Modelling, Simulation and Control of an Offshore Load Transfer System Dimuthu Dharshana1, Jagath Srilal2, Subodha Tharangi3 1Department of Mechanical & Manufacturing Engineering, University of Ruhuna, Galle, Sri Lanka, 2Department of Engineering Sciences, University of Agder, Grimstad, Norway , 3Department of Electrical & Information Engineering, University of Ruhuna, Galle, Sri Lanka *
[email protected]
Abstract Load transfer cranes play a significant role when transporting pay loads in industrial applications. The research presents an accurate method to model and control a knuckle boom loader crane [1]. The crane is controlled along a given reference path. At first, a real HMF crane is simplified to a Dynamic Link Library (DLL) file using SimulationX software [1, 2]. Kinematic relationships of the crane are mathematically modelled to transfer reference inputs to controllable outputs through proper coordinate systems and geometrical dynamics. Subsequently, control architecture is developed using Labview software and simulated with a 3D Simulink crane model. Kinematics is implemented in Labview together with controllers [3]. Parameters of the controllers are numerically tuned to achieve the desired tool path. In the second stage, the control architecture is programmed using TIA portal software which is integrated with a Siemens Programmable Logic Controller (PLC). PLC is connected to a real time Labview PC via TCP/IP communication to run the DLL model and it is configured for three modes of operations as initialization mode, manual mode and automatic mode where it allows controlling the position and velocities of the actuators by operating analog inputs [4, 5]. Finally, the accuracy of the crane movement is verified comparing simulation results with real-time operation. Keywords: Control, Kinematics, Simulink, Labview, PLC
I. INTRODUCTION Load transfer systems are essentially used in offshore installation projects. Transportation of loads and passengers are more often executed through the vessels in oil gas or offshore wind energy systems. These loads and personnel are needed to be transferred safely by the cranes. The crane systems utilized in offshore have to compensate motions induced on the load caused by the sea, wind and other external disturbances. These induced motions take the form of heave (vertical motion) and pendulation of the load. It is important to keep the tool tip of the crane at a specified distance from the moving target. Therefore it is needed to have an improved system model and control design to address some of the main criteria such as automatic tool tip tracking, minimum reach to the target, manual controllability of the tool tip, etc. In this work, a dynamic model (DLL file) of an available HMF knuckle crane is used for the analysis [1]. The work is carried out to present an accurate technique to control the movement of the crane tool tip on XZ plane. Control system aims at maintaining the position of the tool tip within one meter by one meter square relative to an inertial frame of measurement. In the crane, actuation is provided by two swinging arms and a telescopic actuator. Hydraulic pistons are used to force these arms to move. II. MODELLING OF KNUCKLE BOOM LOADER The crane [FIG. I] is mathematically modelled to obtain Forward, Inverse and Jacobian kinematic relationships [3]. Forward kinematics is used to obtain the position of the
tool tip for given angular positions of the actuators. Inverse kinematics is used to map the angular position of the actuators (q2, q3) with tool tip position (Tx, Tz).
FIG. I Crane model, skeleton view and coordinate systems
=− + cos( + ⊿ ) + cos( + − ⊿ ) (1) = + sin( + ⊿ ) + sin( + − ⊿ ) (2)
Equations (1) and (2) describe the tool tip position in terms of joint angles. Inverse Jacobian is used to map velocities of the tool tip to angular velocities of the actuators. These equations are used to obtain Jacobian matrix [Equation (3)]. Tool tip position in x and z direction is differentiated with respect to the joint angles q2 and q3 to calculate the elements of the Jacobian matrix [Equation (4)].
=
=
=
(3)
=−
(
−⊿
+
) −
(⊿
+
) (4)
It is necessary to obtain the inversion of the Jacobian matrix [Equation (6)] in order to calculate the angular velocities of the actuator joints [Equation (5)] with respect to given velocities of the tool tip. A numerical Jacobian matrix is obtained by substituting provided values for constants , , , ⊿ and ⊿ . ̇
= ̇ =
used to configure DLL file with standard inputs and outputs [FIG. III].
̇
(5) ̇ − −
FIG. II Velocity components along the reference tool path
Inputs to the DLL model are configured as valve openings of the two hydraulic actuators. Outputs are configured as angular positions and angular velocities of the actuators and linear positions of the tool tip on the xz plane.
(6)
Inverse kinematics and inverse Jacobian play an important role by converting the reference positions and velocities of the desired tool path in to reference angular positions and angular velocities of two actuator joints. III. CONFIGURATION OF TOOL PATHS It is proposed to operate the tool path mainly in two segments. Firstly, the tool path is controlled in between current position of the tool tip and target point such that it reaches the target through the shortest possible path with a given velocity. Thereafter, tool tip travels along the given reference path. A boolean switch is implemented to switch the operation of the tool path between above segments. The reference values for tool tip position and velocities are fed to inverse Jacobian and inverse kinematics to calculate the inputs to the control loop. FIG. II overviews the velocities along the x and z directions with respect to each segments of the tool path to be followed. When boolean switch is true, tool point follows the desired reference path. The tool path is implemented in Matlab and imported to Labview project. IV. DEVELOPMENT AND SIMULATION OF CONTROL ARCHITECTURE IN LABVIEW The HMF crane is modelled in SimulationX software to obtain the dynamic model (DLL File). Labview software is
FIG. III Crane Model in Labview configured for respective inputs and outputs
V. CONTROL ARCHITECTURE FIG IV suggests implementing the control architecture with two Proportional (P) and Proportional-Integral (PI) controllers for controlling the tool tip position [3]. Position and the velocity of the tool tip are selected as reference inputs to the system. Length of the actuator 2 and 3 are given as the input reference to the P controllers and stroke velocities in hydraulic cylinders are given as the input reference to the PI controllers. System parameters are mapped with controller parameters using four function blocks which are described as Inverse Kinematics, Inverse
Jacobian, Actuator Kinematics 1 and Actuator Kinematics 2. Feedback loop is implemented by mapping outputs of the crane model with controller feedbacks through actuator kinematics.
programming, Labview interface is used to operate the DLL model of the crane. Initially, the communication between Labview, real time target and PLC are connected via TCP/IP communication [4]. A desktop PC is used as a Real time Target (RT) to run Labview simulations. The communication among Windows PC, PLC and Real time target was built up as shown in FIG VI. The Simulink model of the crane is run in windows PC with Labview and the control architecture is implemented in PLC.
FIG. VI Communication between Labview, PLC and real time target [Hardware-In-the-Loop(HIL) test]
FIG. IV Proposed control architecture
Block diagram of the control loop in FIG. IV is implemented in Labview in connection with the DLL model [FIG. V]. TABLE I shows the tuned controller parameters obtained through trail and error PID tuning techniques.
FIG. V Control loop with P,PI controllers in Labview TABLE II TUNED PARAMETERS OF THE CONTROLLERS Controller P_L2 P_L3 PI_L2Dot PI_L3Dot
Tuned values P I 50 0 50 0 0.05 0.001 0.05 0.001
VI. DEVELOPMENT AND SIMULATION OF CONTROL ARCHITECTURE IN STEP 7 TIA It is desired to control the physical crane by implementing the control architecture in a Programmable Logic Controller (PLC). A compatible soft tool; TIA Step7 is used to program Siemen’s ET200 PLC. For the initial
In the ET200S PLC, three digital switches and two analog switches are configured in order to obtain desired path by controlling the velocity of the tool tip. First analog switch is used to control the flow rate of hydraulic actuator 1 and the second is used to control the flow rate of actuator 2. The digital switches are used to switch the mode of operation as described in the section III. VII. TESTING WITH HMF CRANE Operation of the crane is demonstrated in three modes, point initializer mode, auto mode and manual mode. The crane is monitored by watching its movements. As the first step, point initializer, i.e point switch was enabled. Crane started to move from the default initial position for the given velocity of 0.05 ms-1. Gradually velocity was increased up to maximum value 0.1 ms-1 and it was observed that the crane was travelling at its shortest possible path to reach the starting point of the next cycle. To start the next tool path, auto switch was enabled. Consequently crane began its journey along the reference square tool path. By varying the analog input 1, velocity of the tool tip was changed. As long as the auto switch was kept enabled, crane repeated the square tool path. When the crane was at an arbitrary location auto switch was disabled and manual switch was enabled to start the manual operation. By varying the analog input 1 and analog input 2 it was able to control the movement in the xz plane. Finally, point switch was again enabled in order to get the tool tip in to initial location through the shortest path. All three modes were working at a successful level with minimum deviations. VIII.
RESULTS
Lab view control with crane DLL model FIG VIII presents the reference tool path and controlled tool path by Labview control system implemented for the DLL model.
for this deviation. Dynamic model is given quick responses for input valves which may drive the plant to easily unstable.
FIG VII HMF Crane is in operation with PLC, Mechatronics Laboratory, University of Agder, Norway
FIG XIII Actual tool path obtained through HMF crane
FIG VIII Reference & desired tool path in Labview control system
FIG. IX, X and FIG XI, XII reveal how process variables change with reference actuator lengths and reference actuator velocities respectively. Highlighted area presents how the process variables follow the reference paths when square tool path is executed. It becomes quite evident that process variables almost overlap with the set point assuring insignificant error.
FIG IX Performance of P
Fig X Performance of P controller
controller in L2
in L3
Modelling of real crane involves complex derivations in order to implement more accurate control system, which is neglected here. Since parameters of the controllers are tuned to a simpler model than the real plant, deviations are obviously expected. Also the modelled dynamic system is not a linear one and, linearized control system design is applied, which could affect the accuracy of the results. In HIL test dedicated hardware is used to run the controllers and DLL model [5]. Hence the deviation is minimized comparing with Labview control system. It is concluded that the HIL test shows more accurate results compared to Labview control system. Real-time experimental result in FIG. XIII reveals that, deviation error lies in +/-3 cm range with an offset of 35cm of the reference path along X direction. This could be overcome by modifying the applied coordinate references for actuator joint 1. The fluctuation error is almost negligible as it is less than 1 cm. It is witnessed that the real crane test shows more successful reference tracking compared to Labview and HIL tests. ACKNOWLEDGEMENT The author would like to thank Mechatronics Innovation Laboratory, Faculty of Engineering and Science, Univeristy of Agder, Grimstad, Norway for providing necessary software and hardware facilities to conduct the research. REFERENCES
FIG XI Performance of PI
FIG XII Performance of PI
controller in L2
controller in L3
PLC control system with real crane FIG. XIII reveals the actual tool path obtained from HMF crane controlled by PLC. The crane was operated with the maximum velocity 0.1 ms-1. IX. CONLUSION Results in section VIII reveals that control system with DLL model in Labview shows a deviation of +/-5 to 10 cm from the reference tool path. There could be many reasons
[1]
[2]
[3]
[4] [5]
HMF Knuckle Boom Loader 1420-K, (2014, June 29). Retrieved from Http://Www.Wtsnsw.Com/Pdf/Handycranes.Pdf. 1st ed. 2017. Print ESI ITI GmbH, Dresden (2015), Germany User Manual SimulationX. Retrieved from http://www.tu.kielce.pl/~rokach/instr/mud/UserManual.pdf. Ang, Kiam Heong, Gregory Chong, and Yun Li. "PID control system analysis, design, and technology." IEEE transactions on control systems technology 13.4 (2005): 559-576. D. Reynders & E. Wright (2003), “Practical TCP/IP and Ethernet Networking”, Boston, USA, Newnes. Grega, Wojciech. "Hardware-in-the-loop simulation and its application in control education." Frontiers in Education Conference, 1999. FIE'99. 29th Annual. Vol. 2. IEEE, 1999.
