Add to ORKGThe contribution is aimed at predictive control of nonlinear processes with the help of artificial neural networks as the predictor. Since this methodology is relatively wide, paper only concentrates on the prediction via artificial neural networks. Special attention is paid to the usage of offline-learnt predictor based on multilayer feed forward neural network. The proposed method is tested in simulations on a nonlinear system
This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to pre...
Since the last three decades predictive control has shown to be successful in control industry, but ...
Abstract: – This paper presents a solution to computation of predictive control using non-linear au...
Design and implementation are studied for a neural network-based predictive controller meant to gove...
Purpose - To develop a new predictive control scheme based on neural networks for linear and non-lin...
This paper discusses neural multi-models based on Multi Layer Perceptron (MLP) networks and a comput...
Model Predictive Control (MPC) refers to a class of algorithms that compute a sequence of manipulate...
Model predictive control (MPC) is a popular and an advance control technique for linear system with ...
A neural network based predictive controller design algorithm is introduced for nonlinear control sy...
The behavior of a multivariable predictive control scheme based on neural networks applied to a mode...
This paper presents new results on a neural network approach to nonlinear model predictive control. ...
This paper proposes a neural network approach to nonlinear model predictive control (NMPC). The NMPC...
A neural network predictive control scheme is compared with a first principle model predictive contr...
Many processes in the chemical industry have modest nonlinearities; i.e., linear dynamics play a dom...
This paper presents stabilizing Model Predictive Controllers (MPC) in which prediction models are in...
This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to pre...
Since the last three decades predictive control has shown to be successful in control industry, but ...
Abstract: – This paper presents a solution to computation of predictive control using non-linear au...
Design and implementation are studied for a neural network-based predictive controller meant to gove...
Purpose - To develop a new predictive control scheme based on neural networks for linear and non-lin...
This paper discusses neural multi-models based on Multi Layer Perceptron (MLP) networks and a comput...
Model Predictive Control (MPC) refers to a class of algorithms that compute a sequence of manipulate...
Model predictive control (MPC) is a popular and an advance control technique for linear system with ...
A neural network based predictive controller design algorithm is introduced for nonlinear control sy...
The behavior of a multivariable predictive control scheme based on neural networks applied to a mode...
This paper presents new results on a neural network approach to nonlinear model predictive control. ...
This paper proposes a neural network approach to nonlinear model predictive control (NMPC). The NMPC...
A neural network predictive control scheme is compared with a first principle model predictive contr...
Many processes in the chemical industry have modest nonlinearities; i.e., linear dynamics play a dom...
This paper presents stabilizing Model Predictive Controllers (MPC) in which prediction models are in...
This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to pre...
Since the last three decades predictive control has shown to be successful in control industry, but ...
Abstract: – This paper presents a solution to computation of predictive control using non-linear au...