To avoid casualties and economic loss caused by vehicle yawing motion during the tire blowout, first, by changing several key parameters of the characteristics, this article uses CarSim software and MATLAB/Simulink to establish a vehicle model of tire blowout based on the UniTire model. This model is implemented to simulate tire blowout caused by the change of the vehicle motion state. Second, considering the driver error and radical-operated steering wheel after tire blowout leads to runaway car problems. This article takes the target trajectory and actual trajectory of error and error rate as the system input; an adaptive fuzzy proportional-integral-derivative controller is designed to determine the vehicle steering wheel angle during the tire blowout and replace the driver to control the direction of the vehicle. The results indicate that the designed controller is capable of ensuring the vehicle constancy and keeping the vehicle on the original track.
To facilitate the active magnetic bearing (AMB) design and analysis, an accurate and fast model that considers both rotor eccentricity and the saturation effect is necessary. In this article, a novel hybrid analytical model (HAM) for effective calculation of the magnetic field of the AMB is proposed. Eccentricity and local saturation are considered in the proposed HAM. In the proposed HAM, the stator and rotor are modeled by elementary subdomains (ESDs) and the air-gap is modeled by magnetic equivalent circuit (MEC). Direct coupling between the solutions in the ESD regions with MEC completes the whole model matrices. Compared to the existing literature, the proposed model considers both the rotor eccentricity and material nonlinearity. The effectiveness and accuracy of the proposed HAM are validated by both the finite element model and experimental results. The results show that the proposed HAM can accurately predict the magnetic quantities of the AMB.
A vision-based fuzzy controller for a quadrotor is proposed in this paper to realize ground target tracking. Due to the under-actuated property of quadrotors as well as the coupled dynamics in the image plane, it is challenging to design an image-based visual servoing controller for the quadrotor. Since the fuzzy control does not require an accurate model, a fuzzy-based approach is presented to solve the image-based tracking problem. Fuzzy controller takes image moments as inputs and its outputs are used to control the position of quadrotor in a form of tilt angles and vertical velocity adjustment. The proposed approach is verified by experiment.
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