Adaptive mobile robots formation control using neural networks
Control Conference（2013）
摘要
In this paper we present the tracking problem of controlling a particular formation among mobile robots, using feedback linearization techniques. Reference tracking will be made using look ahead control. Look ahead control will be obtained by feedback linearization. To cancel the modeling errors or/and external perturbations, the closed loop will incorporate an adaptive element performed by a one neural network. The adaptive controller, implemented through a hidden layer feed-forward neural network, has its weights realtime updated to cope with external perturbations as well as modeling errors. The control procedures required for tracking control, are inspired in the Lyapunov stability theory.
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关键词
lyapunov methods,adaptive control,closed loop systems,feedback,feedforward neural nets,mobile robots,neurocontrollers,stability,tracking,lyapunov stability theory,adaptive controller,adaptive element,adaptive mobile robots formation control,closed loop,external perturbations,feedback linearization techniques,hidden layer feed-forward neural network,look ahead control,modeling errors,neural networks,reference tracking,tracking control,adaptive systems,mathematical model
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