Abstract
This paper presents a novel adaptive iterative learning control (AILC) scheme to improve the tracking performance of the manipulator for spraying hull to achieve high-quality spraying effectively. First, a novel way of modifying the reference trajectory is proposed to deal with arbitrary initial states and iteration-varying reference trajectory when the manipulator reciprocates spraying. The modified way comprises constructing an error variable containing an initial correction term and determining the shortest limited time of completely tracking the desired trajectory by optimization principle. Based on this, an AILC scheme uses adaptive and backstep** techniques to handle the system’s uncertain physical parameters and external disturbance. Theoretically, this control scheme can guarantee the tip-position of the spraying manipulator to perfectly track the desired reference trajectory within an appropriate, limited time under arbitrary initial states and iteration-varying reference trajectory. Simulations and experiments verify the proposed method’s effectiveness and advantage by comparison with other control algorithms.
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This work was supported by the National Natural Science Foundation of China (No.61973265).
Ting Zhang received her Ph.D. degree in control science and engineering from Yanshan University, Qinhuangdao, China, in 2023. Her research interests include repetitive control (RC), iterative learning control (ILC), trajectory tracking control, autonomous farming vehicle control, and spraying manipulator control.
**aohong Jiao received her Ph.D. degree in mechanical engineering from Sophia University, Tokyo, Japan, in 2004. She is a Professor with the School of Electrical Engineering, Yanshan University, Qinhuangdao, China. Her research interests include robust control of nonlinear systems and applications to hybrid distributed generation systems and automotive powertrains.
Zhong Wang received his Ph.D. degree in control engineering from Yanshan University, Qinhuangdao, China, in 2020. He is a lecturer with the School of Vehicle and Energy, Yanshan University, Qinhuangdao, China. His research interests include intelligent control of construction machinery, such as manipulator control.
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Zhang, T., Jiao, X. & Wang, Z. Adaptive Iterative Learning Trajectory Tracking Control for Spraying Manipulator With Arbitrary Initial States and Iteration-varying Reference Trajectory. Int. J. Control Autom. Syst. 22, 1958–1970 (2024). https://doi.org/10.1007/s12555-023-9030-9
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DOI: https://doi.org/10.1007/s12555-023-9030-9