Multi‐actuator control with modal switching and different disturbance for scanning imaging motion compensation

Abstract

Scanning imaging can be used to obtain wide field-of-view, high-resolution remote-sensing images with a telescope lens. However, the motion between the image and the sensor causes blurring during scanning, which reduces the image quality. In this paper, a motion compensation method based on multi-actuator control with modal switching is proposed. In this method, the tracking controller realizes scanning and compensation; the cooperative controller reduces the relative motion that causes motion blur, and modal switching solves the travel limitation of the linear actuator. Further, to improve the control performance, an adaptive sliding mode controller is proposed and combined with a disturbance observer. The stability theorems for multi-actuator and modal switching are studied. Experimental results show that the accuracy, robustness, and frame rate of the proposed method improved compared with those of traditional methods. Compared with the non-cooperative structure using a PD controller, the root mean square error is reduced by 76.61%.

Distributed online adaptive subgradient optimization with dynamic bound of learning rate over time‐varying networks

“…Online convex optimization, as an effective measure to handle various scientific and engineering tasks such as blast furnace ironmaking [1], electric vehicle charging [2], signal processing [3], image processing [4] and automatic control [5], has been greatly concerned by researchers. Online convex optimization means that the real‐time loss of agent is generated by adversary after agent takes action.…”