An Introduction for Mechanical Engineering Students
Course Overview
Mechatronics 2 is the continuation of the Mechatronics sequence and represents the transition from understanding individual components to engineering complete systems. Where Mechatronics 1 established the operational principles of circuits, microcontrollers, sensors, and actuators, this course develops the three skills that define a practicing mechatronic engineer.
Learning Objectives
- CO1 – Apply statistical methods to characterize experimental measurement data, compute confidence intervals, and perform hypothesis tests
- CO2 – Quantify and correctly report measurement uncertainty using the Kline-McClintock method for multi-variable models
- CO3 – Design signal conditioning circuits (instrumentation amplifiers, active filters, Wheatstone bridges) to meet target performance specifications
- CO4 – Configure a data acquisition system correctly; apply Nyquist criterion; diagnose and prevent aliasing
- CO5 – Compute and interpret the FFT of a measured signal; apply linear and nonlinear curve fitting and assess goodness of fit
- CO6 – Select appropriate sensors from the major families; predict sensor output from calibration data; identify sources of measurement error in a complete signal chain
- CO7 – Derive transfer functions from differential equation models; characterize first- and second-order systems from step response and Bode plot data
- CO8 – Assess closed-loop stability using gain and phase margins; interpret system behavior in the frequency domain
- CO9 – Design and implement a PID controller; apply systematic tuning methods; implement a digital control loop on an embedded microcontroller
- CO10 – Design, build, calibrate, document, and present an integrated measurement and control system that addresses a real engineering challenge
Topics Covered
Module 1: Precision Measurements and Signals
- Measurement system performance; statistics and uncertainty propagation; calibration; instrumentation amplifiers; Wheatstone bridges; active filters; data acquisition; FFT and curve fitting
Module 3: Dynamic Systems Modeling
- Differential equation models for mechanical, electrical, thermal, and fluid systems; Laplace transforms and transfer functions; block diagrams; first- and second-order response; poles, zeros, stability; Bode plots; experimental system identification
Module 5: Advanced Embedded and Systems
- Interrupt-driven programming; finite state machines; real-time constraints; I2C, SPI, UART, and CAN protocols; sensor fusion on microcontrollers; complete mechatronic system design process
Module 2: Advanced Sensors
- Strain and force; temperature (thermocouples, RTDs, thermistors); pressure and flow; displacement and motion (encoders, LVDTs); MEMS inertial sensors; IMU sensor fusion; introduction to machine vision
Module 4: Feedback Control
- Closed-loop control architecture; PID controller structure and actions; Ziegler-Nichols and ITAE tuning; anti-windup; practical stability analysis; introduction to digital PID implementation