scholarly journals The Stable Trajectory Tracking Control of a Skid-Steered Mobile Platform with Dynamic Uncertainties

10.5772/61241 ◽  
2015 ◽  
Vol 12 (9) ◽  
pp. 122 ◽  
Author(s):  
Seungwoo Jeon ◽  
Wootae Jeong
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Mobile Platform ◽  
Trajectory Tracking Control ◽  
Stable Trajectory ◽  
Dynamic Uncertainties

A novel recursive formulation for dynamic modeling and trajectory tracking control of multi-rigid-link robotic manipulators mounted on a mobile platform

2020 ◽  
pp. 095965182097390
Author(s):  
AM Shafei ◽  
H Mirzaeinejad
Keyword(s):  
Dynamic Modeling ◽  
Predictive Control ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Robotic System ◽  
Mobile Platform ◽  
Reference Trajectory ◽  
Trajectory Tracking Control ◽  
Recursive Formulation ◽  
Mobile Base

This article establishes an innovative and general approach for the dynamic modeling and trajectory tracking control of a serial robotic manipulator with n-rigid links connected by revolute joints and mounted on an autonomous wheeled mobile platform. To this end, first the Gibbs–Appell formulation is applied to derive the motion equations of the mentioned robotic system in closed form. In fact, by using this dynamic method, one can eliminate the disadvantage of dealing with the Lagrange Multipliers that arise from nonholonomic system constraints. Then, based on a predictive control approach, a general recursive formulation is used to analytically obtain the kinematic control laws. This multivariable kinematic controller determines the desired values of linear and angular velocities for the mobile base and manipulator arms by minimizing a point-wise quadratic cost function for the predicted tracking errors between the current position and the reference trajectory of the system. Again, by relying on predictive control, the dynamic model of the system in state space form and the desired velocities obtained from the kinematic controller are exploited to find proper input control torques for the robotic mechanism in the presence of model uncertainties. Finally, a computer simulation is performed to demonstrate that the proposed algorithm can dynamically model and simultaneously control the trajectories of the mobile base and the end-effector of such a complicated and high-degree-of-freedom robotic system.

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