Quantized Model-Free Adaptive Control for a Class of MIMO Nonlinear Systems

To solve the problem that the quantization process of data transmission in the network brings bad influence into the control system, this paper develops a quantized model-free adaptive control (QMFAC) algorithm for the multi-input multioutput (MIMO) networked control system. Firstly, an encodingdecoding mechanism capable of attenuating quantization error is studied. Then, a QMFAC algorithm is proposed, which adds the data quantization process for the system outputs and output difference values to the control loop. By this design, the quantization error cannot propagate and accumulate during the progress of decoding, so the adverse effect of the quantification process on the control system can be reduced. Moreover, the convergence of the QMFAC algorithm is verified by the contraction mapping and Gershgorin circle theorems. Finally, numerical simulations of a networked control system and a threetank remote water level control system are carried out to test and verify the proposed QMFAC algorithm.