Flatness-Based Feedforward Control of a Stacker Crane with Online Trajectory Generation

Abstract

Flatness-based feedforward control is an approach for combining fast motion with low oscillations for nonlinear or flexible drive systems. Its desired trajectories must be continuously differentiable to the degree of the system order. Designing such trajectories, that also reach the dynamic system limits, poses a challenge. Common solutions, like Gevrey functions, usually require lengthy offline calculations. To achieve a quicker and simpler industrial-suited solution, this paper presents a new online trajectory generation scheme. The algorithm utilizes higher order s-curve trajectories created by a cyclic filtering process using moving average filters. An experimental validation proves the capability as well as industrial applicability of the presented approach for flexible structures like stacker cranes.