High utility itemset mining is the process of producing itemsets that generate high profits. Mining regular high utility itemsets are to discover all high utility itemsets that appear regularly in static databases. In some real-world applications, the itemsets' occurrence behavior may be changed significantly by inserting new transactions into the original database. Regular high utility itemsets mining methods for static databases cannot be applied to incremental databases. An efficient method called RHUINC miner (Regular High Utility Itemset mining for the incremental database) is proposed for discovering regular high utility itemsets from incremental databases. It uses uList structure to avoid the creation of unpromising itemsets. Using uList, it can maintain the itemsets information and provide efficient strategies to generate regular high utility itemsets. Experimental results show that the proposed algorithm is efficient in terms of runtime and memory utilization.