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Dr. Greg Luecke


Dr. Luecke has been an innovator in coupling a solid background in theoretical dynamics and controls with a hands-on component in the laboratory.  “Theory is fine, but in the real world, each parameter, each block in the diagram, and each signal line has a physical counterpart.  Until you understand each of these the model and control system will not work.”

blueball.gif (324 bytes)ME 310 - Kinematics

Four-bar linkages, Vector loop equations, Position, Rate, and Acceleration analysis of Machines.  MATLAB programming.

blueball.gif (324 bytes)ME 311 - Mechanical Systems

Modeling and simulation of mechanical systems. Development of equations of motion and dynamic response characteristics.  Fundamentals of classical controls applications, including mathematical analysis and design of closed loop control systems.  Introduction to computer interfacing for data acquisition and control. Laboratory exercises for hands-on motion and control implementation

blueball.gif (324 bytes)ME 370Engineering Measurements

Fundamentals of design, selection, and operation of components of measuring systems. Measurement processes, data acquisition systems, analysis of data, and propagation of measurement uncertainty.

blueball.gif (324 bytes)ME 410X - Mechatronic Systems-An exciting new course developed by Dr. Luecke!

The fundamentals of sensor characterization, signal conditioning, and motion control are coupled with the concept of embedded computer control.  Digital and analog components used for interfacing with computer controlled systems.  Mechanical system analysis, combined with various control approaches.  Focus on automation of hydraulic actuation processes.  Laboratory exercises provide hands-on development of mechanical system.

This course provides the basic knowledge required to understand and analyze mechanical systems.  It provides the students with practice in designing systems to accomplish desired objectives.  This course provides open ended design problems that require establishment of reasonable engineering assumptions and realistic constraints.  The laboratory component teaches the students to work effectively in teams on problems that cross content boundaries.

blueball.gif (324 bytes)ME 411 - Automatic Control

Modeling and simulation of mechanical, electrical, fluid, and/or thermal systems. Development of equations of motion and dynamic response characteristics in time and frequency domains. Fundamentals of classical control applications, including mathematical analysis and design for closed loop control systems. Introduction to computer interfacing for simulation, data acquisition, and control. Laboratory exercises for hands-on system investigation and control implementation..

blueball.gif (324 bytes)ME 415Mechanical Systems Design

Mechanical Engineering Capstone Design course. Team approach to solving design problems involving mechanical systems. Teams will use current design practices they will encounter in industry. Document decisions concerning form and function, material specification, manufacturing methods, safety, cost, and conformance with codes and standards. Solution description includes oral and written reports. Projects often worked with industry sponsors.

blueball.gif (324 bytes)ME 418 - Mechanical Considerations in Robotics

Three dimensional kinematics, dynamics, and control of robot manipulators, hardware elements and sensors. Laboratory Experiments and demonstrations using industrial robots.

blueball.gif (324 bytes)ME 511 - Advanced Control Design

Application of control design methods using continuous, discrete, and frequency-based models. Approaches include classical, pole assignment, model reference, internal model, and adaptive control methods. Mechanical design projects.

blueball.gif (324 bytes)ME 513X - Advanced Control of Robotic Systems – A great new technical course developed by Dr. Luecke!

An introduction to the fundamentals of dynamics and control for a variety of robotic mechanisms.  This course develops control techniques for application to Multi-Input-Multi-Output systems using linear, nonlinear, and adaptive approaches.  Control is developed and implemented for position, velocity, and force commands. Computer simulation is used for dynamic analysis of robotic systems, and for the development and implementation of various control schemes.  Current methods in the literature are examined and analyzed.