The objective of this work is to formulate and demonstrate the methodology of multi-models for improving the performance of existing advanced control strategies. Multiple models are used to capture the nonlinear proce...The objective of this work is to formulate and demonstrate the methodology of multi-models for improving the performance of existing advanced control strategies. Multiple models are used to capture the nonlinear process dynamics relating to gain and time constant variations. The multi-model strategy was implemented on several controllers such as Smith-Predictor using PI （Proportional-lntegral） and GPC （Generalized Predictive Control）. Computer simulations and experiments were conducted on several nonlinear systems and compared to the original form of these controllers. The enhanced approach was tested on controlling the screw speed of an injection molding machine and temperature of a steel cylinder.展开更多
文摘The objective of this work is to formulate and demonstrate the methodology of multi-models for improving the performance of existing advanced control strategies. Multiple models are used to capture the nonlinear process dynamics relating to gain and time constant variations. The multi-model strategy was implemented on several controllers such as Smith-Predictor using PI （Proportional-lntegral） and GPC （Generalized Predictive Control）. Computer simulations and experiments were conducted on several nonlinear systems and compared to the original form of these controllers. The enhanced approach was tested on controlling the screw speed of an injection molding machine and temperature of a steel cylinder.
