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Maneuvering control of planar snake robot: An adaptive robust approach with artificial time delay
Author(s) -
Mukherjee Joyjit,
Roy Spandan,
Kar Indra Narayan,
Mukherjee Sudipto
Publication year - 2021
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5430
Subject(s) - control theory (sociology) , adaptive control , lyapunov function , controller (irrigation) , computer science , robust control , bounded function , tracking error , control system , engineering , artificial intelligence , control (management) , mathematics , nonlinear system , physics , mathematical analysis , quantum mechanics , agronomy , biology , electrical engineering
This article proposes an adaptive‐robust maneuvering control framework for a planar snake robot under the influence of parameter uncertainties. The entire control objective of maneuvering control can be viewed as the simultaneous establishments of two goals: one to maintain a time‐varying body shape of the snake robot for consistent motion (called the outer layer) and the other dealing with the velocity and head‐angle tracking of the same (called the inner layer). Unknown variations in the ground friction coefficients have been considered to be the primary source of time‐varying uncertainties which affects the control performance in both the layers. Accordingly, an artificial time delay‐based adaptive‐robust control (ARC) framework, dual adaptive‐robust time‐delayed control (ARTDC), is proposed. The term dual signifies simultaneous application of ARTDC for the outer as well as the inner layer. ARTDC comprises of two segments: an artificial time delay‐based time‐delayed estimation (TDE) part and an ARC part. While TDE approximates the completely unknown friction forces, the ARC tackles the approximation error arising from the TDE. More importantly, compared with the existing ARC methodologies, the proposed ARTDC neither presumes the overall uncertainty to be upper bounded by a constant nor requires any prior knowledge of the bound of uncertainty to implement the controller. A Lyapunov function‐based method has been adopted for analyzing the stability of the closed‐loop system. Simulation studies affirm the improved performance of the ARTDC in contrast to the classical artificial delay‐based methodology.