Course Description

Course Name:	Numerical Computing with Simulink. A “Model Based Design” Approach Using Simulink and Simscape for: Specification Capture; Simulation; Design; Code Generation; Validation; Verification
Time & Date:	6 - 9 PM, Tuesdays, April 13, 27, May 4, 11, 18, 25
Location:	Holiday Inn Select Hotel, 15 Middlesex Canal Park Rd, Woburn, MA
Speaker:	Richard Gran, Mathematical Analysis Co.
Text:	Numerical Computing with Simulink, Volume 1” by Dr. Gran

Introduction:

For some systems, simulation is the only way a designer can develop a design. Examples are in designing subsystems for use in spacecraft and aircraft where testing a system design is extremely expensive (or dangerous as is the case for manned vehicles). However, even for inexpensive systems, the demand for improved performance can force the designer to account for extremely complex dynamics. A good example of this is the design of computer disk drives. Improving the performance of a hard disk requires that more bits be stored in ever-smaller spaces and these be written and read at higher and higher speeds. The vibration dynamics of the disk and the read/write head, the aerodynamic flow around the head, and even the thermal distortions become limiting factors in the design and the only way to develop an optimized design is to simulate these effects. Simulink, from The MathWorks, allows engineers to develop designs and to create embedded software. This product is complex and as a result, it users tend to treat it as a black box. To get a better understanding of the use of Simulink, this course introduces the numerical methods used to create simulations with Simulink.

The newest member of the Simulink family is Simscape, a tool for using a strictly visual representation of a system to develop a simulation. As electrical engineers, we are all familiar with this “schematic diagram” approach, but for other disciplines (mechanical, thermodynamic, hydraulic, pneumatic, and others) this is a new approach. In Simscape, an engineer can create a model of a system that has electric machines, electronics, mechanical systems (like linkages), hydraulic devices, pneumatic devices, and model the underlying thermodynamics using the same visual programming tool. The model is a picture of the system and the interconnections among the subsystems. When the simulation runs, Simscape reduces the picture to the differential and algebraic equations that the picture represents and then simulates the resulting equations. This eliminates the tedious work needed to reduce the pictorial representation by hand. Simscape works with all of the other tools from the MathWorks, including MATLAB, Simulink and Stateflow. The course will introduce Simulink, Simscape, Stateflow, and many of the Simulink Blocksets (including the dsp Blockset). Over eighty detailed examples taken from the book “Numerical Computing with Simulink” will be provided to the students along with a copy of the book.

Outline:

Introduction to Simulink
1. Using a Picture to Write a Program
2. Example 1 – Leaning Tower of Pisa
3. Example 2 – Modeling a Pendulum Clock
4. Example 3 – Complex Rotations, the Foucault Pendulum
Linear Differential Equations, Matrix Algebra and Control Systems in Simulink
1. Linear Differential Equation and Linear Algebra
2. Linear Control Systems
3. Linearization in Simulink
4. Analyzing Models for Stability
5. Obtaining Transfer functions of linear and nonlinear simulations
6. P, PD, and PID control systems in Simulink
Nonlinear Differential Equations
1. Example 4 – The Lorenz Attractor
2. The differential equation solvers in Simulink
3. Using tabulated (experimental) data in Simulink
4. Rotations in 3 dimensions
5. Example 5 – Modeling a satellite in orbit
Digital Signal Processing in Simulink
1. Difference equation models
2. Digital filters with Simulink experiments
3. Matrix algebra in discrete systems
4. Analyzing discrete feedback systems
5. Digital filter design and the sampling theorem
6. The signal processing Blockset
7. The Phase-Locked loop
Random Numbers, White Noise and Stochastic Processes in Simulink
1. Modeling random variables and Monte Carlo simulations
2. Simulating white noise – Brownian motion
3. Simulating systems with “colored” (not white) noise
4. Modeling Partial Differential Equations
5. The heat equation
6. Vibration
Stateflow
1. Building a simple state machine
2. Example of a controller for a home heating system
Physical Modeling Using Simscape
1. SimPowerSystems and Simelectronics
2. SimMechanics
3. Thermodynamic Systems
4. Hydraulic Systems
5. Pneumatic Systems
6. Mechanical Systems
7. Extending Simscape for a different physical modeling application
Using Simulink, Stateflow and Simscape in a Model Based System Design Process
1. Specification development and capture
2. Modeling a system that incorporates the specifications
3. Design of subsystems to meet the specifications
4. Verification and Validation of the design
Creating Embedded Code

Target Audience:

Engineers, from all disciplines, who are being asked to design complex systems.
Anyone who wants to understand both Simulink and Stateflow, and how to use these tools to build simulation models.
Engineering managers that are responsible for the creation of system design tools, specification capture tools and related activities.
Computer software programmers that are tasked with creating embedded code and want to understand how automatic coding can be used to improve the reliability of the code they generate.

Benefits of Attending:

You will learn how to create simulations with Simulink, Stateflow, and Simscape that will allow you to design a complex system. In the process, you will learn about the underlying mathematics that makes these tools so powerful and easy to use. Finally, you will also learn how to use these tools in a structured design process for specification captures, design, validation and verification and code generation.

Speaker’s Bio:

Dr. Gran spent over twenty years as the head of the Dynamics and Control Theory Laboratory in the Grumman Corporate Research Center. He also was instrumental in the creation of a computer aided design tool called Protoblock that was a precursor of Simulink. After retiring from Grumman, he started the Mathematical Analysis Co., where he spent five years as an executive consultant for The MathWorks, in Natick. For over ten years he taught courses as an Adjunct Professor at the State University of New York at Stony Brook (in the Department of Applied Mathematics), and he also was an Adjunct Professor in the Electrical Engineering Department of the Polytechnic Institute of Brooklyn, where he received his PhD in 1969. He was part of the team that developed the digital autopilot for the Grumman Lunar Module in the early 1960’s. During a 3-year field assignment from Grumman (at the MIT Instrumentation Labs in Cambridge), he created code for the Lunar Module Guidance Computer. This led to his lifelong goal of automating the creation of embedded software.

Material with Course:

Each student will receive a copy of the book “Numerical Computing with Simulink, Volume 1” by Dr. Gran and a disk with the over 80 examples that will be discussed in the course. The students will be expected to have a computer and access to Simulink, Simscape, Stateflow and some of the Blocksets.

Decision (Run/Cancel) Date for this Courses is Monday, April 5, 2010

FEES

Payment received by April 1: IEEE Members $400

Payment received by April 1: Non-members $440

Payment received after April 1: IEEE Members $440

Payment received after April 1: Non-members $480

On-line registration to this course is closed. You may register from 5:30PM - 6:00PM, Tuesday, April 13, 2010 at the Holiday Inn Select, 15 Middlesex Canal Park Road, Woburn, MA or by calling the IEEE Boston Section office at 781-245-5405.