Robust Adaptive Control for Vision-Based Stabilization of a Wheeled Humanoid Robot

2016 ◽  
Vol 13 (03) ◽  
pp. 1650010 ◽  
Author(s):  
Zhengcai Cao ◽  
Longjie Yin ◽  
Yili Fu ◽  
Jian S. Dai
Keyword(s):  
Adaptive Control ◽  
Humanoid Robot ◽  
Controller Design ◽  
Robust Adaptive Control ◽  
Lyapunov Theory ◽  
Control Technique ◽  
Robot Kinematics ◽  
Unknown Parameters ◽  
Actuator Dynamics ◽  
Robust Adaptive

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.

scholarly journals Robust Adaptive Control of MIMO Pure-Feedback Nonlinear Systems via Improved Dynamic Surface Control Technique

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 96672-96685 ◽  
Author(s):  
Yang Zhou ◽  
Wenhan Dong ◽  
Shuangyu Dong ◽  
Yong Chen ◽  
Renwei Zuo ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Dynamic Surface Control ◽  
Robust Adaptive Control ◽  
Control Technique ◽  
Dynamic Surface ◽  
Surface Control ◽  
Robust Adaptive

Adaptive control of a class of non-linear systems preceded by backlash-like hysteresis

2014 ◽  
Vol 24 (5) ◽  
Author(s):  
JIANPING CAI ◽  
LUJUAN SHEN ◽  
FUZHEN WU
Keyword(s):  
Differential Equation ◽  
Adaptive Control ◽  
Linear Systems ◽  
Tracking Error ◽  
Robust Adaptive Control ◽  
Unknown Parameters ◽  
Control Scheme ◽  
Non Linear ◽  
Non Linear Systems ◽  
Robust Adaptive

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.

scholarly journals Robust Fractional Adaptive Control Based on the Strictly Positive Realness Condition

2009 ◽  
Vol 19 (1) ◽  
pp. 69-76 ◽  
Author(s):  
Samir Ladaci ◽  
Abdelfatah Charef ◽  
Jean Loiseau
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Robust Adaptive Control ◽  
Adaptive Controllers ◽  
Actuator Dynamics ◽  
Control Scheme ◽  
Positive Realness ◽  
Robust Adaptive ◽  
Model Reference Adaptive ◽  
Strictly Positive Realness

Robust Fractional Adaptive Control Based on the Strictly Positive Realness ConditionThis paper presents a new approach to robust adaptive control, using fractional order systems as parallel feedforward in the adaptation loop. The problem is that adaptive control systems may diverge when confronted with finite sensor and actuator dynamics, or with parasitic disturbances. One of the classical robust adaptive control solutions to these problems makes use of parallel feedforward and simplified adaptive controllers based on the concept of positive realness. The proposed control scheme is based on the Almost Strictly Positive Realness (ASPR) property of the plant. We show that this condition implies also robust stability in the case of fractional order controllers. An application to Model Reference Adaptive Control (MRAC) with a fractional order adaptation rule is provided with an implementable algorithm. A simulation example of a SISO robust adaptive control system illustrates the advantages of the proposed method in the presence of disturbances and noise.

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