Abstract-- A non-linear predictive controller is presented. It judiciously combines predictive controllers with a local model network utilizing a neural-network-like gating system. It avoids the time consuming quadratic optimization calculation, which is normally necessary in non-linear predictive control. A controller simulation on a Continuous Stirred Tank Reactor (CSTR) case study was shown to be satisfactory both in terms of set point tracking and regulation performance over the entire operating range. Moreover, the inherent integration action in the local predictive controller provides zero static offsets. Key words- model predictive control, local model network, local controller network, non-linearity, neural network. ________________...
Learning-based controllers, and especially learning-based model predictive controllers, have been us...
The contribution is aimed at predictive control of nonlinear processes with the help of artificial n...
Abstract: – This paper presents a solution to computation of predictive control using non-linear au...
A non-linear predictive controller is presented. It judiciously combines predictive controllers with...
Model Predictive Control (MPC) refers to a class of algorithms that compute a sequence of manipulate...
In this paper, a neural network model-based predictive control has been developed to solve problems ...
Model predictive control (MPC) is an advanced technique for process control. It is based on iterativ...
Design and implementation are studied for a neural network-based predictive controller meant to gove...
© 2017 IEEE. This paper presents a comparative study of two widely accepted model predictive control...
This paper presents a new approach for non-linear predictive control based on the local model ideas....
In this work the optimization of the local model network structure and predictive control that utili...
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from ...
In this paper stability of one-step ahead predictive controllers based on non-linear models is estab...
This paper presents a nonlinear model‐based controller based on the ideas of parametric predictive c...
An adaptive control algorithm with a neural network model, previously proposed in the literature for...
Learning-based controllers, and especially learning-based model predictive controllers, have been us...
The contribution is aimed at predictive control of nonlinear processes with the help of artificial n...
Abstract: – This paper presents a solution to computation of predictive control using non-linear au...
A non-linear predictive controller is presented. It judiciously combines predictive controllers with...
Model Predictive Control (MPC) refers to a class of algorithms that compute a sequence of manipulate...
In this paper, a neural network model-based predictive control has been developed to solve problems ...
Model predictive control (MPC) is an advanced technique for process control. It is based on iterativ...
Design and implementation are studied for a neural network-based predictive controller meant to gove...
© 2017 IEEE. This paper presents a comparative study of two widely accepted model predictive control...
This paper presents a new approach for non-linear predictive control based on the local model ideas....
In this work the optimization of the local model network structure and predictive control that utili...
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from ...
In this paper stability of one-step ahead predictive controllers based on non-linear models is estab...
This paper presents a nonlinear model‐based controller based on the ideas of parametric predictive c...
An adaptive control algorithm with a neural network model, previously proposed in the literature for...
Learning-based controllers, and especially learning-based model predictive controllers, have been us...
The contribution is aimed at predictive control of nonlinear processes with the help of artificial n...
Abstract: – This paper presents a solution to computation of predictive control using non-linear au...