The paper is devoted to a new adaptive variable-structure system (VSS) control algorithm and its applications in underwater robotics. The proposed approach is based on the usage of sliding mode parameter (SMP) in order to have adaptation in VSS. It is demonstrated that the extreme values of SMPs are directly associated with high efficiency of transient processes in VSS. The essence of the presented adaptation algorithm consists on the adjustment of switching surface parameters such that the SMPs move from the assigned desirable value to the extreme values, with the overall effect to accelerate transients. The effectiveness of the derived approach is proven by applying it for controlling a real remotely operated vehicle. Copyright © 2015 John Wiley & Sons, Ltd.

An adaptive VSS control for remotely operated vehicles / Dyda, Alexander A; Oskin, Dmitry A.; Longhi, Sauro; Monteriu', Andrea. - In: INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING. - ISSN 0890-6327. - ELETTRONICO. - 31:4(2017), pp. 1099-1115. [10.1002/acs.2565]

An adaptive VSS control for remotely operated vehicles

LONGHI, SAURO
;
MONTERIU', Andrea
2017-01-01

Abstract

The paper is devoted to a new adaptive variable-structure system (VSS) control algorithm and its applications in underwater robotics. The proposed approach is based on the usage of sliding mode parameter (SMP) in order to have adaptation in VSS. It is demonstrated that the extreme values of SMPs are directly associated with high efficiency of transient processes in VSS. The essence of the presented adaptation algorithm consists on the adjustment of switching surface parameters such that the SMPs move from the assigned desirable value to the extreme values, with the overall effect to accelerate transients. The effectiveness of the derived approach is proven by applying it for controlling a real remotely operated vehicle. Copyright © 2015 John Wiley & Sons, Ltd.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/229820
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