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The complex influence of various disturbances on an inertially stabilized platform (ISP) restricts the further improvement of its servo performance. This article investigates the mapping relationship between internal and external disturbances and servo performance by establishing a high-precision dynamics model of the servo device with simulation and experiment. For internal disturbances, a nonlinear model of friction and backlash is established based on a BP neural network, and the transmission error is reconstructed based on the principle of main order invariance. For external disturbances, the road disturbance torque, changing inertia, and mass imbalance torque are modeled. The quantitative mapping relationship between internal and external disturbances and servo performance is obtained through simulation, in which friction and road disturbance are the largest internal and external factors affecting the servo performance, respectively. These conclusions are verified by load simulation experiments on a certain type of servo device, in which the servo performance is improved by 17% for every 25% reduction of friction torque, and the servo performance is reduced by 12% for every 33% increase of road disturbance torque. The research results provide a reference for servo device selection, performance indicator assignment, and performance prediction of the ISP. [ABSTRACT FROM AUTHOR]

Friction is a complex nonlinear behavior and a significant factor that limits the performance improvement of servo systems. Drawing inspiration from the particular prestiction friction phenomenon exhibited by direct-drive systems upon sudden emergency stops, this paper introduces a dynamic and continuous friction model that includes pre-sliding and gross-sliding regimes. By analyzing the friction dynamics when the system velocity briefly reaches zero, a concave function related to the previous state of the system is used to describe the transition of friction in the pre-sliding regime. The Stribeck model is employed to represent the friction behavior in the gross-sliding regime, ensuring stationarity during friction regime switching. Based on the established friction model, a friction compensation method is developed in velocity control mode. The superior performance of this proposed friction compensation method is confirmed through sine-tracking experiments. Compared with the proportional integral controller and the Stribeck friction compensation method, the peak-to-peak value of the proposed method is reduced by up to 61.1 %, and the root-mean-square (rms) value is reduced by up to 81 %, with the smallest rms value reaching 0.13 mrad, significantly improving the dynamic tracking performance of the system. [ABSTRACT FROM AUTHOR]

The dual-motor precision transmission mechanism (DMPTM) is an alternative way to eliminate backlash while ensuring the stiffness of the servo system. However, most of the established models of DMPTM are not accurate enough, and are not conducive to the optimization of system performance and the design of high-precision controllers. In this paper, based on the detailed linear model of the single components of the DMPTM, the dead-zone model, considering the time-varying stiffness, is proposed to describe the backlash of the two transmission chains, and the friction of the mechanism is depicted by the Stribeck model. Then, a high-precision dynamic model of the DMPTM is formed. Finally, the model validation experiments for the open-loop and closed-loop are carried out in the time domain and frequency domain. The experimental results show that the proposed model can accurately describe the nonlinear characteristics of the mechanism. The Pearson correlation coefficient between the proposed model and the actual system is r open - loop > 99.41%, for the open-loop, and r closed - loop > 83.7%, for the closed-loop, and these results are both better than those of the existing model. In the frequency domain, whether it is the open-loop or closed-loop model, the frequency response of the proposed model also reproduces the actual system well, which verifies the accuracy of the model. [ABSTRACT FROM AUTHOR]

This study presents a compound control algorithm that enhances the servo accuracy and disturbance suppression capability of direct drive components (DDCs). The servo performance of DDCs is easily affected by external disturbance and the deterioration of assembly characteristics due to a lack of deceleration device. The purpose of this study is to compensate for the impact of external and internal disturbances on the system. First, a linear state space model of the system is established. Second, we analyzed the main factors restricting the performance of DDCs which includes sensor noise, friction and external disturbance. Then, a fractional-order proportional integral (FOPI) controller was used to eliminate the steady-state error caused by the time-invariable disturbance which can also improve the system's anti-interference capability. A state-augmented Kalman filter (SAKF) was proposed to suppress the quantization noise and compensate for the time-varying disturbances simultaneously. The effectiveness of the proposed compound algorithm was demonstrated by comparative experiments, demonstrating a maximum 89.34% improvement. The experimental results show that, compared with the traditional PI controller, the FOPISAKF controller can not only improve the tracking accuracy of the system, but also enhance the disturbance suppression ability. [ABSTRACT FROM AUTHOR]