Model Based Predictive Control (MBPC) or only Predictive Control is one of the control methods which have developed considerably over a few past years. It is mostly based on discrete models of controlled systems. Model of a controlled system is used for computation of predictions of the systems output on the basis of past inputs, outputs and states and designed sequence of future control increments. This paper is focused in comparison of various approaches to computation of multi - step ahead predictions using a multivariable input - output model. Computational aspects of derivation of predictions can be limitting especially in adaptive predictive control
A predictive control algorithm uses a model of the controlled system to predict the system behavior ...
The purpose of this Master Thesis concerns further development of ABB´s multivariable prediction c...
Several new computational algorithms are presented to compute the deadbeat predictive control law th...
Model Based Predictive Control (MBPC or simply MPC) is a control methodology that uses the process m...
Model Predictive Control (MPC) is an application of control that is highly popular due to its sensib...
Based on previous results on linear predictors and Kalman filter, this paper will formulate multi-st...
Predictive control relies on predictions of the future behaviour of the system to be controlled. The...
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....
The control of multi-input multi-output (MIMO) systems is a common problem in practical control scen...
The benefits of applying the range of technologies generally known as Model Predictive Control (MPC)...
Model predictive control (MPC) has been used successfully in industry. The basic characteristic of t...
The paper is focused on an implementation of a multivariable predictive controller with a colouring ...
This paper proposes to study the potential of use a three-tank system in laboratory scale to teach h...
Abstract—The interest in applying model-based predictive control (MBPC) for power-electronic convert...
A predictive control algorithm uses a model of the controlled system to predict the system behavior ...
The purpose of this Master Thesis concerns further development of ABB´s multivariable prediction c...
Several new computational algorithms are presented to compute the deadbeat predictive control law th...
Model Based Predictive Control (MBPC or simply MPC) is a control methodology that uses the process m...
Model Predictive Control (MPC) is an application of control that is highly popular due to its sensib...
Based on previous results on linear predictors and Kalman filter, this paper will formulate multi-st...
Predictive control relies on predictions of the future behaviour of the system to be controlled. The...
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....
The control of multi-input multi-output (MIMO) systems is a common problem in practical control scen...
The benefits of applying the range of technologies generally known as Model Predictive Control (MPC)...
Model predictive control (MPC) has been used successfully in industry. The basic characteristic of t...
The paper is focused on an implementation of a multivariable predictive controller with a colouring ...
This paper proposes to study the potential of use a three-tank system in laboratory scale to teach h...
Abstract—The interest in applying model-based predictive control (MBPC) for power-electronic convert...
A predictive control algorithm uses a model of the controlled system to predict the system behavior ...
The purpose of this Master Thesis concerns further development of ABB´s multivariable prediction c...
Several new computational algorithms are presented to compute the deadbeat predictive control law th...