Gimbal control of inertially stabilized platform for airborne remote sensing system based on adaptive RBFNN feedback model. (June 2021)

• Record Type: Journal Article
• Authors: Xiang, Biao; Mu, Quanqi
• Is Part Of: IFAC journal of systems and control. Volume 16(2021)
• Publication Date: 2021-06
• Subjects: Inertially stabilized platform -- Adaptive control -- Attitude stabilization precision -- State feedback control; Automatic control -- Periodicals; Relay control systems -- Periodicals; Embedded computer systems -- Periodicals; Feedback control systems -- Periodicals; Artificial intelligence -- Periodicals; Artificial intelligence; Automatic control; Embedded computer systems; Feedback control systems; Relay control systems; Electronic journals; Periodicals; 629.89
• DOI: 10.1016/j.ifacsc.2021.100148
• Languages: English
• ISSNs: 2468-6018

Abstract

Abstract: The attitude stabilization precision of inertially stabilized platform (ISP) directly affect the resolution of remote sensing image by stabilizing the airborne remote sensing system and holding the line of sight. Therefore, an adaptive control model based on radial basis function neural network (RBFNN) is designed to improve the attitude stabilization precision of ISP gimbal in this article. The adaptive control law and the RBFNN weight adaptive law are designed based on the Lyapunov stability theorem, and the inputs of state feedback control and disturbance observer are combined into the control input. Both simulation and experimental results indicate that the adaptive control based on RBFNN can improve the attitude stabilization precision of ISP gimbal compared to the state feedback control.