Title :
Model predictive trajectory planning with fallback-strategy for an active Heave Compensation system
Author :
Richter, Maximilian ; Arnold, Eckhard ; Schneider, Klaus ; Eberharter, Johannes K. ; Sawodny, Oliver
Author_Institution :
Inst. for Syst. Dynamics, Univ. of Stuttgart, Stuttgart, Germany
Abstract :
Active Heave Compensation (AHC) systems need an active control of the heaving winch in order to decouple the offshore crane´s lift operation from the vertical motion of the vessel. Two-degree-of-freedom control (2DOF) can give good tracking control performance for such applications. However, every 2DOF control system requires a reference trajectory which has to fulfill requirements regarding continuity and differentiability. In case of AHC applications, the drive system of the winch is usually limited by velocity and acceleration constraints. Thus, the trajectory planning needs to take these constraints into account. Furthermore, the trajectory needs to be generated in real-time which narrows down the number of possible algorithms. In this work, a real-time model predictive trajectory planner is presented. By means of predictions of the vertical position and velocity of the crane tip, an optimal control problem is formulated and solved online for every time step. Furthermore, state constraints are taken into account. For the case when no optimal control solution can be found within the available time, a repetitive polynomial-based trajectory planner is used as fallback-strategy. The proposed approach is validated with simulations as well as experiments on the Liebherr AHC test bench.
Keywords :
cranes; lifting; motion control; optimal control; polynomials; predictive control; real-time systems; trajectory control; 2DOF; AHC systems; Liebherr AHC test bench; active control; active heave compensation system; differentiability; fallback-strategy; lift operation; offshore crane; optimal control; real-time model predictive trajectory planner; repetitive polynomial; two-degree-of-freedom control; vertical motion; vessel; Acceleration; Optimal control; Planning; Prediction algorithms; Predictive models; Trajectory; Winches; Mechatronics; Optimal control; Predictive control for linear systems;
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
Print_ISBN :
978-1-4799-3272-6
DOI :
10.1109/ACC.2014.6859017