@inproceedings{discovery10199524,
       publisher = {Robot Intelligence Technology and Applications (RiTA) Association},
            note = {This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.},
       booktitle = {the 12th International Conference on Robot Intelligence Technology and Applications (RiTA 2024)},
           month = {December},
         address = {Ulsan, South Korea},
            year = {2024},
           title = {Prescribed Vibration Control for Long Slender Remote Systems in Nuclear Decommissioning},
        keywords = {Nuclear decommissioning, flexible manipulator, control barrier function, vibration suppression, disturbance rejection},
        abstract = {. In nuclear decommissioning and other hazardous environments, long slender remote manipulators are crucial for performing tasks
where human intervention is not possible. However, their inherent flexibility poses critical challenges such as deformation and vibration, which
can degrade control precision and induce risks in rapid operations. To
address such issues, this paper presents a new vibration suppression control strategy for a specialised type of flexible manipulators. A two-link
model, featuring a fixed, flexible first link and a rigid second link, is
considered to capture the core effects of one typical kind of long-reach
remote systems, which consist of a relatively rigid manipulator supported
by a long slender structure. The system dynamics are modelled using the
assumed mode method, and a prescribed vibration control (PVC) framework is developed, integrating two prescribed vibration control barrier
functions (PV-CBFs) and a finite-time disturbance observer to manage
unmodelled uncertainties and external disturbances. This framework ensures predefined vibration performance and accurate end-point positioning by formulating a quadratic programming (QP) problem that adjusts
a baseline tracking controller. The proposed method is validated through
rigorous theoretical analysis and simulation tests, demonstrating better
tracking performance compared to traditional methods.},
             url = {https://2024.icrita.org/},
          author = {Wang, Xinming and Yan, Yunda and Zhang, Kaiqiang and Liu, Cunjia}
}