Robustness and performance of modified smith predictors for processes with longer dead times.
Gurusamy Saravanakumar, R. S. D. Wahidabanu, V I George
Abstract
Gurusamy Saravanakumar, R. S. D. Wahidabanu, V I George
Abstract
Processes that contain a large transport lag [exp (Td S) ]can be difficult to control because the disturbance in set point or load does not reaches the output of the process until Td units of time have elapsed . The control trajectory known as dead time compensating controller is also referred to as a Smith predictor. The control algorithm in a smith predictor is normally a PI controller. This paper describes the advantage of modified smith predictors which has the advantage over the dead time compensating controllers is that although it contains five parameters, only three are adjusted by the operator namely the gain, integral time and dead time. The controller is also suited for processes with varying longer dead times and can be tuned manually in the same way as a PID Controller and has the advantage over the other smith predictor based controllers.
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Processes that contain a large transport lag [exp (Td S) ]can be difficult to control because the disturbance in set point or load does not reaches the output of the process until Td units of time have elapsed . The control trajectory known as dead time compensating controller is also referred to as a Smith predictor. The control algorithm in a smith predictor is normally a PI controller. This paper describes the advantage of modified smith predictors which has the advantage over the dead time compensating controllers is that although it contains five parameters, only three are adjusted by the operator namely the gain, integral time and dead time. The controller is also suited for processes with varying longer dead times and can be tuned manually in the same way as a PID Controller and has the advantage over the other smith predictor based controllers.
Key concepts: Smith predictor, Dead time, Control theory (sociology), PID controller, Robustness (evolution), Set point, Controller (irrigation), Trajectory