Lew Gordon

Select the Best Process Control

在设计一个新进程时,重要的是exercise some decision-making restraint. One critical area to hold back is selecting an advanced process control technology. The choice of PID, model predictive control, or something else should not be decided until the project has been qualified and reasonable objectives have been established.

一个先进的控制项目

A financially successful advanced process control (APC) project requires a project manager with skills to adequately qualify the project, negotiate contracts, and shape project schedules. In most APC efforts, the volume of information is not large, but a precise understanding of process characteristics and performance objectives is critical from the beginning, since it is the basis for applicat...

Proving Control System Performance

It used to be straightforward. When new instrumentation or automatic control applications were needed, the necessary equipment was purchased, installed, and commissioned. When it was running smoothly, everyone moved on to the next project. It's not that simple anymore—performance usually has to be proven.

Profitable Process Control

Previous articles in this series have discussed how best to achieve a set of control objectives. Specifying those objectives has not been an issue. This article discusses creating and integrating a process optimization function with process control functions. The ultimate goal: move the process from current operating objective to a more profitable one.

Model Predictive Controller

Despite many challenges in applying model predictive control (MPC) to a process control problem, it is worth the effort. Performance of this technology can be significantly better than more familiar control methods. Consequently, its use is becoming more important in achieving plants' production-and-efficiency goals—driven by today's environment of intense economic competition.

Model-based Reactor Control

Future trajectory of a controlled variable is the consequence of the recent and current values of the variables that affect it. The concepts of feed-forward and decoupling control, presented earlier in this series, are steps toward using this idea, but they are limited to steady-state relationships. The dynamic histories of the variables are not included in the design of feed-forward systems.

Advanced Process Control: Fuzzy Logic and Expert Systems

Applying fuzzy logic to control the reactor using only the three existing process measurements—output flow, composition, and temperature—imposes a severe performance limit on the system. Without a mathematical derivative capability in the rule syntax the system can react to the current values of the measurements, but not to how fast they are changing.

Rule-based Reactor Control

Using language rules to address control issues was borne of the need to deal with problems that resisted precise mathematical definition for one reason or another. Also, the traditional control technologies of basic regulatory control (BRC) and advanced regulatory control (ARC) discussed in the previous installments assume the availability of robust signals from field transmitters to provide th...

Advanced Regulatory Control: Decoupling

Feedforward control systems act to isolate the controlled variable from influences that would otherwise disturb it. When a process has multiple loops and the various control loops upset each other, use of a reciprocal system that isolates the loops from each other may be required. Such a design is referred to as decoupling control.

Advanced Regulatory Control: Adaption and Feedforward

Encompassing a number of techniques that address specific loop problems and fundamental design techniques, advanced regulatory control can be applied to deal with variable gains, variable operating conditions, external disturbances, and control loop interaction. Many factors can degrade the performance of single-loop controls.