Intelligent robust control of a robotic unicycle based on a new physical measure for mechanical controllability

The posture stability driving control of a human riding-type unicycle has b een realized. The robotic unicycle is considered as a biomechanical system using an internal world representation with a description of emotion, insti nct and intuition mechanisms. We introduced intelligent control methods bas ed on soft computing, and confirmed that such an intelligent control and bi ological instinct as well as intuition together with a fuzzy inference is v ery important for emulating human behaviors or actions. For the fitness fun ction of the generic algorithm, a new physical measure of the minimum entro py production for a description of the intelligent behavior in a biological model is introduced. The calculation of robustness and controllability of the robotic unicycle is presented. This paper provides a general measure to estimate the mechanical controllability both qualitatively and quantitativ ely, even if any control scheme is applied. The measure can be computed usi ng a Lyapunov function coupled with the thermodynamic entropy change. Fuzzy simulation and experimental results of a robust intelligent control motion for the robotic unicycle are discussed.