In the UAV electro-optical pod of the two-axis four-gimbal, the characteristics of a coarse–fine composite structure and the complexity of dynamics modeling affect the entire system’s high precision control performance. The core goal of this paper is to solve the high precision control of a two-axis four-gimbal electro-optical pod through dynamic modeling and theoretical study. In response to this problem, we used finite element analysis (FEA) and stress study of the key component to design the structure. The gimbals adopt the aerospace material 7075-t3510 aluminum alloy in order to meet the requirements of an ultralight weight of less than 1 kg. According to the Euler rigid body dynamics model, the transmission path and kinematics coupling compensation matrix between the two-axis four-gimbal structures are obtained. The coarse–fine composite self-correction drive equation in the Cartesian system is derived to solve the pre-selection and check problem of the mechatronic under high-precision control. Finally, the modeling method is substituted into the disturbance observer (DOB) disturbance suppression experiment, which can monitor and compensate for the motion coupling between gimbal structures in real time. Results show that the disturbance suppression impact of the DOB method with dynamics model is increased by up to 90% compared to PID (Proportion Integration Differentiation method) and is 25% better than the traditional DOB method.

Coarse–fine composite mechatronic systems face numerous challenges due to the structural complexity and diversification of multi-gimbals. The core goal of this manuscript is to address the issue of the coarse-fine composite mechatronic system stability of a UAV (unmanned aerial vehicle) multi-gimbal electro-optical pod using USM-VCM (ultrasonic motor and voice coil motor) mechatronic design, Euler dynamics modeling, and stability DOB (disturbance observer) control. In response to this problem, a Hall effect electromagnetic circuit and USM-VCM drive acquisition circuit are designed. A Euler dynamics model in the Cartesian coordinate system is built to derive the kinematics coupling compensation matrix and mechanical parameter optimization method between the gimbals. Finally, the model is substituted into the DOB suppression control, which can monitor and compensate the motion coupling between the coarse–fine composite mechatronic systems in real time. Results show that the disturbance suppression impact of the DOB method with the Euler optimization model and USM-VCM mechatronic design is increased by up to 90% compared to the PID (proportion integration differentiation) method and 20% better than the traditional DOB method.

A small deviation in the time-delay of the image tracker is essential for improving the tracking precision of an electro-optical system, and for future advances in actuator technology. The core goal of this manuscript is to address issues such as tracking the controller time-delay compensation and the precision of an electro-optical detection system using an advanced filter design, a fire control modeling, and an anti-occlusion target detection system. To address this problem, a small deviation in the time-delay prediction and control method of the image tracker is proposed based on the principle of linear motion transformation. The time-delay error formation is analyzed in detail to reveal the scientific mechanism between the tracking controller feedback and the line-of-sight position correction. An advanced N-step Kalman filtering controller model is established by combining a line-of-sight firing control judgment and a single-sample training anti-occlusion DSST target tracking strategy. Finally, an actuator platform with three degrees of freedom is used to test the optical mechatronics system. The results show that the distribution probability of the line-of-sight measuring error in a circle with a radius of 0.15 mrad is 72%. Compared with the traditional control method, the tracking precision of the optimal method is improved by 58.3%.

Electro-optical detection systems face numerous challenges due to the complexity and difficulty of targeting controls for “low, slow and tiny” moving targets. In this paper, we present an optimal model of an advanced n-step adaptive Kalman filter and gyroscope short-term integration weighting fusion (nKF-Gyro) method with targeting control. A method is put forward to improve the model by adding a spherical coordinate system to design an adaptive Kalman filter to estimate target movements. The targeting error formation is analyzed in detail to reveal the relationship between tracking controller feedback and line-of-sight position correction. Based on the establishment of a targeting control coordinate system for tracking moving targets, a dual closed-loop composite optimization control model is proposed. The outer loop is used for estimating the motion parameters and predicting the future encounter point, while the inner loop is used for compensating the targeting error of various elements in the firing trajectory. Finally, the modeling method is substituted into the disturbance simulation verification, which can monitor and compensate for the targeting error of moving targets in real time. The results show that in the optimal model incorporating the nKF-Gyro method with targeting control, the error suppression was increased by up to 36.8% compared to that of traditional KF method and was 25% better than that of the traditional nKF method.