Dynardo Gmbh

Design of a control system model in SimulationX using calibration and optimization

Dynardo GmbH

1 © Dynardo GmbH

Notes

• Please let your microphone muted

• Use the chat window to ask questions

• During short breaks we will answer your questions

Supported versions

• From version 4.1 optiSLang supports SimulationX since version 3.5

Design of a control system model in SimulationX 2 using calibration and optimization © Dynardo GmbH

1. Introduction 2. Process integration

3. Sensitivity 4. Optimization analysis

5. Trainings & Contact

Design of a control system model in SimulationX 3 using calibration and optimization © Dynardo GmbH

1. Introduction 2. Process integration

3. Sensitivity 4. Optimization analysis

5. Trainings & Contact

Design of a control system model in SimulationX 4 using calibration and optimization © Dynardo GmbH

Dynardo

• Founded: 2001 (Will, Bucher, CADFEM International) • More than 60 employees, offices at Weimar and Vienna • Leading technology companies Daimler, Bosch, E.ON, Nokia, Siemens, BMW are supported

Software Development

CAE-Consulting • Mechanical engineering • Civil engineering & Dynardo is engineering specialist for Geomechanics CAE-based sensitivity analysis, • Automotive industry optimization, robustness evaluation • Consumer goods industry and robust design optimization • Power generation

Design of a control system model in SimulationX 5 using calibration and optimization © Dynardo GmbH

Application of Multi-disciplinary Optimization

• Virtual prototyping is an interdisciplinary process • Multidisciplinary approach requires to run different solvers in parallel and to handle different types of constraints and objectives • Arbitrary engineering software with complex non-linear analysis have to be connected • The resulting optimization problem may become very noisy, very sensitive to design changes or ill conditioned for mathematical function analysis (e.g. non-differentiable, non-convex, non-smooth)

Design of a control system model in SimulationX 6 using calibration and optimization © Dynardo GmbH

Excellence of optiSLang

• algorithmic toolbox for • sensitivity analysis, • optimization, • robustness evaluation, • reliability analysis • robust design optimization (RDO) • complete functionality of stochastic analysis to run real world industrial applications • optiSLang advantages: • easy and reliable application, • predefined workflows, • algorithmic wizards and • robust default settings

Design of a control system model in SimulationX 7 using calibration and optimization © Dynardo GmbH

Example: design of a control system

dynamic system

• control loop consisting of a dynamic system and a controller • system transfer function should fit with a measured one from a real system • consequence is a difference between input and output signal • controller has to minimize the difference between both signals

Step 1: calibration of the dynamic system

Design parameters Responses Task • System gain • Output signal • Minimize the difference • Delay time between output signal • 2 time constants and measured reference signal

SimulationX model

measured reference signal

1. Introduction 2. Process integration

3. Sensitivity 4. Optimization analysis

5. Trainings & Contact

Process Integration

Parametric model as base for • User defined optimization (design) space • Naturally