Data-Driven Adaptive Predictive Control Method With Autotuned Weighting Factor for Nonlinear Systems Using Triangular Dynamic Linearization

Abstract

Dear Editor, In this letter, a novel data-driven adaptive predictive control method is proposed using the triangular dynamic linearization technique. The proposed method only contains one time-varying parameter with explicit physical meaning, which can prevent severe deviation in parameter estimation. Specifically, a triangular dynamic linearization (TDL) data model is employed to predict future system outputs, and then to correct inaccurate predictive outputs, a feedback regulator is designed. An autotuned weighing factor is introduced to alleviate the computational burden in practical applications and further improve output tracking performance. Closed-loop stability conditions are derived by rigorous analysis. Simulation results are provided to demonstrate the efficacy of the proposed method.