Advanced process control: Difference between revisions

Revision as of 04:15, 25 March 2025

Revision as of 04:23, 25 March 2025

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* Advanced regulatory control (ARC) refers to several proven advanced control techniques, such as override or adaptive gain (but in all cases, "regulating or feedback"). ARC is also a catch-all term used to refer to any customized or non-simple technique that does not fall into any other category. ARCs are typically implemented using function blocks or custom programming capabilities at the DCS level. In some cases, ARCs reside at the supervisory control computer level.

* Advanced process control (APC) refers to several proven advanced control techniques, such as feedforward, decoupling, and inferential control. APC can also include Model Predictive Control, described below. APC is typically implemented using function blocks or custom programming capabilities at the DCS level. In some cases, APC resides at the supervisory control computer level.

* Multivariable [[model predictive control]] (MPC) is a popular technology, usually deployed on a supervisory control computer, that identifies important independent and dependent process variables and the dynamic relationships (models) between them and often uses matrix-math based control and optimization algorithms to control multiple variables simultaneously. One requirement of MPC is that the models must be linear across the operating range of the controller. MPC has been a prominent part of APC ever since supervisory computers first brought the necessary computational capabilities to control systems in the 1980s.

* Nonlinear MPC is similar to Multivariablemultivariable MPC in that it incorporates dynamic models and matrix-math based control; however, it does not require model linearity. Nonlinear MPC can accommodate processes with models with varying process gains and dynamics (i.e., dead times and lag times).

* Inferential control: The concept behind inferential control is to calculate a stream property from readily available process measurements, such as temperature and pressure, that otherwise might be too costly or time-consuming to measure directly in real time. The accuracy of the inference can be periodically cross-checked with laboratory analysis. Inferential controlmeasurements can be utilized in place of actual online analyzers, whether for operator information, cascaded to base-layer process controllers, or multivariable controller CVs.

* Sequential control refers to discontinuous time- and event-based automation sequences that occur within continuous processes. These may be implemented as a collection of time and logic function blocks, a custom algorithm, or a formalized [[sequential function chart]] methodology.

* [[Intelligent control]] is a class of [[Control theory|control]] techniques that use various [[artificial intelligence]] computing approaches like [[Artificial neural network|neural networks]], [[Bayesian probability]], [[fuzzy logic]], [[machine learning]], [[evolutionary computation]], and [[Genetic algorithm|genetic algorithms]].

== Related Technologies ==