PID, APC

Figure: Rate-predictive control (RPC) is inherently adaptive (think naturally self-tuning) to changes in process gain. In the top graph, process gain is 1.0, while in the bottom graph, process gain is 2.0. Control performance remains “perfect,” with no change to RPC tuning parameters. Courtesy: APC Performance LLC
PID, APC October 7, 2019

Top 5 Control Engineering articles September 30 to October 6

Articles about RPC and model-based control, water/wastewater applications, OOIP, advanced process control, and prolonging power plant life were Control Engineering’s five most clicked articles from September 30 to October 6. Miss something? You can catch up here.

By Chris Vavra
Courtesy: CFE Media
PID, APC September 18, 2019

Five advanced process control, data analytics connections

Are there connections between advanced process control (APC) and data analytics? Recent developments in the field of information technology (IT) and its use in the manufacturing world provide insights.

By Jim Ford, Ph.D.
Figure 1: In OOIP, the control design is built from objects which match those in the physical plant or equipment design. Courtesy: ControlSphere Engineering
PID, APC September 18, 2019

OOIP Part 3: interfaces and methods

Interfaces and methods used in object-oriented industrial programming (OOIP) help deliver productivity of object-oriented programming (OOP) without the complexity. Because plants and equipment are assembled from objects, it’s logical that their control programming should be, too.

By Gary L. Pratt, P.E.
Figure: Rate-predictive control (RPC) is inherently adaptive (think naturally self-tuning) to changes in process gain. In the top graph, process gain is 1.0, while in the bottom graph, process gain is 2.0. Control performance remains “perfect,” with no change to RPC tuning parameters. Courtesy: APC Performance LLC
PID, APC September 9, 2019

Advantages of RPC and limits of model-based control

Part 3: Rate-predictive control, an alternative algorithm to proportional-integral-derivative (PID) and model-based control, can provide single-loop control. See three RPC advantages and two model-based control limitations.

By Allan Kern
Figure 3: Here the block diagram from figure 2 has been rearranged into a more familiar configuration that is functionally identical to a traditional feedback controller (blue) equipped with a setpoint filter (green) and a feedforward path (red). Most commercial feedback controllers include setpoint filtering and feedforward as standard options, making this version of model-following control simpler than the original version, and much easier to implement. Source: Control Engineering
PID, APC September 9, 2019

Top 5 Control Engineering articles September 2-8

Articles about model-following control, industrial controller cybersecurity, machine learning, improving engineer retention, and IIoT platforms were Control Engineering’s five most clicked articles from September 2-8. Miss something? You can catch up here.

By Chris Vavra
Figure 3: Here the block diagram from figure 2 has been rearranged into a more familiar configuration that is functionally identical to a traditional feedback controller (blue) equipped with a setpoint filter (green) and a feedforward path (red). Most commercial feedback controllers include setpoint filtering and feedforward as standard options, making this version of model-following control simpler than the original version, and much easier to implement. Source: Control Engineering
PID, APC August 30, 2019

The basics of model-following control

Two proportional-integral-derivative (PID) controllers can be better than one. Model-following control may be the best choice if it's important to get the process variable to the setpoint without hunting or overshoot.

By Control Engineering
Pump selection for parallel pump control is critical in determining the desired total system output. Check pump curves to make sure that the number of pumps, flow, head, and multi set points are adequate for your system needs. Head pressure may not remain constant in some cases, as the flow is increased to multiple pumps. Courtesy: Crane Pumps & Systems.
PID, APC August 15, 2019

Use of variable frequency drives in injection molding saves money

Variable frequency drives (VFDs) improves process cooling optimization and pump efficiency.

By Timothy Albers and Dan Roberts
Figure 2: The moving platen (yellow structure) is visible above the fixed lower bolster of the 2,430-ton Hoesch press. Courtesy: Delta Computer Systems Inc.
PID, APC August 12, 2019

Motion controller gives old presses new life

Case study: Retrofit controller on four hydraulic presses used a new programmable logic controller (PLC) to control the moving platen and the levelling cylinders would be controlled by a new electrohydraulic motion controller.

By Bruce Coons
Figure 2: Next-generation APC consists of many software modules working together to deliver improved plant performance. Courtesy: Yokogawa Corp.
PID, APC August 7, 2019

Advanced process control improves refinery, chemical plant operations

Next-generation advanced process control (APC) shatters processing barriers for process facilities.

By Hiroshi Wakasugi and Sanjay Venugopal
Figure 1: In OOIP, the control design is built from objects that match those in the physical plant or equipment design. Courtesy: Coherent Technologies Inc.
PID, APC August 4, 2019

Leveraging OOIP, Part 2: Abstraction, nesting and interfaces

Part 2: Plants and equipment are assembled from objects, and controls architecture should be too. Industrial programmers can realize the productivity of object-oriented programming (OOP) without the complexity by using object-oriented industrial programming (OOIP). See nine ways to determine if a development system supports OOIP.

By Gary L. Pratt, P.E.