Add to ORKGThe used of model in Model Predictive Controller (MPC) is significant as poor model can lead to degradation of the product outputs and even potential in harming the equipment used as well as the whole plant production. The study of model-plant mismatch (MPM) detection is crucial to avoid the tedious process of whole model reidentification thus remodeling is focused only to the affected submodel
We propose an improved offset-free model predictive control (MPC) framework, which learns and utiliz...
On the basis of the equivalent dynamic linearization model (EDLM), we propose a kind of model predic...
This article proposes a data driven technique for quantifying the performance of state estimators in...
The performance of MPC highly depends on the accuracy of the model of the plant used in the design ...
For Model Predictive Controlled (MPC) plants, the quality of the plant model determines the quality ...
AbstractProcess model is the kernel element of Model Predictive Control (MPC) system. It is always d...
In model predictive control of processes. the process model plays an important role. The performance...
AbstractExisting model-plant mismatch detection and isolation methods mainly employ correlation anal...
The number of MPC installations in industry is growing as a reaction to demands of increased efficie...
Um dos desafios que ainda precisa ser superado com o objetivo de melhorar o desempenho do controle p...
In closed-loop control systems, the model accuracy exerts large influences on the controllability, s...
Model predictive control (MPC) strategies have become the standard for advanced control application...
In model predictive control (MPC) of processes, the model fidelity plays an important role. The perf...
A model-predictive controller (MPC) uses the process model to predict future outputs of the system....
Plant model is one of the important aspects in the design and implementation of Model Predictive Con...
We propose an improved offset-free model predictive control (MPC) framework, which learns and utiliz...
On the basis of the equivalent dynamic linearization model (EDLM), we propose a kind of model predic...
This article proposes a data driven technique for quantifying the performance of state estimators in...
The performance of MPC highly depends on the accuracy of the model of the plant used in the design ...
For Model Predictive Controlled (MPC) plants, the quality of the plant model determines the quality ...
AbstractProcess model is the kernel element of Model Predictive Control (MPC) system. It is always d...
In model predictive control of processes. the process model plays an important role. The performance...
AbstractExisting model-plant mismatch detection and isolation methods mainly employ correlation anal...
The number of MPC installations in industry is growing as a reaction to demands of increased efficie...
Um dos desafios que ainda precisa ser superado com o objetivo de melhorar o desempenho do controle p...
In closed-loop control systems, the model accuracy exerts large influences on the controllability, s...
Model predictive control (MPC) strategies have become the standard for advanced control application...
In model predictive control (MPC) of processes, the model fidelity plays an important role. The perf...
A model-predictive controller (MPC) uses the process model to predict future outputs of the system....
Plant model is one of the important aspects in the design and implementation of Model Predictive Con...
We propose an improved offset-free model predictive control (MPC) framework, which learns and utiliz...
On the basis of the equivalent dynamic linearization model (EDLM), we propose a kind of model predic...
This article proposes a data driven technique for quantifying the performance of state estimators in...