Teaching

Graduate

MEGR 7090/8090: Dynamic System Learning and Estimation (UNC Charlotte) Review of linear systems and probability theory, observability, Luenberg observer, system ID via least-square parameter estimation and stepwise model determination, maximum likelihood estimation, Kalman filters (discrete-time, continuous-time, extended KF, unscented KF), recursive Bayesian estimation, particle filters, machine-learning-based regression (neural networks and Gaussian processes) for dynamic system modeling, and dynamic mode decomposition.
Textbooks: (1) D. Simon, Optimal State Estimation: Kalman, H infinity, and Nonlinear Approaches, John Wiley & Sons, 2006. (2) course lecture notes.
Offered: Fall 2022, Fall 2024
Course homepage: [Link]

CSC 476/576: Introduction To Robotics (Catholic University) Bug algorithms, configuration spaces, forward/inverse kinematics for manipulators, potential fields, cell decompositions, probabilistic roadmaps, tree-based motion planning (RRT, EST, etc.), robot locomotion and equations of motion, open-loop control, closed-loop (PID) control, uncertainty and error propagation.
Textbook: (1) Course notes adapted from Prof. Erion Plaku’s course. (2) H. Choset, K. Lynch, et al., Principles of Robot Motion, MIT Press, 2005. (3) S. LaValle, Planning Algorithms, Cambridge University Press, 2006.
Offered: Fall 2017

Undergraduate

MEGR 3111: Dynamic Systems I (UNC Charlotte) Particle kinematics and kinetics (2D), reference frames (rectangular, polar, path), relative motion, constrained motion, work/energy, linear and angular momentum, impulse, power and efficiency, 2D rigid body dynamics, energy, and momentum.
Textbooks: (1) J. L. Meriam, L. G. Kraige, J. N. Bolton, Engineering Mechanics: Dynamics, John Wiley & Sons, 2018 (2) N. J. Kasdin, D. A. Paley. Engineering Dynamics, Princeton University Press, 2011.
Offered: Fall 2021, Fall 2022, Fall 2023, Fall 2024
Course homepage: [Link]

MEGR 3122: Dynamic Systems II (UNC Charlotte) Review of 1st and 2nd Order ODEs, Laplace transforms, inverse Laplace transforms, ODE solutions via Laplace transform, MATLAB simulation, damped harmonic oscillator, transfer functions for translational and rotational motion, lumped parameter models, basic models of thermal and electrical systems, sinsuoidal transfer function, resonance, transmissibility, vibration isolators, multi-DOF vibrations (modes/mode shapes), vibration aborbers, Bode diagrams, intro to block diagrams and PID control.
Textbooks: (1) M. A. Davies, T. L. Schmitz, System Dynamics for Mechanical Engineers, Springer, 2015 (2) K. Ogata. System Dynamics, Pearson Prentice Hall, 2004.
Offered: Spring 2021, Spring 2022, Spring 2023, Spring 2024

ENGR 207: Programming Robots and Sensors (Catholic University) Types of robots and applications, locomotion, homogeneous coordinates and transformations, simulating equations of motion via Euler’s method, sensor technologies, intro. random vectors and uncertainty, intro. feedback control, intro. motion planning. Labs: hands-on programming and prototyping of circuits and programming a mobile robot Zumo 32U4 in the Arduino (C++ based) language.
Textbook: (1) Course notes provided by instructor (2) J. Blum, Exploring Arduino, John Wiley & Sons, 2012.
Offered: Spring 2017, Spring 2018