Title :
Performance increasing of multiple model based control
Author :
Shamsaddinlou, Ali ; Tohidi, Akbar ; Shamsadinlo, Behrang
Author_Institution :
Adv. Process Autom. & Control (APAC) Res. Group in Electr. Eng. Dept., K.N. Toosi Univ. of Technol., Tehran, Iran
Abstract :
In this paper, two novel supervisory method for Multiple Models Predictive Control (MMPC) algorithm presented. Enhanced decision-making unit in MMPC is designed based on practical applicability notions and new fundamental control concepts. The goal is performance increasing of regulation and disturbance rejection. Presented algorithms are evaluated in simulation study on nonlinear pH neutralization process and Mean Arterial Pressure. Comparison results are provided to evaluate the performance and robustness characteristics of the proposed methods.
Keywords :
blood vessels; chemical variables control; control system synthesis; decision making; nonlinear control systems; pH; performance index; predictive control; robust control; MMPC algorithm; control design; decision-making unit; disturbance rejection; mean arterial pressure; multiple model based control; multiple models predictive control; nonlinear pH neutralization process; performance increase; regulation performance; robustness characteristics; supervisory method; Adaptation models; Blood pressure; Computational modeling; Predictive models; Process control; Switches;
Conference_Titel :
Control Applications (CCA), 2013 IEEE International Conference on
Conference_Location :
Hyderabad
DOI :
10.1109/CCA.2013.6662815
