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Fractional-Order Control for Two-Legged Dynamic Walking

  • Graduate Student: Kevin Leyden
  • Principal Investigator: Dr. Bill Goodwine
  • Funding: National Science Foundation
  • Goal: To improve efficiency in walking robots by leveraging a novel control strategy

This research seeks greater efficiency for walking robots. Efficiency can be improved in two ways: better performance (i.e. less wasted motion) and reduced energy consumption. Fractional-order control is a pathway to both of these improvements because of the flexibility it offers in designing a control strategy.

Compared to the existing proportional-derivative architecture, changing the order of the derivative - the number of derivatives taken - to real numbers other than 1 has yielded both types of improvement for a simulated walker. The evidence of better performance is the leg angles' improvement in maintaining a desired relationship with respect to one another. Depending on the controller chosen, the walker can also be made to achieve the original level of performance with reduced control signals and less torque delivered to the hip joint, implying greater energy efficiency.