Comparison of Linear Quadratic Gaussian and Recent Methods for 4-Wheel Independent Steering State Space Model

In this study, we designed a disturbance observer (DOB) and linear quadratic Gaussian (LQG) filter for 4-wheel independent steering systems considering a state space model. First, the state space structure of a 4-wheel independent steering system was defined. Second, a DOB and Kalman filter problem was designed by estimating the sideslip angle of the 4-wheel state space model. The two design processes were compared based on the estimation results; the LQG method outperformed the DOB method by changing the Kalman filter gain via the observer and controller eigenvalue separation principle.