Embedding Simulink Algorithms into ifix and GE Fanuc Series 90 PLCs

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1 Embedding Simulink Algorithms into ifix and GE Fanuc Series 90 PLCs Krzysztof Kołek AGH University of Science and Technology Institute of Automatics Al. Mickiewicza 30, Kraków, Poland Abstract The paper presents two new target platforms for the C-code generated by the Simulink/RTW toolboxes: the ifix SCADA system and the GE Fanuc Series 90 PLCs. The presented solutions build interfaces to the C-code generated by the RTW toolbox and allow building the executable files that are functionally equivalent to the source Simulink diagrams. The executables are executed outside the Simulink directly by the ifix engine or by the PLC processor. Dedicated software functions are created to initialize the code, to trigger the execution of the generated executables at the required time point and to terminate the execution. As well dedicated driver blocks are described that transfer the signals between the ifix signal database and the executable files or between the PLC references and the executable modules. Finally, three practical examples are shown. 1. Introduction MATLAB and Simulink environments are widely used to developed and analyze control systems. A huge set of MATLAB functions and Simulink blocks create a powerful and flexible tool for data analysis dedicated for control system development. The Simulink diagrams may be also used for rapid prototyping of real-time applications. The RTW toolbox generates a C-code that is functionally equivalent to the source Simulink diagram. The C-code contains the algorithmic part of the Simulink diagram and may be executed outside the Simulink environment. The execution can be controlled by a system that can create an interface to the generated C-code and that is able to trigger the execution of the code at the required time periods. There exist ready-touse interfaces to a selected target laboratory and industrial hardware architectures [1][2][3][4][5]. They cover laboratory requirements however omit the most popular industrial control elements like PLC controllers and SCADA systems. Let us bring the SCADA and PLC controllers near to MATLAB/Simulink and build a bridge that translates the functions of Simulink diagrams to become executables running directly at the ifix SCADA system and at the GE Facuc Series 90 PLCs. 2. Remarks corresponding to the RTW generated code The Simulink package is oriented to simulation. Variable or fixed step algorithms numerically solve the diagrams. At the beginning the Simulink solver initializes the diagram data. After that, at each simulation step (either variable of fixed time step) the solver calculates the response of the diagram blocks. Finally, at the last simulation step the solver performs cleanup operations and stores the simulation results. The RTW toolbox [1] can be applied to generate the C-code from the Simulink diagram. The code is functionally equivalent to the diagram. The style of the generated code may be customized by the TLC [6] language. The generated C-code can operate in a standalone mode outside the Simulink environment. In principle the execution of the C-code under control of a real-time environment contains: the initialization stage, the part invoked at each execution step and the termination phase. Also the following features have to be considered: the variable step algorithms are not suitable for real-time applications because usually a fixed period interrupt signal triggers the calculations. Such operation mode requires a fixed-step solver, when each calculation step is executed at a constant period it must be guaranteed that the duration of the calculation is less than the execution period, the real-time programs interact with the surrounding environment. The simulation programs usually communicate only with file data and with the operator. The real-time programs as well operate with files and interact with the user but their main goal is to read and send data to measurement and control devices. In the case of the Simulink diagrams there must exist dedicated device driver blocks responsible for the communication with the external I/O signals. In the rapid development path the Simulink diagrams evaluate as shown in Fig.1. The upper blocks express the X/05/$ IEEE

2 off-line simulation mode. In the real-time operating mode the off-line data sources and sinks are replaced by the on-line measurements and control device driver signals. The execution is excited by a real-time clock signal. From file From operator Measurements Device driver Data processing Rapid development of real-time applications Data processing To file To operator Control signals Device driver Figure 1. Simulink diagram evolution. In the Simulink environment the real-time executables can be created automatically from the Simulink diagrams. The automatic generation requires that the C-code generated by the RTW is wrapped by the procedures which: perform initialization, handle timer requests, perform device driver operations and finally terminate the real-time application. The wrapping procedures create an interface between the generated C-code and the requirements of the target execution platform. 3. ifix target ifix is a Supervisory Control And Data Acquisition Human Machine Interface (SCADA HMI) program. It may be successfully applied for supervision control and for process monitoring but the default contents of the package does not include any sophisticated data processing methods similar to these supported by Simulink. ifix contains built-in Visual Basic for Applications (VBA) that is a convenient tool for creating interfaces to external programs. Unfortunately, VBA does not process low-level ifix signals and an alternative method has to be developed for low-level data processing Operating mode of the ifix engine The heart of the ifix data processing is the Scan And Control (SAC) engine. The SAC processes blocks included in the signal database. The blocks are organized in chains. The SAC periodically or in an event-driven manner performs execution of the block chains. Each block has its own data processing algorithm. Some blocks operate as device driver interfaces transferring data to SAC or outside SAC. Some blocks perform simple operations under signals coming from other blocks. The operations associated with the signal database blocks are very simple the most complex block is just a simple PID controller. A user familiar to Simulink has to be disappointed in a poor SAC functionality Details of the Simulink/iFIX interface [7][8] A new database block that embeds the algorithms developed as Simulink diagrams into the database processing are created. The new block must be responsible for initialization of the calculations and for the execution of the processing algorithm at each time moment required by the SAC. The development of the new ifix database block requires a dedicated software [9]. The obvious approach is to generate separate database blocks from each Simulink diagram that is going to transfer the functions into ifix. It requires a large number of new blocks and at each time requires the block generation tools. To omit this requirement it is suggested the following solution: the C-code generated by RTW from the Simulink diagram is compiled to a kind of the DLL library. The library exports functions responsible for initialization, termination and solving the single step of the algorithm. It may be important to notify that the generation of the executable library is fully automatic and can be started directly from the Simulink environment, it is created only a single new database block. The block can at the run-time link to the generated executable files. The block calls the initialization procedure during the loading phase and the solving procedure each time the database chain is executed. As the block is created only once the block generation tools are not required each time a new Simulink algorithm is transferred into ifix, driver blocks are added to the Simulink diagrams to allow data transfer between the executable file and the numerical fields of the signal database blocks. When a procedure from the executable file is executed the drivers call SAC procedures to access numerical data from the signal database. The Simulink diagrams process only numerical data. It causes that the string and binary data types from the ifix signal database are not accessible by the generated executables Example At AGH University of Science and Technology in Kraków the central heating system of the university campus buildings is supervised by the ifix application [10][11]. The main campus heating substation supplies heat and hot water to a group of 16 lecturing, administration and laboratory buildings. The maximum heat consumption is 25GJ/h. In the heating substation a single valve is applied to control the volume of the hot water taken from the municipal heating system. A couple of years ego it were investigated applications of neural networks to control the heat consumption [11]. The

3 output of the neural networks was applied to set the position of the control valve (see Fig.2). TREFCO TPCO TZM NN FMDES UCO associate the signals from the signal database to the signals processed by the executable file. The example of the association for the Simulink diagram shown in the lower part of Fig.3 is presented in Fig.4. UCO(FM) Figure 2. Neural central heating controller. There are three inputs of the neural network block (NN): the central heating reference temperature (T REFCO ), the current temperature of the central heating (T PCO ) and the temperature of the water in the municipal heating system (T ZM ). The NN block calculates the volume of the warm water F MDES that has to be supplied from the municipal system to follow the reference temperature. The U CO (F M ) block calculates the control signal for the valve in such a way that the flow does not depend on the fluctuations of the pressure in the municipal network. To develop the NN controller a standard NN is trained (see the upper part of Fig.3). The quality of the network has been tested in the off-line mode. Input 1 FIX ( 1 ) Trefco FIX ( 2 ) TPco FIX ( 3 ) Tzm p{1} 3 3 p{1} y{1} Neural Network p{1} y{1} Neural Network Rapid development FIX ( 1 ) FmDes y{1} Figure 3. Evolution of the Simulink diagram. After the testing phase the input and output signals were replaced by the device drivers (see the lower part of Fig.3). The drivers allow access to the numerical data of the ifix signal database. Three input drivers and a single output driver are applied (the input drivers are shown in red at the left side and output driver in blue at the right side of Fig.3). Each driver contains a parameter that is a number at the list of input and output signals. At Fig.3 the input positions are numbered as (1), (2) and (3) and the output position as (1). The Simulink diagram equipped with the drivers is applied to generate the executable file. The executable file was used by the new database block for the direct on-line processing of the database signals. The new database block has to Figure 4. Association to the database signals. In Fig.4 the lists of the input and output database numerical fields are shown. The Simulink diagram (the lower part of Fig.3) requires three inputs and a single output. The indexes of the inputs are 1, 2 and 3 that are defined at the IO1, IO2 and IO3 fields. There is required only the single output signal which index is 1. The respective signal name is defined in the O01 field. The results of the experiment are given in Fig.5 and Fig.6. Two days history of the central heating system is presented. The system was controlled by ifix SCADA equipped with the new block. The new block periodically executed neural algorithm generated by the Simulink diagram. The calculation results were used to set the position of the control valve Trefco, Tzco, Tout [C] Trefco Tzco Tout : : : : : : :00 Figure 5. Temperatures in the central heating system. The outside temperature (T out ), the reference and the current central heating temperature (T refco and T zco respectively) are depicted in Fig.5. The temperature follows the reference value except the nighttime and early morning-time. During the nighttime the reference

4 temperature is decreased. Therefore the central heating system must decrease its temperature. Each morning the system increases the reference to rise the temperature inside the rooms. The central heating temperature may not be able to follow the reference if the temperature of the water in the municipal system is too low Uco [%] between the PLC references and the data processing algorithm. An example of the Simulink diagram is presented in Fig.7. In the upper part of the diagram the input device driver (I2 block) reads the value of the %I2 reference. Then the %I2 value is inverted. The non-inverted and inverted values are sent to the output device driver (Q_1_2 block). The output driver set the %Q1 and %Q2 binary outputs. In the middle of the diagram the value of the %I3 reference is applied to trigger the execution of the Repeating Sequence block. Respectively to the calculation results the output device driver Q_4_5_6_7_8 sets the %Q4, %Q5, %Q6, %Q7 and %Q8 outputs. The CS block forces the PLC to execute the LD program at constant sweep period (equal to 100ms in this case) : : : : : : :00 Figure 6. Control signal of the main valve. The control signal of the main valve is shown in Fig PLC target The Programmable Logic Controllers (PLC) are widely used in industrial applications. The most common PLC programming method is the Ladder Diagram (LD) language. Similarly to the default ifix processing methods the LD does not include any advanced data processing facilities Operating mode of PLC At PLCs the processor unit executes the programs. The LD programs process data from input or internal references and set data into output or internal reference locations. Usually the external inputs are denoted %I in the case of discrete inputs and %AI in the case of analog inputs. The discrete and analog outputs are denoted %Q and %AQ respectively. The internal PLC data are denotes %M, %T, %S or %R and are applied to store binary data as well as longer data structures Details of the Simulink/PLC interface The GE Fanuc Series 90 PLCs contain a tool [12] that allows creating new LD blocks as C-programs. This tool was applied to create wrapper functions that call the C-code generated by the RTW toolbox. As the results there are automatically created new LD blocks executed directly by PLC. The new blocks execute exactly the same data processing algorithms as the Simulink predecessor. Dedicated device driver blocks, included into a Simulink diagram, are responsible for data transfer Figure 7. Basic Simulink diagram oriented to PLC execution. The diagram given in Fig.7 is trivial and is given only to show how data are passed from PLC references into the algorithmic part of the PLC block, and finally to the output references. One might imagine the power of this solution knowing that an arbitrary Simulink diagram would be placed between the input and output references Incremental encoder interface The first example presents the interface to the incremental encoder. The incremental encoder logic generates two waves A and B (see Fig.8). The relation between the waves depends on the rotation direction. A change of either A or B wave causes the interface counter to increase or decrease their value. Sometimes a third signal is applied to reset the encoder counter and to set the origin position.

5 Wave A Wave B Counter Change Figure 8. Incremental encoder waves FFT example In the Simulink environment the FFT analysis may be applied in a very simply way. There are available blocksets that contain the ready-to-use FFT blocks. On the contrary to the previous example the author cannot imagine how to build the FFT block using only LD logic. To allow a PLC to calculate spectrum bars the Simulink diagram shown in Fig.11 is created. The Finite State Machine (FSM) of the encoder interface is designed in Stateflow (see Fig.9). It contains five states and transitions between states. The FSM transitions are triggered by the states of the inputs. Some transition cause the increment and some decrement of the counter value. When the Reset state is reached the counter is set to zero. Spectrum Analyser %R (Integer) --> [] R_300_363 PLC Model Periodogram FFT %R (Integer) [] --> R_364_395 Figure 11. Simulink diagram of the FFT processing. The diagram uses the Periodogram block that calculates FFT. As the input to the FFT algorithm are given signal samples stored in the %R references from %R300 to %R363. The results are stored in the references %R364 to %R395. Based on the diagram presented in Fig.11 the new LD block is automatically generated. The new block becomes a part of a LD program as shown in Fig.12. Figure 9. FSM of the incremental encoder interface. The encoder FSM has been tested in the off-line mode. After validation the Simulink diagram shown in Fig.10 is created. The sources of the input A, B and Reset signals are the %I2, %I3 and %I4 inputs. The result is stored in the %R200 reference. Figure 12. FFT block embedded into the LD program. Figure 10. Simulink diagram of the encoder interface. The diagram from Fig.10 has been used to build a new LD block. The block is executed by a PLC as a part of the LD program. The LD program is executed by PLC connected to the ifix package. ifix generates the test input signals for the PLC. The time diagram of the input signal and the spectrum bars calculated by the LD program are displayed in Fig.13.

6 Figure 13. Results of the FFT calculated by PLC. 5. Conclusions [7] Matlab-2-FIX Interface. User s Guide, InTeCo Ltd, [8] Pilat A., Kołek K.: Industrial SCADA Software Enriched with MATLAB/Simulink Functionality Applied to the AMB System, proceedings of The Second International Symposium On Stability Control Of Rotating Machinery, Gdańsk, 4-8 August 2003, p [9] Database Dynamo Toolkit Manual, Intellution Inc., [10] Grega W., Kołek K.: Monitoring and Control of Heat Distribution, International Carpathian Control Conference ICCC 2002, Malenowice, Czech Republic, May 27-30, 2002, pp [11] Kołek K., Mitkowski W.: Zastosowanie sieci neuronowych do analizy i sterowania głównego węzła CO AGH, NeuroMet, [12] C Programmer s Toolkit for Series 90 PLCs. User s Manual, GE Fanuc Automation, The Simulink environment contains a huge number of blocks that may be applied to develop and analyze real control systems. The popular industrial control and monitoring environments, the GE Fanuc Series 90 PLCs and the ifix SCADA system are poor in advanced data processing methods. A user who extensively uses MATLAB and Simulink immediately notice gaps in functionality of data processing algorithms practically implemented at the SCADA or PLC platforms. Fortunately, the RTW toolbox opens a method to port Simulink algorithms to new platforms. Once the porting is developed the transfer of the Simulink algorithms into a new form is done automatically and a user does not require to know the details of this transformation. The automatically generated executables are embedded into the target architectures. It means that they are executed in the same way as original target components. As presented in this paper the ifix package and the Series 90 PLCs are able to process data exactly the same way as Simulink diagrams do. Also other software as well as hardware target platforms may be considered in the future to embed Simulink diagram algorithms. References [1] Real-Time Workshop. User s Guide, The MathWorks Inc. [2] Real-Time Windows Target. User s Guide, The MathWorks Inc. [3] xpc Target. User s Guide, The MathWorks Inc. [4] Real-Time Workshop Embedded Coder. User s Guide, The MathWorks Inc. [5] TargetLink, dspace GmbH. [6] Real-Time Workshop. Target Language Compiler Reference Guide, The MathWorks Inc.