Results 231 to 240 of about 158,186 (268)

Neural Adaptive Ignition Control

SAE Technical Paper Series, 1998
<div class="htmlview paragraph">To be able to meet the demands of low emissions and low fuel consumption of modern combustion engines, new ways have to be found to control the engine efficiently. We measure the pressure in the combustion chamber and analyze this signal with a neural network in order to receive the point of 50% conversion of ...
Rainer Müller, Hans-Hubert Hemberger
openaire   +1 more source

Neural networks adaptive control

[1992] Proceedings of the IEEE International Symposium on Industrial Electronics, 2003
Neural networks have the function of self-learning and are adaptive. Control systems using neural networks provide improved performances than those using conventional methods. Based on the analysis and study of backpropagation neural networks, the authors propose a new method of adaptive control-neural networks adaptive control, and give some ...
null Jianyuan Hu, null Xinhan Huang, null Jinjiang Chen   +2 more
openaire   +1 more source

Learning and adaptive neural controller

[Proceedings] 1991 IEEE International Joint Conference on Neural Networks, 1991
A neural learning and adaptive scheme, called inverse-dynamics adaptive control (IDAC) is presented. The IDAC scheme provides a learn-while-functioning capability. The error signal, defined as a difference between the desired and the actual outputs, modifies the controller weights until the controller structure becomes an approximate inverse-dynamics ...
M.M. Gupta, D.H. Rao, H.C. Wood
openaire   +1 more source

Adaptive robust neural controller for robots

Robotics and Autonomous Systems, 2004
Abstract This paper presents an investigation on the trajectory control of a robot using a new type of recurrent neural network. A three-layered recurrent neural network is employed to estimate the forward dynamics model of the robot. Standard backpropagation (BP) algorithm is used as a learning algorithm for this network to minimise the difference ...
openaire   +2 more sources

Combining adaptive and neural control

IFAC Proceedings Volumes, 1991
Abstract Even though developments in the computer industry have moved towards highly integrated parallel processing, the control industry generally only makes use of the computer as a digital numerical manipulation tool for controlling the plant with a monitoring ability for failure detections.
M. Roele, K. Warwick
openaire   +1 more source

Neural Networks and Adaptive Control

1993
This chapter provides an overview of some adaptive control methods and how artificial neural networks are being used as components of adaptive control systems. It suggests, however, that the adaptive control methods developed by control engineers can be misleading guides to thinking about control in biological systems.
Andrew G. Barto, Vijaykumar Gullapalli
openaire   +1 more source

Adaptive Hopfield neural controller

ISIE '97 Proceeding of the IEEE International Symposium on Industrial Electronics, 2002
In this paper, the characteristics of a new neural network controller, composed of two Hopfield neurons, and experimental results obtained from the real time control of a DC motor are described. The model and implementation details of the neuron are shown and the adaptive Hopfield neural controller and its training are described.
S.Y. Cavalcanti Catunda, J.H. Feitosa Cavalcanti   +1 more
openaire   +1 more source

Neural network controller characteristics with regard to adaptive control

IEEE Transactions on Systems, Man, and Cybernetics, 1992
The authors attempt to clarify neural network (NN) controller characteristics by comparison with the adaptive control theory. The authors clarify the classification of the NN controller architecture and the dynamic NN structure. Comparison between the NN controller and the adaptive controller clarifies that the framework of a linear two-layer NN-type ...
Tetsuro Yabuta, Takayuki Yamada
openaire   +1 more source

Genetic Representation of Adaptive Neural Controllers

2011
The manual design of adaptive controllers for robotic systems that face unpredictable environmental changes is often challenging. There is thus a growing interest in the development of automatic design tools to assist control engineers. One of the most common approaches in this domain is the evolutionary synthesis of Artificial Neural Networks (ANNs ...
openaire   +1 more source

Modified adaptive discrete control system containing neural estimator and neural controller

Artificial Intelligence in Engineering, 2000
Abstract In this paper a modified discrete adaptive control system with neural estimator and neural controller is presented. The structure of the adaptive controller is based on the model presented by Etxebarria (Etxebarria V. Adaptive control of discrete systems using neural networks. IEE Proc. Control Theory Application, Vol. 141, No. 4, July, 1995)
Sohrab Khanmohammadi, Iraj Hassanzadeh, Mohammad Bagher Bannae Sharifian   +2 more
openaire   +1 more source