In this paper, a design method of neural-net based PID controllers is proposed for multivariable nonlinear systems with mutual interactions. The proposed method adopt both a static pre-compensator and some multi-layered neural networks. The former is used for roughly decoupling the controlled object, and the latter is used in order to improve decoupling and to linearize the approximately decoupled controlled object. Also the design scheme based on the relationship between PID law and the generalized minimum variance control (GMVC) law is adopted. The effectivenes of the proposed control scheme is evaluated on a simulation example.