Teaching

MAE 4733 Introduction to Mechatronics (Spring, 2016-2020, every year)

  • Prerequisites: MAE 3113 (Measurements and Instrumentation) or MAE 3403 (Computer Methods in Analysis and Design)
  • Outline (Arduino-based): Introduction to Mechatronics, Arduino programming language and Atmel microcontrollers. Digital input/output (DIO), interrupts, timers, sensors, analog-to-digital (A/D) conversion, digital-to-analog (D/A) conversion, transistors, pulse-width-modulation (PWM), stepper motors, DC motors, servomotors, serial communication (RS-232) and related protocols, introduction to assembly language programming, introduction to wireless communication, use of MATLAB software for simulation and interface with Arduino boards, introduction to control theory and PID controller.
  • Sample projects: Wireless Door Sensor (https://youtu.be/JxlsL_jNtDs , https://youtu.be/rc6UCU0aRGI), Affordable Automated Robot Arm (https://youtu.be/DmI42qQ4wMk), Room specific temperature control (https://youtu.be/n0pIbt9cyZ0), Home Automation: Remote Oven Control (https://youtu.be/BVdQBZ977lk), Autonomous Irrigation System (https://youtu.be/rwEUQAKaKeQ), Power Pen Automatic Writing System (https://youtu.be/KLdZO-dGB3g),

MAE 5473 Digital Control Systems (Fall, 2015, 2017, 2019, odd years)

  • Prerequisites: Automatic Control Systems or equivalent
  • Outline: Introduction to continuous and digital control systems. Laplace and z transformations. Analysis of discrete time control systems: impulse sampling, zero-order and first-order holds, effects of sampling, Shannon sampling theorem, aliasing. Review of linear algebra. State space analysis: state-space models, canonical forms, stability, stability based on Lyapunov stability theorem, controllability and observability. Design of control systems based on root-locus and frequency methods. Design of control systems based on state-space techniques: pole placement, observer design, state estimation. Dynamic programming and linear quadratic optimal control.
  • Sample projects (Hardware based): Golf Cart Steering Control (https://photos.app.goo.gl/Zf1YihrtYzP6mMZm1), Digital Filtering and Implementation (https://www.dropbox.com/s/lfoblczzr7r81fb/DigitalFilteringDemo.MOV?dl=0)

MAE 5433 Robotics: Kinematics, Dynamics and Control (Fall, 2016, 2018, 2020, even years)

  • Prerequisites: MAE 4053 (Automatic Control Systems) or ECEN 4413 or equivalent, and consent of the instructor. Solid background in linear algebra and good knowledge of MATLAB
  • Outline: Kinematic and dynamic analysis of robot manipulators. Forward and inverse kinematics, differential kinematics, motion planning and trajectory generation. Industrial practice in robot servo control. Dynamics and control in the presence of constraints. Actuators and sensors. Robotic force control and its applications in industry. Passivity-based control algorithms. Nonlinear and Adaptive control techniques for motion and force control. Introduction to advanced robotics topics, including coordination of multiple robots and simultaneously localization and mapping (SLAM).

MAE 6453 Adaptive Control (Spring, 2019, odd years)

  • Prerequisites: MAE 4053 (Automatic Control Systems) or ECEN 4413 or equivalent, and consent of the instructor. Solid background in linear algebra and good knowledge of MATLAB
  • Outline: Introduction to Adaptive Control, and a review of Lyapunov theory and other preliminaries. On-line parameter estimation (gradient and least-square methods, persistency of excitation(PE) condition). Indirect adaptive pole placement (APP) control. Direct model reference adaptive control (MRAC). Robustness properties (against disturbances, unmodeled dynamics, etc.). Advanced topics including nonlinear adaptive control (adaptive backstepping), extremumseeking, neuro-adaptive observer and controller.