D R . T A R E K A . T U T U N J I

A D V A N C E D M O D E L I N G A N D S I M U L A T I O N

M E C H A T R O N I C S E N G I N E E R I N G D E P A R T M E N T

P H I L A D E L P H I A U N I V E R S I T Y , J O R D A N

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Modeling and Simulation Principles

What is a Model?

A model is a partial representation of a system’s (dynamic) behavior. There is no the model for a system. Many different models can be associated with the same system depending on what level of approximation we desire. The latter is a function of the purpose for the desired model. A model should be represented with a quality tag indicating its fidelity in reproducing the system’s behavior, or the range of signals it is valid for, or the size of approximation error we may expect

[Ref] Albertos and Mareels

What is a System?

Model Categories

Continuous vs. discrete

Static vs. dynamic

Linear vs. nonlinear

Time-variant vs. time-invariant

Deterministic vs. stochastic

SISO vs. MIMO

Modeling Cycle

Verification and Validation

Model verification investigates whether the executable model reflects the conceptual model within the specified limits of accuracy. Implementation

Alternative models

Animation

Model validation tell us whether the executable model is suitable for fulfilling the envisaged task within its field of application. Replicative validity

Predictive validity

Simulation Advantages over Experiments

It is cheaper (time and money) to model virtual prototypes than it is to build real prototypes.

Some system states cannot be brought about in the real

system Normally all aspects of virtual experiments are

repeatable Simulated models are generally completely controllable Simulated models are generally fully monitorable

Mathematical Models

Mathematical process models for static and dynamic behavior are required for various steps in the design of mechatronic systems, such as simulation, control design, and reconstruction of variables.

There are two ways to obtain these models:

Theoretical modeling based on first (physical) principles

Experimental modeling (identification) with measured input and output variables

[Ref.] Prof. Rolf Isermann

Physical Modeling

In physical modeling the laws of physics are used to describe the behavior and inner action mechanism of a system or a component.

The selection of the relevant relationships depending upon suitability and efficiency and the establishment of cause and effect chains, requires a comprehensive understanding of the system and remains an engineering task

Experimental Modeling

Experimental modeling consists of the development of mathematical models of dynamic systems on the basis of measured data or at least providing existing models with parameters

Parameter estimation estimates parameter values using existing models

System identification creates models to fit experimental data

Experimental Models

Modeling vs. Experimental Validation

[Ref.] Craig and Stolfi

Mechatronic Design Process

[Ref.] Prof. Divdas Shetty

Bottom-up design process

Top-down design process

V-Model MSD from Association of German Engineers Guidelines, VDI 2206

Integrated Design Issues

Concurrent engineering of the mechatronics approach relies heavily on the use of system modeling and simulation throughout the design and prototyping stages.

It is especially important that it be programmed in a visually intuitive environment.

block diagrams, flow charts, state transition diagrams, and bond graphs.

Computer-Aided Systems: Important Features

Modeling: Block diagrams for working with understandable multi-disciplinary

models that represent a physical phenomenon.

Simulation: Numerical methods for solving models containing differential, discrete,

linear, and nonlinear equations.

Project Management: Database for maintaining project information and subsystem models for eventual reuse.

Design: Numerical methods for constrained optimization of performance

functions based on model parameters and signals.

Computer-Aided Systems: Important Features

Analysis: Frequency-domain and time-domain tools

Real-Time Interface: A plug-in card is used to replace part of the model with actual hardware

by interfacing to it with actuators and sensors.

Code Generator: Produces efficient high-level source code (such as C/C++) from the block

diagram. The control code will be compiled and used on the embedded processor.

Embedded Processor Interface: Communication between the process and the computer-aided

prototyping environment.

Information Systems: Modeling

Modeling is the process of representing the behavior of a real system by a collection of mathematical equations and logic.

Models can be static or dynamic Static models produce no motion, heat transfer, fluid flow, traveling

waves, or any other changes.

Dynamic models have energy transfer which results in power flow. This causes motion, heat transfer, and other phenomena that change in time.

Models are cause-and-effect structures—they accept external information and process it with their logic and equations to produce one or more outputs. Parameter is a fixed-value unit of information

Signal is a changing-unit of information

Models can be text-based programming or block diagrams

Information Systems: Simulation

Simulation is the process of solving the model and is performed on a computer.

Simulation process can be divided into three sections:

Initialization

Iteration,

Termination.

Simulation Methods

[Ref.] Prof. Rolf Isermann

Real-Time Simulation

[Ref.] Prof. Rolf Isermann

Hardware-In-the-Loop (HIL)

The hardware-in-the-loop simulation (HIL) is characterized by operating real components in connection with real-time simulated components.

Usually, the control system hardware and software is the real system, as used for series production. The controlled process (consisting of actuators, physical processes, and sensors) can either comprise simulated components or real components,

PC-Based Hardware-in-the-Loop Simulation

Control Prototyping

For the design and testing of complex control systems and their algorithms under real-time constraints, a real-time controller simulation (emulation) with hardware (e.g., off-the-shelf signal processor) other than the final series production hardware (e.g., special ASICS) may be performed.

The process, the actuators, and sensors can then be real. This is called control prototyping

Real-Time Simulation

[Ref.] Prof. Rolf Isermann

Reference

George Pelz. Mechatronic Systems: modeling and simulation with HDLs. Chapter 2 Wiley 2003

Devdas Shetty and Richard A Kolk. Mechatronics System Design, 2nd edition. Chapter 2. Cengage Learning 2011

Rolf Isermann “Mechatronics Design Approach” Chapter 2 in Mechatronics Handbook edited by Bishop