Add to ORKGAbstract:-This paper presents a new neuro-predictive tuning procedure for PID controllers. The tuning method is based on the optimization of an objective function subject to constraints over a finite prediction horizon in time, making use of a neural process model. The performance of this new self tuning method implemented as a tuner is substantiated by experiments on a level-flow pilot plant and by comparison with a conventional controller
This paper describes the application of artificial neural networks for automatic tuning of PID contr...
It is critical that modern control theory techniques be integrated into assignments which involve th...
Purpose - To develop a new predictive control scheme based on neural networks for linear and non-lin...
Many controller tuners are based on linear models of both the controller and process. Desired perfor...
A scheme of automatically tuning the existing industrial PID controllers using neural networks is pr...
A neural network enhanced proportional, integral and derivative (PID) controller is presented that c...
In this paper, a neural network model-based predictive control has been developed to solve problems ...
This work presents a novel predictive model-based proportional integral derivative (PID) tuning and ...
This work presents a novel predictive model-based proportional integral derivative (PID) tuning and ...
PID is a prevalent tool of automatic control in both industry and home environment, and PID paramete...
Modern automation systems largely rely on closed loop control, wherein a controller interacts with a...
In this paper, a scheme for the automatic tuning of PID controllers on-line, with the assistance of ...
A recent servey (1) has reported that the majority of industrial loops are controlled by PID-type co...
A new method with a two-layer hierarchy is presented based on a neural proportional-integral-derivat...
PID controllers are widely used in industrial applications. Because the plant can be time variant, ...
This paper describes the application of artificial neural networks for automatic tuning of PID contr...
It is critical that modern control theory techniques be integrated into assignments which involve th...
Purpose - To develop a new predictive control scheme based on neural networks for linear and non-lin...
Many controller tuners are based on linear models of both the controller and process. Desired perfor...
A scheme of automatically tuning the existing industrial PID controllers using neural networks is pr...
A neural network enhanced proportional, integral and derivative (PID) controller is presented that c...
In this paper, a neural network model-based predictive control has been developed to solve problems ...
This work presents a novel predictive model-based proportional integral derivative (PID) tuning and ...
This work presents a novel predictive model-based proportional integral derivative (PID) tuning and ...
PID is a prevalent tool of automatic control in both industry and home environment, and PID paramete...
Modern automation systems largely rely on closed loop control, wherein a controller interacts with a...
In this paper, a scheme for the automatic tuning of PID controllers on-line, with the assistance of ...
A recent servey (1) has reported that the majority of industrial loops are controlled by PID-type co...
A new method with a two-layer hierarchy is presented based on a neural proportional-integral-derivat...
PID controllers are widely used in industrial applications. Because the plant can be time variant, ...
This paper describes the application of artificial neural networks for automatic tuning of PID contr...
It is critical that modern control theory techniques be integrated into assignments which involve th...
Purpose - To develop a new predictive control scheme based on neural networks for linear and non-lin...