Trajectory tracking control of unconstrained objects based on the SIRMs dynamically connected fuzzy inference model

A trajectory tracking experiment system taking a table-tennis ball as control object is constructed, and a fuzzy controller based on the SIRMs dynamically connected fuzzy inference model is proposed. The fuzzy controller defines a SIRM and an importance degree for each input item. Especially for the input item of velocity, its importance degree is tuned dynamically according to the moving condition. The summation of the products of the importance degree and the fuzzy inference result of the SIRMs is calculated to control the angles of a table with level surface, making the ball on the table move along a desired trajectory. The maximum tracking error in more than 80% of the experiments on two kinds of circles is less than 0.05 m, and the sampling steps necessary for tracking one cycle in an experiment almost keep constant.