  In this brief, a model-free adaptive predictive control (MFAPC) is proposed.
It outperforms the current model-free adaptive control (MFAC) for not only
solving the time delay problem in multiple-input multiple-output (MIMO) systems
but also relaxing the current rigorous assumptions for sake of a wider
applicable range. The most attractive merit of the proposed controller is that
the controller design, performance analysis and applications are easy for
engineers to realize. Furthermore, the problem of how to choose the matrix
{\lambda} is finished by analyzing the function of the closed-loop poles rather
than the previous contraction mapping method. Additionally, in view of the
nonlinear modeling capability and adaptability of neural networks (NNs), we
combine these two classes of algorithms together. The feasibility and several
interesting results of the proposed method are shown in simulations.
