A multiobjective control problem has been handled in many different ways such as fuzzy, neural network and reinforcement learning, etc. Among them, a reinforcement learning method solves a multiobjective control problem without any prior knowledge. In this article, a new reinforcement learning method for a multiobjective control problem is proposed in consideration of it.,, convergence. The proposed method, in which objective eligibility is considered for handling multirewards, reformulates a multiobjective control problem in a form of a reinforcement learning problem under non-Markov environment. Using a similar relation to eligibility. the proposed method dealt with the previous research results of eligibility and A as implemented with the concept of a decoupled fuzzy sliding mode control (DFSMC). (C) 2003 Wiley Periodicals, Inc.