Workflow for Control System Design and Implementation

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Workflow for Control System Design and Implementation - Dhirendra Singh, Application Engineer - Shobhit Shanker, Application Engineer 2012 The MathWorks, Inc. 1

Agenda Industry Trends and Challenges Design PID Controller & Feedback Compensator Adding Control logic Implementing control algorithm 2

Challenge- Increasing Software Content Lights Engine Control Power Management Adaptive Front Lighting Systems Traction Control Voice Recognition Instrumentation Driver Drowsiness Stability Controls ABS Steering Adaptive Cruise Control Climate Controls Infotainment Windows Navigation Airbags Software content increasing 3x Doors 5x per year How Transmission to develop and manage Crash such large Control amount of software? Avoidance Wireless Connectivity Passenger Detection Obstacle Detection Ride Control Tire Pressure Monitoring 3

Growth of Automotive Electronics and Software Modeling Hybrids x-ev s Driver-less C Microcode/Assembly BCM HVAC AFS Abstraction HUD Motorola 6800 8 bit/ 1 MHz / 4 kbytes ABS ESC ACC Freescale MPC5674F LDWS 32 bit / 200+ MHz / 4000 kbytes PCS Processor Ignition Fuel Injection ETC GDI DCT HCCI 1970 1980 1990 2000 2010 2020 4

Model-Based Design- Controller Design RESEARCH REQUIREMENTS DESIGN Environmental Models C, C++ Mechanical Control Algorithms Supervisory Logic Electrical IMPLEMENTATION VHDL, Verilog Structured Text TEST & VERIFICATION MCU DSP FPGA ASIC PLC INTEGRATION 5

What is Our End Goal? Code Generation Real-Time or Embedded Embedded Processor or ECU 6

Problem Formulation Higher Performance: 1. Faster trajectory Vmax: 150 250 rad/s Amax: 2000 5000 rad/s 2 2. Decreased error at standstill error < 1 rad 7

Agenda Industry Trends and Challenges Design PID Controller & Feedback Compensator Adding Control logic Implementing control algorithm 8

Control Design: solving your design problem Tuning a PID controller Specifying the controller structure in Simulink Setting up your design environment Analyzing and tuning the closed loop Discretizing controller Optimizing design parameters Designing fault detection logic Demo 9

PID Controller Block with Automatic Tuning 10

Agenda Design PID Controller & Feedback Compensator Adding Control logic Implementing control algorithm 11

Designing Fault Detection Logic 12

Model-Based Design- Implementation RESEARCH REQUIREMENTS DESIGN Environmental Models C, C++ Mechanical Control Algorithms Supervisory Logic Electrical IMPLEMENTATION VHDL, Verilog Structured Text TEST & VERIFICATION MCU DSP FPGA ASIC PLC INTEGRATION 13

Agenda Design PID Controller & Feedback Compensator Adding Control logic Implementing control algorithm 14

Workflow for Control System Design - Implementation Shobhit Shanker Senior Application Engineer- Code Generation and Verification 2012 The MathWorks, Inc. 15

Implement Model as Software On-target Code Generation Real-Time or Embedded Embedded Processor or ECU 16

Demo Code Generation 17

How Did We Get Here? 18

Workflow For Embedded Code Generation Setting up-code Generation Environment Modeling Guidelines Checking Code Generation Advisor Settings e.g. RAM/ROM Add Software Design Details Algorithm Partitioning e.g. reusable libraries, Model reference Data Typing, Scoping of Variables, Fixed Point Details, Sw-DD Generate Code & Review Peer review, Code Walkthrough Standards Compliance e.g. MISRA-AC-AGC Verification and Integration of Code Software-in-loop testing(sil) Processor-in-Loop(PIL) for Target Testing Platform Integration 19

Setting up Code-Generation Environment V Discretizing the model Variable Fixed-Step Code Advisor Float-Fixed point conversion Modeling guidelines checking MAAB, DO178B/C, ISO26262 20

Add Software Design Details Naming of Variable Storage class(scope) Datatype Comments Algorithm Partitioning Functions Reusable Functions Inline #Pragmas 21

Generate Code and Review Traceability Static Code Metrics RAM Call Tree SLOC Comments 22

Continuous Test and Verification (SIL/PIL) Executable Specifications Design with Simulation Models Continuous Test and Verification Automatic Code Generation 2012 The MathWorks, Inc. 23

Model Testing Develop test inputs Types of inputs: Functional requirement High level use case Sensitivity analysis Edge Case testing Robustness testing etc Apply the test inputs to model Analyze the results Expected output Measure coverage 24

Log Signals of Interest Identify numerical differences Supports: Normal, SIL, PIL Logged signals Imported signals HTML reports 25

Software-in-the-Loop (SIL) Testing: Verify Production Controller with Software-in-the-loop Execution Host/Host Nonreal-time Code Generation Compiled C Code S-Function (Windows DLL) 26

Processor-in-the-Loop (PIL) Testing: Verify Production Controller with Processor-in-the-loop Execution Host/Target Nonreal-time Code Generation Production Processor 27

BLACK BOX P O W E R V R C S I N P U T B L U E G R E E N R E D Platform Integration Controller Model Communication Interfaces Comm Drivers Generated Algorithm Code Output Drivers M Actuators Sensors A B C Input Drivers Optional Target Optimized Code Special Device Drivers Tuning RGBSplit-4 Special Interfaces Scheduler/Operating System and Support Utilities 28

Summary Design, Tune and Test Controllers in Simulink Convert Controller Models to Embedded Code Test Generated Code on Target 29

What s Next? Explore >>rtwdemos Attend Embedded Code Generation class www.mathworks.com/services/training/courses/slec_1.html Request Advisory Services: Developing Embedded Targets, Model-Based Design for ISO 26262 or DO-178 www.mathworks.com/services/consulting/areas/design.html Read Technical Articles and User Examples www.mathworks.com/programs/techkits/pcg_tech_kits.html Thank You! 30