1. MESB374 System Modeling and Analysis Introduction

2. Example Vehicle speed control MODEL: ANALYSIS: t v Increasing grade - + + - CONTROL: input output states linearization Inertia force Traction: input, excitation Gravitation: disturbance Friction: damping

3. Course Overview One of the most important and multi-disciplinary courses you’ll ever take Physics Kinematics Mathematics Time and frequency response analysis Engineering judgment Remember these? i.e. Can you explain the basic concepts to other people? Leveraging previous coursework and preparing for future coursework Mechanics, electrical, electromechanical Fluid-thermal Calculus, differential equations, complex algebra Measurements/instrumentation understanding Emphasize combination of theoretical and conceptual understanding

4. Basic Concepts System Modeling Analysis A combination of components acting together to perform a specific objective A procedure to obtain a model describing important characteristics of system Investigation of performance of system, whose model is known, under specified conditions

5. Motivation for MESB 374 Pervasiveness Why should we care about modeling and analysis? Explaining interesting Phenomenon Component and Machine Design Feedback Control Design and Adding Intelligence

6. Definitions Related to System OutputA variable that we observe and consider important Measurements/instrumentation Not necessary what we want to know StateA variable that is used to describes the internal system dynamics A set of states can be used to fully describe system’s current situation. With two identical sets of initial values of states, performance of a system is the same Do you get all the states of system ? InputA variable that excites a system Inputs are not always known beforehand Inputs are always responsible for problems in systems

7. Lumped SystemA System with a finite number of state variables Lumped parameter/ discrete system Usually an artificial/modeling concept Different Systems/System Descriptions Distributed SystemA System with infinitely many state variables Continuous elastic structures (beams, shells, and plates) Fluid systems (ocean and atmosphere) Can often be approximately described with lumped models (FEM, AMM) Continuous-time SystemAll the signals are continuous in time Everything is defined at each instant time Also called Analog systems Discrete-time Systems Variables are only defined at discrete times Also called sampled data systems Hybrid System Continuous-time + discrete-time

8. More Different Systems/System Descriptions Time-varying System (in practice) The characteristics of system changes with time going time-varying parameters time-varying dynamics Linear System Equations describing system are linear Principle of superposition Nonlinear System Linearize it near a operating condition to obtain a linear approximation Time-invariant System (ideal) The features of system never ever changes Usually a good approximation for most engineering application A good starting point to obtain main features of system Relatively easy to analyze

9. Interdisciplinary and System Nature of ME 375 Analogous systems Models are the same regardless of the physical domain of interest We only need to understand how to analyze one model, but the results are applicable for four seemingly different types of physical systems! u y = = =

10. Big Picture Physical System Develop Idea Model Verify Model GET PAID !! Predict Performance Build Actual System and Verify Design Meet Performance Spec. Meet Performance Spec. Feedback/ Feedforward Control Design Simulation Study Implement on Actual System No Yes No Yes Not So great Good OK No Not Good Yes Modeling Analysis Design Implementation Test

11. Course Outline Introduction Components/ elements Connections/ interconnects Mechanical Thermal Electrical Electromech Hydraulic Input/output Vs. state-variable models Time-frequency tools of systems analysis Feedback and system design