Intelligent control of an experimental articulated leg for a galloping machine

Abstract

Intelligent controllers are being used with increasing effectiveness on complex systems. This work verifies the effectiveness of fuzzy control, an intelligent method, on a single, articulated-leg that was designed to be used on a high-speed galloping quadruped. Intelligent methods are compared to other control methods in simulation and on the OSU DASH (Dynamic Articulated Structure for High-performance) leg. It is shown that the intelligent controllers outperform non-learning methods. Using fuzzy control, the OSU DASH leg performs stable hopping on a treadmill moving at 2.0 m/s.