An Iterative Tuning Method for Feedforward Control of Parallel Manipulators Considering Nonlinear Dynamics

Abstract Feedforward control is one of the most effective control techniques to increase the robot’s tracking accuracy. However, most of the dynamic models used in the feedforward controllers are linearly simplified such that the nonlinear and time-varying characteristics of dynamics in the workspace are ignored. In this paper, an iterative tuning method for feedforward control of parallel manipulators by taking nonlinear dynamics into account is proposed. Based on the robot rigid-body dynamic model, a feedforward controller considering the dynamic nonlinearity is presented. An iterative tuning method is given to iteratively update the feedforward controller by minimizing the root mean square (RMS) of the joint errors at each cycle. The effectiveness and extrapolation capability of the proposed method are validated through the experiments on a 2-DOF parallel manipulator. This research proposes an iterative tuning method for feedforward control of parallel manipulators considering nonlinear dynamics, which has better extrapolation capability in the whole workspace of manipulators.