Motion control of three-link brachiation robot by using final-state control with error learning

This paper demonstrates that motion control of a three-link brachiation robot can be performed via final-state control for a linear parameter-varying system with error learning. Since the root joint of the brachiation robot has no drive unit, the control problem is treated as that for an open-chain manipulator possessing nondriven joints in circumstances with gravity. Also, the brachiation robot possesses a nonlinear property in its wide motion area from an initial state to a final desired state. We treat the brachiation robot as a discrete-time linear parameter-varying system by using an extended linearization method and Euler´s method. In the experiments, the second and third joints of the brachiation robot are directly driven by AC servo motors installed in each joint. The free vibration of the brachiation robot is coincident with that of the simulation and gives suggestions of the final time to reach a desired state that has to be specified for final-state control. By simulations and experiments, it is demonstrated that the feedforward input obtained by the final-state control method can bring the three-link brachiation robot from an initial state to a desired state in a specific time. Its robustness under a variation of the link mass is also verified