Courses

ECEN672/472: Modeling and Control of Drones

Instructor: Dr. Ali Karimoddini, Dept. of Electrical and Computer Engineering, NC A&T University, Email: akarimod at ncat.edu

Prerequisite: ELEN-410 or consent of instructor

Course Overview: This course introduces a systematic approach to modeling and control of Unmanned Aerial Vehicles (UAVs). The course explores different topics including UAV kinematics, rigid body dynamics, UAV mathematical model, automatic control, flight sensing and control mechanisms, and flight control design. In addition, the course will have some lab sessions for actual implementation of flight control systems on a small drone and/or software development and flight simulations.

Course link: https://www.accesslab.net/education-and-outreach/courses/ecen672-472

ECEN885: Self-driving Cars: Perception and Control

Instructor: Dr. Ali Karimoddini, Dept. of Electrical and Computer Engineering, NC A&T University, Email: akarimod at ncat.edu

Prerequisite: ELEN-668 or consent of instructor

Course Overview: This course will cover recent developments in control of autonomous cars and discusses fundamental problems that an autonomous car faces while moving in its environment. The course covers basic concepts of autonomous cars and feedback control of autonomous cars including sensors, estimation, sensor fusion, planning, navigation, and control.

Course link: https://www.accesslab.net/education-and-outreach/courses/ecen885-selfdrivingcars

ECEN872: Decision Making and Supervisory Control of Discrete Event systems

Instructor: Dr. Ali Karimoddini, Dept. of Electrical and Computer Engineering, NC A&T University, Email: akarimod at ncat.edu

Prerequisite: ECEN-668 or equivalent or consent of instructor

Course Overview: Discrete Event Systems (DES) are time abstracted systems which can be described by sequences of events. Modelling and control of discrete event systems can address a wide range of problems in different areas including computer systems, manufacturing systems, robotics, aerospace systems, process control, software engineering, communication networks, smart grids, and system biology. Many applications such as decision making, task allocation, resource allocation, etc can be addressed within the context of discrete event systems. This course therefore studies the modeling and control of Discrete Event Systems, and their applications. Different techniques such as automata theory, language, and Petri Nets will be studied to model discrete event systems. Then, several techniques will be introduced for the design of supervisory control of discrete event systems. Finally, the applications of supervisory control of discrete event systems will be explored.

Course link: https://www.accesslab.net/education-and-outreach/courses/ecen872

ECEN668: Theory of Linear Control Systems

Instructor: Dr. Ali Karimoddini, Dept. of Electrical and Computer Engineering, NC A&T University, Email: akarimod at ncat.edu

Prerequisite: ELEN-410 or consent of instructor

Course Overview: The aim of a control system is to influence the system's behavior to achieve a desired performance. Many control systems can be described by a linear model for which there are well developed analysis and synthesis tools. The focus will be on linear time invariant lumped systems which are described either by state space equations or rational transfer functions. Different analysis and design techniques will be discussed. The course will discuss both the continuous and discrete time systems.

Course link: https://www.accesslab.net/education-and-outreach/courses/ecen668-468

ECEN865: Optimal Control Systems

Instructor: Dr. Ali Karimoddini, Dept. of Electrical and Computer Engineering, NC A&T University, 336-285-3313, akarimod at ncat.edu

Prerequisite: ECEN-668 or equivalent or consent of instructor

Course Overview: In many practical control problems it is required to find a control technique to optimally improve the dynamical system's performance while satisfying different physical constraints. The system performance can be quantified as a performance index or a cost function. Then, the problem will be reduced to find a control law to optimize a given cost functions. This course explores theory and application of optimal control for linear and nonlinear systems. The course uses optimal control theory and computational optimal control algorithms to improve the system's performance, reduce the control energy, and stabilize the system.

Course link: https://www.accesslab.net/education-and-outreach/courses/ecen865

ECEN885: Advance Robotic Systems

Instructor: The course is collaboratively offered by Dr. Jamshidi at UTSA University and by Dr. Karimoddini at NC A&T University.

Prerequisite: ECEN-668 or consent of instructor

Course Overview: This course will cover recent developments in control of robotic systems by utilizing different techniques such as positioning, navigation, localization, and Motion Control. Available toolboxes and techniques for control of robotic systems will be reviewed. The course materials will be applied to robotic platforms and simulators.

Course link: https://www.accesslab.net/education-and-outreach/courses/ecen885