Based on equivalent-dynamic-linearization model (EDLM), we propose a kind of model predictive control (MPC) for single-input and single-output (SISO) nonlinear or linear systems. After compensating the EDLM with disturbance for multiple-input and multiple-output nonlinear or linear systems, the MPC compensated with disturbance is proposed to address the disturbance rejection problem. The system performance analysis results are much clear compared with the system stability analyses on MPC in current works. And this may help the engineers understand how to design, analyze and apply the controller in practical
Model Predictive control (MPC) is shown to be particularly effective for the self-tuning control of ...
Model predictive control (MPC) strategies can efficiently deal with constraints on system states, in...
This paper presents a multimodel approach to control nonlinear systems. The system of the inverted p...
On the basis of the equivalent dynamic linearization model (EDLM), we propose a kind of model predic...
In the past decades, model predictive control (MPC) has been widely used as an efficient tool in are...
This research effort addresses the important issue of developing an adaptive strategy for Model Pred...
The control of multi-input multi-output (MIMO) systems is a common problem in practical control scen...
This article provides an overview of model predictive control (MPC) frameworks for dynamic operation...
This paper presents a novel approach to linearize the input-output (IO) response of nonlinear mechan...
Model predictive control (MPC) refers to a family control method which applies to discrete and conti...
This project thesis provides a brief overview of Model Predictive Control (MPC).A brief history of i...
Abstract--This article concerns non-linear control of single-input-single-output processes with inpu...
In this paper, a new model predictive controller (MPC), which is robust for a class of model uncerta...
In this paper, a novel hierarchical multirate control scheme for nonlinear discrete-time systems is ...
2012-08-27Model predictive control (MPC) is a widely used advanced process control technique in the ...
Model Predictive control (MPC) is shown to be particularly effective for the self-tuning control of ...
Model predictive control (MPC) strategies can efficiently deal with constraints on system states, in...
This paper presents a multimodel approach to control nonlinear systems. The system of the inverted p...
On the basis of the equivalent dynamic linearization model (EDLM), we propose a kind of model predic...
In the past decades, model predictive control (MPC) has been widely used as an efficient tool in are...
This research effort addresses the important issue of developing an adaptive strategy for Model Pred...
The control of multi-input multi-output (MIMO) systems is a common problem in practical control scen...
This article provides an overview of model predictive control (MPC) frameworks for dynamic operation...
This paper presents a novel approach to linearize the input-output (IO) response of nonlinear mechan...
Model predictive control (MPC) refers to a family control method which applies to discrete and conti...
This project thesis provides a brief overview of Model Predictive Control (MPC).A brief history of i...
Abstract--This article concerns non-linear control of single-input-single-output processes with inpu...
In this paper, a new model predictive controller (MPC), which is robust for a class of model uncerta...
In this paper, a novel hierarchical multirate control scheme for nonlinear discrete-time systems is ...
2012-08-27Model predictive control (MPC) is a widely used advanced process control technique in the ...
Model Predictive control (MPC) is shown to be particularly effective for the self-tuning control of ...
Model predictive control (MPC) strategies can efficiently deal with constraints on system states, in...
This paper presents a multimodel approach to control nonlinear systems. The system of the inverted p...