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Decentralized wireless networked model predictive control design for large and complex systems
(2020-10-07)
Decentralized Networked Model Predictive Control system (DNMPC) is a decentralized control system that involves the exchange of information between subsystems across a mutual communication network. Decentralized structures ...
Sensitivity analysis by neural networks applied to power systems transient stability
(Elsevier B.V., 2007-05-01)
This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by ...
RBF circuits based on folded cascode differential pairs
(2008-12-01)
We propose new circuits for the implementation of Radial Basis Functions such as Gaussian and Gaussian-like functions. These RBFs are obtained by the subtraction of two differential pair output currents in a folded cascode ...
RBF circuits based on folded cascode differential pairs
(2008-12-01)
We propose new circuits for the implementation of Radial Basis Functions such as Gaussian and Gaussian-like functions. These RBFs are obtained by the subtraction of two differential pair output currents in a folded cascode ...
Networked control systems: Research challenges and advances for application
(2018-01-01)
The research topic of networked control systems has been the focus over the last 15 years for the academic and industrial sectors. Networked control systems (NCSs) are distributed control systems in which the sensors, ...
Projeto E análise de uma rede neural para resolver problemas de programação dinâmica
(2001-01-01)
Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. Neural networks with ...
Projeto E análise de uma rede neural para resolver problemas de programação dinâmica
(2001-01-01)
Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. Neural networks with ...