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JDCTA
2010
155views more  JDCTA 2010»
13 years 3 months ago
Multi-factor predication of diesel engine by using artificial neural networks
The paper presents an algorithm which combining a neural network observer, it give more flexible and accurate control on the engine operation. In recent year, several researchers ...
Wenyong Xiao
ESANN
2000
13 years 9 months ago
A comparative design of a MIMO neural adaptive rate damping for a nonlinear helicopter model
Using a nonlinear 15-state helicopter model in 6 DOF, two di erent neural control systems, both acting as rate damping, have been designed and compared. They are both based on the ...
Piero A. Gili, Manuela Battipede
AUTOMATICA
2004
104views more  AUTOMATICA 2004»
13 years 8 months ago
Input-to-state stability of networked control systems
A new class of Lyapunov uniformly globally asymptotically stable (UGAS) protocols in networked control systems (NCS) is considered. It is shown that if the controller is designed ...
Dragan Nesic, Andrew R. Teel
AUTOMATICA
2006
90views more  AUTOMATICA 2006»
13 years 8 months ago
An ISS-modular approach for adaptive neural control of pure-feedback systems
Controlling non-affine non-linear systems is a challenging problem in control theory. In this paper, we consider adaptive neural control of a completely non-affine pure-feedback s...
Cong Wang, David J. Hill, S. S. Ge, Guanrong Chen
IJCSA
2007
213views more  IJCSA 2007»
13 years 8 months ago
Adaptive Depth Control for Autonomous Underwater Vehicles Based on Feedforward Neural Networks
This paper studies the design and application of the neural network based adaptive control scheme for autonomous underwater vehicle's (AUV's) depth control system that i...
Yang Shi, Weiqi Qian, Weisheng Yan, Jun Li