This paper proposed a double-layer model predictive control (DLMPC) strategy integrated with zone control. In the steady-state target calculation (SSTC) layer, the controlled output variables are pretreated based on the analysis of process principle and production data. Subsequently, the optimal input–output targets and corresponding zone parameters are obtained by solving the steady-state optimization problem and transmitted to the dynamic control layer for tracking. Meanwhile, the weighted and priority soft constraints relaxation methods are discussed when the SSTC problem is infeasible. Compared with conventional DLMPC and zone model predictive control (ZMPC), the proposed algorithm can not only achieve smooth control, but also hav...
This paper considers a two-phase model predictive control (MPC) which utilize a parsimonious paramet...
This paper concern the development of a stable model predictive controller (MPC) to be integrated wi...
This paper considers a two-phase model predictive control (MPC) which utilize a parsimonious paramet...
In order to solve the problem of the high sensitivity of conventional double-layer model predictive ...
Model predictive control (MPC) is usually implemented as a control strategy where the system outputs...
Several MPC applications implement a control strategy in which some of the system outputs are contro...
Model predictive control (MPC) is usually implemented as a control strategy where the system outputs...
In this work, we propose a framework for economic model predictive control (EMPC) with zone tracking...
Several MPC applications implement a control strategy in which some of the system outputs are contro...
In the real applications, the model predictive control (MPC) technology is separated into two layers...
Modern day industrial processes are becoming ever more complex and require a method that is computat...
Two-layer model predictive control is restricted in the field of high real-time control and poor com...
The problem of cooperation of Model Predictive Control (MPC) algorithms with steady-state economic o...
Two-layer model predictive control is restricted in the field of high real-time control and poor com...
This paper deals with the problem of tracking target sets using a model predictive control (MPC) law...
This paper considers a two-phase model predictive control (MPC) which utilize a parsimonious paramet...
This paper concern the development of a stable model predictive controller (MPC) to be integrated wi...
This paper considers a two-phase model predictive control (MPC) which utilize a parsimonious paramet...
In order to solve the problem of the high sensitivity of conventional double-layer model predictive ...
Model predictive control (MPC) is usually implemented as a control strategy where the system outputs...
Several MPC applications implement a control strategy in which some of the system outputs are contro...
Model predictive control (MPC) is usually implemented as a control strategy where the system outputs...
In this work, we propose a framework for economic model predictive control (EMPC) with zone tracking...
Several MPC applications implement a control strategy in which some of the system outputs are contro...
In the real applications, the model predictive control (MPC) technology is separated into two layers...
Modern day industrial processes are becoming ever more complex and require a method that is computat...
Two-layer model predictive control is restricted in the field of high real-time control and poor com...
The problem of cooperation of Model Predictive Control (MPC) algorithms with steady-state economic o...
Two-layer model predictive control is restricted in the field of high real-time control and poor com...
This paper deals with the problem of tracking target sets using a model predictive control (MPC) law...
This paper considers a two-phase model predictive control (MPC) which utilize a parsimonious paramet...
This paper concern the development of a stable model predictive controller (MPC) to be integrated wi...
This paper considers a two-phase model predictive control (MPC) which utilize a parsimonious paramet...