Fiber optic gyroscope (FOG) is one of the important components of Inertial Navigation Systems (INS). In order to improve the accuracy of the INS, it is necessary to suppress the random error of the FOG signal. In this paper, a variational mode decomposition (VMD) denoising method based on beetle swarm antenna search (BSAS) algorithm is proposed to reduce the noise in FOG signal. Firstly, the BSAS algorithm is introduced in detail. Then, the permutation entropy of the band-limited intrinsic mode functions (BLIMFs) is taken as the optimization index, and two key parameters of VMD algorithm, including decomposition mode number K and quadratic penalty factor $\alpha$ , are optimized by using the BSAS algorithm. Next, a new method based on Hausdorff distance (HD) between the probability density function (PDF) of all BLIMFs and that of the original signal is proposed in this paper to determine the relevant modes. Finally, the selected BLIMF components are reconstructed to get the denoised signal. In addition, the simulation results show that the proposed scheme is better than the existing schemes in terms of noise reduction performance. Two experiments further demonstrate the priority of the proposed scheme in the FOG noise reduction compared with other schemes.

Disturbance from luminance variation in the identification of visual sensors causes instability in the control system of target tracking, which leads to field of vision (FOV) motion and even the target missing. To solve this problem, a linear active disturbance reject controller (LADRC) is adopted to the visual tracking and inertial stable platform (VTISP) for the first time to improve the system’s robustness. As a result, the random disturbance from identification can be smoothed by the tracking differentiator (TD).An improved linear extended state observer (LESO) modified by the TD is provided to obtain the high-order state variables for feedback. That makes the system avoid noise in a differential process from the MEMS gyroscope and enhances the response time and stability in tracking control. Finally, simulation and experimental studies are conducted, and the feasibility of the LADRC is verified. Moreover, compared with the other controller in the VTISP for remote sensing, the superiority of the LADRC in system response time and stability is proved by the experiments.

This paper investigates an anticipatory activation anti-windup approach based on Linear Active Disturbance Rejection Control (LADRC) to address the influences of accelerated saturation on the actuators in a Miniaturized Inertial Stabilized Platform (MISP) with extreme external disturbance. The proposed method aims to eliminate the high-frequency vibrations on the Line of Sight (LOS) of electro-optical devices during actuator saturation. To achieve this, the Linear Extended State Observer (LESO) is modified by adding saturation feedback to the total disturbance observed state variable, which is operated as an anticipatory activation anti-windup compensator. The stability of the proposed controller is discussed, and the gains are optimized by the Linear Matrix Inequality (LMI) constraints though quadratic programming and an H-infinite performance indicator. Additionally, as the multiple activated scheme for anti-windup, the effectiveness of immediate activation in dealing with accelerated saturation is compared and analyzed. These comparisons and verification are implemented through simulations, where the external disturbance is introduced using recorded attitude data from USV sailing. Finally, experiments are conducted on an MISP for a visual tracking system, demonstrating that the anticipatory activation mothed effectively suppresses high-frequency vibrations on the LOS during instances of accelerated saturation.

A feedforward strap-down control with a compensator base on the linear extended state observer (LESO) is proposed for a miniaturized camera stabilized platform, which reduces the influence of the dead zone in speed regulation and uncertainties in parameters to reduce the level of angular bias to the field of vision (FOV) in a low-cost stabilized platform. Firstly, the feedforward control is inspired by an approximate linear model proposed for the dead zone to improve the response velocity of the system when tracking the varying reference. Then, the compensator, combining the LESO and proportional differential (PD) law, is designed to eliminate the disturbances including the model bias in the dead zone, inaccuracy in the plant model, and external disturbance. Moreover, the observation performance of the LESO is improved by a preprocessor based on a tracking differentiator (TD) to deal with the time delay and nonlinearities in sampling the state variables. Meanwhile, the complex and uncertain control plant is also simplified by an approximate model combining a disturbance compensator for practical application. Finally, the feasibility of the proposed controller is verified and analyzed by the simulation, and its effectiveness is simultaneously validated by the 2-DOF camera stabilized platform.