Advanced process control: Difference between revisions

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In [[control theory]] '''Advanced process control''' (APC) refers to a broad range of techniques and technologies implemented within industrial process control systems. Advanced process controls are usually deployed optionally and in addition to ''basic'' process controls. Basic process controls are designed and built with the process itself, to facilitate basic operation, control and automation requirements. Advanced process controls are typically added subsequently, often over the course of many years, to address particular performance or economic improvement opportunities in the process.

[[Process control]] (basic and advanced) normally implies the process industries, which includes chemicals, petrochemicals, oil and mineral refining, food processing, pharmaceuticals, power generation, etc. These industries are characterized by continuous processes and fluid processing, as opposed to discrete parts manufacturing, such as automobile and electronics manufacturing. The term [[process automation]] is essentially synonymous with process control.

Process controls (basic as well as advanced) are implemented within the process control system, which usuallymay meansmean a [[Distributed control system|distributed control system (DCS)]], [[Programmable logic controller|programmable logic controller (PLC)]], and/or a supervisory control computer. DCSs and PLCs are typically industrially hardened and fault-tolerant. Supervisory control computers are often not hardened or fault-tolerant, but they bring a higher level of computational capability to the control system, to host valuable, but not critical, advanced control applications. Advanced controls may reside in either the DCS or the supervisory computer, depending on the application. Basic controls reside in the DCS and its subsystems, including PLCs.

== Types of Advanced Process Control ==

Following is a list of the bestwell known types of advanced process control:

* Advanced regulatory control (ARC) refers to several proven advanced control techniques, such as feedforward, override or adaptive gain. 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.

* 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 (i.e. they must be repeatable at all points ofacross 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.

* Inferential Measurements: The concept behind inferentials is to calculate a stream property from readily available process measurements, such as temperature and pressure, that otherwise would require either an expensive and complicated online analyzer or periodic laboratory analysis. Inferentials can be utilized in place of actual online analyzers, whether for operator information, cascaded to base-layer process controllers, or multivariable controller CVs. Inferentials do not perform control, they must be connected into a control strategy as a replacement for a physical measurement.

* Sequential control refers to dis-continuous 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 using a formalized [[Sequential function chart]] methodology.

* Compressor control typically includes compressor anti-surge and performance control.

* Nonlinear MPC: Similar to Multivariable MPC in that it incorporates dynamic models and matrix-math based control; however, it does not have the requirement for model linearity. Nonlinear MPC is capable of accommodating processes with models that have varying process gains and dynamics (i.e. dead-times and lag times).<ref>http://www.aspentech.com/products/advanced-process-control/aspen-nonlinear-controller/</ref>

* Inferential Measurements: The concept behind inferentials is to calculate a stream property from readily available process measurements, such as temperature and pressure, that otherwise wouldmight requirebe eithertoo ancostly expensiveor andtime-consuming complicatedto onlinemeasure analyzerdirectly orin real time. The accuracy of periodicthe inference can be periodically cross-checked with laboratory analysis. Inferentials can be utilized in place of actual online analyzers, whether for operator information, cascaded to base-layer process controllers, or multivariable controller CVs. Inferentials do not perform control, they must be connected into a control strategy as a replacement for a physical measurement.

* Sequential control refers to dis-continuousdiscontinuous 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 using a formalized [[Sequential function chart]] methodology.

* Compressor control typically includes compressor anti-surge and performance control.

== Related Technologies ==