Efficient controls require feedback

Control design: Closing the feedback loop with the appropriate sensors improves equipment and process efficiency. Identify areas where feedback can improve and optimize machine operation and process control. Carefully select from available process control and measurement sensors, and ensure each loop is programmed with the right parameters. See 7-point feedback selection checklist.

01/21/2015


Figure 1: Providing feedback to a centralized automation system allows closed-loop control for a variety of different machines and processes. Courtesy: AutomationDirectClosing the loop with feedback improves control, measuring, and monitoring of packaging, process, and custom machinery. Checking the actual output condition and adjusting the commanded output helps machinery automatically adapt to changing conditions. Open-loop systems save money initially, but will almost always be less efficient and not as repeatable, resulting in a higher total cost of ownership.

Feedback loops can be configured in many different ways, but all have the same basic characteristics. An output signal from some type of controller drives a device that affects the controlled variable. Measurement of this variable is the feedback signal delivered to the controller (Figure 1). The controller compares the desired with the measured variable to determine the error, and adjusts its output accordingly to minimize the error, creating a closed-loop system. This is in contrast to an open-loop system where there is no measurement of the controlled variable, forcing the controller to operate blindly.

Closing the feedback loop on a process has advantages; practical examples can help illustrate basic design techniques. Installation tips and techniques below improve closed-loop control in new and retrofit feedback applications. Closed-loop motion control is more complex. (See related article links at bottom of this article.) 

Closing the loop

Simple discrete feedback systems, such as sensors to detect end-of-stroke on pneumatic cylinders, or the use of discrete handshaking signals between equipment instead of timers to adjust controller output, improves control and monitoring. The same is true for properly designed closed-loop feedback on a process.

Closed-loop control—which includes measurement, computation, and correction—is taught in engineering programs across the world. Laplace transforms and related functions are studied in detail to explain and improve upon closed-loop control. The characteristics and advantages of closed-loop control systems are well documented, but closed-loop control extends beyond the theoretical to include identification of the advantages of feedback, and the application of feedback in particular machine operations and processes. 

Feedback advantages

Using feedback in closed-loop systems improves control by automatically adjusting the controller output to reduce the error. This helps reduce the effects of dynamic disturbances. Feedback also adds stability to an unstable process, ensuring a repeatable and reliable control loop. Table 1 lists some of the main reasons to add closed-loop feedback to a machine or process. 

Many processes have been manually "tweaked" for years, with operators adjusting the controller output to reduce the error. With today's sensor and controller technology, many of these open loops can make use of feedback and a controller to improve operation.

Reducing human involvement in the feedback loop greatly reduces process variations, and allows for continuous improvement as control loop parameters can be continually adjusted to optimize control. These adjustments can be made automatically by various loop tuning software algorithms and programs, or manually by experienced operators. In many cases, a combination of the two methods is used, with operators evaluating recommended changes from loop tuning software, and implementing recommendations judiciously.

Use of feedback in 24/7 operations can reduce process variations and changes that may occur at shift changes as different operators put their own spin on manual loop control. It can also reduce the number of operators needed, or allow operators and other plant personnel to concentrate on other areas such as optimizing operations.

With automatic control enabled by feedback and change control functionality enforced in the controller, process repeatability is improved along with output quality. 

Designing closed-loop systems

Figure 2: Pressure, level, flow, and temperature sensors can measure the difference or error between desired and actual values, allowing control closer to setpoint. Courtesy: AutomationDirectMany types of feedback devices are available to help the actual output match the desired output in process control and measurement applications. Feedback sensors measure many variables, such as temperature, flow, pressure, level, weight, and position (Figure 2). Each of these variables can be sensed or measured with a variety of transducers, transmitters, and detectors. Because they are so many choices with widely varying costs and performance, the feedback device must be carefully selected. A checklist to help with some common specifications is included in Table 2, and it can be used as a guide when selecting the proper feedback sensor. 

Once the type of sensor is chosen—a temperature sensor, for example—measurement range is often the driving requirement. It's important to leave enough headroom for unexpected changes or process upgrades, but not to excess as this will negatively impact accuracy, increase costs, or both. If the sensor measurement range is properly specified, then most other specifications will fall into place. Feedback sensor accuracy and resolution are other important requirements to carefully consider, whether the sensing element is part of a transmitter or a signal conditioner is used. 

Sensor considerations

There are two main types of sensing devices, analog and digital, also referred to as a smart sensor.

With an analog sensor, the resolution of the sensing device output and its corresponding analog input at the controller must be considered. Whenever possible, it's best to stick with the common 12-bit resolution as this cuts cost and promotes standardization. Upgrading to higher resolution 16- or 20-bit devices and inputs is of course possible, but it's often not necessary.

In fact, in cases where higher resolution is needed, it's often best to instead use digital or smart sensors. These devices connect to the controller over a high-speed and high-resolution digital data link. Although more expensive than their analog counterparts, they are often cheaper than very high resolution analog sensors and input cards. But, even high-speed digital communication networks can't match the speed of analog, so loops requiring very quick response times are often better served with analog. 

Required resolution

If a temperature transmitter with 0 to 100 C range and <0.02 C resolution works with the application, a 12-bit analog input card will be sufficient to maintain the desired accuracy. In another example, a pressure transmitter has 11-bit resolution. Dividing the total range of the transmitter by 2,048 shows the pressure change required to see a corresponding change in the transmitter's analog output. With a common 0-100 psi pressure transducer, 100/2,048 = 0.05, so the transducer will change its output by one step for every 0.05 psi pressure change. This level of resolution is adequate for most applications, particularly given the vagaries of total system measurement and control.

If multiple feedback devices are present, the feedback output signal should stay consistent wherever possible. Mixing 4 to 20 mA, 0 to 20 mA, 0 to 5 V dc, 0 to 10 V dc, +/-10 V dc, thermocouple and RTD signals can increase the complexity of a control system. Feedback output signals can be specified at a common signal level such as 4 to 20 mA, or interposing devices can be used to convert other signals to a standard 4 to 20 mA.


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