Inverse kinematic optimization and MPC on a four-link hydraulic manipulator

Sammanfattning

Operating individual joints on a hydraulic manipulator can be tedious and unproductivewith limited experience. Therefore, this thesis presents a method to easeoperator strain and lessen experience requirements by enabling cartesian controlof the robot tool. This is achieved with differential closed-loop inverse kinematicsand linear model predictive motion control. References are generated with apseudo-inverse Jacobian algorithm formulated as a quadratic program with a secondarynull-space objective to exploit redundant joints. A sensitivity analysis of anon-linear hydraulic model resulted in a linear first-order model which was used todesign an MPC that tracks the references. Results from a simulated robot showrobust tracking performance even when the robot is exposed to noise and unmodeleddisturbances. The designed null-space objective manages to control null-spacemotion and the CLIK is shown to reject unmodeled disturbances.