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In this brief, a model-free adaptive predictive control (MFAPC) is proposed.It outperforms the current model-free adaptive control (MFAC) for not onlysolving the time delay problem in multiple-input multiple-output (MIMO) systemsbut also relaxing the current rigorous assumptions for sake of a widerapplicable range. The most attractive merit of the proposed controller is thatthe controller design, performance analysis and applications are easy forengineers to realize. Furthermore, the problem of how to choose the matrix{\lambda} is finished by analyzing the function of the closed-loop poles ratherthan the previous contraction mapping method. Additionally, in view of thenonlinear modeling capability and adaptability of neural networks (NNs), wecombine these two classes of algorithms together. The feasibility and severalinteresting results of the proposed method are shown in simulations.

A New Model-Free Method Combined with Neural Networks for MIMO Systems