Bichop R.H. (Ed.) Mechatronic Systems, Sensors, and Actuators: Fundamentals and Modeling

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18-16 Mechatronic Systems, Sensors, and Actuators

continuously tracks the same cycle of a ground wave signal can transfer frequency with an uncertainty

of about 1 × 10

−12

when averaged for 1 day.

NIST operates LF radio station WWVB from Fort Collins, Colorado at a transmission frequency of

60 kHz. The station broadcasts 24 h per day, with an effective radiated output power of 50 kW. The

WWVB time code is synchronized with the 60 kHz carrier and contains the year, day of year, hour,

minute, second, and flags that indicate the status of daylight saving time, leap years, and leap seconds.

The time code is received and displayed by wristwatches, alarm clocks, wall clocks, and other consumer

electronic products [2,7,15].

18.4.2.3 Global Positioning System

The Global Positioning System (GPS) is a navigation system developed and operated by the U.S. Depart-

ment of Defense (DoD) that is usable nearly anywhere on the earth. The system consists of a constellation

of at least 24 satellites that orbit the earth at a height of 20,200 km in six fixed planes inclined 55° from

the equator. The orbital period is 11 h 58 m, which means that each satellite will pass over the same

place on earth twice per day. By processing signals received from the satellites, a GPS receiver can

determine its position with an uncertainty of <10 m.

The satellites broadcast on two carrier frequencies, L1 at 1575.42 MHz and L2 at 1227.6 MHz. Each

satellite broadcasts a spread spectrum waveform, called a pseudo random noise (PRN) code on L1 and

L2, and each satellite is identified by the PRN code it transmits. There are two types of PRN codes. The

first type is a coarse acquisition (C/A) code with a chipping rate of 1023 chips per millisecond. The second

is a precision (P) code with a chipping rate of 10230 chips per millisecond. The C/A code is broadcast

on L1, and the P code is broadcast on both L1 and L2. GPS reception is line-of-sight, which means that

the receiving antenna must have a clear view of the sky [16].

Each satellite carries either rubidium or cesium oscillators, or a combination of both. These oscillators

are steered from DoD ground stations and are referenced to the United States Naval Observatory time scale,

UTC (USNO), which by agreement is always maintained within 100 ns of UTC (NIST). The oscillators

provide the reference for both the carrier and the code broadcasts.

GPS signals now dominate the world of high performance time and frequency transfer, since they

provide reliable reception and exceptional results with minimal effort. A GPS receiver can automatically

compute its latitude, longitude, and altitude from position data received from the satellites. The receiver

can then calibrate the radio path and synchronize its on-time pulse. In addition to the on-time pulse,

many receivers provide standard frequencies such as 5 or 10 MHz by steering an OCXO or rubidium

oscillator using the satellite signals. GPS receivers also produce time-of-day and date information.

A GPS receiver calibrated for equipment delays has a timing uncertainty of <20 ns relative to UTC

(NIST), and the frequency uncertainty is often <2 × 10

−13

when averaged for 1 day. Figure 18.14 shows

an Allan deviation plot of the output of a low cost GPS receiver. The stability is near 1 × 10

−13

after about

1 day of averaging.

TABLE 18.7 LF Time and Frequency Broadcast Stations

Call Sign Country

Frequency

(kHz) Always On?

DCF77 Germany 77.5 Yes

DGI Germany 177 Yes

HBG Switzerland 75 Yes

JG2AS Japan 40 Yes

MSF United Kingdom 60 Yes

RBU Russia 66.666 No

RTZ Russia 50 Yes

TDF France 162 Yes

WWVB United States 60 Yes

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Fundamentals of Time and Frequency 18-17

18.5 Closing

As noted earlier, time and frequency standards and measurements have improved by about nine orders

of magnitude in the past 100 years. This rapid advance has made many new products and technologies

possible. While it is impossible to predict what the future holds, we can be certain that oscillator Qs will

continue to increase, measurement uncertainties will continue to decrease, and new technologies will

continue to emerge.

References

1. Jespersen, J., and Fitz-Randolph, J., From Sundials to Atomic Clocks: Understanding Time and Fre-

quency, 2nd ed., Dover, Mineola, New York, 1999.

2. Kamas, G., and Lombardi, M. A., Time and Frequency Users Manual, NIST Special Publication 559,

U.S. Government Printing Office, Washington, DC, 1990.

3. Levine, J., Introduction to time and frequency metrology, Rev. Sci. Instrum., 70, 2567, 1999.

4. Hackman, C., and Sullivan, D. B., Eds., Time and Frequency Measurement, American Association of

Physics Teachers, College Park, Maryland, 1996.

5. ITU Radiocommunication Study Group 7, Selection and Use of Precise Frequency and Time Systems,

International Telecommunications Union, Geneva, Switzerland, 1997.

6. Novick, A. N., Lombardi, M. A., Zhang, V. S., and Carpentier, A., A high performance multi-channel

time interval counter with an integrated GPS receiver, in Proc. 31st Annu. Precise Time and Time

Interval (PTTI) Meeting, Dana Point, California, p. 561, 1999.

7. Lombardi, M. A., Time measurement and frequency measurement, in The Measurement, Instrumen-

tation, and Sensors Handbook, Webster, J. G., Ed., CRC Press, Boca Raton, FL, 1999, chaps. 18–19.

8. Sullivan, D. B., Allan, D. W., Howe, D. A., and Walls, F. L., Eds., Characterization of Clocks and

Oscillators, NIST Technical Note 1337, U.S. Government Printing Office, Washington, DC, 1990.

9. Jespersen, J., Introduction to the time domain characterization of frequency standards, in Proc. 23rd

Annu. Precise Time and Time Interval (PTTI) Meeting, Pasadena, California, p. 83, 1991.

10. IEEE Standards Coordinating Committee 27, IEEE Standard Definitions of Physical Quantities for

Fundamental Frequency and Time Metrology—Random Instabilities, Institute of Electrical and Elec-

tronics Engineers, New York, 1999.

11. Walls, F. L., and Ferre-Pikal, E. S., Measurement of frequency, phase noise, and amplitude noise, in

Wiley Encyclopedia of Electrical and Electronics Engineering, John Wiley & Sons, New York, 1999,

12, 459.

FIGURE 18.14 Frequency stability of GPS receiver.

–11

–12

–13

–14

Averaging time, , seconds

Allan deviation,

( )

Tau (s)

600

1200

2400

4800

9600

19200

38400

76800

153600

307200

Sigma

5.32e-12

3.19e-12

1.80e-12

1.04e-12

6.77e-13

4.82e-13

3.06e-13

1.33e-13

7.74e-14

7.70e-14

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18-18 Mechatronic Systems, Sensors, and Actuators

12. Howe, D. A., An extension of the Allan variance with increased confidence at long term, IEEE Int.

Freq. Control Symp., 321, 1995.

13. Vig, J. R., Introduction to quartz frequency standards, Army Research and Development Technical

Report, SLCET-TR-92-1, October 1992.

14. Hewlett-Packard Company, Fundamentals of Quartz Oscillators, HP Application Note 200-2, 1997.

15. Carr, J. J., Elements of Electronic Instrumentation and Measurement, 3rd ed., Prentice-Hall, NJ, 1996.

16. Hoffmann-Wellenhof, B., Lichtenegger, H., and Collins, J., GPS: Theory and Practice, 3rd ed.,

Springer-Verlag, New York, 1994.

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19-1

Sensor and Actuator

Characteristics

19.1 Range ........................................................................ 19-1

19.2 Resolution ................................................................. 19-2

19.3 Sensitivity .................................................................. 19-2

19.4 Error .......................................................................... 19-2

19.5 Repeatability ............................................................. 19-3

19.6 Linearity and Accuracy ............................................ 19-3

19.7 Impedance ................................................................ 19-4

19.8 Nonlinearities ........................................................... 19-5

19.9 Static and Coulomb Friction .................................. 19-5

19.10 Eccentricity ............................................................... 19-6

19.11 Backlash .................................................................... 19-6

19.12 Saturation ................................................................. 19-7

19.13 Deadband .................................................................. 19-7

19.14 System Response ...................................................... 19-8

19.15 First-Order System Response .................................. 19-8

19.16 Underdamped Second-Order System Response .... 19-9

19.17 Frequency Response ................................................. 19-12

Reference ............................................................................... 19-14

Mechatronic systems use a variety of sensors and actuators to measure and manipulate mechanical,

electrical, and thermal systems. Sensors have many characteristics that affect their measurement capa-

bilities and their suitability for each application. Analog sensors have an output that is continuous over

a finite region of inputs. Examples of analog sensors include potentiometers, LVDTs (linear variable

differential transformers), load cells, and thermistors. Digital sensors have a fixed or countable number

of different output values. A common digital sensor often found in mechatronic systems is the incremental

encoder. An analog sensor output conditioned by an analog-to-digital converter (ADC) has the same

digital output characteristics, as seen in Figure 19.1.

19.1 Range

The range (or span) of a sensor is the difference between the minimum (or most negative) and maximum

inputs that will give a valid output. Range is typically specified by the manufacturer of the sensor. For

example, a common type K thermocouple has a range of 800°C (from −50°C to 750°C). A ten-turn

potentiometer would have a range of 3600 degrees.

Joey Parker

University of Alabama

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19-2 Mechatronic Systems, Sensors, and Actuators

19.2 Resolution

The resolution of a sensor is the smallest increment of input that can be reliably detected. Resolution is

also frequently known as the least count of the sensor. Resolution of digital sensors is easily determined.

A 1024 ppr (pulse per revolution) incremental encoder would have a resolution of

The resolution of analog sensors is usually limited only by low-level electrical noise and is often much

better than equivalent digital sensors.

19.3 Sensitivity

Sensor sensitivity is defined as the change in output per change in input. The sensitivity of digital sensors

is closely related to the resolution. The sensitivity of an analog sensor is the slope of the output versus

input line. A sensor exhibiting truly linear behavior has a constant sensitivity over the entire input range.

Other sensors exhibit nonlinear behavior where the sensitivity either increases or decreases as the input

is changed, as shown in Figure 19.2.

19.4 Error

Error is the difference between a measured value and the true input value. Two classifications of errors

are bias (or systematic) errors and precision (or random) errors. Bias errors are present in all measure-

ments made with a given sensor, and cannot be detected or removed by statistical means. These bias

errors can be further subdivided into

•

Calibration errors (a zero or null point error is a common type of bias error created by a nonzero

output value when the input is zero)

•

Loading errors (adding the sensor to the measured system changes the system)

•

Errors due to sensor sensitivity to variables other than the desired one (e.g., temperature effects

on strain gages)

FIGURE 19.1 Analog and digital sensor outputs.

FIGURE 19.2 Sensor sensitivity.

Analog

output

Digital

output

Input

Low sensitivity

region

Intermediate

sensitivity region

High sensitivity

region

Input

Output

1 revolution

1024 pulses

------------------------------

360 degrees

1 revolution

------------------------------

× 0.3516

degrees

pulse

-----------------

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Sensor and Actuator Characteristics 19-3

19.5 Repeatability

Repeatability (or reproducibility) refers to a sensor’s ability to give identical outputs for the same input.

Precision (or random) errors cause a lack of repeatability. Fortunately, precision errors can be accounted

for by averaging several measurements or other operations such as low-pass filtering. Electrical noise and

hysteresis (described later) both contribute to a loss of repeatability.

19.6 Linearity and Accuracy

The accuracy of a sensor is inversely proportional to error, that is, a highly accurate sensor produces low

errors. Many manufacturers specify accuracy in terms of the sensor’s linearity. A least-squares straight-

line fit between all output measurements and their corresponding inputs determines the nominal output

of the sensor. Linearity (or accuracy) is specified as a percentage of full scale (maximum valid input), as

shown in Figure 19.3, or as a percentage of the sensor reading, as shown in Figure 19.4. Figures 19.3 and

19.4 show both of these specifications for 10% linearity, which is much larger than most actual sensors.

Accuracy and precision are two terms that are frequently confused. Figure 19.5 shows four sets of

histograms for ten measurements of angular velocity of an actuator turning at a constant 100 rad/s. The

first set of data shows a high degree of precision (low standard deviation) and repeatability, but the

FIGURE 19.3 Linearity specified at full scale.

FIGURE 19.4 Linearity specified at reading.

–10

Nominal straight line + 10% full scale

Nominal straight line

Actual sensor output

Input (% full scale)

Output (% full scale)

100

110

–10

Nominal straight line + 10% of reading

Nominal straight line

Actual sensor output

Input (% full scale)

Output (% full scale)

100

110

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19-4 Mechatronic Systems, Sensors, and Actuators

average accuracy is poor. The second set of data shows a low degree of precision (high standard deviation),

but the average accuracy is good. The third set of data shows both low precision and low accuracy, while

the fourth set of data shows both high precision, high repeatability, and high accuracy.

19.7 Impedance

Impedance is the ratio of voltage and current flow for a sensor. For a simple resistive sensor (such as a

strain gage or a thermistor), the impedance Z is the same as the resistance R, which has units of ohms (Ω),

For more complicated sensors, impedance includes the effects of capacitance, C, and inductance, L.

Inclusion of these terms makes the impedance frequency sensitive, but the units remain ohms:

where is the imaginary number and

is the driving frequency. The impedance form is

particularly nice for analyzing simple circuits, as parallel and series inductances can be treated just like

resistances. Two types of impedance are important in sensor applications: input impedance and output

impedance. Input impedance is a measure of how much current must be drawn to power a sensor (or

signal conditioning circuit). Input impedance is frequently modeled as a resistor in parallel with the

FIGURE 19.5 Examples of accuracy and precision.

Set 1: Precise, but not accurate Set 2: Accurate, but not precise

Set 3: Neither accurate nor precise Set 4: Both accurate and precise

Sensor output, rad/s

True value

Tr u e va lu e

94 96

100 102 104 106 108

94 96

100

102

104 106 108 94 96

100

102

104 106 108

94 96

100 102 104 106 108

True value

Sensor output, rad/s

---

R==

---

-----------

and Z

---

== ==

j 1–=

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Sensor and Actuator Characteristics 19-5

input terminals. High input impedance is desirable, since the device will then draw less current from the

source. Oscilloscopes and data acquisition equipment frequently have input impedances of 1 MΩ or more

to minimize this current draw. Output impedance is a measure of a sensor’s (or signal conditioning

circuit’s) ability to provide current for the next stage of the system. Output impedance is frequently

modeled as a resistor in series with the sensor output. Low output impedance is desirable, but is often

not available directly from a sensor. Piezoelectric sensors in particular have high output impedances and

cannot source much current (typically micro-amps or less). Op-amp circuits are frequently used to buffer

sensor outputs for this reason. Op-amp circuits (especially voltage followers) provide nearly ideal cir-

cumstances for many sensors, since they have high input impedance but can substantially lower output

impedance.

19.8 Nonlinearities

Linear systems have the property of superposition. If the response of the system to input A is output A,

and the response to input B is output B, then the response to input C (= input A + input B) will be output

C ( = output A + output B). Many real systems will exhibit linear or nearly linear behavior over some

range of operation. Therefore, linear system analysis is correct, at least over these portions of a system’s

operating envelope. Unfortunately, most real systems have nonlinearities that cause them to operate

outside of this linear region, and many common assumptions about system behavior, such as superpo-

sition, no longer apply. Several nonlinearities commonly found in mechatronic systems include static

and coulomb friction, eccentricity, backlash (or hysteresis), saturation, and deadband.

19.9 Static and Coulomb Friction

In classic linear system analysis, friction forces are assumed to be proportional to velocity, that is, viscous

friction. With an actuator velocity of zero, there should be no friction. In reality, a small amount of static

(no velocity) or Coulomb friction is almost always present, even in roller or ball type anti-friction

bearings. A typical plot of friction force versus velocity is given in Figure 19.6. Note that the static friction

force can assume any value between some upper and lower limit at zero velocity. Static friction has two

primary effects on mechatronic systems:

1. Some of the actuator torque or force is wasted overcoming friction forces, which leads to ineffi-

ciency from an energy viewpoint.

2. As the actuator moves the system to its final location, the velocity approaches zero and the actuator

force/torque will approach a value that exactly balances frictional and gravity loads. Since static

friction can assume any value at zero velocity, the actuator will come to slightly different final

resting positions each time—depending on the final value of static friction. This effect contributes

to some loss of repeatability in mechatronic systems.

FIGURE 19.6 Static and Coulomb friction.

Velocity

Actual

Linear (viscous)

Friction

force

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19-6 Mechatronic Systems, Sensors, and Actuators

19.10 Eccentricity

The ideal relationships for gears, pulleys, and chain drives assume that the point of gear contact remains

at a fixed distance from the center of rotation for each gear. In reality, the true center of the gears pitch

circle and the center of rotation will be separated by a small amount, known as the eccentricity. Small

tooth-to-tooth errors can also cause local variations in the pitch circle radius. The combination of these two

effects can lead to a nonlinear geometrical relationship between two gears like that of Figure 19.7, where

the nonlinear behavior is greatly exaggerated for clarity. Eccentricity impacts the accuracy of position

measurements made on the input side of the gear pair, as the output gear is not exactly where the sensor

measurement indicates.

19.11 Backlash

If two otherwise perfect gears are not mounted on a center-to-center distance that exactly matches the

sum of the pitch radii, there will be a small clearance, or backlash, between the teeth. When the input

gear reverses direction, a small rotation is required before this clearance is removed and the output gear

begins to move. Gear backlash is just one of many phenomena that can be characterized as hysteresis,

as shown in Figure 19.8. Clearance between shafts and bearings can cause hysteretic effects also. Backlash

exhibits effects similar to those for eccentricity, that is, a loss of repeatability, particularly when approach-

ing a measured point from different directions. The gear backlash problem is so prevalent and potentially

harmful that many manufacturers go to great lengths to minimize or reduce the effect:

•

Gears mounted closer together than the theoretically ideal spacing

•

Split “anti-backlash” gears that are spring loaded to force teeth to maintain engagement at all times

•

External spring-loaded mounts for one of the gears to force engagement

•

Specially designed gears with anti-backlash features

FIGURE 19.7 Gear eccentricity.

FIGURE 19.8 Gear backlash.

Actual

Linear

out

Actual

out

Linear

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Sensor and Actuator Characteristics 19-7

19.12 Saturation

All real actuators have some maximum output capability, regardless of the input. This violates the linearity

assumption, since at some point the input command can be increased without significantly changing the

output; see Figure 19.9. This type of nonlinearity must be considered in mechatronic control system design,

since maximum velocity and force or torque limitations affect system performance. Control systems mod-

eled with linear system theory must be carefully tested or analyzed to determine the impact of saturation

on system performance.

19.13 Deadband

Another nonlinear characteristic of some actuators and sensors is known as deadband. The deadband is

typically a region of input close to zero at which the output remains zero. Once the input travels outside

the deadband, then the output varies with input, as shown in Figure 19.10. Analog joystick inputs

frequently use a small amount of deadband to reduce the effect of noise from human inputs. A very

small movement of the joystick produces no output, but the joystick acts normally with larger inputs.

Deadband is also commonly found in household thermostats and other process type controllers, as

shown in Figure 19.11. When a room warms and the temperature reaches the setpoint (or desired value)

FIGURE 19.9 Saturation.

FIGURE 19.10 Deadband.

FIGURE 19.11 Thermostat deadband.

Actual

Linear

Output

Input

command

Actual

Linear

Deadband

Output

Input

command

Output

Temperature

Deadband

Setpoint

OFF

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