The opto-electric servomechanism (OES) plays an important role in obtaining clear and stable images from airborne infrared detectors. However, the inherent torque disturbance and the noisy speed signal cause a significant decline in the inertial stability accuracy and low-speed performances of OESs. Traditional linear control schemes cannot deal with the nonlinear torque disturbance well, and the speed obtained by the finite difference (FD) method cannot effectively balance the tradeoff between the noise filtering and phase delay. Therefore, this paper proposes a strap-down stability control scheme, in the combination of a proportional-integral(PI) controller and a state-augmented Kalman filter (SAKF), where the PI is used to regulate the linear part of the servomechanism, and with the SAKF performing torque disturbance observation and speed estimation simultaneously. The principle and the implementation of the controller are introduced, and the tuning guidelines for the controller parameters are presented as well. Finally, the experimental verifications based on OESs with three transmission types (i.e., the direct-driving, the harmonic-driving, and the rotate vector-driving(RV-driving) OESs) are carried out respectively. The experimental results show that the proposed control scheme can perform better speed observation and torque disturbance compensation for various types of OESs, thus effectively improving the low-speed performance and stability accuracy of the mechanism.
Relative to the passive suspension, automotive active suspension car driving more ride comfort and stability, has a vital role to further improve the performance of the vehicle. For such a typically complex active suspension system research, the key issue is the selection of control strategies. The problems in the currently active suspension control strategy, the principle of a simple, effective, this paper, a single neuron PID control strategy used in the automotive active suspension system. The results show that compared with other control strategies, single neuron PID control strategy is reliable, has more advantages.
Balance valve is the key component of crane lifting system, its performance determines the hoisting performance. Through in-depth study on the dynamic characteristics of the balance valve, find out the influence of parameters of the stability of the system, and carried on the simulation analysis using AMESim software, and to find the simulation process, put forward the optimization measures.
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