• Fuzzy logic for control.
  • Neural nets for control.
  • Implement controller with programmable logic
  • Optimal control.
  • DSP processors, and their use in control systems.
  • Control of non-linear systems.
  • Adaptive control.
  • Efficient computer implementation of discrete controllers
  • Examine a specific system and design and implement a controller.
  • Derive Mason’s gain formula.
  • Derive the Routh-Hurwitz criterion.
  • Derive relationships for observability and/or controllability.
  • Derive Ackerman’s formula
  • Control a “Satellite” system
  • Control a gantry crane or inverted pendulum.
  • Resurrect and control a ball-and-beam experiment

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