Adaptive Prescribed-Time Parameter Estimation for Nonlinear Systems with Unknown Switched Parameters - Li, Qiyao; Huang, Yingbo; Chen, Siyu; Na, Jing (Chinese Control Conference, 2024)
This paper proposes an adaptive prescribed-time (PT) parameter estimation method for nonlinear systems subject to unknown switched parameters. The notable feature of the PT parameter estimation is that the estimated parameters can converge to their true values within a finite settling time that can be selected regardless of the initial condition. To achieve the objective, the nonlinear system is first transformed as a linear system with parameter jump behaviour. To address the inherent unknown parameters, a set of auxiliary filtered variables are introduced to extract the parameter error information. Then, a time-varying function concerning on the parameter jump and prescribed convergence time of the estimated parameters is designed. With the obtained parameter estimation error and time-varying function, an adaptive PT parameter estimation algorithm is constructed to guarantee the accuracy and convergence time of the estimated parameters. Theoretical studies are conducted to confirm the convergence of the estimated parameters, and make a comparison between the suggested adaptive law and both finite-time (FT) and fixed-time (FxT) schemes. Numerical simulation results of the parameter estimation performance are provided to verify the effectiveness of the proposed method.