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Discrete-time adaptive backstepping nonlinear control via high-order neural networks
(2007)
This paper deals with adaptive tracking for discrete-time multiple-input-multiple-output (MIMO) nonlinear systems in presence of bounded disturbances. In this paper, a high-order neural network (HONN) structure is used to ...
Discrete-time adaptive backstepping nonlinear control via high-order neural networks
(2007)
This paper deals with adaptive tracking for discrete-time multiple-input-multiple-output (MIMO) nonlinear systems in presence of bounded disturbances. In this paper, a high-order neural network (HONN) structure is used to ...
Discrete-time neural control for electrically driven nonholonomic mobile robots
(2012)
An inverse optimal neural controller for discrete-time unknown nonlinear systems, in the presence of external disturbances and parameter uncertainties, is presented. It is based on a discrete-time recurrent high-order ...
Discrete-time neural control for electrically driven nonholonomic mobile robots
(2012)
An inverse optimal neural controller for discrete-time unknown nonlinear systems, in the presence of external disturbances and parameter uncertainties, is presented. It is based on a discrete-time recurrent high-order ...
Real-time discrete backstepping neural control for induction motors
(2011)
This brief focuses on real-time implementation, as applied to a three-phase induction motor, of results already published in 2007. The proposed controller is based on a high-order neural network, trained online using Kalman ...
Discrete-time adaptive backstepping nonlinear control via high-order neural networks
(2012)
A new bandstop filter is presented providing a two-state discrete wide tuning range from 20 to 30GHz with the same high rejection level of 36dB. In the design, metal-insulator-metal capacitors are placed on one end of the ...
Real-time torque control using discrete-time recurrent high-order neural networks
(2013)
This paper presents a discrete-time direct current (DC) motor torque tracking controller, based on a recurrent high-order neural network to identify the plant model. In order to train the neural identifier, the extended ...
Real-time torque control using discrete-time recurrent high-order neural networks
(2013)
This paper presents a discrete-time direct current (DC) motor torque tracking controller, based on a recurrent high-order neural network to identify the plant model. In order to train the neural identifier, the extended ...
Decentralized neural identifier and control for nonlinear systems based on extended Kalman filter
(2012)
A time-varying learning algorithm for recurrent high order neural network in order to identify and control nonlinear systems which integrates the use of a statistical framework is proposed. The learning algorithm is based ...