modeling and simulation principles · mathematical process models for static and dynamic behavior...
TRANSCRIPT
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
2 0 1 3
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