The aim of this work was to study the color matching model based on chaos theory, particle swarm optimization algorithm, fuzzy clustering and artificial neural network. Particle swarm optimization algorithm was improved by the combined use of chaos theory and adaptive strategy, obtaining the chaotic self-adaptive particle swarm optimization algorithm. The algorithm was then used to optimize the hidden centers, spreads and weights of radial basis function artificial neural network. Fuzzy clustering was used to classify the sample data, to obtain the CSAPSO RBF ANN model, which was then compared with other color matching methods. The average absolute deviation, mean square error and color difference of CSAPSO RBF ANN were 0.0106, 0.000 96 and 1.9122, respectively. The performance of CSAPSO RBF ANN model for color matching was superior with good universality, versatility and generalization ability.