4.7 Article

Adaptive Nonlinear Crane Control With Load Hoisting/Lowering and Unknown Parameters: Design and Experiments

Journal

IEEE-ASME TRANSACTIONS ON MECHATRONICS
Volume 20, Issue 5, Pages 2107-2119

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMECH.2014.2364308

Keywords

Hoisting/lowering; Lyapunov methods; nonlinear control; underactuated mechatronic systems

Funding

  1. National Natural Science Foundation of China [11372144]
  2. National Science and Technology Pillar Program of China [2013BAF07B03]
  3. National Science Fund for Distinguished Young Scholars of China [61325017]

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For practical underactuated cranes, vertical load motion is always involved, which, owing to the internal nonlinear coupling, may trigger larger amplitude load oscillations, making the control problem muchmore cumbersome and challenging than the constant-rope-length case. Moreover, cranes always suffer from unknown or uncertain plant parameters such as load mass and friction parameters besides the underactuated nature, which makes accurate gravity compensation in the case of load vertical hoisting/lowering impossible and induces vertical positioning errors. To address these problems, a new adaptive coupling control approach is presented for underactuated cranes with load hoisting/lowering subject to unknown plant parameters, which achieves fast precise trolley positioning and load hoisting/lowering as well as rapid load swing elimination. We construct a new adaptive mechanism to deal with the system uncertainties, which can accurately identify the unknown load weight. As far as we know, the presented strategy yields the first closed-loop control solution, with guaranteed theoretical analysis, to successfully address the crane antiswing and positioning problem in the presence of load hoisting/lowering and uncertain parameters, with simultaneous load weight identification as an additional benefit. The performance of the designed control system is theoretically ensured by Lyapunov-like analysis and (extended) Barbalat's lemmas. Experimental and simulation results suggest the effectiveness and superior performance of the proposed method for crane control by comparing it with existing methods.

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