Self-Position Control of Unmanned Vehicle Using Online System Identification

Abstract This paper presents a real-time system identification method for unmanned ground vehicle (UGV) using a System Identification (SI) approach. The online System Identification approach is introduced to select and estimate the significant parameters of unmanned systems, thereby enhancing the dynamic performance of an adaptive control system. The technique is demonstrated using a rover vehicle. A Recursive-Least-Square (RLS) algorithm is applied to estimate the unknown parameters. Additionally, a self-position controller based on continuous estimation of rover parameters is designed and evaluated. The simulation results show that the developed model using SI satisfies the rover model. Moreover, the developed self-position controller has a high performance.