Pennsylvania State University 4 credits EE
This course presents both classical and modern approaches to modeling, analysis, and design of control systems for continuous time systems. Students learn how to model both mechanical and electrical systems in the time and frequency domains using differential equations, transfer functions, state space methods and frequency domain (Bode) techniques. Modeling is followed by an in-depth study of systems analysis, including stability, transient response and steady state characteristics. The study of stability involves examining the effects of pole and zero placement, and the Routh criterion is used extensively. In the consideration of transient response characteristics, students investigate rise time, peak time, overshoot, and settling time. The primary steady state feature studied is the error between the reference signal input and the system output, and students learn to characterize steady state error through the determination of system type and computation of the error constants. Design of control systems focuses on altering one or more of the system characteristics by adding compensation. Students employ a variety of root locus techniques as well as proportional-integral-derivative (PID), state feedback, and frequency response methods. Students begin with simple proportional, closed-loop control and examine pole migration through root locus plots. They then learn to apply more robust pole placement techniques using proportional and derivated (PD) control. Next, PID controllers are examined with a number of opportunities for design. After learning the classical control techniques, students then concentrate on state feedback control methods, including the design of partial- and full-order observers. Finally, students learn the relationship between time domain analysis and design and frequency domain (Bode) analysis of both magnitude and phase. This course includes a laboratory in which students use MATLAB and Simulink for modeling, analysis and control system design. To be successful in this course, students should have a solid background in differential equations, Laplace transform techniques, Bode analysis, linear algebra, complex variables, and they should have a familiarity with MATLAB.
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