Entwicklung mechatronischer Systeme in der Luft- und Raumfahrt

Similar documents
Master Class: Diseño de Sistemas Mecatrónicos

System modeling using Simulink and Simscape

Matlab Simulink Simscape

Vom Konzept zum Modell physikalischer Systeme Smarter Modellieren mit Simscape

Introduction to Physical Modelling Rory Adams Senior Application Engineer

Physical Modeling of Multi-Domain System

Physical Modelling with Simscape

Virtuelle Inbetriebnahme und Optimierung von Robotersystemen mit Simscape The MathWorks, Inc. 1

Integrating Mechanical Design and Multidomain Simulation with Simscape

Real-Time Simulation of Simscape Models

Integrating Mechanical Design and Multidomain Simulation with Simscape

Modeling and Simulation of Electromechanical Systems

MathWorks Technology Session at GE Physical System Modeling with Simulink / Simscape

Development and Deployment of ECU based Control Systems through MBD. Imperative role of Model based design in System Engineering

MATLAB/Simulink in der Mechatronik So einfach geht s!

Model-based Design/Simulation

Connecting MATLAB & Simulink with your SystemVerilog Workflow for Functional Verification

Developing Algorithms for Robotics and Autonomous Systems

How Simscape Supports Innovation for Cyber-Physical Systems

Model-based Design/Simulation

Simulink as Your Enterprise Simulation Platform

Rapid Control Prototyping with MATLAB/Simulink Case Study: Ball-on-Wheel

What s New in Simulink in R2015b and R2016a

Ein Modell - viele Zielsysteme

SIMPACK - A Tool for Off-Line and Real- Time Simulation

ConfigurationDesk/RTI. Compatibility with Toolboxes and Blocksets Provided by MathWorks

SimMechanics Getting Started Guide. R2013b

ConfigurationDesk/RTI. Compatibility with Toolboxes and Blocksets Provided by MathWorks

Hardware and Software Co-Design for Motor Control Applications

Plant modeling: A First Step to Early Verification of Control Systems

Real Time Testing of PMSM Controller using xpc Target Turnkey solution

Model Based Systems Engineering Engine Control: from concept to validation. Jan Smolders Technical Account Manager

MATLAB/Simulink 기반의프로그래머블 SoC 설계및검증

Verification and Validation Introducing Simulink Design Verifier

M-Target for Simulink. For perfect simulation and model based design.

Automatic Code Generation Technology Adoption Lessons Learned from Commercial Vehicle Case Studies

Simcenter Motion 3D. Mechatronics - Improve Design Dynamics Performance: Combine 3D Multi-Body Simulation with 1D Actuation & Controls Simulation

다중센서기반자율시스템의모델설계및개발 이제훈차장 The MathWorks, Inc. 2

DSH plus a HWPA Program Gateway into Model-Based Design of Mechatronic Systems

2015 The MathWorks, Inc. 1

Design and Verification of Motion Control Algorithms Using Simulation

Hardware Software Co-Design and Testing Using Simulink Real-Time Paul Berry and Brian Steenson

Leveraging Integrated Concurrent Engineering for vehicle dynamics simulation. Manuel CHENE MSC.Software France

Introduction to Control Systems Design

DRYING CONTROL LOGIC DEVELOPMENT USING MODEL BASED DESIGN

Design optimisation of industrial robots using the Modelica multi-physics modeling language

Introduction to Simulink. Todd Atkins

Mathematical Modelling Using SimScape (Mechanical Systems)

Hardware-in-the-Loop and Real-Time Testing Techniques

Optimization and Implementation of Embedded Signal Processing Algorithms Jonas Rutström Senior Application Engineer

Advanced AC Motor Control S/W Development Sang-Ho Yoon Senior Application Engineer The MathWorks

Real-Time Testing in a Modern, Agile Development Workflow

How Real-Time Testing Improves the Design of a PMSM Controller

Integrated Workflow to Implement Embedded Software and FPGA Designs on the Xilinx Zynq Platform Puneet Kumar Senior Team Lead - SPC

Introducing Simulink Release 2012b for Control System Development Mark Walker MathWorks

Designing a Pick and Place Robotics Application Using MATLAB and Simulink

Hardware-Software Co-Design and Prototyping on SoC FPGAs Puneet Kumar Prateek Sikka Application Engineering Team

Modelling, Simulation, and Real-Time Testing for Model-Based Design GianCarlo Pacitti Application Engineer MathWorks

From Design to Production

What s New in MATLAB and Simulink

Simulation-based Test Management and Automation Sang-Ho Yoon Senior Application Engineer

Experiment 8 SIMULINK

What's new in MATLAB and Simulink for Model-Based Design

Experiment 6 SIMULINK

2015 The MathWorks, Inc. 1

Model-Based Design for Safety-Critical and Mission-Critical Applications Bill Potter Technical Marketing April 17, 2008

Real time implementation on FPGA Summer School EMR 17 - Lille 19 au 21 juin dspace 7 parc Burospace Bièvres FRANCE

Reconfigurable Manipulator Simulation for Robotics and Multimodal Machine Learning Application: Aaria

Team-Based Collaboration in Simulink Chris Fillyaw Application Engineer Detroit, MI

Targeting Motor Control Algorithms to System-on-Chip Devices

Testing Simulink Models

Volvo Car Group Jonn Lantz Agile by Models

Simulink to Embedded Hardware Paul Peeling MathWorks

Model-Based Design: Design with Simulation in Simulink

Motor Control: Model-Based Design from Concept to Implementation on heterogeneous SoC FPGAs Alexander Schreiber, MathWorks

Mathieu Dutré - Application Specialist MBSE. Analysis and optimization of physical models for HIL simulation

Speeding up Simulink. Murali Yeddanapudi The MathWorks, Inc. 1

WEC-Sim Training Course

Design and Verification of FPGA and ASIC Applications Graham Reith MathWorks

MathWorks Products and Prices Euro Academic September 2016

ANNALS of Faculty Engineering Hunedoara International Journal of Engineering

Model-Based Design: Generating Embedded Code for Prototyping or Production

Simulation Data Management Approach for Developing Adaptronic Systems The W- Model Methodology

c) Determine that the temperature range is acceptable. b) Determine what fluid compatibility is necessary.

What s New in MATLAB and Simulink Prashant Rao Technical Manager MathWorks India

Needs for performance of Large Scale Modeling & Simulation

Using RecurDyn. Contents

2015 The MathWorks, Inc. 1

Dynamic Simulation of a KUKA KR5 Industrial Robot using MATLAB SimMechanics

System Requirements & Platform Availability by Product for R2016b

Decoupling Test Cases from Real and Virtual Test Systems with ASAM HIL API

What s New in MATLAB & Simulink. Prashant Rao Technical Manager MathWorks India

Control System Design and Rapid Prototyping Using Simulink Chirag Patel Sr. Application Engineer Modeling and Simulink MathWorks India

What s New with the MATLAB and Simulink Product Families. Marta Wilczkowiak & Coorous Mohtadi Application Engineering Group

Multidisciplinary Methodology For Control Surface Simulation. Mechanical Systems Installation Department - Alenia Aeronautica. Speaker: Luigi MORRONE

SIMPACK Code Export. Customer Application Examples. The Basis for Mechatronic Simulation

Non Linear Control of Four Wheel Omnidirectional Mobile Robot: Modeling, Simulation and Real-Time Implementation

Model-Based Design for Large High Integrity Systems: A Discussion Regarding Model Architecture

Extending Model-Based Design for HW/SW Design and Verification in MPSoCs Jim Tung MathWorks Fellow

MECHATRONICS SYSTEM ENGINEERING FOR CAE/CAD, MOTION CONTROL AND DESIGN OF VANE ACTUATORS FOR WATER ROBOT APPLICATIONS

Transcription:

Entwicklung mechatronischer Systeme in der Luft- und Raumfahrt Eva Pelster 2015 The MathWorks, Inc. 1

Key Points Create intuitive models that all teams can share Requirements 1. Mechanical System Simulate system in one environment to Perform tradeoff studies Optimise system performance Test without prototypes Configure Model Real-Time Hardware Generate C Code Tune Parameter 2

Agenda Example: Flight actuation system Benefits of Model-Based Design Actuator design Modeling the mechanical system Determining actuator requirements Testing Electrical and Hydraulic Designs Optimising System-Level Design HIL testing 3

Example: Aileron Actuation System System Desired Angle Controller Actuator Force Measured Angle Simulation goals 1. Determine requirements for actuation system 2. Test actuator designs 3. Optimise system performance 4. Run simulation on real-time hardware for HIL tests 4

Traditional Design Process REQUIREMENTS Cannot validate design against requirements DESIGN Cannot test or optimize fully integrated design Control Mechanical IMPLEMENTATION Emb. Code INTEGRATION AND TEST Electrical Can only find problems using hardware prototypes Manual coding is slow, buggy, and hard to verify 5

TEST & VERIFICATION Model-Based Design REQUIREMENTS Detect Cannot errors validate right design away with against continuous requirements verification SYSTEM DESIGN LEVEL DESIGN Control Mechanical Electrical IMPLEMENTATION IMPLEMENTATION Emb. Code HIL System Optimize Cannot design test or optimize in a single simulation fully integrated environment design Can only Lower find costs problems using using hardware HIL tests prototypes Save Manual time coding by automatically is slow, generating buggy, and embedded hard to verify code INTEGRATION INTEGRATION AND TEST AND TEST 6

Agenda Example: Flight actuation system Benefits of Model-Based Design Actuator design Modeling the mechanical system Determining actuator requirements Testing Electrical and Hydraulic Designs Optimising System-Level Design HIL testing 7

Modeling the Mechanical System CAD System: Joints θ Aileron Simscape Problem: Model the mechanical system within Simulink Solution: Import the mechanical model from CAD into Simscape Multibody 8

9

Determining Actuator Requirements Model: θ Aileron Problem: Determine the requirements for an aircraft aileron actuator Solution: Use Simscape Multibody to model the aileron and Simscape to model an ideal actuator 10

Testing Electrical and Hydraulic Designs Model: Problem: Test different actuator designs in the system Solution: Use Simscape Fluids and Simscape Electronics to model the actuators, and variant subsystems to test them 11

Agenda Example: Flight actuation system Benefits of Model-Based Design Actuator design Modeling the mechanical system Determining actuator requirements Testing Electrical and Hydraulic Designs Optimising System-Level Design HIL testing 12

Optimising System Performance Model: Angle Current ω Speed Control i Current Control Problem: Optimise the speed controller to meet system requirements Solution: Tune controller parameters with Simulink Design Optimization ω Speed Control K p K i 0.62 0.3 0.29 0.3 13

14

Agenda Example: Flight actuation system Benefits of Model-Based Design Actuator design Modeling the mechanical system Determining actuator requirements Testing Electrical and Hydraulic Designs Optimising System-Level Design HIL testing 15

Configuring an Electrical Actuator for HIL Testing Model: Variable step, implicit solver (Reference) Controller Numerically Stiff System Problem: Configure solvers to minimize computations and convert to C code for real-time simulation Solution: Use Simscape local solvers on stiff physical networks and Simulink Coder to generate C code Configure Model Generate C Code Real-Time Hardware Tune Parameter 16

17

Key Points Create intuitive models that all teams can share Requirements 1. Mechanical System Simulate system in one environment to Perform tradeoff studies Optimise system performance Test without prototypes Configure Model Real-Time Hardware Generate C Code Tune Parameter 18