POSCO YARD CRANE AUTOMATION

Sangchul Won ∗, Sang-un Kim∗, Seung-Gap Choi ∗∗

and Chintae Choi ∗∗∗

∗Department of Electrical Engineering, Pohang Universityof Science and Technology, Pohang, Korea

∗∗ Technical Research Labotory, POSCO, Pohang, Korea∗∗∗Department of Mechanical and Electrical Engineering,

RIST, Pohang, Korea

Abstract: This paper describes an integrated approach for crane automation atthe Kwangyang steel works, POSCO. Unmanned cranes are composed of severaltechnologies,which include anti-sway control, precision position control, optimaltrajectory computation, and coil shape recognition. Crane position while travelingand the traverse axis are controlled by PID position controllers. In order to preventswaying during crane operation, the sway angle is consistently suppressed from thestart point to the destination using an anti-sway algorithm. For optimal trajectorycontrol, 3-axis motion was analyzed and variable speed drives were used. A 3Dobject recognition system for picking up coils, based on stereo vision, is in progress.Some of the described control strategies have been successfully applied to the 10-1crane in the No. 4 CGL (Continuous Galvanizing Line) of the Kwangyang steelworks, POSCO. Substantial cost reduction and improved productivity are expectedbenefits of crane yard automation. Copyright c©2005 IFAC

Keywords: Crane automation, Position control, Anti-sway control, Recognition

1. INTRODUCTION

Cranes compose a diverse group of machines thatnot only lift heavy objects but also shift themhorizontally. Cranes have come into their presentwidespread application since the introduction ofsteam engines, internal-combustion engines, andelectric motors, beginning in the 19th century.

In an effort to improve the efficiency of the overalloperation of plants, POSCO, a major Korean steelproducer, recognized the following problems inthe coil yard operation which required immediateattention: high labor cost - approximately 500crane operators were on staff in the coil yard, highmaintenance costs - unskilled substitute operatorsdamaged cranes by rough usage during frequentcrane operator strikes. In order to solve the prob-

lem POSCO’s top management considered the fullautomation of existing yard cranes.

For decades much research has focused on over-head cranes automation, but only a few successfulresults has been reported. Integrated crane controlsystems designed by well known engineering com-panies are still expensive and are not satisfactoryin the view of maintenance and reliability. Tothis end, a more appropriate control system fitto requirements of various cranes at POSCO wasdesigned and applied to a rolling plant which hasbeen successfully operated for 1 year. The newsystem has better rope anti-sway and positioncontrol capabilities.

POSCO is currently, undertaking automation of

coil yards at the hot rolling plants and cold rollingplants at Kwangyang, using newly developed tech-nologies. Up to now, 4 cranes have been auto-mated, while the remainder are awaiting upgradesduring the next regular maintenance period.

The project scope includes mechanical refurbish-ment and complete electrical retrofits of eachcrane, as well as the addition of a new coil track-ing and inventory system. The crane retrofits in-clude conversion variable speed AC drives, PLCcontrollers and wireless network communicationsystems. Each crane was also equipped with laser-based distance meters for actual absolute positionmeasurement.

Positions of the traveling and traverse axes arecontrolled by PID position controllers. The con-troller was designed in the continuous time do-main by using a loop-shaping method which wasthen converted to a discrete form for computercode generation by z-transform. Coil-handlingcranes have long rope and short sheave distances,and therefore rope sway occurs easily. A Longsway period introduced by the long rope makeslong sway decay time and un-manned operationdifficult. Sway of the rope is suppressed by ananti-sway control algorithm. The sway angle ofthe rope is measured by a sway angle sensor whichmechanically touches the rope and is consistentlysuppressed from the start point to the destina-tion by PD control law. The control frequency ofthe overall controller, which is comprised of theposition and the anti-sway controller, is 25Hz onaccount of the dynamics of moving axes. Somealgorithms required for coil yard operations, whichalso main control algorithms, such as referenceposition generation, position control and anti-sway control, have been designed and fully testedon the new crane simulator. The newly designedcrane control system has shown satisfactory per-formance on position control accuracy and theanti-sway of rope. The maximum positional erroris 30mm and the maximum sway error is 0.1degrees.

A skilled human operator has intimate knowledgeof the process at hand, and a performs givenjobs most efficiently to meet various operationalgoals under various circumstances. Therefore, theautomated system should also perform given jobsin minimum time for productivity. For this reason,special attention has been given to the optimiza-tion of the crane movement required to carryout each type of work instruction, to facilitateshort crane cycle time. Simultaneous movementson traveling, traverse and hoist axes have beenrealized over the collision-free height to reducecycle time. The proposed control strategies havebeen successfully applied to the 10-1 crane in

the No. 4 CGL of at POSCO’s Kwangyang SteelWorks.

2. OUTLINE OF UNMANNED CRANE

Prior to this project, cranes were operated manu-ally. The crane job supervisor accessed the Level3 yard planning system through a terminal com-puter at the central pulpit, and work instructionsfor crane movements were transferred between thesupervisors in the pulpit and the crane operatorsvia telecommunication. The new automated cranesystem performs the above job by itself, without ahuman supervisor. The major features of the newautomation system include:

• Unmanned Crane Operation - Each crane ex-ecutes work instructions, which are generatedeither automatically by the Level 3 enterprisesystem or manually by the operator in thecentral pulpit.

• Remote Crane Operation - In order to pre-pare exceptional work conditions, any motionfor a selected crane can be made directly bythe operator from any of two remote opera-tion stations located in the central pulpit.

• Automatic Slab Tracking - All slab move-ments are traced and stored in a centraldatabase.

• Variable Speed Drives - Improved crane per-formance and control, and a reduction inmechanical damage.

• Precise Position Control - Feedback-basedposition control achieves precise positioningat the goal position and reduces surface dam-age of a coil when it is placed on the skid.

• Anti-Sway Control - Consistent suppressionof rope sway by feedback control during cranemovement fully satisfies sway bound at thegoal position.

• Integrated Crane and Conveyor Control -Conveyor motion is interlocked with cranemotion to enhance safety and reduce equip-ment damage.

• Modern Diagnostic System - Based on thelatest Human Machine Interface (HMI) tech-nology.

• Coil shape recognition system - Based onstereo vision technology and an object recog-nition algorithm.

The crane system consists of the main controlcomputer in the pulpit and a Programmable LogicController(PLC) on the crane. The data com-munication between the main control computerat ground and the programmable logic controlleris done by wireless LAN. Figure 1 shows theoverview of the unmanned crane. The main con-trol computer sends coil move commands andreceives crane status information. The PLC gen-

Fig. 1. Overview of the unmanned crane.

erates moving trajectories and performs real-timecontrol of crane positions and rope sways, andreports crane status to the main control computer.The main control computer determines which coilto move and positions to pick up and place thecoil. Whenever a coil transfer command is gen-erated, the computer sends coil transfer positiondata and data related to the coil itself, such asouter diameter, width, weight and so on. Thiscrane control system allows operators to interfereautomated process and can pause and resumecrane movement at any time during operations.

Figure 2 shows the location of sensors for positionand velocity control, anti-sway and crane safety.

Fig. 2. Sensor locations.

(1) Obstacle sensor - to detect obstacles underthe crane during lift down

(2) Coil hole sensor - to determine whether shoesare correctly positioned at the center of thecoil hole

(3) Lifter load sensor - to determine whethercoils are lifted off normally

(4) Coil tactile sensor - to determine whether thelifter arm grips the coil properly

(5) Lifter rotation sensor - to detect rotation ofthe lifter (90, 180, 270 degrees)

(6) Rotation angle sensor - to measure the rota-tion angle of the lifter (for acceleration anddeceleration)

(7) Shoe In/Out sensor - to determine whethershoes are in or out

(8) Rotation limit switch - to detect the limit oflifter rotation

(9) Lifter arm sensor - to detect the opening ofthe lifter arm

(10) Lifter arm limit switch - to determine themaximum and minimum of lifter arm open-ing

(11) Coil top sensor - to determine whether thecoil is positioned correctly right under thelifter

(12) Coil center sensor - to determine whether thelifter is at the center of the coil.

3. AUTOMATION TECHNOLOGIES

Figure 3 shows a flow chart of the unmanned craneprocess. A new control algorithm was developedand applied to the position control, trajectorygenerator and coil shape recognition of the sys-tem. The control algorithm is composed of 4 parts;

Fig. 3. Flow chart of unmanned crane process.

1) position and anti-sway controllers, 2) velocityconstraints attendant on the working area, 3) asimultaneous 3-axis motion process, and 4) a coilshape recognition system.

3.1 Design of Position and Anti-sway Controllers

Figure 4 shows an overall block diagram of the po-sition and anti-sway control system. It is assumedthat the transfer functions of the dynamic modelof position control system on the traveling andtraversing axes are 2nd-order systems. The trans-fer function on the traveling axis are modelled asfollows:

Gm(s) =0.24

s(0.5s + 1)(1)

Fig. 4. Overall block diagram of position and anti-sway control.

The open-loop Bode plot for G(s) is shown in Fig.5. The roll-off rate at the cross-over frequency is -20 dB/dec. But if a large proportional gain is usedin the feedback controller, the loop shape goes up,and the roll-off rate in the cross-over frequencywill be -40 dB/dec. Positions of the traveling andtraverse axes are controlled by PID position con-trollers. The controller was designed in the con-tinuous time domain using a loop-shaping methodand converted to the discrete form for computer

Fig. 5. Bode plot of the trolley dynamics(weighted open loop).

code generation by z-transform. So insertion oftwo finite zeros near the cross-over frequency andan integrator guarantees that the target loop willhave -20 dB/dec. The shaped plant is obtained byinserting a loop compensator, where -0.4 and -0.5are assigned to T1 and T2, respectively. Anotherpole is introduced to satisfy properness of thetransfer function. The kp was set at 100 to theposition error sufficiently attenuate. A feedbackcontrol system with a designed compensator gavea good transient response. It also showed that thehigher roll-off rate in the higher-frequency regiongives robustness to measurement noise.

As shown in Fig. 4 the transfer function of swaydynamics Gs(s) where the input is a trolley po-sition and the output is sway angle, has two un-damped poles and two zeros at the origin.

Θ(s)X(s)

= Gs(s) =−s2

ls2 + g(2)

The zeros near the origin dominate plant dynam-ics and undamped poles make rope sway decayvery difficult. Rope sways in the traveling direc-

tion and the traverse direction is suppressed byPD control laws. The position controller and the

Fig. 6. Bode plot of the sway dynamics.

anti-sway controller designed in the continuousdomain is transformed to a discrete-time domaincontroller through bilinear transformation. Thealgorithm was written in PASCAL language foractual control in PLC, and executed every 0.04sec.

3.2 3-axis simultaneous motion of the crane

Typical functions of the POSCO yard crane con-sist of a sequence of motions such as verticalhoisting, traversing, traveling, traversing and ver-tical dropping. Skilled crane operators performtwo motions at the same time to reduce the cycletime. However the speed of each motion dependson the level of skill. The new crane control systemgenerates an optimal trajectory in the safety zonefor each job and performs 3-axis motions simulta-neously to minimize cycle times. The safety yardheight (h1) is set by considering the height ofthe largest coil or instruments and the safety coilheight (h2) is set by computing the half outer ra-dius of coil carried by lifter. Then the safety zoneheight (h3) where crane travels, the traverse is setat h3 = h1 + h2. The start-winding distance(d) is500mm from the traveling axis, and 300mm fromthe traverse axis.

Fig. 7. 3-axis linked movement process.

3.3 Working area velocity constraints

The crane control system divided the working areaof the POSCO yard into two categories. One is”normal area” or ”unsafe area” where only coilsare stored and the other is the unsafe area wheretrucks or workers move around. Figure 8 showsthe working area of the 4 CGL yard. Dependingon the area, the control system generates a cranetrajectory which reduces speed when the cranemoves into crowded unsafe areas. Typical highspeed in a normal area is 108mpm, and theaverage low speed in a unsafe area is 36mpm.

Fig. 8. Working area of the 4 CGL yard.

3.4 Coil shape recognition system

Image based vision processing is effective in recog-nizing important geometric features of an objectand leads to accurate estimation of the object’sposition/orientation required for pickup opera-tions by a crane. In order to recognize the coilshape and to compute the position and orientationof the coil, a 3D disparity map was establishedusing stereo images. The 3D vision system is im-plemented on FPGA chips generating disparityvalues from stereo camera images at high speed.The system can measure the 3D features of a coilsuch as position, orientation, width and radiusfor unmanned cranes. This system consists of faststereo vision and a 3D object recognition algo-rithm. The fast stereo vision system accepts theleft and right images from the stereo cameras andgenerates disparity images. A disparity image canbe converted into the range image that contains3D information. The 3D object recognition algo-rithm is based on 3D planar surface extraction bysegment based stereo vision using range imagesand cylinder fitting technique.

Stereo vision as shown in Fig. 9 builds a 3Ddescription of a scene observed from two or moreviewpoints. Once disparity values between twoimages are found, depth was obtained using thetriangulation principle. The disparity is the dif-ference between the corresponding points on bothstereo images, which are two projected points ofthe same world point on both cameras. For fast

Fig. 9. Stereo vision geometry.

processing, a trellis-based stereo matching methodis implemented on a FPGA chip. Since the stereomatching algorithm has a systolic array struc-ture, it is well suited to parallel processing andis easy to be implemented. Moreover, this schemeenables connection of several chips for increasedperformance. The current system uses two FPGAchips and handles two stereo 1300×640 imagesto generate the disparity image. The two FPGAchips have proceed a pair of 1300×640 images at30 frames per second. However, the real speed ofthe vision system is about 7 frames per second dueto PCI bus band-width limit. Fig. 10 and Fig. 11shows each camera image and the disparity image.

Fig. 10. Stereo image in steel coil yard.

4. CONCLUSION

This paper presented the POSCO unmannedcrane project. The new crane control system iscomposed of several technologies, which includeanti-sway control, precision position control, opti-mal trajectory computation, and coil shape recog-nition. The newly developed crane control system

Fig. 11. Disparity image generated from stereoimages.

Fig. 12. Segmented surfaces and recognized ob-ject.

has been applied at the Kwangyang steel works,POSCO. The unmanned crane has been operatedfor 24 hours a day. Moreover, several remote-controlled cranes have been operated successfullyby only one operator. Through crane automation,labor costs have been substantially reduced andproductivity has been increased.

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