This paper presents the stabilization for positive nonlinear systems using polynomial fuzzy models. To conform better to the practical scenarios that system states are not completely measurable, the static output feedback (SOF) control strategy instead of the state feedback control method is employed to realize the stability and positivity of the positive polynomial fuzzy system (PPFS) with satisfying L₁-induced performance. However, some troublesome problems in analysis and control design will follow, such as the non-convex problem. Fortunately, by doing mathematical tricks, the non-convex problem is skillfully dealt with. Furthermore, the neglect of external disturbances may lead to a great negative impact on the performance of positive systems. For the sake of guaranteeing the asymptotic stability and positivity under the satisfaction of the optimal performance of the PPFS, it is significant to take the L₁-induced performance requirement into consideration as well. In addition, a linear co-positive Lyapunov function is chosen so that the positivity can be extracted well and the stability analysis becomes simple. By using the sum of squares (SOS) technique, the convex stability and positivity conditions in the form of SOS are derived. Eventually, for illustrating the advantages of the proposed method, a simulation example is shown in the simulation section.