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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...
It presents a computer control system for process control based on data-driven. The system focuses on process data and is able to deal with the complex problems such as nonlinearity, significant delay, strong coupling and stochastic uncertainty, which are ubiquitous in process control. It adopts both modeling method based on data and learning control theory. The computer control system is composed...
Model predictive control (MPC) has become the leading form of advanced multivariable control in the chemical process industry. The objective of this work is to introduce a multiple model adaptive control strategy for multivariable MPC. The method of approach is to design multiple linear MPC controllers. This strategy maintains performance of multiple linear MPC controllers over a wide range of operating...
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