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:

• The process to be controlled.

• A sensor (or instrument) that measures the condition of the process.

• A transmitter that converts the measurement into an electronic signal.

• A controller that decides whether or not the process condition is acceptable.

• An actuator (or final control element) that applies a corrective action to the process according to the controller’s instructions.

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 the setpoint. The controller subtracts the latest process variable measurement from the setpoint to generate an error signal. The magnitude and duration of the error signal then determine the value of the controller’s output or controlled variable, which in turn dictates the corrective efforts applied by the actuator.

Cruising

For example, a car equipped with a cruise controller uses a speedometer to measure and maintain the car’s speed. If the car is traveling too slowly, the controller instructs the accelerator to feed more fuel to the engine. If the car is traveling too quickly, the controller lets up on the accelerator. The car is the process, the speedometer is the sensor, and the accelerator is the actuator.

The car’s speed is the process variable. Other common process variables include temperatures, pressures, flow rates, and tank levels. These are all quantities that can vary constantly and can be measured at any time. Common actuators for manipulating such conditions include heating elements, valves, pumps, and dampers.

For a discrete process, the variable of interest is measured only when a triggering event occurs, and the measure-decide-actuate sequence is typically executed just once for each event. There’s really no “loop” involved. For example, the eyes of the human controller driving the car measure ambient light levels at the beginning of each trip. If it’s too dark to see well, the driver decides to turn on the car’s lights. No further adjustment is required until the next triggering event, such as the end of the trip.

Feedback loops for discrete processes are generally much simpler than continuous control loops, since discrete processes do not involve as much inertia. The driver controlling the car gets instantaneous results after turning on the lights, whereas the cruise controller sees much more gradual results as the car slowly speeds up or slows down.

Inertia tends to complicate the design of a continuous control loop, since a continuous controller typically needs to make a series of decisions before the results of its earlier efforts are completely evident. It has to anticipate the cumulative effects of its recent corrective efforts and plan future action accordingly. Waiting to see how each one turns out before trying another simply takes too long.

The ubiquitous proportional-integralderivative (PID) control algorithm can foresee the future if it is configured or tuned to complement the behavior of the process. A fast-acting PID controller that makes aggressive control decisions works well on a slow process and vice-versa. See “Loop Tuning Fundamentals,” CE, July 2003.

Vance J. VanDoren, Ph.D., P.E.,Control Engineering, controleng@msn.com