Observer-Based Robust Tracking Control for a Class of Switched Nonlinear Cascade Systems

This paper is devoted to robust output feedback tracking control design for a class of switched nonlinear cascade systems. The main goal is to ensure the global input-to-state stable (ISS) property of the tracking error nonlinear dynamics with respect to the unknown structural system uncertainties and external disturbances. First, a nonlinear observer is constructed through state transformation to reconstruct the unavailable states, where only one parameter should be determined. Then, by virtue of the nonlinear sliding mode control (SMC), a discontinuous nonlinear output feedback controller is designed using a backstepping like design procedure to ensure the ISS property. Finally, an example is provided to show the effectiveness of the proposed approach

Finite-time stochastic input-to-state stability and observer-based controller design for singular nonlinear systems

This paper investigated observer-based controller for a class of singular nonlinear systems with state and exogenous disturbance-dependent noise. A new sufficient condition for finite-time stochastic input-to-state stability (FTSISS) of stochastic nonlinear systems is developed. Based on the sufficient condition, a sufficient condition on impulse-free and FTSISS for corresponding closed-loop error systems is provided. A linear matrix inequality condition, which can calculate the gains of the observer and state-feedback controller, is developed. Finally, two simulation examples are employed to demonstrate the effectiveness of the proposed approaches

Neural Gradient Regularizer

Owing to its significant success, the prior imposed on gradient maps has consistently been a subject of great interest in the field of image processing. Total variation (TV), one of the most representative regularizers, is known for its ability to capture the sparsity of gradient maps. Nonetheless, TV and its variants often underestimate the gradient maps, leading to the weakening of edges and details whose gradients should not be zero in the original image. Recently, total deep variation (TDV) has been introduced, assuming the sparsity of feature maps, which provides a flexible regularization learned from large-scale datasets for a specific task. However, TDV requires retraining when the image or task changes, limiting its versatility. In this paper, we propose a neural gradient regularizer (NGR) that expresses the gradient map as the output of a neural network. Unlike existing methods, NGR does not rely on the sparsity assumption, thereby avoiding the underestimation of gradient maps. NGR is applicable to various image types and different image processing tasks, functioning in a zero-shot learning fashion, making it a versatile and plug-and-play regularizer. Extensive experimental results demonstrate the superior performance of NGR over state-of-the-art counterparts for a range of different tasks, further validating its effectiveness and versatility

Interplay between spin wave and magnetic vortex

In this paper, the interplay between spin wave and magnetic vortex is studied. We find three types of magnon scatterings: skew scattering, symmetric side deflection and back reflection, which associate with respectively magnetic topology, energy density distribution and linear momentum transfer torque within vortex. The vortex core exhibits two translational modes: the intrinsic circular mode and a coercive elliptical mode, which can be excited based on permanent and periodic magnon spin-transfer torque effects of spin wave. Lastly, we propose a vortex-based spin wave valve in which via inhomogeneity modulation we access arbitrary control of the phase shift.Comment: 33 pages, 23 figures, 1 tabl

Preparation and imaging of intravascular high-frequency transducer

Intravascular ultrasound (IVUS) imaging is by far the most favorable imaging modality for coronary artery evaluation. IVUS transducer design and fabrication, a key technology for intravascular ultrasound imaging, has a significant impact on the performance of the imaging results. Herein, a 35-MHz side-looking IVUS transducer probe was developed. With a small aperture of 0.40 mm × 0.40 mm, the transducer exhibited a very wide -6 dB bandwidth of 85% and a very low insertion loss of -12 dB. Further, the in vitro IVUS imaging of a porcine coronary artery was performed to clearly display the vessel wall structure while the corresponding color-coded graph was constructed successfully to distinguish necrotic core and fibrous plaque via image processing. The results demonstrated that the imaging performance of the optimized design transducer performs favorably