Introduces modeling, analysis, and control of dynamic systems, using ordinary differential and difference equations. Emphasizes the properties of mathematical representations of systems, the methods used to analyze mathematical models, and the translation of concrete situations into appropriate mathematical forms. Primary coverage includes ordinary linear differential and difference equation models, transform methods and concepts from classical control theory, state-variable methods and concepts from modern control theory, and continuous system simulation. Applications are drawn from social, economic, managerial, and physical systems. Cross-listed as MAE 6620. Prerequisite: APMA 2130 or equivalent.

A case-based approach to the design of user interfaces with a focus on iterative project experiences. Display design concepts are related to ecological factors, situational awareness, attention, vision, and information processing. Project cases are tied to real-world problems of decision support on mobile platforms, large scale command and control, and data visualization, among others. Graduate version includes 4-5 advanced discussion sessions.

For master's students.

Special Topics in Distance Learning

This course is designed to develop cross-competency in the technical, analytical, and professional capabilities necessary for the emerging field of Cyber-Physical Systems (CPS). It provides convergence learning activities based around the applications, technologies, and system designs of CPS as well as exploring the ethical, social, and policy dimensions of CPS work. The course also emphasizes the importance of communication as a necessary skill.

Detailed study of graduate course material on an independent basis under the guidance of a faculty member.

Formal record of student commitment to project research under the guidance of a faculty advisor. Registration may be repeated as necessary.

Bayesian theory of forecasting and decision making; judgmental procedures and statistical models for probabilistic forecasting, post-processors of deterministic forecasts; sufficient comparisons of forecasters, verification of forecasts, combining forecasts; optimal decision models using probabilistic forecasts including static decision models, sequential decision models, stopping-control models; economic value of forecasts. Prerequisite: SYS 6005 or STAT 6190.

Weekly meeting of graduate students and faculty for presentation and discussion of contemporary systems engineering problems and research. This seminar is offered every spring and fall semesters.

Detailed study of graduate course material on an independent basis under the guidance of a faculty member.