This course provides a practical introduction to the modeling and design of control systems for a variety of applications. It provides the basis for an intuitive understanding of how control can change the behavior of physical systems, making them respond faster and more accurately, reducing vibration, etc. The course also provides quantitative tools for design to achieve specified levels of improved performance.

Two widely used modeling techniques are introduced and used to develop models of laboratory hardware, which will then be placed under control systems designed in subsequent laboratory projects.

The two main control design techniques, frequency domain and state space methods, will be introduced and used to design control systems for laboratory hardware.

As an undergraduate course, it provides an in-depth treatment of control system topics touched on in earlier course (ASEN 2003, ASEN 3200, ASEN 3128). As a graduate course, it provides a practical complement to the theory of Linear Systems found in ASEN 5014.

After taking this course, you should be able to:

• Physical System Modeling
  1. model physical systems using Lagrangian dynamics.
  2. model physical systems using interconnected 2-terminal elements.
  3. convert between state space and transfer function models; use block diagrams to describe an interconnected system.
  4. determine a system's natural (free) response given initial conditions, and the system's forced response to a given input.
• Frequency Domain Control Design
  1. determine a system's frequency response, and describe how an input signal has its frequency spectrum altered (filtered) as it passes through the system.
  2. use Bode and Nyquist plots to determine feedback control loop stability and closed loop performance.
  3. design lead/lag compensation to achieve specified closed loop bandwidth and stability margins.
• State Space Control Design
  1. test a state space system for controllability and use state variable feedback to place closed loop poles.
  2. test a state space system for observability and design an observer to recover internal state.
• Simulation and Implementation
  1. simulate transfer function and state space models in MATLAB/SIMULINK.
  2. implement control system designs in laboratory hardware using Labview and evaluate closed loop performance.
  3. understand how practical effects limit achievable control system stability and performance.