Abstract-- In this paper, a controller design of a voice coil motor (VCM) with enhanced disturbance input decoupling performance, especially for precise automated manufacturing processes, is proposed. To enhance the force control accuracy, a disturbance state filter for force control is applied to estimate and compensate for the varying dynamics of VCM systems, such as nonlinearly variable loads and other uncertainties. The state filter estimation accuracy in the presence of system parameter errors is fully analyzed. In addition, the proposed disturbance decoupling method is computationally efficient and robust to other parameter errors. The proposed algorithm is implemented in a developed VCM actuator and verified to be appropriate for a VCM drive system with unknown disturbances.

Index Terms-- Voice coil motor (VCM), disturbance input decoupling, precise automated manufacturing processes.

I. INTRODUCTION

Voice coil actuators (VCAs) based on moving coil technology are applied in a wide range of precise automated manufacturing processes, e.g., for auto-focusing of digital cameras, die bonding, button/switch testing of portable devices, laser cutting, and integrated circuit inspection [1-4]. Compared to pneumatic and hydroelectric systems, VCAs deliver compact size, light weight, extreme speed, and high precision with an exceptional degree of accuracy and repeatability. Because of these characteristics, voice coil motors (VCMs) have gained attention in advanced and complex manufacturing environments. These advantages of VCMs are also considered indispensable for control systems requiring multi-axis movements [1]. The minimum allowable positioning accuracy has recently decreased to 0.1 μm, depending on the position sensor resolution, while the force normal to the work surface must be controlled. This is difficult to achieve by position control alone, since uncertainties in the position of the workpiece and in the stiffness of the tool, holding device, and manipulator may result in excessive contact force or loss of contact [5-6]. Industrial experience has shown that control mode-switching is very effective in achieving the desired regulation accuracy and repeatability in motion control applications [7-8]. Therefore, a hybrid of position and force control is commonly adopted in most VCA applications [1].

The VCM for automated manufacturing processes is a direct drive motor that uses a permanent magnetic field and coil winding to produce a force proportional to the current applied to the coil. The schematic layout is shown in Fig. 1; a return spring is added to hold a moving part,

including a shaft, in a vertical plane when power is lost. In practice, this acts like a nonlinear load during operation. VCMs are generally difficult to control precisely as the return spring, friction, and other mechanical characteristics become dominant in the motion dynamics, owing to the small size and small travel displacement [2-3]. However, the open literature includes no investigations into those potential influences on precise control. Moreover, motion coupling between VCAs and rotary actuators considerably disturbs the overall motion path.

While P-PI-type position-velocity controllers are preferred for meeting tracking control requirements in most industrial systems, these requirements are not straightforward in the presence of the disturbances described above. This is because the controller’s cascaded framework results in interaction between command tracking and disturbance rejection, making it very difficult to achieve both functions simultaneously in this structure.

Another important issue relevant to force control is the prompt realization of force commands, which is nontrivial because of internal disturbances such as variation in the force constant and current measurement errors. However, we are not aware of any practical solution in VCM force control applications.

In this paper, computationally efficient disturbance decoupling methods for enhancing VCA control accuracy are introduced. On the basis of the tracking and disturbance rejection requirements for precise automated manufacturing processes, a state-feedback (SFB) style position-velocity controller and a disturbance-estimator-integrated force controller are designed through a combined active disturbance rejection control and feed-forward arrangement by exploiting a unique disturbance estimation and compensation concept. To quantify the disturbance decoupling performance, the dynamic stiffness is derived and analyzed. The design methodology requires very little information about plant dynamics and is easy to tune. The complete methodology is evaluated on a developed VCM actuator to confirm the effectiveness of the proposed disturbance decoupling.

II. DESIGN AND ANALYSIS OF POSITION-VELOCITY

CONTROL

A precision motion controller drives a VCM quickly to reach the target position following a pre-defined position command and land gently on a delicate component with a controlled force to avoid damage to both the component

Disturbance Decoupling Control of Voice Coil Motors for Precise Automated Manufacturing Processes

Sung-Kuk Kim1, Jie Shi2, Young-Sun Lee2, Se-Hwan Kim2, Amir Parastar2, and Jul-Ki Seok2 1 AE�Control R&D Lab., LG Electronics Inc., Korea

2 Power Conversion Laboratory, YeungNam University, Korea

8th International Conference on Power Electronics - ECCE AsiaMay 30-June 3, 2011, The Shilla Jeju, Korea

978-1-61284-957-7/11/$26.00 ©2011 IEEE

[WeP1-012]

and the actuator [1]. With this combined position and force control, the desired pick-and-place or bonding processes can be achieved successfully. In this section, we address how to resolve the control requirement conflict between command tracking and disturbance rejection for precision position control.

Fig. 1. Schematic of VCM system for precise automated manufacturing

processes. Fig. 2(a) shows a diagram for a cascaded P-PI-type

position-velocity controller, where the position command *mmX is fed-forward to produce a part of the velocity

command *'mmV to improve the dynamic performance.

In this figure, mmX and mmV are the position and

velocity feedback, respectively. *mmV is the position

command feed-forward (CFF), *emF represents the force

command, ppK denotes the position control gain, and

spK and siK are the PI velocity control gain,

respectively. The argument (s) indicates that the analysis was done in the s-domain. The cascaded control scheme is advantageous because the bandwidth of each loop can be specified explicitly from the inner loop to the outer loop.

( )sX mm*

( )sX mm

( )sFem*

)(* sVmm

)(' sVmm

)(sVmm

(a) Cascaded P-PI-type position-velocity controller.

( )sX mm*

( )sX mm

( )ss

X mm*

( )ss

X mm

( )sFem*

)(* sVmm

)(sVmm

(b) SFB-style position-velocity controller.

Fig. 2. Block diagram of the position-velocity controller.

In contrast, Fig. 2(b) depicts the proposed SFB-style position-velocity controller, where isaK , saK , and ab

are the feedback gains of the integrated position, the position, and the velocity loop, respectively. Here, we add an integrated position state that has no any physical meaning. The most notable feature is that it is a simple parallel structure that is capable of accurate positioning without an integration action in the velocity control.

From Fig. 2, we obtain the force command of each controller as

( ) ( )

⋅+

⋅⋅++⋅=

dtXKK

XKKKVKtF

errsipp

errspppsierrspPIPem*

/_ (1a)

( )

⋅+

⋅+⋅=

dtXK

XKVbtF

errisa

errsaerraSFBem*

_ (1b)

where errX and errV are the position and velocity

errors, respectively. Although the SFB-style control structure may look unfamiliar to the reader, (1) provides interesting insights about its control behavior. If the control gains in (1a) are adjusted, two different types of controller can provide the same control output. This implies that both controllers can be designed to have exactly the same command tracking properties. Note, however, that the P-PI control output exhibits gain interaction between the position and velocity loop. In other words, errX for position control is directly

affected by the PI gains of the velocity controller. The coupling between controllers arises mainly from the cascaded configuration.

To obtain better insight into disturbance decoupling for position-velocity control, we describe our investigation using the metric “dynamic stiffness” (DS) [9]. The DS is defined as the ratio between the disturbance torque and the position ( mmd XT / ). Thus, the

DS is just a measure of the disturbance rejection for a mechanical system as a function of frequency. A larger DS indicates better disturbance rejection.

The DS and the position closed-loop transfer function of the P-PI type controller can be written as

( )( )

s

KK

KKKsKsMsX

sF

sipp

spppsisppmm

d

⋅+

⋅+++= )(2

(2a)

( )

( ) sippspppsispp

sippspppsisp

mm

mm

KKsKKKsKsM

KKsKKKsK

sX

sX

⋅+⋅+++

⋅+⋅++=

)(

)(23

2

*(2b)

where we consider the mechanical part as a first-order mass model, and pM represents the system’s mass. Fig.

3(a) shows the frequency response of (2a). At high frequencies, the DS is dominated by the mass, which means that any high-frequency disturbances are filtered out by a low-pass featured plant model. Low-frequency disturbance rejection depends on the product of ppK

and siK . This implies that the DS can be enhanced by

increasing the value of ppK and/or siK at low speeds.

However, as shown in Fig. 4, DS enhancement by adjusting ppK and/or siK is directly incorporated into

the bandwidth shift of (2b). This results in an unwanted change in system stability and tracking response because

ppK and/or siK appear as the coefficient of the s term

in the numerator of (2b). Hence, it is difficult to select a value of ppK or siK that simultaneously satisfies the

requirements for position control and disturbance rejection. Despite the design simplicity of cascaded subsystems, precise position control requires considerable time and effort to obtain an acceptable response, which may translate into drive system downtime and loss of productivity.

(a) P-PI-type position-velocity controller.

(b) SFB-style position-velocity controller.

Fig. 3. Dynamic stiffness of the position-velocity controller.

On the other hand, the DS and the position closed-loop transfer function of the SFB controller are computed as

( )( ) s

KKsbsM

sX

sF isasaap

mm

d +++= 2 . (3a)

( )

( ) isasaap

isasaa

mm

mm

KsKsbsM

KsKsb

sX

sX

+++

++=

23

2

*. (3b)

The low-frequency disturbance rejection capability is depicted in Fig. 3(b). The position control bandwidth is much less sensitive to adjustments to the low-frequency

gain, isaK, than that of the P-PI controller, as shown in

Fig. 4. Thus, this attractive feature provides a powerful tool for nearly independent design of disturbance suppression without changing the control law. As a consequence, we expect enhanced robustness to unmodeled dynamics at low frequencies. This benefit exists because each control state has its own control gain in the SFB-style controller.

Fig. 4. Bandwidth sensitivity to control gains.

III. DESIGN AND ANALYSIS OF DISTURBANCE ESTIMATOR

FOR FORCE CONTROL

Precise force control of VCM applications in contact with the environment is essential for satisfying strict force regulation specifications and avoiding component damage or contamination. Here, we advocate armature-current-sensing-based force control, since a force sensor is not reliable or economical in this application [6, 10]. Thus, accurate force control is precluded by the uncertainties resulting from the non-ideal force constant and current sensor as well as nonlinearly variable external disturbances. In particular, the force constant is significantly affected by heat delivered from contact with the control object.

Fig. 5 shows a block diagram of the force control strategy employing a closed-loop velocity observer. Here,

pL and pR represent the motor inductance and

resistance, respectively, and )(sE is the back-EMF

voltage. FK and FK̂ are the real and estimated force

constants, respectively. EK represents the back-EMF

constant and )(sH indicates the current sensor

dynamics. Because the current feedback )(sImea is fed-

forward to the observer as an estimated motor force

cffemF _ˆ , the disturbance )(sFd is estimated at the

output of the observer controller. The estimated

disturbance )(ˆ sFd is compensated for by the command

force in a feed-forward manner.

The closed-loop transfer function of the force controller can be obtained as

( )

( ) c

c

F

F

em

em

sHsK

K

sF

sF

ω⋅+

ω=

)(ˆ* (4)

where cω is a current control bandwidth that is

sufficiently higher than that of the position and velocity control. Note that, from (4), the force control accuracy is

directly influenced by the errors in TF̂ and )(sH ,

which are strongly dependent on temperature changes. Fig. 6 shows the frequency response of the control

accuracy as a function of TF̂ and )(sH .

This paper proposes a disturbance state filter based on the enhanced Luenberger-style observer for velocity estimation. The proposed state filter can estimate and compensate for force deviation resulting from

disturbances and uncertainties. Considering the force constant error as the uncertainty, the estimated disturbance is given by

( )

( )−

−

×+++

++=

)(ˆ

ˆˆ

23

2

sFK

KKsF

KsKsbsM

KsKsbsF

emF

FFd

isosoop

isosood

(5)

where isoK , soK , and ob represent the observer

gains, and pM̂ is the estimated mass used in the

observer. In VCM applications, the mass can be accurately estimated at the commissioning stage and does not change during operation. Equation (5) shows that the estimated disturbance consists of two components: 1) real external disturbances

pp RsL +

1

sM p

1

( )sH

s

1s

1

sM pˆ1

ob

soK

isoK

( )sFd

( )sFem( )sFem*

( )sFdˆ

( )sFdˆ−

( )sVmm

( )sVmm ( )sVmmˆ

( )sVmmˆ

( )sI * ( )sI

( )sE

FK̂

1

( )sImea

FK

FK̂

EK

cffemF _ˆ

scω

Fig. 5. Block diagram of the proposed disturbance estimation and compensation approach for force control.

()

()

ωω jF

jF emem *

()

()

[]°

∠ωω j

F

jF emem *

ˆ

ˆ

ˆ

( ) ( )sHsH 9.0=

( ) ( )sHsH 0.1=

( ) ( )sHsH 1.1=

(a) (b)

Fig. 6. Frequency response of force control. (a) force constant error. (b) current sensor gain errors.

and 2) uncertainties. Thus, the proposed state filter can be an effective tool for accurately estimating and compensating for disturbances while reducing computational complexity.

IV. EXPERIMENTAL RESULTS

The proposed algorithm was programmed and implemented on a developed VCM actuator system, as described in Table I. The armature current was sampled at 25 μs, and a 500-pulse-per-mm linear encoder was attached to measure the moving coil velocity, as shown in Fig. 7. A 10-W servo motor was installed to provide rotary motion to the shaft through a belt. The return spring disturbed the overall motion path considerably. The bandwidth of the position-velocity control is fixed at 100 rad/s, and a value of 50 Hz is selected for the poles of the state filter.

Fig. 7. Developed VCM actuator system.

The quality of the proposed SFB-style position-

velocity control was tested by observing the percentage root-mean-squared position error. With the standard P-PI-type control (Fig. 8), increasing the low-frequency gains of the DS is undesirable since it may cause system stability problems, depending on the mechanical system’s condition and the control bandwidth. In contrast, the position errors (Fig. 8) of the SFB controller can be significantly reduced by increasing isaK without

affecting the pre-designed control law. By employing the proposed controller, we could improve the positioning accuracy in the presence of unknown disturbances at low frequencies.

[ ]Hzf

[]

%_

rms

mm

XΔ

Fig. 8. Position control accuracy of P-PI and SFB controllers.

To test the effect of system uncertainties on force control without disturbance compensation, the force constant was intentionally changed to 50% of its nominal value, as shown in Fig. 9. The tests were performed for a 2 Hz sinusoidal force command. In this test, the actual force was assessed by the measured velocity because the force sensor was not mounted in the developed VCM system. Here, the return spring also provides an external disturbance that is a function of the position. The measured velocity response shows that the generated force has a distorted, fluctuating waveform. We conclude that feedback control alone is very vulnerable to the existence of disturbances and uncertainties.

TABLE I RATINGS AND KNOWN PARAMETERS OF DEVELOPED VCM

Rating and Parameter Value Unit

Rated voltage

Rated current

Nominal armature resistance

Nominal armature inductance

Force constant

Mass

12

2

12

0.3

7

0.4

V

A

Ω

mH

N/A

Kg

[ ]divsTime /5.2

FK9.0FK FK8.0 FK7.0 FK6.0 FK5.0

FK̂

[ ]divsmmvmm //50

[ ]divAimea /1.0

( )a

( )b

( )c

[ ]divsTime /5.2

FK9.0FK FK8.0 FK7.0 FK6.0 FK5.0

FK̂

[ ]divsmmvmm //50[ ]divsmmvmm //50

[ ]divAimea /1.0[ ]divAimea /1.0

( )a

( )b

( )c

Fig. 9. Force control performance without disturbance compensation. (a) force constant. (b) measured velocity. (c) controlled armature current.

[ ]divsTime /5.2

FK̂

( )a

( )b

( )c

FK9.0FK FK8.0 FK7.0 FK6.0 FK5.0

[ ]divsmmvmm //50

[ ]divAimea /1.0

[ ]divNFd /1.0ˆ

( )d

[ ]divsTime /5.2

FK̂

( )a

( )b

( )c

FK9.0FK FK8.0 FK7.0 FK6.0 FK5.0

[ ]divsmmvmm //50[ ]divsmmvmm //50

[ ]divAimea /1.0[ ]divAimea /1.0

[ ]divNFd /1.0ˆ

( )d

Fig. 10. Proposed force control with disturbance compensation. a) force constant. (b) measured velocity. (c) controlled armature current.

(d) estimated disturbance

Fig. 10 demonstrates the result of a test of the proposed disturbance decoupling force control. Although force constant errors and unknown disturbances exist in the control loop, little distortion and variation appear in the measured velocity. The bottom plot of Fig. 10 shows the estimated disturbance from the state filter, which causes the controlled current in Fig. 10 (c) to automatically adjust. Hence, the proposed algorithm anticipates disturbances and so yields well-behaved force responses compared to feedback control alone. This is considered a very significant performance improvement by manufacturers using precise automated processes.

V. CONCLUSIONS

A disturbance state filter for force control has been shown to provide a powerful tool capable of enhancing disturbance rejection in precisely controlled VCM systems. The proposed state filter was found to be very effective for decoupling unknown disturbances and uncertainties involved in the force control mode. This suggests an accurate disturbance decoupling methodology that does not sacrifice implementation simplicity. Although the analysis presented in this paper is limited to single-stage VCMs, the concepts and conclusions can be extended to control of multi-axis actuator applications.

ACKNOWLEDGMENT

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MEST) (2010-0029429).

REFERENCES

[1] SMAC Inc., 2010. [Online]. Available: http://www.smac-mca.com

[2] C. S. Liu, P. D. Lin, P. H. Lin, S. S. Ke, Y. H. Chang, and J. B. Horng, “Design and characterization of miniature auto-focusing voice coil motor actuator for cell phone camera applications”, IEEE Trans. Mag., vol. 45, pp. 155-159, Jan. 2009.

[3] Y. T. Liu, R. F. Fung, and C. C. Wang, “Application of the nonlinear, double-dynamic taguchi method to the precision positioning device using combined piezo-vcm actuator”, IEEE Trans. Ultrasonics, Ferroelectrics and Frequency Control, vol. 54, pp. 240-250, Feb. 2007.

[4] Y. D. Chen, C. C. Fuh, and P. C. Tung, “Application of voice coil motors in active dynamic vibration absorbers”, IEEE Trans. Mag., vol. 41, pp. 1149-1154, Mar. 2005.

[5] D. Jeon and M. Tomizuka, “Learning hybrid force and position control of robot manipulators”, IEEE Trans .Robot. Autom., vol. 9, no. 4, pp.423-431, Aug. 1993.

[6] S. Katsura, Y. Matsumoto, and K. Ohnishi, “Modeling of force sensing and validation of disturbance observer for force control”, IEEE Trans. Ind. Electron., vol. 54, no. 1, pp.530-538, Feb. 2007.

[7] Sigma II Series Servo System User’s Manual, Yaskawa Electric Amer. Inc., Waukegan, IL, 2000.

[8] J. K. Seok, K. T. Kim, and D. C. Lee, “Automatic mode switching of P/PI speed control for industry servo drives using on-line spectrum analysis of torque command”, IEEE Trans. Ind. Electron., vol. 54, no. 5, pp.2642-2647, Oct. 2007.

[9] P. B. Schmidt and R. D. Lorenz, “Design principles and implementation of acceleration feedback to improve performance of drives,” IEEE Trans. Ind. Appl., vol. 28, no. 3, pp. 594-599, May/June 1992.

[10] Y. Ohba, M. Sazawa, K. Ohishi, T. Asai, K. Majima, Y. Yoshizawa, and K. Kageyama, “Sensorless force control for injection molding machine using reaction torque observer considering torsion phenomenon”, IEEE Trans. Ind. Electron., vol. 56, no. 8, pp.2955-2960, Aug. 2009.