Optimal fuzzy reasoning methods based on robust goals/constraints

Different from the dominant view of treating fuzzy reasoning as generalization of classical logical inference, fuzzy reasoning may be treated as an optimization problem. Several optimal fuzzy reasoning methods had been presented in previous papers based on different reasoning goals/constraints, which mean the fuzzy relation gained from fuzzy premise and fuzzy consequence should be closest to that from rules. In this paper, reasoning goals/constraints on robustness are introduced into fuzzy reasoning. Simulation results display that the robust fuzzy reasoning methods can be used for modeling and control of complex systems and for decision-making under complex environments.