Von der Idee bis zur Umsetzung in einer Entwicklungsumgebung State of the Art von Dr. Simon Ginsburg 2013 The MathWorks, Inc. 1
Key Takeaways Model-Based Design drives innovation scales for enterprises of any size can be used for YOUR development environment 2
MathWorks at a Glance Earth s topography on a Miller cylindrical projection, created with MATLAB and Mapping Toolbox Headquarters: Natick, Massachusetts US Revenue Worldwide: ~750M $ Switzerland:~10M CHF Founded 1984 Privately held 2800+ Employees Worldwide 14 Employees in Switzerland Worldwide training and consulting Distributors serving more than 20 countries 3
Key capabilities drive MathWorks business Verification, Validation, and Test Test and measurement Model checking Code verification Certification kits Automatic Code Generation Rapid prototyping and HIL Embedded code DSP support packages HDL code PLC code MATLAB to C/HDL System Modeling and Simulation Simulink DSP designs State charts Physical Communications systems modeling Discrete-event simulation Video processing Computer vision System objects Data Analysis and Algorithm Development Control design Signal processing Optimization Statistics Image processing Computational finance Computational biology Technical Computing MATLAB Application deployment Student version Instrument and database connectivity Parallel computing MATLAB Mobile for iphone/ipad 1985 1990 1995 2000 2005 2010 Founded in 1984 4
Findings of Aberdeen Group from a survey of companies performing mechatronic design Source: System Design: New Product Development for Mechatronics, January 2008, Aberdeen Group 5
Integrating multiple disciplines presents complications Multidiscipline complexity Source: System Design: New Product Development for Mechatronics, January 2008, Aberdeen Group 6
Discovering integration problems early is difficult Multidiscipline complexity Problems uncovered late Source: System Design: New Product Development for Mechatronics, January 2008, Aberdeen Group 7
As errors propagate through a project they become more expensive to fix in later phases Relative cost to fix an error Type of error: - requirements - design - implementation Requirements Design Implementation Integration & Testing Project phase where error is fixed Source: Return on Investment for Independent Verification & Validation, NASA, 2004 8
Model-Based Design- Describe the system dynamics DESIGN Electrical Components Control Algorithms Mechanical Components FPGA ASIC MCU DSP PLC PAC 9
Model-Based Design- Describe the system dynamics DESIGN Model-Based Design uses block diagrams to mathematically model the system behavior. Electrical Components FPGA ASIC Control Algorithms MCU DSP Mechanical Components PLC PAC You design the way the system should perform. Controller and Plant are modeled in one environment. 10
Model-Based Design DESIGN Electrical pos Components vel r_por Force Control Algorithms Force Mechanical Components Pos Vel Testing the braking and stability system. FPGA ASIC MCU DSP PLC PAC Controller Plant 11
Haldex Reduces Braking and Stability System Development Time by 50% with MathWorks Tools and Consulting Challenge To develop a vehicle stability control system within a tight deadline without relying on costly physical prototypes Solution Use MathWorks products and MathWorks consulting to develop a model of the vehicle dynamics and design, simulate, and optimize control strategies Results Design process improved Development time halved Costs reduced Testing the braking and stability system. MathWorks tools helped us to simplify our design process by providing an integrated environment for creating the innovative technical features that our customers demand. Laurence Lane Haldex Link to user story 12
Model-Based Design- Design and test using simulation RESEARCH DESIGN REQUIREMENTS Requirements are linked to the model. Plant Models Mechanical Electrical Control Algorithms Supervisory Logic TEST & VERIFICATION Intellectual property and engineering data are reused from existing designs and CAE tools, such as CAD, FEA, and SPICE models. Testing control algorithms against requirements is done by simulating the model. 13
Model-Based Design RESEARCH REQUIREMENTS DESIGN Environmental Models Mechanical Electrical Control Algorithms Supervisory Logic TEST & VERIFICATION KIMM s prototype maglev-based antirolling system for mobile harbors. Test before HW is available 14
KIMM Develops Prototype Maglev-Based Antirolling System for Mobile Harbors Challenge Build a prototype antirolling system for stabilizing mobile harbors Solution Use Model-Based Design to design and simulate the controller, prototype hardware, and generate real-time control code Results Development time reduced by 70% $20,000 or more in potential prototyping costs saved Confidence in design performance increased Link to user story KIMM s prototype maglev-based antirolling system for mobile harbors. We completed the prototype in just three months with Model-Based Design. We saved months of development time by using an integrated environment to model the controller and the physical system, simulate them together, generate code, and create a real-time hardware prototype that worked flawlessly. Cheol Hoon Park Korea Institute of Machinery and Materials 15
Model-Based Design RESEARCH REQUIREMENTS DESIGN Environmental Models Mechanical Electrical Control Algorithms Supervisory Logic TEST & VERIFICATION Vehicle model created with PSAT. Improve Test when HW is available 16
Argonne National Laboratory Develops Powertrain Systems Analysis Toolkit with MathWorks Tools Challenge Evaluate designs and technologies for hybrid and fuel cell vehicles Solution Use MathWorks tools to model advanced vehicle powertrains and accelerate the simulation of hundreds of vehicle configurations Results Distributed simulation environment developed in one hour Simulation time reduced from two weeks to one day Simulation results validated using vehicle test data Link to user story Vehicle model created with PSAT. We developed an advanced framework and scalable powertrain components in Simulink, designed controllers with Stateflow, automated the assembly of models with MATLAB scripts, and then distributed the complex simulation runs on a computing cluster all within a single environment." Sylvain Pagerit Argonne National Laboratory 17
Model-Based Design- Test and validate in real-time RESEARCH DESIGN Plant Models REQUIREMENTS Automatically generate code from the simulation model for real-time testing of the control algorithms. C, C++ Mechanical Control Algorithms Supervisory Logic Electrical REAL-TIME TESTING VHDL, Verilog Structured Text TEST & VERIFICATION Automatically generate code from the simulation model for real-time system simulation of hardware for testing the real microcontroller, FPGA, or PLC MCU DSP FPGA ASIC PLC 18
Model-Based Design RESEARCH REQUIREMENTS DESIGN Plant Models C, C++ Mechanical Control Algorithms Supervisory Logic Electrical REAL-TIME TESTING VHDL, Verilog Structured Text TEST & VERIFICATION manroland s state-of-the-art printing press. Test and validate in real-time MCU DSP FPGA ASIC PLC 19
manroland Develops High-Precision Commercial Printing Press Controller with MathWorks Tools Challenge Implement a new design process to support development of a precision controller for a state-ofthe-art commercial printing press Solution Use MathWorks products for Model-Based Design to design and model the controller, run real-time simulations, and deploy a production system Results Development time reduced by one year Design iterations completed in minutes, not weeks Error analysis streamlined for manroland customers Link to user story manroland s state-of-the-art printing press. MathWorks tools made it easy for us to test ideas, introduce new algorithms, and compare one controller against another... We could quickly change the structure of the controller and immediately see the results. The ability to perform rapid iterations enabled us to optimize quality and functionality while greatly reducing development cycle time." Thomas Debes manroland 20
Model-Based Design- Implement embedded software RESEARCH DESIGN REQUIREMENTS Automatically generate code from the simulation model for implementing directly on production targets: C, C++ Mechanical Plant Models Control Algorithms Supervisory Logic Electrical IMPLEMENTATION VHDL, Verilog Structured Text TEST & VERIFICATION Microcontrollers FPGAs PLC IDEs MCU DSP FPGA ASIC PLC INTEGRATION 21
Model-Based Design RESEARCH REQUIREMENTS DESIGN C, C++ Mechanical Plant Models Control Algorithms Supervisory Logic Electrical IMPLEMENTATION VHDL, Verilog Structured Text TEST & VERIFICATION ATB Technologies permanent magnet synchronous motor. Verify the design on the target MCU DSP FPGA ASIC PLC INTEGRATION 22
ATB Technologies Cuts Electric Motor Controller Development Time by 50% Using Code Generation for TI s C2000 MCU Challenge Develop control software to maximize the efficiency and performance of a permanent magnet synchronous motor Solution Use MathWorks tools for Model-Based Design to model, simulate, and implement the control system on a target processor Results Development time cut in half Design reviews simplified Target verification and deployment accelerated ATB Technologies permanent magnet synchronous motor. MathWorks tools enabled us to verify the quality of our design at multiple stages of development, and to produce a high-quality component within a short time frame. Markus Schertler ATB Technologies Link to user story 23
Model-Based Design RESEARCH REQUIREMENTS DESIGN C, C++ Mechanical Plant Models Control Algorithms Supervisory Logic Electrical IMPLEMENTATION VHDL, Verilog Structured Text TEST & VERIFICATION The Semtech SX1231 wireless transceiver. Verify the design on the target MCU DSP FPGA ASIC PLC INTEGRATION 24
Semtech Speeds Development of Digital Receiver FPGAs and ASICs Challenge Accelerate the development of optimized digital receiver chains for wireless RF devices Solution Use MathWorks tools for Model-Based Design to generate production VHDL code for rapid FPGA and ASIC implementation Results Prototypes created 50% faster Verification time reduced from weeks to days Optimized, better-performing design delivered The Semtech SX1231 wireless transceiver. Writing VHDL is tedious, and the handwritten code still needs to be verified. With Simulink and HDL Coder, once we have simulated the model we can generate VHDL directly and prototype an FPGA. It saves a lot of time, and the generated code contains some optimizations we hadn t thought of. Link to user story Frantz Prianon Semtech 25
Model-Based Design drives innovation through the way systems are designed, implemented, and tested Address math and algorithmic content in system design Drive innovation through early design iterations Eliminate manual C/C++/FPGA/PLC coding Improve quality through early verification and validation Allow collaboration across disciplines Cause collaboration across development stages Lets you streamline system development: to do things better, faster, more easily to do completely new things 26
Key Takeaways Model-Based Design drives innovation scales for enterprises of any size can be used for YOUR development environment Model-Based Design Works for you too! Visit us at our booth and we can show you how! 27