Abstract
Adaptive fuzzy sliding-mode control design for omnidirectional mobile robots with prescribed performance is presented in this work. First, an error transformation which transforms the constrained variable into an unconstrained one is carried out. Next, a fuzzy logic system (FLS) for approximating the unknown dynamics is constructed. Based on such a model, a nominal adaptive linearizing controller incorporating a serial-parallel model (SPM)-based composite algorithm, which improves the tracking performance of the overall closed-loop system, is synthesized. To solve the so-called “loss of controllability” problem, a smooth-switching algorithm is embedded which hands over the control authority to an auxiliary sliding-mode controller until the danger is safely bypassed. The proposed design ensures the semi-globally uniformly ultimately bounded stability of the closed-loop signals. Simulation works demonstrating the validity of the proposed design are presented in the final.
Highlights
Omnidirectional mobile robots (OMR) are platforms that are able to move in any direction without reorientation
The cases with an unknown control gain function and unknown nonlinearity arising from unmodeled dynamics, exogenous disturbances such as low-velocity friction [29], etc., are considered together at once; The fuzzy logic controllers (FLCs) is invoked to approximate the lumped unknown nonlinearity, which renders the adaptive control easy to formulate; The prescribed performance control (PPC) technique is incorporated to ensure the fulfillment of a prescribed performance requirement imposed on the configuration variables; The composite update algorithm is incorporated to improve the tracking performance further
W defines a region without a sharp boundary of the value det[YaT θa ], within which the sliding-mode control is in charge due to the approach of singularity
Summary
Omnidirectional mobile robots (OMR) are platforms that are able to move in any direction without reorientation. To render the adaptive control applicable, an FLS is invoked to approximate the unknown dynamics Based on such a model, a nominal adaptive linearizing controller incorporating an SPM-based composite algorithm, which exhibits better tracking performance than the conventional. The cases with an unknown control gain function and unknown nonlinearity arising from unmodeled dynamics, exogenous disturbances such as low-velocity friction [29], etc., are considered together at once; The FLC is invoked to approximate the lumped unknown nonlinearity, which renders the adaptive control easy to formulate; The PPC technique is incorporated to ensure the fulfillment of a prescribed performance requirement imposed on the configuration variables; The composite update algorithm is incorporated to improve the tracking performance further.
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