With the increase in processor CPU power and the ability of having more load, the number of modern advanced process control (APC) technologies available to customers has reached a level where everyone should apply them if there is an opportunity to improve their plant operation. However, in some older plants, due to still low processor CPU power usage and high business financial constraints a cascade, feedforward or some other complex control loops could be considered also one of the advanced process control (APC) strategies.
Dead time compensation is one of the first advanced process control (APC) concepts that are still not very well understood by many. Utilizing the most famous dead time compensation function, called Smith Predictor, allows the control loop to adjust the model bias according to the magnitude of the disturbance. An adaptive Smith Predictor allows the controller to adjust the gain as well as the bias depending on the disturbance. The model in the Smith Predictor can be presented by transfer function, any 1st principle, empirical model with multi-inputs or any other capable model for predicting the controlled process variable.
A second advanced process control (APC) concept is the adaptive control. Any PID or advanced process control (APC) controller that exhibits changes in the process response that are essentially linear for that portion of the operating range is a candidate for this specific concept. Actually, changes in process or operating conditions which causes the process model parameters to change a lot (more than 20%) can be a good candidate for mentioned advanced process control (APC) concept. For its implementation the designer needs to know how many control regions there are and where the changes occur in the response of the PID or advanced process control (APC) concept.
The third advanced process control (APC) concept is a feedforward control. It requires measurements of disturbance and controlled variables in the process. The complete procedure consists of two steps: first to calculate the effect of disturbance on the controlled variable and then to determine the required movement of the manipulated variable to cancel measured disturbance. Benefits of using this advanced process control (APC) approach are huge: proactive action by removing the disturbance effect completely at the beginning of its entrance in the process and creating stable process conditions.
PiControl Solutions PITOPS software is capable to respond to the needs of entire DCS-based advanced process control (APC). It identifies multivariable process models from process data and mathematically calculates the feedforward model parameters, where typically the estimation of these feedforward tuning parameters is typically done by guesswork with little chance of being correct. Guessed and wrong feedforward parameters will produce out-of-phase control action that will be harmful and better than no feedforward control scheme at all!
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