Analysis of a dual-arm mobile robot dynamics and balance compensation

2011 ◽  
Vol 41 (3/4) ◽  
pp. 246 ◽  
Author(s):  
Ting Yu Zhang ◽  
Jian Jin ◽  
Guo Xian Zhang
Keyword(s):  
Author(s):  
Michel Lopez-Franco ◽  
Alma Y. Alanis ◽  
Nancy Arana-Daniel ◽  
Carlos Lopez-Franco

In this chapter, a Recurrent Higher Order Neural Network (RHONN) is used to identify the plant model of discrete time nonlinear systems, under the assumption that all the state is available for measurement. Then the Extended Kalman Filter (EKF) is used to train the RHONN. The applicability of this scheme is illustrated by identification for an electrically driven nonholonomic mobile robot. Traditionally, modeling of mobile robots only considers its kinematics. It has been well known that the actuator dynamics is an important part of the design of the complete robot dynamics. However, most of the reported results in literature do not consider all parametric uncertainties for mobile robots at the actuator level. This is due to the modeling problem becoming extremely difficult as the complexity of the system dynamics increases, and the mobile robot model includes the uncertainties of the actuator dynamics as well as the uncertainties of the robot kinematics and dynamics.


Robotica ◽  
2014 ◽  
Vol 34 (2) ◽  
pp. 449-467 ◽  
Author(s):  
Zhengcai Cao ◽  
Longjie Yin ◽  
Yili Fu ◽  
Jian S Dai

SUMMARYThis paper investigates the vision-based pose stabilization of an electrically driven nonholonomic mobile robot with parametric uncertainties in robot kinematics, robot dynamics, and actuator dynamics. A robust adaptive visual stabilizing controller is proposed with the utilization of adaptive control, backstepping, and dynamic surface control techniques. For the controller design, the idea of backstepping is used and the adaptive control approach is adopted to deal with all uncertainties. We also apply the dynamic surface control method to avoid the repeated differentiations of virtual controllers existing in the backstepping design procedure such that the control development is easier to be implemented. Moreover, to attenuate the effect of disturbances on control performance, smooth robust compensators are exploited. It is proved that all signals in the closed-loop system can be guaranteed to be uniformly ultimately bounded. Finally, simulation results are presented to illustrate the performance of the proposed controller.


2009 ◽  
Vol 419-420 ◽  
pp. 829-832
Author(s):  
Dong Yue Qu ◽  
Yong Zhan

This paper discusses the structure of wheel mobile robot, dynamics model and control model are developed. The method is tested by computer simulation, which is used to control the wheel mobile robot to follow straightaway and circle path, and numerical results show good result.


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