Using a simple linearized model of induction motors, we design robust adaptive controllers and unknown parameters update laws. The control design and parameters estimators are proved to have global stable performance against sudden load variations. All closed loop signals are guaranteed to be bounded. Simulations are performed to show the efficacy of the suggested scheme


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