On Disturbance Rejection Control of Servo System Based on the Improved Disturbance Observer

Active Vibration Isolation of a Maglev Inertially Stabilized Platform Based on an Improved Linear Extended State Observer

“…To accelerate the convergence rate and improve the error accuracy with suitable gain, this paper adopts a method based on the track error of each order to enhance the estimation accuracy of LESO [28] , which can meet the accurate compensation requirements of the active vibration isolation control system of a MISP. The improved LESO is given as: Therefore, the equation for track error can be expressed as: (25) where it is noted that = 4 and 2 , 3 can be rewritten as: As long as the roots of (30) have negative real parts, the stability and convergence of will be guaranteed. According to Routh-Hurwitz conditions, the parameters to be met are as follows: Finally, the boundary of track errors can be given as: In contrast to the boundary of track errors with the improved linear extended state observer, the boundary of track errors ′ with the traditional LESO applied in the MISP control system can be obtained (with identical gain) and expressed as: proposed method is controlled by adjusting gain parameters based on the stability of the system.…”

“…In this paper, we address the suppression effect for low-frequency vibrations on a MISP. An improved linear extended state observer [25][26][27][28] is designed to estimate the dynamic input vibration, which uses next-order error to substitute the first-order error (displacement error) to speed up the convergence, and the observation error is reduced significantly, which is theoretically deduced and proven. In addition, a vibration isolation controller is built to compensate for the input vibration and eliminate the adverse effects of input vibration.…”

Anti-Inertia Disturbance Control of Permanent Magnet Synchronous Motor Based on Integral Time-Varying Fast Terminal Sliding Mode

“…Currently, numerous researchers have proposed equally numerous methods in antiinertia disturbance, such as PI control [1][2][3][4], adaptive control [5][6][7][8], intelligent control [9][10][11][12], fuzzy control [13][14][15], predictive control [16][17][18], and sliding mode control [19][20][21][22][23][24], among others. Their methods are mainly divided into two categories: added observers and no observers.…”

“…Although the effectiveness of the method can be verified by experiments, simple PI parameter adjustments cannot meet the complex parameter changes of multivariate systems. Other studies [3,4] also identify and compensate for the disturbance inertia using the inertia disturbance observer established by the Kalman filter. Said compensation system has good anti-inertia disturbance performance and robustness, but its adjustment of PI parameters still cannot meet the complex parameter change requirements.…”