Vance J. VanDoren

Feedback loops control discrete, continuous processes

Arguably, the most basic tool of the control engineering profession is the feedback loop, shown below. It consists of five fundamental elements: This measure-decide-actuate sequence repeats as often as necessary until the desired process condition is achieved. For a continuous process, a feedback loop attempts to maintain a process variable (or manipulated variable) at a desired value known as ...

PID: Still the One

Negative feedback has been used to control continuous processes since the late 18th century. James Watt used a flyball governor to automatically apply more steam to his famous engine when its speed dropped too low and to throttle back the steam when the engine's speed rose too high. This simple balancing act remains the fundamental function of process controllers today: Measure the process vari...

Adaptive Controllers Work Smarter, not Harder

Every process controller is "adaptive" in the sense that it changes its output in response to a change in the error between the setpoint and the process variable. However, an "adaptive controller" can adapt not only its output, but its underlying control strategy as well. It can tune its own parameters or otherwise modify its own control law so as to accommodate fundamental changes in the beh...

Controllers balance performance with closed-loop stability

If high-speed response is not required, any continuous process can be controlled easily enough. A feedback controller need only measure the process variable, determine if it has deviated too far from the setpoint, apply the necessary corrective effort, wait to see if the error goes away, and repeat as necessary.

Basics of Proportional-Integral-Derivative Control

A feedback controller is designed to generate an output that causes some corrective effort to be applied to a process so as to drive a measurable process variable towards a desired value known as the setpoint. The controller uses an actuator to affect the process and a sensor to measure the results.

Tuning Fundamentals: Basics of Proportional-Integral-Derivative Control

PID controllers are by far the most popular feedback controllers for continuous processes. Here's a look at how they work.

Model-Predictive Controller Solves Complex Problems

Model-predictive control is the latest trend in multivariable control technology. Model-predictive controllers (MPCs) use mathematical models to predict the future behavior of the processes they control, then adjust their control efforts to produce the desired results. MPCs are designed to steer multiple process variables towards their respective setpoints while keeping both process input...

Controller Adapts without a Process Model

Theoretically, all information that a feedback controller requires to regulate a continuous process is contained in the process input and output (I/O) data. A PID controller can be manually tuned by analyzing the I/O data from a series of step tests. A self-tuning controller can automatically select its own tuning parameters by analyzing a process model derived from the step test data.