Implementing Fuzzy Logic in the Control of a Biologically Inspired Robotic Cat Leg

This research discusses the implementation of a fuzzy logic control system to drive the movement of a simplified cat leg model. The system’s movement in this paper addresses a planar motion where the model experiences a fixed horizontal velocity and a harmonic vertical displacement. The fuzzy logic (FL) controller applies membership functions to fuzzify the position and velocity errors and applies height defuzzification to generate the time dependant forcing function for the system’s horizontal and vertical governing equations. A PID controller is also applied as a benchmark for this research. Both controllers are optimized using the simplex method for which the FL controller performed just as well as the PID controller with more promise of accounting for the nonlinear influences that were neglected in this simplified cat leg model and requiring actuators with a lower required force range. This research provides the skeletal structure for which an effective total controller can be built on.