scholarly journals Stable Model Predictive Control Design: Sequential Approach

2011 ◽  
Vol 62 (2) ◽  
pp. 99-103
Author(s):  
Vojtech Veselý
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Design Method ◽  
Control Design ◽  
Sequential Design ◽  
Stable Model ◽  
Sequential Approach ◽  
Prediction Horizon ◽  
Guaranteed Cost ◽  
One Step

Stable Model Predictive Control Design: Sequential Approach The paper addresses the problem of output feedback stable model predictive control design with guaranteed cost. The proposed design method pursues the idea of sequential design for N prediction horizon using one-step ahead model predictive control design approach. Numerical examples are given to illustrate the effectiveness of the proposed method.

Design Method of Model Predictive Control for Development of Current Control System of PMSM

2020 ◽  
Vol 140 (11) ◽  
pp. 793-806
Author(s):  
Masahiro Shimaoka ◽  
Shinji Doki
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Design Method ◽  
Current Control

scholarly journals Artificial Pancreas: Model Predictive Control Design from Clinical Experience

2013 ◽  
Vol 7 (6) ◽  
pp. 1470-1483 ◽  
Author(s):  
Chiara Toffanin ◽  
Mirko Messori ◽  
Federico Di Palma ◽  
Giuseppe De Nicolao ◽  
Claudio Cobelli ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Clinical Experience ◽  
Predictive Control ◽  
Artificial Pancreas ◽  
Control Design

scholarly journals Reinforcement Learning of the Prediction Horizon in Model Predictive Control

2021 ◽  
Vol 54 (6) ◽  
pp. 314-320
Author(s):  
Eivind Bøhn ◽  
Sebastien Gros ◽  
Signe Moe ◽  
Tor Arne Johansen
Keyword(s):  
Reinforcement Learning ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Prediction Horizon

Model Predictive Control for DC–DC Boost Converters With Reduced-Prediction Horizon and Constant Switching Frequency

2018 ◽  
Vol 33 (10) ◽  
pp. 9064-9075 ◽  
Author(s):  
Long Cheng ◽  
Pablo Acuna ◽  
Ricardo P. Aguilera ◽  
Jiuchun Jiang ◽  
Shaoyuan Wei ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Switching Frequency ◽  
Boost Converters ◽  
Prediction Horizon

scholarly journals MODEL PREDICTIVE CONTROL TOOLBOX DESIGN FOR NONSTATIONARY PROCESS

2021 ◽  
Author(s):  
Oleksandr V. Stepanets ◽  
Yurii I. Mariiash
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Complex Structure ◽  
Nonstationary Process ◽  
Actual State ◽  
Quadratic Functional ◽  
Linear Quadratic ◽  
Prediction Horizon

Background. Model predictive control (MPC) approach is the basic feedback scheme, combined with high adaptive properties, which determines its successful use in the practice of design and operation of control systems. These advantages allow managing multidimensional objects with a complex structure, including nonlinearity, optimizing processes in real time within the constraints on controlled and managed variables, taking into account uncertainties in the task of objects and perturbations. Objective. The purpose of the paper is to design and analyse control system of carbon monoxide oxidation in the convector cavity based on MPC with linear-quadratic cost functional with constraint. Methods. The design of MPC is based on mathematical model of an object (relatively simple). At the current step, the prediction of object dynamic response on some final period of time (prediction horizon) is carried out; control optimization is performed, the purpose of which is to approximate the control variables of the prediction model to the corresponding setpoint on the predict horizon. The found optimal control is applied and measurement of an actual state of object at the end of a step is carried out. The prediction horizon is shifted one step further, and this algorithm are repeated. Results. The results of modeling the automatic control system show that the MPC approach provides maintenance of carbon dioxide content when changing oxygen consumption and overshoot caused by introduction bulk does not exceed 0.6 % that meets the technological requirements of the process. Conclusions. A fuse of the MPC and the quadratic functional given the constraints on the input signals is proposed. The problems of control degree of carbon oxidation in the convector cavity include non-stationarity, so the use of classical control methods is difficult. The MPC approach minimizes the cost function that characterizes the quality of the process. The predicted behaviour of a dynamic system will usually differ from its actual motion. The obtained quadratic functional is optimized to find the optimal control of degree of CO oxidation to CO2.

Model predictive control design for DC-DC converters applied to a photovoltaic system

2018 ◽  
Vol 103 ◽  
pp. 537-544 ◽  
Author(s):  
Ahmad Dehghanzadeh ◽  
Gholamreza Farahani ◽  
Hani Vahedi ◽  
Kamal Al-Haddad
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Design ◽  
Photovoltaic System
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