Abstract:
A method includes obtaining information identifying (i) uncertainties associated with multiple time-domain parameters of a model and (ii) time-domain performance specifications for a model-based industrial process controller. The model mathematically represents a MIMO industrial process. The method also includes generating multiple tuning parameters for the controller based on the uncertainties and the time-domain performance specifications. The tuning parameters include vectors of tuning parameters associated with the controller, and each vector includes values associated with different outputs of the industrial process. The time-domain parameters could include a process gain, a time constant, and a time delay for each input-output pair of the model. The time-domain performance specifications could include requirements related to worst-case overshoots, settling times, and total variations. The uncertainties could be specified as intervals in which the time-domain parameters lie.
Abstract:
A method includes obtaining information identifying (i) uncertainties associated with multiple time-domain parameters of a model and (ii) time-domain performance specifications for a model-based industrial process controller. The model mathematically represents a MIMO industrial process. The method also includes generating multiple tuning parameters for the controller based on the uncertainties and the time-domain performance specifications. The tuning parameters include vectors of tuning parameters associated with the controller, and each vector includes values associated with different outputs of the industrial process. The time-domain parameters could include a process gain, a time constant, and a time delay for each input-output pair of the model. The time-domain performance specifications could include requirements related to worst-case overshoots, settling times, and total variations. The uncertainties could be specified as intervals in which the time-domain parameters lie.
Abstract:
A method includes obtaining information identifying uncertainties associated with multiple parameters of a model for an industrial model-based controller. The method also includes obtaining information identifying multiple tuning parameters for the controller. The method further includes generating a graphical display identifying (i) one or more expected step responses of an industrial process that are based on the tuning parameters of the controller and (ii) an envelope around the one or more expected step responses that is based on the uncertainties associated with the parameters of the model. The parameters could include a process gain, a time constant, and a time delay associated with the model. The uncertainties associated with the parameters of the model could include, for each parameter of the model, an uncertainty expressed in the time domain. The information identifying the tuning parameters could include a settling time and an overshoot associated with the controller.
Abstract:
A method includes obtaining a reference tracking performance ratio and a disturbance rejection performance ratio associated with a model predictive control (MPC) controller. The method also includes filtering an output target signal for the controller using a first filter based on the reference tracking performance ratio. The method further includes filtering a feedback signal for the controller using a second filter based on the disturbance rejection performance ratio. The filters can provide two degrees of freedom for tuning reference tracking and disturbance rejection operations of the controller. The reference tracking operation of the controller and the disturbance rejection operation of the controller can be independently tunable. The reference tracking performance ratio can control how aggressively the controller responds to a change in the output target signal. The disturbance rejection performance ratio can control how aggressively the controller responds to a disturbance in the feedback signal.
Abstract:
A method includes obtaining a reference tracking performance ratio and a disturbance rejection performance ratio associated with a model predictive control (MPC) controller. The method also includes filtering an output target signal for the controller using a first filter based on the reference tracking performance ratio. The method further includes filtering a feedback signal for the controller using a second filter based on the disturbance rejection performance ratio. The filters can provide two degrees of freedom for tuning reference tracking and disturbance rejection operations of the controller. The reference tracking operation of the controller and the disturbance rejection operation of the controller can be independently tunable. The reference tracking performance ratio can control how aggressively the controller responds to a change in the output target signal. The disturbance rejection performance ratio can control how aggressively the controller responds to a disturbance in the feedback signal.