Do you want to learn the basics of control
and navigation of aerial and underwater vehicles? Here is a
course for you.
EEL 4930: Control of Marine and Aerial Vehicles – Fall
2015
Time: T 10:40am-11:30pm and R 10:40am-12:20
Grading: 70% project, 30% HW
Instructor: Professor Mohseni
This course provides an introduction to the basic theory and
practical aspects of control and navigation of marine and
aerial vehicles. The first part of the course will cover basic
materials while the later part of the course introduces a
selective introduction of the state of the art research
problems currently under investigation.
This: Command not found.
The first part of the course covers topics such as the basic
of marine and aerial vehicle terminology, kinematics and
dynamics of moving frames, vehicle dynamics, nonlinear
equations of motion and linearization, maneuvering tests,
fundamental of controls (stability and transfer matrix, PID,
state space representation, etc), Control design, sensors for
aircrafts and marine vehicles, Kalman filter, autopilot design
via successive loop closure, state estimation, guidance, path
planning. The second part of the course is more focused on
advanced topics and could cover materials from probabilistic
models for control problems (probability introduction, Bayes
approach and inference, [mohseni]# The first part of the
course covers topics such as the basic of marine and aerial
vehicle terminology, kinematics and dynamics of moving frames,
vehicle dynamics, nonlinear equations of motion and
linearization, maneuvering tests, fundamental of controls
(stability and transfer matrix, PID, state space
representation, etc), Control design, sensors for aircrafts
and marine vehicles, Kalman filter, autopilot design via
successive loop closure, state estimation, guidance, path
planning. The second part of the course is more focused on
advanced topics and could cover materials from probabilistic
models for control problems (probability introduction, Bayes
approach and inference, ….), uncertainty analysis in vehicle
motion, sensor measurement and modeling, localization and
SLAM.
Badly placed.