Reference State Trajectory Generation for Output Tracking with Constraints using Search Trees
Jonathan Eden, Ying Tan, Darwin Lau, Denny Oetomo
2018 ANNUAL AMERICAN CONTROL CONFERENCE (ACC) | IEEE | Published : 2018
This paper generates a reference state trajectory from a given reference output trajectory for redundant nonlinear affine dynamic systems subject to input, state and output constraints. Extending upon the expansive search tree (EST) methodology, a new probabilistic sampling method is proposed to address time dependence and output mappings. It is shown that the methodology is able to find a feasible solution given constraints, if such a solution exists. The use of the proposed methodology is illustrated by considering the end effector tracking of a multi-link cable-driven parallel robot.
Awarded by Research Grants Council
The work was supported by the grants from the Early Career Scheme sponsored by the the Research Grants Council (Reference No. 24200516).