A grey clustering evaluation system for the selection of prescribed performance constraint functions in prescribed performance controllers based on interval grey number measurement is constructed. A comprehensive performance evaluation index system based on finite time convergence characteristics, convergence time, tracking accuracy, maximum anti-interference ability, and comprehensive energy consumption was constructed, and interval grey number was used as the index evaluation measure. The combination weighting method that can integrate the advantages of subjective and objective weighting methods was used to determine the index weights. A grey clustering evaluation method based on the mixed possibility function of center points is constructed for evaluating the comprehensive performance of the controlled system under various prescribed performance constraint functions. An example analysis of trajectory tracking prescribed performance control for a permanent magnet linear motor (PMLM), comparing and evaluating the influence of six prescribed performance constraint functions on the comprehensive performance of trajectory tracking error, verified the effectiveness of the designed evaluation system and the reliability of the evaluation results.