Detection of transition to chaos during stability roughness smoothing of a robot arm

We introduce in this paper an online transition detection method of degradation of control predictability to robotic systems which can behave chaotically depending on the variations of the control parameter. This method allows us to control such systems at the boundary of the chaotic region until the onset of degradation thus allowing us to use the whole richness of information for control. In our approach, a safe control parameter interval is chosen initially where the system is certainly nonchaotic and the system behavior is initiated The maximum Lyapunov exponents corresponding to each parameter value are estimated online. The parameter interval is then widened according to the estimated exponents until the maximum exponent approaches a small negative value. At this value, the estimation is ended and the controller begins to work in this maximum possible controller parameter interval. This method allows the designer to have a more efficient controller and a more agile system. This approach is applied to a robot arm under dynamic load.