CON USING FIELDBUS IN REAL-TIME CONTROL SYSTEMS FOR ROBOTICS APLLICATIONS

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1 V CONGRESSO NACIONAL DE ENGENHARIA MECÂNICA V NATIONAL CONGRESS OF MECHANICAL ENGINEERING 25 a 28 de agosto de 2008 Salvador Bahia - Brasil August 25 28, Salvador Bahia Brazil CON USING FIELDBUS IN REAL-TIME CONTROL SYSTEMS FOR ROBOTICS APLLICATIONS André Luis Dias, diasdre@yahoo.com.br 1 Leonardo Marquez Pedro, lmpedro@sc.usp.br 1 Glauco Augusto de Paula Caurin, gcaurin@sc.usp.br 1 1 University of São Paulo, Av. Trabalhador São-carlense, 400, São Carlos, São Paulo, Brazil Abstract: The purpose of this work is to study fieldbuses used in industries, and by the implementation of a real-time control system, analyse the impact of using a fieldbus in its closed loop. The main problem of it, are the network delays that may affect the performance of the system. The methodology used was applied in a DC motor position control, widely used in robotic joints, comparing the closed loop using analog signals (traditional) with a fieldbus network (tendency). This work used a CAN-based network. The experiments were conducted with different reference inputs, and the system output behavior was analysed. The research showed that CAN is a good option for this kind of system, especially because it s free and many components on the market already have an embedded CAN module. The conclusion of the research assures that a CAN-based network could be used in real-time controls systems for robotics applications, allowing some advantages like, the cabling reduction, noises immunity and facility of installations. Keywordse: fieldbus, CAN, real-time, control systems. 1. INTRODUCTION Currently, the major part of sequential and real-time control systems is based on the direct feedback through electrical signals (0-10volts or 4-20mA) between sensors, actuators and controllers. The new technological trend points the use of fieldbus network as an alternative solution. Many advantages like cabling reduction, better distribution of the control systems and noises immunity explain this change. This project shows a comparison between the performance of a solution based on electrical signals and another one based on a fieldbus network to perform the real-time closed loop control, commonly used in robotics applications. To obtain data for analysis, an experimental environment containing the controller and interface boards were implemented. Additionally a fieldbus network was created adopting a CAN protocol. Through the integration of these components with a real-time simulation platform, data could be collected for analysis of the impact of the networks delays in real-time controls systems. These network delays are inherent problems in fieldbus communications and they may affect significantly the system performance. This problem occurs because the controller should execute the following tasks: read the sensor measurements through the network, calculate the control signal, and finally send the control signal to the set of actuators back through the network. The time delay between data transmission depends on the network characteristics like the topology and routing schemes. The problems severity increases when data losses occurs during a network transmission. The control design techniques, should take the delays into account, allowing the network-based control systems to maintain the pre-established performance requirements. Several methods have been formulated based on multiple types of network behaviors and configurations in conjunction with several ways to treat the delay problems in network-based control systems (CHOW, 2001). The analysis of the networks delays influence in the control systems will contribute directly in the system performance improvement, reducing costing and making it more flexible. The second session of the work shows the research description, including fieldbus basic concepts, especially the CAN protocol, and materials and methods used. At the third session the results obtained are shown. 2. WORK S DESCRIPTION 2.1. Fieldbuses history review In the second half of the 1980 s two areas of fieldbus were presenting good results, FIP in France and PROFIBUS in Germany, both with national standards and suggestions for international standardization through IEC (International

2 Electrotechnical Commission). But the protocols differences were significant: PROFIBUS were based in distributed system and support object-oriented communication in terms of the client-server model of the MAP/MMS specification. At the other side, FIP had developed with central control, but could be used in real-time control systems. So, they had not become standardized, because a universal fieldbus should combine the benefits of both protocols. These technologies had developed, as an extension of FIP, to become the WorldFIP, the functionality of the clientserver model was added. On the other side, the ISP (Interoperable System Project) attempted to demonstrate how PROFIBUS could be enhanced with the publisher-subscriber communication model. The ISP was abandoned in 1994 before reaching a mature state due to strategic reasons. Until the first half of 90 s, IEC was not able to show any relevant results, except the definition of the physical layer through IEC in In 1995, after long years of efforts between German and French experts to combine the FIP and PROFIBUS approaches, several mainly American companies decided to no longer watch the endless discussions. With the end of the ISP project, they began the definition of a new fieldbus optimized for the process industry: the Foundation Fieldbus (FF). Since IEC do not found an international acceptable fieldbus standard, Europeans invested in the elaboration of protocols and devices, so they created CENELEC, and finally all the national standards were considered European standards. The standards were divided according to their main application areas. In the later phases of the European standardization process, the British National Committee submitted also FF, DeviceNet, and ControlNet for inclusion in the European standards (FELSER, 2002). Finally, in 2000 the IEC standard was created, simply including all fieldbus systems Fieldbus basics Fieldbus is used at the lowest level industrial network in computer communication hierarchy of factory automation and process control systems. (PARK, 2002) In industrial network communication systems, fieldbus is especially used to interconnect field devices, like process controllers (DCS and PLC), sensors, actuators, IHM s and others (TOVAR, 1999 and THOMESSE, 2005). Fieldbus created the possibility to substitute digital interfaces like RS-232 and RS-422 or electrical signals like the standard analog signal 4-20mA/0-10 volts, and for digital signals 0-24V, that comes from sensors and were sent to actuators through a bus that connect all equipments. PARK (2002) e INBERG (2001) showed in those works the main advantages of using a fieldbus: Cabling reduction, that means lower space occupied and installations costs reduction. Before the fieldbus, two wire were necessary to connect a analog or digital signal, and a wire for each bit of a binary number; Less susceptibility to noises interferences, so sensors and actuators could stay far from the main control system. Especially in analog signals, where the distance may cause signal distortion, so the system receive inexact answers; More functionality from intelligent field devices; Reduction of central computing, improving the system performance and reliability. Each node has its own controller that compute the decisions with its own local variables; Greater network modularity simplifying its expansion; User friendly installation and maintenance. In the specific case of real-time applications the main problem of this network type are the network delays during data transmission. CHOW (2001) suggested three kinds of delays: Sensor-to-controller delay: when a sensor transmits a measurement to a controller, the measured signal should be transformed into data, then transmitted to the controller that, finally receives the information. Computational delay: is the time required by a controller to compute a control signal based on the received measurement. Controller-to-actuator delay: this delay occurs when a controller sends a control signal to an actuator through the bus. So, the data should be transformed into electrical signals compatible with actuator input requirements. The networks errors, like data loss in a transmission, could affect the network delays sensor-to-controller and controller-to-actuator. In addition, is important to know that all the kinds of delays could happen simultaneously, and because of this the system could be corrupted CAN (Controller Area Network) The Controller Area Network (CAN) is a serial communication protocol which efficiently supports real-time control with a very high security level (BOSCH, 1991). It is an International Standardization Organization (ISO) defined in ISO (CAN, 2005) This protocol was originally developed for automotive industry substituting the cabling complexity for a two wire bus. Due to its characteristics, it became popular and used for a great variety of sectors like, marine, medical, manufacturing (production lines) and aerospace (CORRIGAN, 2002).

3 The physical layer uses the Non-Return-to-Zero method (NRZ) for bit encoding, i.e. when the network sends a logic zero, the bus keeps a dominant bit, and when it sends a logic one, the bus keeps a recessive bit. When it is necessary to send several signals with the same logic levels, a technique called Bit Stuffing is used to avoid errors. This technique inserts automatically an opposite bit after 5 repeated bits. The most used physical media is the twisted-pair with differential signals as common return. The connection between the CAN controller and the physical media are done through a CAN transceiver according to the physical layer standards. The transceiver consists of a sender and an amplified receptor, it also protects the controller against overload, reduces the electromagnetic radiation, etc. For the data link layer, the media access control is the CSMA/CD +AMP (carrier-sense multiple-access with collision detection and arbitration). It means that each bus node has to wait until the bus became idle before try to send a message. Data collisions are treated through a priority system pre-programmed in the message identifier. The message with high priority wins the bus access (CORRIGAN, 2002). The types of frames used in CAN protocol are (a) Data frame, that carries data from the sender to the receptors. (b) Remote frame, that are transmitted from a bus node asking a Data frame transmission with the same identifier; (c) Error frame transmitted for any node that detect a fault in the bus; and finally the (d) Overload frame, used to generate a delay between Data or Remote previous frame and the successor frame. At the application layer there are many implemented forms for a CAN network according to the necessities for each sector or group, and they varies according to the strategy adopted to attend an application (YABARRENA, 2006). Some standards in the market are: CAL (CAN Application Layer), CANopen, DeviceNet, SDS (Smart Distribution Systems), SAE939, DIN 9684 and ISO Node A Node B Node C Node D Transceiver Transceiver Transceiver Transceiver CanH CanL Figure 1. Basic structure of a CAN based network For further information about CAN protocol, see BOSCH, 1991 and DIAS, Materials used In this work, an old VME bus based computer platform running a MVME162 controller board was used, it is suitable for monitoring and real time embedded control applications. The hardware platform has additionally Industry Packs (IP) for electronical I/O interfacing purposes. Each IP has a memory space for individual usage (IP memory space), a space for access of identification registers inside the IP, and a space for access of operational registers, called input/output space. Two industry packs were used, one for analog outputs and another one for analog inputs. The VxWorks 5.5 was adopted as the real-time operating system. VxWorks 1 is a multitask asynchronous real-time operational system. This operational system supports POSIX, operational system standard based on Unix, created by IEEE. It includes a group of tools for the host (development computer), for the target (target computer), and communication options (serial and Ethernet). To perform editing, compiling and debugging tasks the Tornado Integrated Development Environment - IDE (TORNADO, 1996) was used. Figure 2. MVME Plataform equipped with Industry Packs 1 VxWorks is a real-time operating system sold by Wind River Systems of Alameda, California, USA.

4 The next section shows how this structure was used for data acquisition purposes Data acquisition procedure For the data acquisition purposes, one controller and two CAN interfaces, for field devices communication, were implemented. The plant was simulated using the embedded platform, previously described. Simulink and Real-Time Workshop were also used to generate the simulation code. Controller DSP / Interface board R H PLANT C Sensor B VME / Simulink / RTW Figure 3. Basic structure of the experimental approach As an example for testing purposes a software based position control of an motor axis was adopted. The controlled plant consists of a 20 W DC motor, driven by a Linear Amplifier. The corresponding model and transfer functions are base on (MARQUES, 2005). The discrete sample time was 4ms, the same period is also used for the system controller. Figure 4. Simulink diagram schematics for the analysis method The block S-Funcion 1 and S-Function 2 were programmed in C, and they are responsible for sending signals from the simulated plant to the interfaces boards through the IPs. S-function 1 sends the reference signals and receives the control signals from the controller. S-Function 2 sends the feedback signal, closing the control loop. A PID control was implemented and its parameters defined using the Ziegler-Nichols method, details can be found in DIAS, The experiments compared a real-time control system based on a fieldbus communication and another one without it. Figure 5 and 6 shows the structure for different reference inputs. Texas board1 is responsible for the plant control system, so, it is the system controller. Texas board 2 is responsible for CAN interface within field devices, receiving analog signals from de Industrial PC, transforming them into data, and sending back to the controller, and vice-versa. Both boards are based on TMS320F2812 DSP from Texas Instruments embedded in ezdsp F2812 board, that have a CAN module. At the Interface board there are devices that are responsible for the CAN network implementation, like the transceivers (SN65HVD230), board security (optocouplers), signal processing, with low band filters and operational amplifiers and, in additional a RS232 was implemented for errors verification. On the VME platform (Industrial PC) the plant was simulated with the help of MATLAB, Simulink and Real-Time Workshop, sending signals through the IPs. For system monitoring the Ethernet network was used, so that graphical answers of the system could be generated analyzed on an conventional host PC. With these data, networks delays could be observed, reaching the work s target.

5 Texas Board 1 (TMS320F281 Interface board Electrical signals IP220.. IP320 VME (Industrial PC) MATLAB / Simulink (PC) ETHERNET Bus Figure 5. Control system without fieldbus, closed loop with electrical signals (traditional) Experiment 1 Texas Board 1 (TMS320F281 2) Terminator Interface board CAN bus Texas Board 2 (TMS320F281 2) Interface board Terminator Electrical signals IP220 IP320 VME (Industrial PC) MATLAB / Simulink (PC) ETHERNET bus Figure 6. Control system with CAN fieldbus (Tendency) Experiment 2 The complete analysis method ambient is shown in figure 7.

6 Industrial PC CAN node 2 Programmer of CAN node 1 CAN node 1 Data acquisition and programmer of CAN node 2 3. RESULTS Figure 7. Analysis method ambient The experiments were repeated for different reference inputs, the results are shown in graphics in the next pages. The transmission rate of CAN network used in the experiments was 1Mbps, with two nodes in the bus. To obtain a higher traffic in the bus, data frames had been configured for transmission of 8 bytes of data, while only 12 bits really were important, they were the only who carries the information of the motor position. The first experiment had been done using a step input, with amplitude of 2π radians, simulating a complete rotation for the motor axis. At this experiment the setting time and the capacity of stability of the control system was observed. The figure 8 shown the result. Figure 8. Comparison between closed loop with electrical signals and CAN for a step input The graphic shows that electrical signals and CAN produced that are very close, the system output had the similar behavior, in the transient and constant steady state. Analyzing the settling time, it seems that using CAN the time was 8ms slower, than using electrical signals. But this value could be accepted because the sample time was 4 ms. With the objective of seeing how the system could follow a reference signal, a square wave signal was used, with 1 Hz of frequency and 5 radians of amplitude. The result is shown in figure 9.

7 Figure 9. Comparison between closed loop with electrical signals and CAN for a square wave input reference Like in the previous experiment, could be noted that the output of the control system had the same behavior, showing that CAN could have a good performance in real-time control system. The setting time using CAN kept an average of 4 ms slower then using electrical signals, a acceptable result. For a sinus input, a frequency of 2 Hz and amplitude of 2 radians was used. The obtained results are shown in figure 10. Figure 10. Comparison between closed loop with electrical signals and CAN for a sinus input reference To increase the task requirements, moving it to a more critical behavior, another experiment using a sinus input reference had been conducted. Now the frequency was double the previous experiment, 4Hz with the same amplitude. The result is shown in figure 11. Figure 11. Comparison between closed loop with electrical signals and CAN for a sinus input reference (4 Hz) Note that the outputs had the same behavior even with the increase of frequency. The delay average between CAN and electrical signals was approximately 4ms that could be acceptable because the delay between the reference and the output was approximately 50ms. For the last experiment, a triangular input with the amplitude of 2π radians and frequency of 2,5Hz was used. Figure 12 shows the result of this experiment. Like in others experiments, the outputs were similar, showing the great performance of CAN protocol. The average time delay between CAN and electrical signals was approximately 4ms, while the output delay between system reference and output was 50ms.

8 Figure 12. Comparison between closed loop with electrical signals and CAN for a triangular input. 4. CONCLUSION The control systems trend to implement fieldbus communication interconnecting controllers, sensors, and actuators was analyzed in this paper. This kind of network can be found in a large number of application areas, like robotics (the focus of this work), automobile industry, medical equipment, safety, aerospace, etc. For these reasons the study of fieldbus in real-time control systems could be used to increase the number of applications. Based on the outputs analysis of the control systems for a step, square wave, sinus and triangular inputs, it is possible to conclude that the CAN protocol could be used in real-time control systems for robotics applications. The network delays inherent of fieldbuses could be verified through experimental tests, and they were approximately 4ms in relation of electrical signals, while the sample time used was equal, 4 ms. A robot trajectory planner compute new references each 40 or 50 ms, so the networks delays could be considered acceptable for this kind of system. 4. ACKNOWLEGMENT The authors would like to thank FAPESP and CNPq for the financial support, and also Jorge Felix Herrera and Jean Mimar Santa Cruz Yabarrena for the technical support. 5. REFERENCES BOSCH, R. (1991). CAN Specification Version 2.0, Sttutgart. BUTTAZZO, G.C. (1997). Hard Real-Time Computing System: Predictable Scheduling Algorithms and Application, Ed. Kluwer Academics Publisher. CAN in Automation (CiA), URL: acessado em 10 de agosto de CHOW, M.; TIPSUWAN, Y. (2001). Network-Based Control Systems: A Tutorial, The 27th Annual Conference of the IEEE Industrial Electronics Society. CORRIGAN, S. (2002). Introduction to the Controller Area Network (CAN), Application Report, Texas Instruments. DIAS, A. L. (2006). Estudo e implementação de rede de campo em um sistema de controle de tempo real, Processo FAPESP n 2005/ FELSER, M.(2002). The Fieldbus Standards: History and Structures, University of Applied Science Berne, Technology Leadership Day 2002, Organized by MICROSWISS Network, HTA Luzern. FRANKLIN, G. F., POWELL, J. D. (1994). Feedback Control of Dynamic Systems. p INBERG, J.; LEHTO, E.; VIRVALO, T. (2001) CAN-Bus in a closed loop hydraulic position servo, Tampere University of Technology. PARK S. G. (2002). Fieldbus in IEC61158 Standard, Proceedings on the 15th CISL Winter Workshop, Kushu, Japan. PEDRO L. M. (2005). Projeto de um Sistema de Acionamento Aplicado a um Projeto de Mão Artificial Robótica Processo CNPq n / SCHICKHUBER, G.; MCCARTHY. O. (1997). Distributed fieldbus and control network systems, IEEE Computing & Control Engineering Journal, 1997, n. 8 v. 1, p STANKOVIC, J.A. (1988). Misconception about real-time computing. In: IEEE Computer, vol. 21 (10). THOMESSE, J. (2005). Fieldbus Technology in Industrial Automation, Proceedings Of The IEEE, Vol. 93, No. 6. TORNADO User s Guide (Windows Version).(1996) Wind River Systems. TOVAR, E. M. M.; VASQUES F.(1999). Real-time Fieldbus communications using Profibus Networks, IEEE Transactions on industrial eletronics, pp TOVAR, E. M. M.(1999). Supporting Real-Time Communications with Standard Factory-Floor Networks, Faculdade de Engenharia da Universidade do Porto. YABARRENA, J.M.S.C. (2006). Tecnologias System On Chip e CAN em Sistemas de Controle Distribuído, Escola de Engenharia de São Carlos, Universidade de São Paulo. 6. RESPONSIBILITY NOTICE The authors are the only responsible for the printed material included in this paper.

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