Data-driven Closed-loop Update Tuning Taking Account of Stability Margin

The paper proposes a data-driven parameter tuning based on closed-loop update law. The proposed method is derived from a closed-loop update law due to controller parameter tuning. Thus, the proposed method is called the Data-driven Closed-loop Update Tuning (DD-CLUT). The DD-CLUT explicitly characterizes the closed-loop system after updating controller parameters. The paper provides a design method for the DD-CLUT that takes account of stability margin by way of solving a quadratic programming problem with a constraint that ${\mathcal{H}_\infty }$ norm of the sensitivity function is less than a prescribed level. The paper also shows the proposed method can be reduced into a semi-definite programming problem with constraints expressed by several LMIs (Linear Matrix Inequality). The effectiveness is demonstrated through a numerical example.