Efficient Trajectory Planning and Tracking Control for Underactuated Crane

Abstract

The crane is a typical underactuated plant, which makes the trajectory planning and control to be challenging. To solve this problem, parameterized reduced-dimension trajectory planning and tracking control are carried out. The plant is reduced in dimension by using the differential flatness (DF) method, wherein the state and control variables are represented directly through the flat output (FO). Combined with the pseudospectral method (PSM) wherein multiple constraints are taken into account, the FO is parameterized by using the polynomial functions, and the trajectory planning in the FO space is transformed into a parameter planning problem. By doing so, it can reduce the degree of freedoms to be optimized. For the high-order terms and various disturbances in the FO, the extended state observer is used for estimation and compensation. Both numerical simulation and hardware experiments are performed to demonstrate the feasibility and efficiency of the proposed method.

DOI: 10.61416/ceai.v25i2.8307