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» Nonlinear predictive control based on neural multi-models
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ICRA
2005
IEEE
144views Robotics» more  ICRA 2005»
15 years 3 months ago
Hill-Based Model as a Myoprocessor for a Neural Controlled Powered Exoskeleton Arm - Parameters Optimization
— The exoskeleton robot, serving as an assistive device worn by the human (orthotic), functions as a humanamplifier. Setting the human machine interface (HMI) at the neuro-muscu...
Ettore Cavallaro, Jacob Rosen, Joel C. Perry, Step...
BC
2000
95views more  BC 2000»
14 years 9 months ago
Cerebellar learning of accurate predictive control for fast-reaching movements
Long conduction delays in the nervous system prevent the accurate control of movements by feedback control alone. We present a new, biologically plausible cerebellar model to study...
Jacob Spoelstra, Nicolas Schweighofer, Michael A. ...
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
15 years 4 months ago
Nonlinear dynamics modelling for controller evolution
The problem of how to acquire a model of a physical robot, which is fit for evolution of controllers that can subsequently be used to control that robot, is considered in the con...
Julian Togelius, Renzo De Nardi, Hugo Gravato Marq...
NECO
2002
78views more  NECO 2002»
14 years 9 months ago
Local Overfitting Control via Leverages
We present a novel approach to dealing with overfitting in black-box models. It is based on the leverages of the samples, i.e. on the influence that each observation has on the pa...
Gaétan Monari, Gérard Dreyfus
AEI
1999
110views more  AEI 1999»
14 years 9 months ago
Self-tuning fuzzy controller design using genetic optimisation and neural network modelling
This article describes a new adaptive fuzzy logic control scheme. The proposed scheme is based on the structure of the self-tuning regulator and employs neural network and genetic...
Duc Truong Pham, Dervis Karaboga