Adaptive neural network compensating control for coordinated motion of space-based robot system with uncertain parameters and external disturbances - Details

author：

Chen, Zhiyong (Chen, Zhiyong.) ^[1] | Chen, Li (Chen, Li.) ^[2] (Scholars：陈力)

Indexed by：

EI Scopus

Abstract：

The　control　problem　of　space-based　robot　system　with　uncertain　parameters　and　external　disturbances　is　considered.　With　Lagrangian　formulation　and　augmentation　approach,　the　dynamic　equations　of　space-based　robot　system　in　workspace　are　derived.　Based　on　the　results,　an　adaptive　neural　network　compensating　control　scheme　for　coordinated　motion　between　the　base＇s　attitude　and　end-effector　of　space-based　robot　system　is　developed.　It　is　based　on　the　inertia-related　method,　and　incorporates　a　neural　network　controller　to　compensate　the　uncertainties.　The　closed-loop　system　stability　with　the　neural　network　adapted　on-line　is　discussed　in　detail　through　the　Lyapunov　stability　approach.　Comparing　with　many　adaptive　and　robust　control　schemes,　the　controller　proposed　does　not　require　one　to　determine　the　regression　matrix　for　space　robot　system　and　then　avoids　tedious　computations.　Numerical　simulations　are　provided　to　show　the　effectiveness　of　the　approach.　Copyright　©　2009　by　ASME.

Keyword：

Adaptive control systems Closed loop systems Controllers Design End effectors Neural networks Robust control System stability Uncertainty analysis

Community：

[ 1 ] [Chen, Zhiyong]College of Mechanical Engineering, Fuzhou University Fuzhou, Fujian, China
[ 2 ] [Chen, Li]College of Mechanical Engineering, Fuzhou University Fuzhou, Fujian, China

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Email：

chenzhiyong0203@foxmail.com

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