On the basis of the equivalent dynamic linearization model (EDLM), we propose a kind of model predictive control (MPC) for single input and single output (SISO) linear systems. Practically, when MPC is designed for the situation of model mismatch, the actual system performance may beyond our expectation. This paper is concerned with the system performance analysis of the proposed method and explains how it works. Most importantly, fewer works are able to analyze the system transient characteristics and steady-state characteristics more clearly than this work, when the system model is offline built inaccurately or the model parameters are online estimated imprecisely. In this paper, we formulate the system characteristics through analyzing t...
The effectiveness of model predictive control (MPC) in dealing with input and state constraints duri...
Model Predictive Controller (MPC) technology has been researched and developed to meet varied demand...
The ill-conditioned model is a common problem in model predictive control. The model ill-conditioned...
On the basis of the equivalent dynamic linearization model (EDLM), we propose a kind of model predic...
Based on equivalent-dynamic-linearization model (EDLM), we propose a kind of model predictive contro...
Model Predictive Control (MPC) can be used for nonlinear systems if they are working around an opera...
The closed loop control performance of MMCs can be significantly improved by using Model Predictive ...
In model predictive control (MPC) of processes, the model fidelity plays an important role. The perf...
Model predictive control (MPC) strategies can efficiently deal with constraints on system states, in...
In this paper, a new model predictive controller (MPC), which is robust for a class of model uncerta...
AbstractModel Predictive Control (MPC) schemes are now widely used in process industries for the con...
AbstractExisting model-plant mismatch detection and isolation methods mainly employ correlation anal...
Model predictive control (MPC) algorithms brought increase of the control system performance in many...
In model predictive control of processes. the process model plays an important role. The performance...
This paper describes a new method for the design of model predictive control (MPC) using non-minimal...
The effectiveness of model predictive control (MPC) in dealing with input and state constraints duri...
Model Predictive Controller (MPC) technology has been researched and developed to meet varied demand...
The ill-conditioned model is a common problem in model predictive control. The model ill-conditioned...
On the basis of the equivalent dynamic linearization model (EDLM), we propose a kind of model predic...
Based on equivalent-dynamic-linearization model (EDLM), we propose a kind of model predictive contro...
Model Predictive Control (MPC) can be used for nonlinear systems if they are working around an opera...
The closed loop control performance of MMCs can be significantly improved by using Model Predictive ...
In model predictive control (MPC) of processes, the model fidelity plays an important role. The perf...
Model predictive control (MPC) strategies can efficiently deal with constraints on system states, in...
In this paper, a new model predictive controller (MPC), which is robust for a class of model uncerta...
AbstractModel Predictive Control (MPC) schemes are now widely used in process industries for the con...
AbstractExisting model-plant mismatch detection and isolation methods mainly employ correlation anal...
Model predictive control (MPC) algorithms brought increase of the control system performance in many...
In model predictive control of processes. the process model plays an important role. The performance...
This paper describes a new method for the design of model predictive control (MPC) using non-minimal...
The effectiveness of model predictive control (MPC) in dealing with input and state constraints duri...
Model Predictive Controller (MPC) technology has been researched and developed to meet varied demand...
The ill-conditioned model is a common problem in model predictive control. The model ill-conditioned...