VIEnCoD PROPOSAL OF A CACSD ENVIRONMENT INTEGRATED TO AN ERP SYSTEM AS A TOOL IN THE CONTROLLERS DEVELOPMENT Loures, E.R. and Busetti, M.A. Pós-Graduação em Informática Aplicada, Laboratório de Automação e Sistemas, Pontifícia Universidade Católica do Paraná, Caixa Postal 6122, 8215-91 Curitiba, PR, BRAZIL ABSTRACT: This paper presents the proposal of an CACSD (Computer-Aided Control System Design) environment integrated with an ERP (Enterprise Resource Planning) system, aimed to the study, design and optimization of controllers for the most varied shop floor plants or industrial processes. More specific optimization, control and supervision methods to the the company are very important and necessary at the shop floor level. In this level, the motivation on integrate the machines and production cells to the higher hierarchical levels of the company appears in most expressive way. The VIEnCoD (Virtual Instrumentation - based Integrated Environment for Controllers Design) assist such objectives giving integral support to the whole Control System Development Cycle, from the phase of Identification and Modelling of the plant to the controller's Synthesis. INTRODUCTION With the growth of the computing systems, they become a powerful tool in the industries to aid and to facilitate the use and management of productive resources as well as in the several ones other sections of the company (finances, human resources, production planning, material management, sales, among other). The Integrated Management Systems appeared for the need of integrating the company as a whole, of the managerial point of view, but forgetting the integration with the machines that really produce. Now the companies are with its interests returned to the ERP systems. However, after the start-up, the integration needs with the shop floor should be executed, where optimization methods, control and more specific supervision to the environment of the company are necessary. In this context, VIEnCoD stands as integration tool of the final elements of production (machines) at the higher layers in an ERP system. Its conception was also motivated by the need of an environment to give support to development and researches objectives in parallel with academic purposes, in the study, analysis and project of classic and complex control strategies for the most varied plants, from mechatronic systems to industrial processes [3],[4]. This flexibility and inclusion is the product of the integration methodology, in an ambient userfriendly, of powerful tools giving support to the whole Control System Development Cycle, from the identification of systems to the controllers synthesis.
The hardware support is provided by the VXIbus platform that with the configuration and programming environment LabWindows/CVI, supply ideal conditions of electronic instrumentation with easy configuration and use of the instruments you modulate (adapted to the needs of the control project). The analytical and mathematical support are due to the Matlab 5. / Simulink 2 tools that are integrated and maneged for VIEnCoD in the visual LabWindows environment. PROCESS CONTROL AND ENTERPRISE INTEGRATION For better understanding of the VIEnCoD motivation as a tool inserted in an Integrated Management Systems, it is necessary some definitions. The figure 1 illustrates a managerial pyramid where some levels are observed. The first two levels of the pyramid are about business management including managerial decisions (planning) such as: corporate strategic planning, market planning, financial planning, attendance strategies to the consumer, capacities and sources planning, etc. The two intermediary levels include decisions or planning of short / medium period where meets the systems MES (Manufacturing Execution Systems) with its main tools: Scheduling (Finite Programming of the Production), Production Resources Management and Quality Management. MANAGEMENT OF THE COMPANY THE BUSINESS MANAGEMENT THE PROCESS MANAGEMENT ERP Process Control Manufacture Control Bus. Manag. Production Management MES Sheduling Supervision Systems Controllers Data Acquisition Integration Technology Instrumentation Network and Comunication Figure 1. Integration pyramid The pyramid s inferior levels corresponds to the shop floor equipments and systems responsible for the data acquisition and the optimization of dynamics operation of industrial plants through controllers. The supervision and control consists of integrating all the industrial processes inputs and outputs signs, helping on monitorating its tendencies, setting production operations parameters and configurations remotely. The VIEnCoD hardware, provided by Virtual Instrumentation concept and VXIbus platform, allows the easy configuration and build of a data acquisition system adapted to each plant or production cell. In addition, this platform joins the following advantages: decrease of time spent on setting the data acquisition system accompanying the lay-out changes of the plants or of the production lines; reduction of the maintenance costs; on-line information of the production line status. The great
graphic capacity of the LabWindows/CVI environment allows the design of whole graph type and Graphical User Interface (GUI), making the access on-line to larger flow of procution data. The necessity of improved efficiency in the plants operation of higher quality products, increased yields and decreased energy consumption, has led industries to adopt advanced process control strategies. The design and implementation of control systems based on such strategies require the deep knowledge of process to be controlled, wich usually requires the model description. Many times such model description is not gotten due to complexity of the plant. This way, it is necessary the identification of the plant by methods that don t alter the real operational conditions of the productive process. Of ownership of the knowledge of the plant, the following stage is to place it in an optimal operation point for attendance of indexes and production needs coming from the intermediary and superior pyramid layers. In this sense, the settings of the controllers parameters on the shop floor level is fundamental because it affects in a direct or indirect way (through all the interfaces of the several hierarchical levels) such productive factors as: equipments maintenance costs, emergency stops for the bad operation of the same ones, reduction in energy consumption, etc. The proposal of VIEnCoD is so to facilitate the identification of the dynamics characteristics of the several plants or processes placing them in optimal operation points turning the controllers to the disturbances from the production as the demand variation. What can be noticed, therefore, is that VIEnCoD with its high degree of flexibility and integration, joins in more intense way results to the production management, performing at shop floor level. VIEnCoD ARCHITECTURE The VIEnCoD architecture is structured in na open hardware configuration based on Virtual Instrumentation (VI) Concept; a programming environment based on VISA architecture (Virtual Instrument Software Architecture) - LabWindows/CVI 4.; and a platform of aid in the analysis and project of control systems - Matlab 5.. LabWindows/CVI is a development tool for Virtual Instrumentation based on an integrated environment of 32 bits visual programming, with analysis libraries, instruments drivers, and project tools of an intuitive GUI (Graphical User Interface). This way it is gotten all the configuration, programming and integration of the system VXIbus in short space of time. In addition, LabWindows/CVI 4. is compatible with most of the development environment C/C++ of 32 bits for Windows 95 and Windows NT. This allows the opening for the exchange of code source and developed libraries. This last characteristic is the key for the management of the tools and routines Matlab adapted in C code for Matlab Compiler. The consequent efficiency in the execution time allows the implementation of recursive control strategies with identification techniques applied to the plant. The LabWindows s library with a high number of instrument drivers makes the choice and development of the acquisiton and interface structure an easy task. This easiness also extends to the communication protocols with industrial controllers, for instance, CLP (Programmable Logical Controllers), Fieldbus, Profibus etc. This makes possible a most effective interface of a CACSD tool with physical elements in an industrial process.
Sistema Real Modelo Físico IDENTIFICAÇÃO Modelo Matemático Análise Problema Identificação Projeto do Controlador OTIMIZAÇÃO Análise REALIZAÇÃO Controlador OK Testes Implementação EXPERIMENTAL For support to the Control System Development Cycle, detailed in the next item, the following components of Matlab are necessary[5] : Simulink; System Identification Toolbox; Control Systems Toolbox; Optimization Toolbox / Nonlinear Control Design Blockset; Matlab Compiler; Real Time Workshop; The functionality of each component inside of the VIEnCoD environment will be approached in the next item. Matlab Compiler allows that algorithms and routines of Toolbox, besides the programs generated by the user under the m-function form, be translated from Matlab code for ANSI C code. Similarly, the Real Time Workshop, translates the Matlab code of the block diagrams implemented in SIMULINK for ANSI C code. This allows the management of these resources for LabWindows/CVI turning the Matlab environment transparent to VIEnCoD, that becomes a powerful tool CACSD. The methodology of integration of these tools are the base of VIEnCoD conception and are shown by figure 2. All the Controllers Development Cicle is supported by the Matlab and LabWindows/CVI tools. A prominence is made to the open interface - devices - with the plant or industrial process. Real Time Conditions Offline simulation LabWindows/CVI vecu virtual Electronic Control Unit Matlab - Simulink data files codes Methodology commands status Supervision Systems HW - Open platform protocol/drivers (communication) Condições de tempo real Plant or Process Figure 2. VIEnCoD Concept
VIEnCoD ENVIRONMENT The main goal of the VIEnCoD environment is to give easy access to all the stages (and sub-stages) of the Control System Development Cycle that will be described in the next item. Through buttons related to each stage of the cycle, in a main panel, GUIs and routines for development and analysis of each stage are selected. All these interfaces should allow the read and write of data, graphical visualization of the results, configuration of the VXI, plant and controller. This way a CACSD is clearer for the user. In the following some of the tasks allowed by these interfaces are presented : Configure System Variables panel : configuration of the VXIbus platform and physical parameters of the plant,measures conversion ; Signal Generation and Acquisition panel : configuration of the excitation signals, graphical visualization of the data (input/output); Hardware-in-the-loop simulation panel : simulation with hardware-in-the-loop in that the obtained controller is implemented physically by VIEnCoD, with the plant or real process inserted in the loop [3]. Figure 3 illustrates this tasks. Figure 3. PID simulation with Hardware-in-the-Loop CONTROL SYSTEM DEVELOPMENT CYCLE Due to the great flexibility in the support to varied control strategies and plants, according to the VIEnCoD goals, makes it necessary the execution of several stages inside of a development cycle, according to exhibition the figure 4 [3],[4]. The methodology of integration of Matlab tools is based on this cycle giving mathematical and analytical support to the each stage. 1 st stage: Modelling and Identification This stage corresponds the real system (plants) modelling through the knowledge and development of a physical model, generation of a mathematical model for a comprehensible description in a computer. VIEnCoD allows the use of the mathematical model of the well-known process under several representation forms: transfer function, state-space equations, polynomials - for continuous or discrete models. In many cases this task of obtaining the model through physical laws becomes difficult, involving complex numeric methods to work with the associated mathematical representation. In addition, adaptative control strategies request the continuous obtaining of this model with the real plant operating [1].
In this context, it becomes necessary the determination of the physical parameters not observed through measures obtained from the plant. Such proposal is denominated Identification. The problem of system identification [1],[2], illustrated in figure 5, is supported integrally by VIEnCoD through the acquisition and data management of the VXIbus platform and the integration of Matlab tools and estimate algorithms of the Toolbox System Identification. The figure 6 illustrates this management and integration. Real System Problem Controller Ok Initial Knowledge Experiment Project Identification Experimental Validation Physical model Identification Data Acquisition and Treatment Tests Mathematical Model Analysis Implementation Model Structure Choice Parameters Estimate Method Choice Optimization Controller Design Analysis Model Validation Yes Not Model Ok? Figure 4. Development cycle Figure 5: Identification process 2 nd stage: Optimization In this stage a parametric control strategy is proposed. Following the proposal of strong interaction of the environment with the VIEnCoD user, the use of the Simulink tools and the Nonlinear Control Design Blockset are suggested. Being used of diagrams blocks the user can configure the control loop to be tuned in, with linear elements or not, optimizing the controllers parameters. This optimization, for example, can be the parameters of a PID (Kp, You, Td), as it will be shown in the case study (next item). Ready VXIbus Answers S l o t V X 4 3 5 3 V X 4 7 8 Conditioner Signals V V V X X X 4 4 4 7 2 7 9 4 3 4 A Excitement Real System Status / Digital Answer Excitement Generation Permition Status Excitement/Answer vector - Mathematical Model Virtual Instrumen MATLAB - System Identification t Answer vector Excitement vector Mathematical Parametric Model Data Parameters Excitement Mathematical Parametric Model Identification Answer Embedded Pentium Figure 6. Integration of the Identification stage
3 rd stage: Experimental implementation The controller s parametric model, obtained and simulated in the optimization stage, is implemented physically and connected to the control loop with the real system inserted in simulation with hardware-in-the-loop, as described in the last item. The obtained experimental result can be recorded in file for comparison with the simulate results (mathematical model) through graphic analysis in the time and frequency domain. Satisfactory the results the controller is validated; otherwise it comes back the identification stage. Data acquisition and treatment CASE STUDY In way to check the functionality of VIEnCoD in whole the Control System Development Cycle, a simple system of 1st order is evaluated. The prototype of a level control system of an industrial process is made of case study. Its transfer function is: 1.4 FT ( s) = 14s + 1 The procedure of acquisition of data was done with PRBS signal (Pseudo-Random Binary Sequence - excitement vector) and the output digitalized and recorded (output vector). The data are analyzed, preprocessed (detrended, prefiltered ) and separate a part for the identification process and another for validation. Identification Of ownership of some initial knowledge (in this case already knowing the physical system) it was used the models ARX and ARMAX as : na = 1; nb = 1; nc = 1 and d = 1. The results, shown in the figure 7 (A), are quite satisfactory. Optimization A control adopted was a discrete PID algorithm for syntony of the loop, being its parameters (Kp, Ti, Td) object of the optimization process based on established approaches. I n 1 5 x 4-1 1 2 2 Ti x 4 m] i] Optimization Lei de Controle u(k)=a1.u(k-1)+...+an.u(k-n) + b1.e(k)+...+bm.u(k-m) Ts 6 5.8 L F ( S ) = h (B) 1.4 14 s+ 1 A q (A) h 4 3 2 1-1 -2 L R 1 Input and O u 5 - - 1 1 2 2 x 4 q M e asu red a nd s im ulated m od el ou tput 1.37 FT ( s) 138 s + 1 5.6 5.4-3 1 1.5 2 2.5 Tim e x 1 4 Planta 5.2 5 4.8 4.6 2 3 4 5 6 7 8 9 1 Figure 7. Case study results
Such acting approaches in the time domain are established based on a step, as reference signal (setpoint of the control loop): rise time, time delay, settling time, maximum overshoot, etc. The obtained parameters are used by a PID discrete algorithm that will implement the physical controller supported by VXIbus - LabWindows/CVI platform. Experimental implementation The implemented controller is inserted in the loop with the real plant (simulation with hardware-inthe-loop) and the obtained answer, shown in figure 7 (B), validating the whole development cycle supported by VIEnCoD. CONCLUSION VIEnCod, presented in this paper, had its conception based in two main points that motivated the its insertion on an Integrated Management Systems. They are: 1. To give to an CACSD environment the hardware and software potentialities that can be obtained from the VXIbus / LabWindows platform, integrated into the tools and algorithms Matlab, state of art in the field of control; 2. The flexibility and easiness in the support to the development and implementation of different control strategies to several types of plants, from the identification of systems to the controllers synthesis with simulation with hardware-in-the-loop. As sees, the environment with its high degree of flexibility and integration, joins in a more intense way results to the production management level, from the shop floor. It is in study to make tests and simulations in a prototype of an industrial process plant with technology Fieldbus. The control strategies are executed with programmers logical controllers. The integration of this sets to an ERP system is the main goal of the TIPS project - Totally Integrated Production System, in progress at the University. REFERENCES [1] L. V. R. Arruda, Etude of algotithmes d' estimation robuste et développement of un système à base de connaissance pour l'identification., Thèse de Doctorat, Université of Nice, Sophia Antipolis, France, 1992. [2] L. V. R. Arruda, R. Lüders, W. C. Amaral, S. S. Bueno,A.S. Bárbara, M. A. Silva, H.J. Almeida and M.C. Chestnut, THE CAD package in industrial process identification. J. Proc. Cont., vol. 2, pp. 155-161, 1992. [3] M.C. Zanella, Conception of an Simulation Environment of Mechatronic Systems with hardware-in-the-loop ". Master Dissertation, CEFET-PR, Brazil, 1996. [4] E. R. Loures, M. R. of Silveira, M. A. Busetti, LEPEC - Laboratory of Teaching and Researches in Energy and Control: A Proposal of Integration ". XXIII Cobenge Proceedings, vol. 1, pp. 61, October 1995. [5] Matlab 5, Simulink 2 User's Guide : Control System Toolbox, System Identification Toolbox,Optimization Toolbox, Matlab Compiler, Nonlinear Control Design Blockset, Real Time Workshop, The Mathworks inc.,prentice Hall, 1996.
[6] T. C. Vollmann, Manufacturing Planning & Control Systems, McGraw Hill, 4th Edition. [7] D. Sipper, R. L. Bulfin, Jr, Production Planning Control and Integration, McGraw Hill. [8] Alsène, E., The Computer Integration of the Enterprise, IEEE Transactions on Engineering Managment, vol. 46, pp. 26-35 February 1999.