INTRODUCTION TO FEEDBACK CONTROL OF AUTONOMOUS SYSTEMS

ME 446

Overview of linear feedback control analysis and design techniques for mechanical systems. Modeling of linear dynamic mechanical systems (review), derivation of their defining differential equations, and analysis of their response using both transient and frequency response techniques; Analysis and design of feedback control of mechanical systems using classical control transform techniques such as root locus and frequency response; Analysis of system robustness through evaluation of phase and gain margins and the Nyquist stability criterion. Design of feedback controllers for mechanical systems using frequency domain loop-shaping methods. Design domains, including mechanical, thermal, and fluid feedback control systems. Effects of non-ideal system characteristics commonly encountered in mechanical systems, such as compliance, delay, and actuator and sensor saturation. Builds on knowledge of high-level computational programming language such as Matlab or Simulink.

EMA 105

Prepares students to operate Unmanned Aircraft Systems (UAS) for commercial purposes. Focuses on remote sensing, automation / artificial intelligence, data analytics and business applications / opportunities for UAS. Teaches all applicable subjects and provides hands-on experience necessary to 1) safely, legally and ethically operate UAS for commercial purposes; 2) effectively apply UAS to solve business problems and 3) manage, process and analyze data collected via UAS. Optional Federal Aviation Administration exam for a remote pilot-in-command (RPIC) certification. Group projects involving real-world drone flights to collect data and produce commercially viable products.

ME 578

Modeling, control, perception, and navigation of autonomous marine robots, including Autonomous Surface Vehicles (ASVs) and Autonomous Underwater Vehicles (AUVs). Core topics include kinematics, dynamics, optimal control, state estimation, perception, communication, and guidance tailored for marine robotic systems. Development and testing of dynamic models, controllers, and perception algorithms on simulated/real marine robot platforms.

ME 738

Rigid body models of robots, constraints and contact, motion planning methods including sampling based, trajectory optimizations, state estimation algorithms including linear observers and filters, Kalman filters, optimization-based filters, feedback control methods including linear controls, Impedance Control, optimization-based controllers, Differential Dynamic Programming, Lyapunov Analysis and Design, and Underactuations. Knowledge of robotic systems [such asE C E/​M E  439andE C E/​M E  441] is strongly recommended.

ME 445

Fundamentals of electromechanical control systems with a focus on subsystem design and their impacts at the system level. Integration of microcontrollers into products for control and/or instrumentation. Creation of intelligent interfaces between motors and sensors. C programming. Control computer system architecture Software and hardware principles for computer control.