Model-Based Design for Embedded Systems

Transcription

1 Model-Based Design for Embedded Systems Dr. Simon Ginsburg Application Engineering 2008 The MathWorks, Inc.

2 Embedded Application Development Requirements Management Configuration Management Process and Standards Organisational Issues Software Development System Development Embedded Application Algorithm Design Legacy Code Integration Data Management Memory Management Verification Validation 2

3 Three Things to Remember What is Model-Based Design? Tools used for Model-Based Design Live Demo 3

4 Recent Metrics from Thales Targeting a DSP MathWorks Aerospace and Defence Conference 2008 Presented by Dr. Nigel Holliday of Thales SoftwareDevelopmentAdvantagesfromReal-TimeWorkshopEmbeddedCoder.pdf 4

5 Recent Metrics from Visteon Automatic code is smaller than production hand code Visteon, SAE Technical Paper , March

6 Introduction to Model-Based Design Model-Based Design involves using computer aided engineering (CAE) tools to develop: Simulating system behavior (e.g., continuous, discrete ) Tracing and verifying requirements Designing open and closed-loop control strategies Generating software for prototyping and production Continuous testing throughout the development process 6

7 Model-Based Design enforces continuous testing and verification throughout the design process System Design Requirements Architecture Real-Time Software Prototypes Environment Subsystem A Component Component A Generate Embedded Software C, C++ System Subsystem B Implement Execution Harness Component Component B HDL (VHDL, Verilog) MCU DSP FPGA ASIC Integration Generate Digital Electronics Continuous Verification & Validation Specifications Generate: Assertions Test results Documentation Perform: Simulation Design Analysis Traceability Analysis Co-simulation System Testing Testing HW-in-the-Loop SW-in-the-Loop Processor-in-the-Loop 7

8 Key MathWorks Products for MBD MATLAB and Simulink System-level modeling multidomain graphical interactive hierarchical Algorithm design Data analysis Simulation model is an executable specification 8

9 Key MathWorks Products for MBD Stateflow Design and simulate event-driven systems Real-Time Workshop Automatic code generation Real-Time Workshop Embedded Coder Simulink Verification and Validation 9

10 e.g., IEC Modeling Standards Checks This Absolute Value block is operating on an unsigned value which may result in unreachable code. This relational operator block is not outputting a boolean data type which can lead to unpredictable results in the generated code. These root-level Inport blocks have undefined attributes. This Absolute Value block is operating on a signed integer value but saturate on integer overflow is not set, which can lead to incorrect results in the generated code. 10

11 MathWorks Code Generation Technology Real-Time Workshop: Rapid prototyping Hardware-in-the-Loop (HIL) Rapid simulation You can deploy code on any microprocessor or DSP using Real- Time Workshop and Real-Time Workshop Embedded Coder because they generate standard C (ANSI/ISO-C) Real-Time Workshop Embedded Coder: Extends Real-Time Workshop Highly efficient and customisable production code Provides verification capabilities - Code readability, and traceability to the design model - Requirements traceability in generated code - Code testing through in-the-loop techniques Embedded IDE Link xx, Target Support Package xx - Makes it easy to deploy generated code with <IDE> on <microprocessor> 11

12 Demo 12

13 Model-Based Design Provides a CAE solution for multidomain system-level development of mechatronics Uses a simulation model to Design with mathematically describe the Simulation system-level behavior of complex equipment Helps you perform design tradeoffs to ensure that you meet product requirements Lets you find errors early in the simulation stage of the project, instead of the hardware phase Implementation where problems with Automatic are more difficult to trace and costly to fix Code Generation Executable Specifications from Models Continuous Test and Verification 13

14 The Value of Model-Based Design Innovation Perform rapid design iterations Conduct cost-effective what-if studies Explore unique features and differentiators Quality Reduce design errors Minimize hand coding errors Eliminate unambiguous communication internally and externally Cost Reduce expensive physical prototypes Reduce re-work Improve testing efficiency Time-to-market Get it right the first time 14