No: EE 449
Title: DESIGN OF AUTOMATIC CONTROL SYSTEMS
Credits: 4
Coordinator: Blake Hannaford, Professor of Electrical Engineering
Goals: To give students the opportunity to experience the entire design cycle for designing automatic feedback control systems.
Learning Objectives:
At the end of this course, students will be able to:
Textbook: None
Reference Texts: Modern Control Systems, R.C. Dorf & R.H. Bishop, 8th ed, Addison Wesley, 1998; Measurement Systems, Applications and Design, E.O. Doebelin, 4th ed, McGraw-Hill, 1990
Prerequisites by Topic:
Topics:
The course is a major team design experience focused on applying control engineering theory and practice to satisfy customer requirements. Projects are offered by outside "customers" recruited by the instructor from within or outside the university. Projects must meet the following requirements:
Project Roadmaps:
Design projects are undertaken for a wide variety of reasons but the design process is essentially the same. At one level, they all follow the same five steps:
At the next level of detail, different kind of projects perform these steps differently. EE449 students have a variety of career goals and interests, so four roadmaps are available to the students to organize the process from different points of view.
Each project group must choose one roadmap and stick with it throughout the quarter. There are deliverables every two weeks in the form of written reports and presentations. The style and overall outline of the report will be the same for each group, but the content will be different depending on their project topic and selected roadmap.
Course Structure: The class meets for up to two lectures a week. Lectures include frequent student presentations.
Computer Resources: The class requires access to PCs or workstations supporting MATLAB and the Control Toolbox.
Laboratory Resources: Access to electronics assembly benches and equipment, lab instrumentation as noted in "topics" above, experimental stations incorporating various elements (e.g. the inverted pendulum laboratory experiment). The Control and Robotic Systems Laboratory supports the class.
Grading: 70% laboratory reports, 20% in-class presentations, 10% instructor discretion.
Outcome Coverage:
(a) An ability to apply knowledge of mathematics, science and engineering. Modeling and analysis of feedback control systems requires application of ordinary differential equations, transform methods, and complex analysis techniques. Engineering and science knowledge is required for systems modeling, covering classical mechanics and electromagnetic theory. (H)
(b) An ability to design and conduct experiments, as well as to analyze and interpret data. Each of the laboratory experiments requires the students to execute all these tasks. Students study and implement the mechanics of control system design: how to postulate a control structure (architecture), perform trade off studies, create simulations in the workstation environment, perform sensitivity studies. They increase their proficiency with current state-of-the-art computer aided design tools. Students validate a design using hardware-in-the-loop simulations. (H)
(c) an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, social, political, ethical, health and safety, manufacturability, and sustainability. Each design project has a human customer who applies real-world constraints on the students' project plans and design activities. Students engage in budget planning within available actual resources and safety analysis. (H)
(d) An ability to function on multi-disciplinary teams. The class is joint listed with Aeronautics and Astronautics. Usually a few mechanical engineering students take the class as well. All experiments are done by teams of AA, EE and ME students. (M)
(e) An ability to identify, formulate and solve engineering problems. All experiments pose typical engineering problems that a control systems engineer must solve. Students must think critically about what appropriate models are, what features of the system they can ignore and what they can't. Students analyze models to determine system properties. Students determine what parameters they need to know, how these are defined, what options they have for measuring the actual parameter values, and the accuracy of the resulting values. (H)
(f)An understanding of professional and ethical responsibilities. Students must complete their project for a "customer", who is usually a principle investigator at the university. Ethical responsibilities to customers in terms of truthful reporting of results, use of the customer's funds and resources, etc. will be addressed. (M)
(g) An ability to communicate effectively. Oral presentations, written reports and team communication. Students also prepare documentation for hardware control systems. (M)
(k) An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice. Students use MATLAB and an associated control system toolbox to solve problems and to support the experimental data analysis and presentation of results. The students also use Digital Signal Analyzers for real time data analysis and validate a design using hardware-in-the-loop simulations. (H)
ABET Criterion 4 Considerations
Engineering standards - Students must develop their laboratory design projects to meet specific performance specifications, some of which include benchmark testing or compliance testing against accepted standards for performance and safety. In EE449, both accepted standards and safety are typically achieved by achieving damping ratios between 0.5 and 1.0 in closed loop step response. However specific performance standards and safety criteria are developed by each design team in conjunction with their customers.
Realistic constraints - Each of the laboratory design projects, in addition to having explicit electrical performance specifications, is fundamentally phrased and graded in terms of the final solution's size, weight, cost, power consumption, alignment ease, component variability, and manufacturability criteria. These criteria are also determined at the project requirements definition phase in conjunction with the team customer.
Prepared By: Blake Hannaford
Last revised: 4/19/10