Force and motion trajectory tracking control of flexible-joint robots

2000 ◽  
Vol 35 (3) ◽  
pp. 363-378 ◽  
Author(s):  
S.Kemal Ider
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Motion Trajectory ◽  
Trajectory Tracking Control ◽  
Flexible Joint ◽  
Flexible Joint Robots ◽  
Force And Motion

scholarly journals Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots

2021 ◽  
Author(s):  
Jorge Montoya‐Cháirez ◽  
Javier Moreno‐Valenzuela ◽  
Víctor Santibáñez ◽  
Ricardo Carelli ◽  
Fracisco G. Rossomando ◽  
...  
Keyword(s):  
Neural Network ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Adaptive Neural Network ◽  
Trajectory Tracking Control ◽  
Flexible Joint ◽  
Flexible Joint Robots

Dynamic analysis and tracking trajectory control of a crane

2016 ◽  
Vol 231 (5) ◽  
pp. 1045-1052 ◽  
Author(s):  
Huang Kang ◽  
Sun Shunqiang ◽  
Zhen Shengchao ◽  
Ge Xinfang ◽  
Zhu Yongqi
Keyword(s):  
Dynamic Model ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Trajectory Control ◽  
Motion Trajectory ◽  
Matlab Simulation ◽  
Trajectory Tracking Control ◽  
System Trajectory ◽  
Simulation Results ◽  
Tracking Trajectory

This paper introduces a method to solve the crane motion trajectory control problem. A dynamic model is proposed based on the Udwadia–Kalaba equation, which can be solved without extra parameters, such as the Lagrange multiplier. The motion trajectory of a crane is used as a constraint (referred to as trajectory tracking constraint). To satisfy the system trajectory, a method to calculate the driving conditions on the basis of the above conditions is proposed. A 2D plane dynamic model of a crane is established. Five stages of crane movement are obtained. Simulation is performed with Matlab. Simulation results simulation show that the Udwadia–Kalaba equation can be well applied to trajectory tracking control of cranes.

Sign in / Sign up

Export Citation Format

Share Document