The paper is focused on an implementation of a multivariable predictive controller with a colouring filter C in a disturbance model. The filter is often essential for practical applications of predictive control based on input-output models. It is commonly considered as a design parameter because it has direct effects on closed loop performance. In this paper a computation of predictions for the case with the colouring filter is introduced. The computation is based on a particular model of the controlled system in the form of matrix fraction which is commonly used for description of a range of multivariable processes. Performance of closed loop system with and without the colouring filter in the disturbance model was compared.Ministry of Ed...
The benefits of applying the range of technologies generally known as Model Predictive Control (MPC)...
The state space and input/output formulations of model predictive control are compared and preferenc...
A predictive control algorithm uses a model of the controlled system to predict the system behavior ...
The paper is focused on an implementation of a multivariable predictive controller with a colouring ...
The paper is focused on an implementation of a predictive controller with a colouring filter C in a ...
Model Based Predictive Control (MBPC) or only Predictive Control is one of the control methods which...
This paper reports a theoretical extension of Multivariable Predictive Control (MPC). The robustness...
This paper proposes to study the potential of use a three-tank system in laboratory scale to teach h...
In technical practice often occur multivariable processes with time delay. Time-delays are mainly ca...
ne of the fundamental difficulties en-countered throughout process con-trol is the presence of time ...
The purpose of this Master Thesis concerns further development of ABB´s multivariable prediction c...
In this paper a Multivariable Predictive Controller has been proposed in a stochastic framework for ...
Models are used in control systems for more than thirty years ago. Among them, Model Predictive Cont...
In this work a new method for designing predictive controllers for linear MIMO systems is presented....
This project thesis provides a brief overview of Model Predictive Control (MPC).A brief history of i...
The benefits of applying the range of technologies generally known as Model Predictive Control (MPC)...
The state space and input/output formulations of model predictive control are compared and preferenc...
A predictive control algorithm uses a model of the controlled system to predict the system behavior ...
The paper is focused on an implementation of a multivariable predictive controller with a colouring ...
The paper is focused on an implementation of a predictive controller with a colouring filter C in a ...
Model Based Predictive Control (MBPC) or only Predictive Control is one of the control methods which...
This paper reports a theoretical extension of Multivariable Predictive Control (MPC). The robustness...
This paper proposes to study the potential of use a three-tank system in laboratory scale to teach h...
In technical practice often occur multivariable processes with time delay. Time-delays are mainly ca...
ne of the fundamental difficulties en-countered throughout process con-trol is the presence of time ...
The purpose of this Master Thesis concerns further development of ABB´s multivariable prediction c...
In this paper a Multivariable Predictive Controller has been proposed in a stochastic framework for ...
Models are used in control systems for more than thirty years ago. Among them, Model Predictive Cont...
In this work a new method for designing predictive controllers for linear MIMO systems is presented....
This project thesis provides a brief overview of Model Predictive Control (MPC).A brief history of i...
The benefits of applying the range of technologies generally known as Model Predictive Control (MPC)...
The state space and input/output formulations of model predictive control are compared and preferenc...
A predictive control algorithm uses a model of the controlled system to predict the system behavior ...