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1. Foreword
In a general mechanical system, a motor used for replacing
human force drives a mechanical device to finish many tasks.
Depending on the power transmission method, a mechanical system
can possess different characteristics. For instance, take systems using
a belt or gears as a power transmission medium. Although the system
has accurate positioning characteristics, its power output is restricted
by the motor properties and the complicated mechanical structure,
thus failing to meet the requirements of high power from a small size.
A hydraulic system uses hydraulic oil as the power transmission
medium, which is ideal for small size with high power output and
high response scenarios.
The hydraulic system was gradually developed from the
hydrostatic transmission theory was first proposed by Blasé Pascal
(1623–1662), a French mathematician and physicist, in the 17th
century. The first hydraulic machine using water as the working
medium was built by English engineer Joseph Braman (1749–1814)
at the end of 18th century and had industrial applications thereafter. In
1905, oil replaced water as the power transmission medium, which
significantly increased the performance of hydraulics. In 1925, F.
Vickers proposed the pressure-balance type vane pump theory to
build a more stable foundation for hydraulics. Hydraulic systems are
still widely used today in industrial fields.
Restricted by their component properties, early hydraulic driving
systems could only control the movement of hydraulic cylinders
using an opening or closing control method. Hydraulic cylinder
pressure was regulated by a spring pressure regulator which was
adjusted manually, thus making it impossible to slightly adjust the
system structure. Therefore, achieving precision control was highly
limited and dynamic adjustment was inflexible.
However, due to the recent maturing of semi-conductor
development, various kinds of precision sensors and servo valves
have come into existence. Subsequently, hydraulic cylinder pressure
can be measured by a pressure sensor, and the pressure output of the
hydraulic cylinder can be controlled using a relief valve. Alternatively,
the force output is measured with a load cell, and the movement
direction of the hydraulic cylinder and the oil flow is controlled using
a servo valve. It is therefore no longer difficult to have precision
positioning and accurate output force control [1, 2, 5].
However, in a hydraulic system, hydraulic oil is compressible.
Friction can develop between the cylinder wall and the piston,
causing leakage problems [6]. In addition, the system characteristics
may also vary with oil temperature. The servo proportional valve also
has a dead-zone and hysteresis problems [7, 8]. The above properties
may consequently have a tremendous effect on the control
performance of the hydraulic servo system. It is therefore impossible
for a general linear controller to achieve effective control.
Therefore, many scholars have proposed using non-linear control
principles to achieve the control, of which a fuzzy controller [3, 4, 9]
is often used. The main feature of a fuzzy controller is that it does not
need to obtain an accurate system mode with no need to establish a
complex system equation. On the contrary, fuzzy controllers are
designed by using rules based on the control principles of experts or
http://dx.doi.org/10.6493/SmartSci.2014.233
Precision Force Control for an Electro-Hydraulic Press Machine
Hong-Ming Chen1,*, Guo-Wei Yang1 and Chong-Cyuan Liao1
1Department of Electronic Engineering, Chienkuo Technology University, Changhua City, Taiwan, ROC * Corresponding Author / E-mail: [email protected]
KEYWORDS : Electro-hydraulic servo press system, Force control, Relief valve, Flow servo valve, Composite control
This thesis is primarily intended to design a PC-based control system to control the force of an electro-hydraulic servo press system for implementing precision force control. The main feature is to develop a composite control by using the relief valve and the flow servo valve. Using feedback from a force sensor, a fuzzy controller was designed with LabVIEW software as the system control core for achieving a precision force control for the hydraulic cylinder on its travel and output. The weakness of hydraulic systems is that hydraulic oil is compressible and prone to leaking, and its characteristics can vary with oil temperature, thus making it difficult for a general linear controller to achieve accurate control. Therefore, a fuzzy controller was designed with LabVIEW along with a NI-PCI_6221 interface card and a load cell to control the servo valve flow and the relief valve to control the pressure source. The testing results indicate that accurate force control output of an electro-hydraulic servo press system can be obtained.
Manuscript received: March 13, 2014 / Accepted: March 31, 2014
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experienced people. Its control effects are thus not inferior to the
performance of other advanced controllers.
In this study, force output was controlled with PC-based real-time
control. The control system consists of the controller designed with
the graphic control software LabVIEW which is developed by
National Instrument Corp. With feedback from the NI-PCI_6221
interface card and the force sensor, the fluid flow is controlled by the
servo valve while the pressure source is controlled by a relief valve,
thus completing precision force control of the electro-hydraulic servo
press system. A fuzzy controller is used in this system and was
designed with assistance of the Fuzzy toolkit in LabVIEW. Using a
real hydraulic servo press system platform for testing the control
principles, generally good control effects were observed with regard
single step, repeated pressure-load, sinusoid trace of force, and multi-
step force increase and decrease response, response speed and steady-
state error.
2. Electro-hydraulic servo force control system
The architecture of the electro-hydraulic servo press system is
shown in Fig. 1. The hydraulic system used in this study is a vertical-
type press. The hydraulic pump is driven by an AC motor, and the
pressure of the hydraulic cylinder is adjusted by a relief valve. The
moving direction of the hydraulic cylinder and the hydraulic flow
volume are controlled by the servo valve to achieve positioning of the
hydraulic cylinder and force control. The hydraulic servo system
consists of a servo valve, a relief valve, a hydraulic cylinder, an
optical ruler, a force sensor, a spring load, a PC and a data-acquisition
card. The hydraulic cylinder moves with a reciprocal stroke travel of
20 cm.
Fig. 1 Architecture of the electro-hydraulic servo press system
In the hydraulic servo system, hydraulic oil is supplied from the
pump driven by the motor to the hydraulic cylinder as a power source.
The control system used to design the fuzzy controller is PC-based as
it offers precision force control to the hydraulic cylinder. Its main
control method is through the hydraulic cylinder pressure, which is
measured by the pressure sensor, and the output force of the hydraulic
cylinder, which is measured by the force sensor. With the PCI-6621
interface card, the pressure and force signals are captured and sent to
the computer where the control level is calculated by LabVIEW as
subject to the control principles of the controller. The control level is
then output via the interface card to control the relief valve for initial
force control of the hydraulic cylinder pressure. At the same time, the
servo valve is controlled by the output of the interface card to fine-
tune the flow, thus achieving composite control and an accurate force
control effect.
3. Description of the electro-hydraulic force servo system
The hydraulic cylinder servo position system is shown in Fig. 2
[6-8]:
Fig. 2 Architecture of the hydraulic cylinder servo position system
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The hydraulic cylinder servo position system mainly consists of
the servo valve and the hydraulic cylinder. The main purpose of
control is to let the fluid flow rate of the hydraulic cylinder reach the
expected value LQ as soon as possible. The relationship between
the servo valve spool position vx and the load flow rate LQ at the
orifice can be determined from the orifice law [6] as follows:
LcvqL PkxkQ (1)
Where, qk is expressed in equation (2):
LvSdvq PxPwckk )sgn(1 (2)
and SP is the oil supply pressure, dC is the fluid emission
coefficient, w is the servo spool area gradient, vx is the servo spool
displacement, is the oil density, LP is the pressure variance
between two sides of the hydraulic cylinder, vk is the servo valve
gain, and ck is the gain constant of the pressure variance.
Since the moving speed of a normal hydraulic cylinder is within
the bandwidth of the servo valve, the servo valve can be assumed to
be under the zero-order system, the direct proportional relationship [7]
of the servo spool displacement vx and the control input u can be
expressed as follows in (3):
ukx av (3)
ka is the amplified gain of the servo valve and u is the control input of
the servo valve. In consideration of the internal leaking and
compressibility of oil in the hydraulic system, from the flow equation
[6] of the hydraulic cylinder the following equation is arrived at:
LtLe
tL PCP
VxAQ
4
(4)
LQ is the total oil flow volume to the hydraulic cylinder from the
orifice of the servo valve, A is the area of the effective cross-section
for the pressure of the hydraulic cylinder, tV is the effective volume
of the hydraulic system, e is the oil compressibility module, and
tC is the total oil leaking coefficient of the hydraulic cylinder. If we
rearrange equations (2) to (4), we can obtain the system mode as
follows:
4
)(44
)( 2
uV
KAK
tFV
KCxV
AtF
t
eaq
t
ect
t
e
(5)
From the equation (5) we see that the hydraulic cylinder force servo
system is a parameter-variable non-linear system. An accurate control
effect is impossible to achieve with a general opening or closing
control method. In the next chapter, a non-linear fuzzy controller will
be outlined specifically for this servo system in order to provide
precision force servo control.
4. Principles and design of a fuzzy controller
The basic structure of a fuzzy controller can be divided into four
parts [3, 4]: the fuzzification interface, the If-Then rule base, the
fuzzy inference engine and the defuzzification interface as shown in
Fig. 3. First, the input error and the error varying rate is fuzzificated
to allow the input value of the error or the error varying rate to fall
within the range set by the fuzzy inference. Therefore, at the input end,
the gain adjustment parameters K1 and K2 are added to allow the
output to fall within the control range. At the output end, a parameter
K3 is also added to adjust the output control. The membership
functions of the input error and the error variance for the fuzzy
controller are shown in Fig. 4 and Fig. 5 and the membership function
of the fuzzy output is shown in Fig. 6. In addition, the rule base
design is completed with the If-Then expressions of the
corresponding relationship between the system control requirements
and expert experience. For the fuzzy inference method, this paper
uses the common Min-Min-Max fuzzy inference of Mamdani. Lastly,
the fuzzy value derived from the fuzzy inference is converted into a
clear value for output through defuzzification to control the system.
There are many means of defuzzification, but this paper uses center of
gravity defuzzification [3, 4, 9] to determine the inference results. The
inference rule base of the fuzzy controller is shown in Fig. 7.
u
Fig. 3 Architecture of a fuzzy controller
Fig. 4 Error membership function of a fuzzy controller
Fig. 5 Error variance membership function of a fuzzy controller
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Fig. 6 Output membership function of a fuzzy controller
Fig. 7 Inference rule base of a fuzzy controller
5. Experimental results and discussion
Fig. 8 shows the real hydraulic servo press system used by this
study. This thesis is primarily intended to design a fuzzy controller
and apply it to the electro-hydraulic servo platform. First, the
LabVIEW software was used as the system control core to design the
human-machine interface control panel, as shown in Fig. 9, and the
fuzzy controller in order to achieve precision force control of the
hydraulic cylinder. The relationship between the input and output of
the relief valve is shown in Fig. 10, from which an obvious hysteresis
can be seen. This would make it difficult to achieve accurate force
control.
Fig. 8 Picture of the hydraulic press system
Fig. 9 Human-machine interface control panel
Fig. 10 Characteristic curve of the relief valve
To achieve precision force control, this study used a mixed force
output control structure to achieve precision control. This mixed force
output control structure is mainly uses the relief valve to control the
hydraulic pressure of the hydraulic cylinder. In the meantime, the
servo valve is also used to achieve an accurate flow. Finally, accurate
force output control can be achieved. Fig. 11 is the block diagram of
this force servo control system.
Fig. 11 Architecture of mixed force output control
To investigate the performance strengths and weaknesses of this
experimental platform as applied to various control structures,
performance was compared with a traditional PID controller as below.
In this study, parameters of the traditional PID controller are
determined by using the ZN rule. The values are then slightly
adjusted following a trial and error method. The parameter values are
as follows:
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Pressure relief valve: Kp=0.015 Ki=0.00237 Kd=0.00023
Servo valve: Kp=0.023 Ki=0.01115 Kd=0.00985
However, the membership function of this fuzzy controller is
designed specifically for the system's characteristics with
consideration of the minimum resolution of the sensor as fine-tuned
with the experimental data. The rule base was established according
to empirical rules. The parameters of K1, K2 and K3 are expressed as
follows:
Servo valve: K1=1.25 K2=2.75 K3=0.00425
This experiment compared the controller performance by single
step response, multi-step increase response, multi-step decrease
response, sinusoid response, and repeated force pressure-load
response of the force output. The red curve shown in each diagram is
the PID response curve, the green curve is the fuzzy response curve,
and the black curve is the setting amount.
First, the multi-step force increase response is shown in Fig. 12.
The initial force was set at 500 kgf with an increase of 100kgf for 10
seconds each until 1000 kgf was reached at which it stopped. The
multi-step increase error response is shown in Fig. 13, from which we
can see the error is about ±0.5 kgf. The multi-step force decrease
response curve is shown in Fig. 14. The initial force was set at 950
kgf with a decrease of 100kgf for 10 seconds each until 550 kgf was
reached at which it stopped. The multi-step decrease error response is
shown in Fig. 15, from which we see the error is also about ±0.5 kgf.
The force sinusoid trace response is shown in Fig. 16, and the
force sinusoid trace error response is shown in Fig. 17, from which
we see the trace error is about ±4 kgf. The force single step response
is shown in Fig. 18, and the force single step error response is shown
in Fig. 19. Its error is also about ±0.5 kgf.
In addition, the repeated force pressure-load response is shown in
Fig. 20, and the repeated force pressure-load error response is shown
in Fig. 21. The repeated pressure-load movement flow was set to the
origin position for the hydraulic cylinder when it started. When it
reached the set cycle, to prevent the hydraulic cylinder and the spring
load from excessive colliding, the hydraulic cylinder was set to
descend slowly. The control pressure did not increase until the
hydraulic cylinder touched the spring load. This is done cyclically.
Fig. 12 Multi-step increase response
Fig. 13 Multi-step increase error response
Fig. 14 Multi-step decrease response
Fig. 15 Multi-step decrease error response
Fig. 16 Force sinusoid trace response
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Fig. 17 Force sinusoid trace error response
Fig. 18 Single step response
Fig. 19 Single step error response
Fig. 20 Architecture of the fuzzy controller
Fig. 21 Repeated force pressure-load error response
The variance between each controller can be observed from the
series of response curve diagrams. This thesis compares the
maximum overshoot and the steady-state error by arranging the
curves as shown in Table 1 & 2. For the maximum overshoot, it is
apparent that the performance of the fuzzy controller is better than
that of the PID controller.
Table 1 Comparison of Maximum Overshoot (kgf)
Single step
response
Multi-step
increase
Multi-step
decrease
Sinusoid force
response
Repeated pressure-
load response
PID 12.25 11.8 5.5 9 12.8
Fuzzy 0.5 5.8 4.8 9.5 10.4
Table 2: Comparison of Steady-State Error (kgf)
Single step
response
Multi-step
increase
Multi-step
decrease
Sinusoid force
response
Repeated pressure-
load response
PID <0.5 <0.5 <5 <2 <0.5
Fuzzy <0.5 <0.5 <5 <3 <0.5
6. Conclusion
In the force control system, the most important is point that the
maximum overshoot must not be excessive. Otherwise, this could
cause damage to the object under pressure load. In consideration of
the press tester, an excessive overshoot could cause collapse of the
object under test. From the data in Tables 1 & 2, the fuzzy controller
can be seen to have a smaller result for the excessive overshoot. The
minimum resolution of the load cell used by this experiment is ±1 kgf.
On the whole, the precision force control effect was thus successfully
implemented. The results are briefly listed as follows:
(1) The design of a fuzzy controller has been completed and
applied to an electro-hydraulic servo force control system.
(2) Precision force servo control was achieved by using a mixed
control of the relief valve and the flow servo valve.
(3) Precision control effect was attained through the single step,
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multi-step, sinusoid trace and repeated pressure-load responses
of force.
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