For strict-feedback nonlinear systems under full-state constraints, current barrier Lyapunov function (BLF) and integral BLF based control solutions rely on feasibility conditions for virtual controllers. In this work, we present a new solution that completely removes such restrictive conditions. First, construct state-dependent purely depends constrained states to cope with full state asymmetric constraints directly; second, introduce coordinate transformation integrate it into each step of...

This paper studies the zero-error tracking control problem of Euler-Lagrange systems subject to full-state constraints and nonparametric uncertainties. By blending an error transformation with barrier Lyapunov function, a neural adaptive scheme is developed, resulting in solution several salient features: 1) action continuous smooth; 2) converges prescribed compact set around origin within given finite time at controllable rate convergence that can be uniformly prespecified; 3) Nussbaum gain...

This article presents a global adaptive asymptotic tracking control method, capable of guaranteeing prescribed transient behavior for uncertain strict-feedback nonlinear systems with arbitrary relative degree and unknown directions. Unlike most existing funnel controls that are built upon time-varying feedback gains, the proposed method is derived from error-dependent normalized function barrier function, together scaling transformation, leading to an improved performance solution following...

In this paper, a neuroadaptive fault-tolerant tracking control method is proposed for class of time-delay pure-feedback systems in the presence external disturbances and actuation faults. The controller can achieve prescribed transient steady-state performance, despite uncertain time delays output constraints as well By combining tangent barrier Lyapunov-Krasovskii function with dynamic surface technique, neural network unit developed scheme able to take its action from very beginning play...

This paper presents a neuroadaptive tracking control approach for uncertain robotic manipulators subject to asymmetric yet time-varying full-state constraints without involving feasibility conditions. Existing algorithms either ignore motion or impose additional In this paper, by integrating nonlinear state-dependent transformation into each step of backstepping design, we develop scheme that not only directly accommodates (position and velocity) but also removes the conditions on virtual...

With set point regulation being the most common goal in control engineering, persistence of excitation (PE) is generically absent adaptive applications. In absence PE, not only parameter estimate guaranteed to converge true value, but state regulated at a rate that necessarily exponential. this technical note we introduce strategy employs time-varying adaptation gains (as well as gains, when appropriate) and achieves exponential plant state, with an uniform initial condition. This idea...

For pure-feedback nonlinear systems under asymmetric output constraint, we present a low-cost neuroadaptive tracking control solution with salient features benefited from two design steps. In the first step, novel output-dependent universal barrier function (ODUBF) is constructed such that not only restrictive condition on constraining boundaries/functions removed but also both constrained and unconstrained cases can be handled uniformly without need for changing structure. second to reduce...

In this article, the problem of constant yet deferred output constraint for uncertain strict-feedback nonlinear systems is studied. By “deferred constraint,” we mean that system free/released from any in initial interval and then preserves within a bounded region right after finite time. Due to such form constraint, normally employed Barrier Lyapunov Function (BLF)-based results become invalid because corresponding BLF undefined period. The will be rather complicated challenging if...

Convolutional neural networks are widely used in the field of hyperspectral image classification because their excellent nonlinear feature extraction ability. However, as sampling position regular convolution kernel is unchangeable, cannot distinctively extract spatial and spectral information around central pixel, which makes results at boundaries ground objects over-smoothed performance degraded. Thus, we propose a novel superpixel guided deformable network (SGDCN) for classification....

Ischemic heart disease invariably leads to devastating damage human health. Nicotinamide ribose (NR), as one of the precursors NAD+ synthesis, has been discovered exert a protective role in various neurological and cardiovascular disorders. Our findings demonstrated that pretreatment with 200 mg/kg NR for 3 h significantly reduced myocardial infarct area, decreased levels CK-MB LDH serum, improved cardiac function rats during ischemia-reperfusion (I/R) injury. Meanwhile, 0.5 mM also...

The influence of a rough structure on wettability has been widely studied, but the quantitative relationship between surface and with same roughness largely ignored. In this work, model describing contact angle surfaces is proposed based fractal parameters. Hydrophilic or hydrophobic multiscale aluminum alloy random were prepared by chemical etching different solutions. dimension scale parameter structures are determined Weierstras–Mandelbrot function. influences parameters studied using...

Rutin has anti-inflammatory, antioxidant, anti-viral, anti-tumor and immune regulatory effects. However, the neuroprotective effects of rutin in spinal cord injury are unknown. The p38 mitogen activated protein kinase (p38 MAPK) pathway is most important member MAPK family that controls inflammation. We assumed mechanism repair associated with inhibition pathway. Allen's method was used to establish a rat model injury. intraperitoneally injected (30 mg/kg) for 3 days. After treatment rutin,...

In this article, a neural network (NN)-based robust adaptive fault-tolerant control (FTC) algorithm is proposed for class of multi-input multi-output (MIMO) strict-feedback nonlinear systems with input quantization and actuation faults as well asymmetric yet time-varying output constraints. By introducing key decomposition quantized input, the developed scheme does not require detailed information parameters. imposing reasonable condition on gain matrix under faults, together inherent...

For the existing adaptive constrained robotic control algorithms, demanding "feasibility conditions" on virtual controller is normally inevitable and extra limits constraining functions have to be imposed, making corresponding approaches more less user friendly in development. Here, we develop a new neuroadaptive strategy for uncertain manipulators presence of position velocity constraints. First, novel unified mapping function (UMF) constructed so that restriction boundaries removed kinds...

This article addresses the entry capture problem (ECP) of uncertain nonlinear systems under asymmetric performance constraints. We show that such ECP is commonly encountered in practice has not been well addressed, whose tracking error free from any constraints initially then driven into prescribed region finite time. For better-transient performance, a unified tunnel (TPP) developed to provide strict and tight allowable set. By utilizing scaling function, together with an function (ESF),...

A redox-reversible BLFMN material demonstrates good performance and coking resistance as the fuel electrode in SOFCs.