Satisficing control remains an important concept in decision making. In this paper, a new epistemic utility satisficing control theory is proposed for a new model of complex CMMO (constrained multi-objective multi degree-of-freedom optimization) system. As well, an epistemic utility function is developed and used to adjust the feasible region of soft constraints. The theory proved in this paper indicates that the utility function not only expresses the subjectivity of the original satisfactory-degree function, but also takes the cost of searching for a solution into account. Thus, the satisfactory-degree function can be adjusted and its rationality can be validated. This theory contributes an analytical method to the inverse satisfactory optimization problem. The findings indicate that this theory has good convergence and outcomes desired for satisfactory-degree functions.