Adaptive discrete-time neural prescribed performance control: A safe control approach.

Most existing results on prescribed performance control (PPC), subject to input saturation and initial condition limitations, focus on continuous-time nonlinear systems. This article, as regards discrete-time nonlinear systems, is dedicated to constructing a novel adaptive switching control strategy to circumvent the singular problem when the PPC undergoes input saturation, while the initial conditions of the system can be released under the framework of PPC. The main design steps and characteristics include: (1) By devising a new discrete-time global finite-time performance function (DTGFTPF), the constructed performance boundary is shown to survive insensitive to arbitrary initial values, which present in the system; (2) A discrete-time adaptive finite-time prescribed performance controller (DTAFPPC) and a discrete-time adaptive backstepping controller (DTABC) are constructed, simultaneously.

Finite-time prescribed performance tracking control of seeker stabilized platform in the discrete-time domain.

Current prescribed performance control (PPC) focuses on continuous-time systems, while this article proposes a novel discrete-time version of PPC for finite-time tracking of seeker stabilized platform in the discrete-time domain. Firstly, the newly developed performance functions are employed to impose finite-time prescribed performance on tracking errors. After that, a type of stabilization functions with respect to transformed errors are constructed for back-stepping controllers designing.

Cognitive dysfunction in diabetes: abnormal glucose metabolic regulation in the brain.

Cognitive dysfunction is increasingly recognized as a complication and comorbidity of diabetes, supported by evidence of abnormal brain structure and function. Although few mechanistic metabolic studies have shown clear pathophysiological links between diabetes and cognitive dysfunction, there are several plausible ways in which this connection may occur. Since, brain functions require a constant supply of glucose as an energy source, the brain may be more susceptible to abnormalities in glucose metabolism.

Fuzzy Neural Pseudo Control With Prescribed Performance for Waverider Vehicles: A Fragility-Avoidance Approach.

A fuzzy-neural-approximation-based pseudo nonaffine control protocol is proposed for waverider vehicles (WVs), which is capable of guaranteeing tracking errors with desired prescribed performance and rejecting the obstacle of fragility inherent to the traditional prescribed performance control (PPC). The pseudo control is defined to approximate the nonaffine dynamics of WVs, while there is no need of model affinization. Furthermore, fuzzy neural approximators are combined with the adaptive compensation strategy to resist both system uncertainties and external disturbances.

Qinling liquid ameliorates renal immune inflammatory damage via activating autophagy through AMPK/Stat3 pathway in uric acid nephropathy.

Background: Excessive deposition of uric acid (UA) is one of the risk factors for kidney damage. Qinling liquid (QL) has a certain therapeutic effect on uric acid nephropathy (UAN), but its regulation mechanism is still unclear.

Methods: UAN rat models and UA induced rat renal tubular epithelial cells (NRK-52E) were constructed to evaluate the functional roles of QL.

Hypersonic tracking control under actuator saturations via readjusting prescribed performance functions.

Prescribed performance control (PPC) has been shown to be an effective tool in pursuing prescribed transient and steady-state specifications. Unfortunately, the existing PPC is incapable of handling the peaking of errors caused by actuator saturations, which is due to the short of the ability of readjusting the prescribed performance functions. In this article, we propose a novel PPC scheme, namely the readjusting-performance-function-based approach, for hypersonic flight vehicles subject to actuator saturations.

Extraction of Intangible Cultural Heritage Visual Elements by Deep Learning and Its Application in Grassland Tourism of the Silk Road Culture.

Inner Mongolia is rich in grassland tourism resources, and the development of grassland tourism is of great significance to Inner Mongolia tourism and promotion of grassland protection. To better promote the grassland tourism of the Silk Road culture, the Conditional Global Area Network (CGAN) and Morphology Connected Component Chan-Vase (MCC-CV) algorithm are used to enhance and segment the traditional embroidery patterns in Inner Mongolia. Firstly, the generative adversarial network (GAN) is optimized, and a new GAN is proposed with the feature vector extracted from the convolutional neural network (CNN) as the constraint condition.

Backstepping Sliding Mode Control for Radar Seeker Servo System Considering Guidance and Control System.

This paper investigates the design of a missile seeker servo system combined with a guidance and control system. Firstly, a complete model containing a missile seeker servo system, missile guidance system, and missile control system (SGCS) was creatively proposed. Secondly, a designed high-order tracking differentiator (HTD) was used to estimate states of systems in real time, which guarantees the feasibility of the designed algorithm.

Tracking control of air-breathing hypersonic vehicles with non-affine dynamics via improved neural back-stepping design.

This study considers the design of a new back-stepping control approach for air-breathing hypersonic vehicle (AHV) non-affine models via neural approximation. The AHV's non-affine dynamics is decomposed into velocity subsystem and altitude subsystem to be controlled separately, and robust adaptive tracking control laws are developed using improved back-stepping designs. Neural networks are applied to estimate the unknown non-affine dynamics, which guarantees the addressed controllers with satisfactory robustness against uncertainties.

Effects of Polygonum cuspidatum on AMPK-FOXO3α Signaling Pathway in Rat Model of Uric Acid-Induced Renal Damage.

Background: To observe the effects of Chinese medicine (CM) Polygonum cuspidatum (PC) on adenosine 5'-monophosphate-activated protein kinase (AMPK), forkhead box O3α (FOXO3α), Toll-like receptor-4 (TLR4), NACHT, LRR and PYD domains-containing protein 3 (NLRP3), and monocyte chemoattractant protein-1 (MCP-1) expression in a rat model of uric acid-induced renal damage and to determine the molecular mechanism.

Methods: A rat model of uric acid-induced renal damage was established, and rats were randomly divided into a model group, a positive drug group, and high-, medium-, and low-dose PC groups (n=12 per group). A normal group (n=6) was used as the control.

[Effects of Tengmei Decoction on the PPAR-y/NF-KB Signaling Pathway in Synovium of Collagen-in- duced Arthritis Rats].

Objective To observe the effects of Tengmei Decoction (TMD) on the expressions of peroxisome proliferator activated receptor gamma (PPARγ) , nuclear factor kappa B (NF-κB) , and IL- 17 in synovium of collagen-induced arthritis (CIA) rats, and to study its molecular mechanismpf. inhibi- ting synovial immune inflammatory injuries. Methods CIA model was established in Sprague-Dawley rats.

Novel prescribed performance neural control of a flexible air-breathing hypersonic vehicle with unknown initial errors.

A novel prescribed performance neural controller with unknown initial errors is addressed for the longitudinal dynamic model of a flexible air-breathing hypersonic vehicle (FAHV) subject to parametric uncertainties. Different from traditional prescribed performance control (PPC) requiring that the initial errors have to be known accurately, this paper investigates the tracking control without accurate initial errors via exploiting a new performance function. A combined neural back-stepping and minimal learning parameter (MLP) technology is employed for exploring a prescribed performance controller that provides robust tracking of velocity and altitude reference trajectories.

High-order tracking differentiator based adaptive neural control of a flexible air-breathing hypersonic vehicle subject to actuators constraints.

In this paper, an adaptive neural controller is exploited for a constrained flexible air-breathing hypersonic vehicle (FAHV) based on high-order tracking differentiator (HTD). By utilizing functional decomposition methodology, the dynamic model is reasonably decomposed into the respective velocity subsystem and altitude subsystem. For the velocity subsystem, a dynamic inversion based neural controller is constructed.

Self-driven one-step oil removal from oil spill on water via selective-wettability steel mesh.

Marine oil spills seriously endanger sea ecosystems and coastal environments, resulting in a loss of energy resources. Environmental and economic demands emphasize the need for new methods of effectively separating oil-water mixtures, while collecting oil content at the same time. A new surface-tension-driven, gravity-assisted, one-step, oil-water separation method is presented for sustained filtration and collection of oil from a floating spill.