Dynamic-quantization-based Model-free Adaptive Privacy Preservation Control for Unknown Nonlinear Systems with Time Delays

A dynamic-quantization-based model-free adaptive privacy preservation control (DQ-MFAPPC) scheme is proposed for nonlinear nonaffine systems with time delays. By using the dynamic linearization tool, a linearized dynamic data model is developed in this work using I/O data to deal with the unknown dynamics. Then, the DQ-MFAPPC is proposed with both a dynamic-quantization-based privacy preservation scheme and a Smith predictor incorporating the tracking differentiator. The preserved output data is used in both the control law and the parameter updating law, which enhance the robustness. The proposed DQ-MFAPPC method with data-driven feature not only can address the time delays, but also has the capbility of preserving the data privacy under the limited communication resource. The simulation results demonstrate the effectiveness of the presented DQ-MFAPPC.