An observer is constructed to estimate the actual sideslip angle of the vehicle with the consideration of uncertainties and disturbances of the system. In this paper, control strategies for the torque of each wheel and the rear-wheel-steering angle are proposed to maintain a stable velocity and approach an ideal reference model for the off-road vehicle by using second-order sliding mode (SOSM) techniques. N2 - Off-road vehicles always experience serious uncertain longitudinal and lateral slips when running on soft and slope terrains, and some parameters of the vehicles, such as the cornering stiffness and the slip of wheels, are always not constants. T1 - Torque Vectoring and Rear-Wheel-Steering Control for Vehicle's Uncertain Slips on Soft and Slope Terrain Using Sliding Mode Algorithm In comparison with conventional yaw moment controllers without the rear-wheel-steering control, the proposed controllers are shown to be more effective.", On this basis, the proposed controllers have been verified to lead good robustness for maintaining the stable velocity and approaching the ideal reference model by using an optimal torque allocation controller at a lower layer. Then, with conditions of bounded uncertainties and disturbances, composite super-twisting (ST) controllers combined with a velocity controller are designed to generate the total torque, the differential torque, and the rear-wheel-steering angle. In comparison with conventional yaw moment controllers without the rear-wheel-steering control, the proposed controllers are shown to be more effective.Ībstract = "Off-road vehicles always experience serious uncertain longitudinal and lateral slips when running on soft and slope terrains, and some parameters of the vehicles, such as the cornering stiffness and the slip of wheels, are always not constants. Of deep reconstruction for fast MRI.Off-road vehicles always experience serious uncertain longitudinal and lateral slips when running on soft and slope terrains, and some parameters of the vehicles, such as the cornering stiffness and the slip of wheels, are always not constants. Number of signal processing issues are discussed for maximizing the potential Networks and differences in-between are highlighted. Three approaches is explained and the analysis of common parts of reviewed Types of deep learning-based approaches are reviewed, the data-driven,
Overview of deep learning-based image reconstruction methods for MRI. Speed up MR reconstruction with reduced measurements. Tremendous success in various fields and also shown potential to significantly
#Liang jing dong pdf#
Download a PDF of the paper titled Deep MRI Reconstruction: Unrolled Optimization Algorithms Meet Neural Networks, by Dong Liang and 3 other authors Download PDF Abstract: Image reconstruction from undersampled k-space data has been playing an
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