Enhanced Pressure Response of Edge-Deposited Graphene Nanomechanical Resonators.

Nanomechanical resonators made of suspended graphene exhibit high sensitivity to pressure changes. Nevertheless, the graphene resonator pressure performance is affected owing to the gas permeation problem between the graphene film and the substrate. Therefore, we prepared edge-deposited graphene resonators by focused ion beam (FIB) deposition of SiO2, and their gas leakage velocities and pressure-sensing ability were demonstrated. In this paper, we characterize the pressure-sensing response and gas leakage velocities of graphene membranes using an all-optical actuation system. The gas leakage velocities of graphene resonators with diameters of 10, 20, and 40 µm are reduced by 5.0 × 106, 2.0 × 107, and 8.1 × 107 atoms/s, respectively, which demonstrates that the edge deposition structure can reduce the gas leakage of the resonator. Furthermore, the pressure-sensing performance of three graphene resonators with different diameters was evaluated, and their average pressure sensitivities were calculated to be 3.4, 2.4, and 1.9 kHz/kPa, with the largest full-range hysteresis errors of 0.6, 0.7, and 1.0%, respectively. The temperature stabilities of the three sizes of resonators in the temperature range of 300-400 K are 0.016, 0.015, and 0.016%/K, and the maximum resonance frequency drift over 1 h is 0.0058, 0.0048, and 0.0112%, respectively. This work has great significance for the improvement of gas leakage velocity characterization of graphene membrane and graphene resonant pressure sensor performance optimization.

Suppressed Defects by Functional Thermally Cross-Linked Fullerene for High-Efficiency Tin-Lead Perovskite Solar Cells.

Mixed tin-lead (Sn-Pb) perovskites have attracted the attention of the community due to their narrow bandgap, ideal for photovoltaic applications, especially tandem solar cells. However, the oxidation and rapid crystallization of Sn2+ and the interfacial traps hinder their development. Here, cross-linkable [6,6]-phenyl-C61-butyric styryl dendron ester (C-PCBSD) is introduced during the quenching step of perovskite thin film processing to suppress the generation of surface defects at the electron transport layer interface and improve the bulk crystallinity. The C-PCBSD has strong coordination ability with Sn2+ and Pb2+ perovskite precursors, which retards the crystallization process, suppresses the oxidation of Sn2+, and improves the perovskite bulk and surface crystallinity, yielding films with reduced nonradiative recombination and enhanced interface charge extraction. Besides, the C-PCBSD network deposited on the perovskite surface displays superior hydrophobicity and oxygen resistance. Consequently, the devices with C-PCBSD obtain PCEs of up to 23.4% and retained 97% of initial efficiency after 2000 h of storage in a N2 atmosphere.

Prescribed-time command filtered control for a class uncertain nonlinear systems.

This article delves into the intricate challenge of implementing prescribed-time command filtered control in the context of uncertain nonlinear systems. Firstly, a prescribed-time function is defined to lay the groundwork for subsequent controller design. Subsequently, a novel prescribed-time command Filtered controller is proposed for high-order nonlinear systems featuring unknown parameters. This controller guarantees swift error convergence within a predefined time range, with the added capability of periodic error convergence to zero during subsequent controller operations. A pivotal innovation in this study lies in the controller's design, which remains unaffected by the system's initial conditions. This unique feature enables the prescribed time to be flexibly set within physical constraints, diverging markedly from conventional finite-time control theory. Theoretical analysis has conclusively shown that the controller achieves full-state tracking error convergence within the specified time frame. The efficacy of the research findings is substantiated through two simulation cases, underscoring a substantial contribution to the refinement and adaptability of nonlinear system control theory.

Safe Robust Adaptive Motion Control for Underactuated Marine Robots.

This article presents an innovative approach to the design of a safe adaptive backstepping control system. Tailored specifically for underactuated marine robots, the system utilizes simple sensors for enhanced practicality and efficiency. Given their operation in diverse oceanic environments fraught with various sources of uncertainties, ensuring the system's safe and robust behavior holds paramount importance in the control literature. To address this concern, this paper introduces a control strategy designed to ensure robustness at both the kinematic and dynamic levels. By emphasizing the compensation for the system uncertainties, the design integrates a straightforward fuzzy system structure. To further ensure the system's safety, a funnel surface is defined, followed by the design of a suitable nonlinear sliding surface as a function of the funnel and tracking error. Using Lyapunov theory, the study formally establishes the Semi-globally Practically Finite-time Stability of the closed-loop system, validated through simulations conducted on underactuated marine robots.

A novel predefined-time neurodynamic approach for mixed variational inequality problems and applications.

In this paper, we propose a novel neurodynamic approach with predefined-time stability that offers a solution to address mixed variational inequality problems. Our approach introduces an adjustable time parameter, thereby enhancing flexibility and applicability compared to conventional fixed-time stability methods. By satisfying certain conditions, the proposed approach is capable of converging to a unique solution within a predefined-time, which sets it apart from fixed-time stability and finite-time stability approaches. Furthermore, our approach can be extended to address a wide range of mathematical optimization problems, including variational inequalities, nonlinear complementarity problems, sparse signal recovery problems, and nash equilibria seeking problems in noncooperative games. We provide numerical simulations to validate the theoretical derivation and showcase the effectiveness and feasibility of our proposed method.

Event-triggered adaptive control for nonlinear systems using time-receding horizons without initial dependence.

This paper investigates the full-state constraint event-triggered adaptive control for a class of uncertain strict-feedback systems. The lack of information on the coupling dynamics of virtual variables in backstepping increases the complexity of feedback design. Given this, the requirements of shaping system performance constraints, eliminating initial dependence, and reducing data transfer costs together give rise to an interesting and challenging problem. Constructing the time-receding horizon (TRH) and stitching it with the quadratic Lyapunov function (QLF) is the key to constrained tracking. Specifying TRHs as a set of smooth bounds with fixed-time convergence and forcing the system to stabilize within the constrained region before the prescribed settling time provide a sufficient condition for practical finite-time stability (PFS). For relaxing the initial dependence, a tuning function is designed to match the performance constraints under arbitrary system initial conditions. A dual-channel event-triggered mechanism (ETM) is developed to automatically adjust the controller and estimator data flow updates with less transmission burden. By combining a specific inequality with backstepping, uncertainties are overcome without the "complexity explosion" in recursion steps. Finally, simulations demonstrate the effectiveness of the proposed method.

Sliding mode coordinated control of hybrid electric vehicle via finite-time control technique.

During the transient mode switching process of the hybrid electric vehicle (HEV) from motor driving mode to hybrid driving mode, dynamic coordinated control of different components is essential to improve the vehicle comfort and dynamic performance. The key to highly quality mode switching control includes fast and stable speed and/or displacement tracking of the engine and motor. The transient mode switching stages of the HEV is divided in this paper. On this basis, by combing the nonlinear sliding mode control and the finite-time stability theory, the global fast integral terminal sliding mode controller (GFITSMC) is designed for the transition stages involving clutch slip. The GFITSMC consists of the global fast integral terminal sliding mode surface (GFITSMS) and the non-smooth reaching law (NSRL). In order to improve the controller convergence and anti-disturbance performance, the proposed controller is synthesized from the perspective of finite-time stability. It is proved that, with proper NSRL and GFITSMS parameters, the speed and displacement tracking error of the motor and engine can reach the sliding mode surface and further converge to zero in a finite time. Simulation and hardware-in-the-loop (HIL) tests are performed to validate the effectiveness of the proposed control method. Research results demonstrate that the proposed strategy not only achieves faster transient mode switching by improving the state trajectory tracking performance, but also reduces the longitudinal jerk caused by the transient mode switching significantly.

Surface-Enhanced Raman Spectroscopy Substrate Time Stability Improvement Using an External Oxygen Barrier Method.

The poor time stability of surface-enhanced Raman scattering (SERS) substrates greatly limits their application potential. Although core-shell structures are commonly used to enhance stability, their complex preparation processes, high costs, and susceptibility under acidic or alkaline conditions result in serious disadvantages for practical applications. Here, we propose a new method of external oxygen barrier to improve spectral stability, in which SERS substrates are stored in an oxygen-free environment. Controlled experiments are carried out under air and vacuum. Raman spectrum intensity is measured 11 times within six months for each group. Using the attenuation formula, the Raman spectrum intensity decay results of each SERS substrate over time are obtained. The effectiveness of the external oxygen barrier method is demonstrated through curve fitting using the corresponding function. The substrate spectral attenuation rates of the vacuum group and the argon group within six months are <20%, proving the effectiveness of the external oxygen barrier method.

Fixed-time terminal sliding mode control for uncertain robot manipulators.

This paper proposes a fixed-time tracking control for robot manipulators in the presence of parametric uncertainties and disturbances. An auxiliary function is first proposed for constructing a fixed-time sliding manifold. Benefited from this fixed-time sliding manifold, a singularity-free robust control is proposed to evade the effects of algebraic loop problem of the commonly-used sliding mode controls (SMC). The key advantages of the proposed approach are: (i) exact fixed-time stability featuring the convergence time does not relate to the initial conditions and is acquired in advance; (ii) the singularity and algebraic loop problems are eliminated completely; (iii) a simple and intuitive control structure is used for easy implementation of trajectory tracking control for uncertain robot manipulators with faster transient and higher steady-state precision. Simulations and experimental comparisons validate the improved tracking performance of the proposed approach.

Neural network-based finite-time command-filtered adaptive backstepping control of electro-hydraulic servo system with a three-stage valve.

This paper aims to improve the tracking control performance of the three-stage valve (TSV) controlled electro-hydraulic servo system (EHSS) with parameter uncertainties and other lumped unknown nonlinearities, including unknown dynamics and disturbances. A more accurate nonlinear model of the TSV-controlled EHSS is established and a neural network-based finite-time command-filtered adaptive backstepping control (NNFCABC) method is proposed for the EHSS. Adaptive control is used to deal with the system parameter uncertainties, and the radial basis function neural network (RBFNN) algorithm is introduced to approximate the lumped unknown nonlinearities. The prediction errors of serial-parallel estimation models (SPEMs) and the tracking errors are utilized together to design adaptive laws to estimate the system parameters and the weights of the RBFNNs. The entire control framework utilizes command-filtered control and backstepping techniques. By applying Levant differentiators as command filters and introducing fractional power terms into the virtual control laws and the SPEMs, the proposed NNFCABC theoretically guarantees the tracking performance of the closed-loop control system with finite-time convergence. Comparative simulations and experiments verify the feasibility and superiority of the proposed control scheme.

A model-free terminal sliding mode control for robots: Achieving fixed-time prescribed performance and convergence.

This paper introduces a new control strategy for robot manipulators, specifically designed to tackle the challenges associated with traditional model-based sliding mode (SM) controller design. These challenges include the need for accurately computed system models, knowledge of disturbance upper bounds, fixed-time convergence, prescribed performance, and the generation of chattering. To overcome these obstacles, we propose the incorporation of a neural network (NN) that effectively addresses these issues by removing the constraint of a precise system model. Additionally, we introduce a novel fixed-time prescribed performance control (PPC) to enhance response performance and position-tracking accuracy, while effectively limiting overshoot and maintaining steady-state error within the predefined range. To expedite the convergence of the SM surface to its equilibrium point, we introduce a faster terminal sliding mode (TSM) surface and a novel fixed-time reaching control algorithm (RCA) with adaptable factors. By integrating these approaches, we develop a novel control strategy that successfully achieves the desired goals for robot manipulators. The effectiveness and stability of the proposed approach are validated through extensive simulations on a 3-DOF SAMSUNG FARA-AT2 robot manipulator, utilizing both Lyapunov criteria and performance evaluations. The results demonstrate improved convergence rate and tracking accuracy, reduced chattering, and enhanced controller robustness.

Adaptive fixed-time sliding mode control for spacecraft reorientation with attitude pointing constraints and disturbance rejection.

Spacecraft reorientation with attitude pointing constraints and the uncertainty of inertia and external disturbance is investigated in this paper. By introducing the potential function into the design of non-singular fixed-time sliding mode surface, the proposed controller can achieve fixed-time convergence and the convergence time of attitude error can be predetermined by selecting appropriate parameters. Meanwhile, the attitude pointing constraints can be satisfied all the time. The designed sliding surface and potential function have two equilibrium points, which guarantees the unwinding-free performance. Furthermore, an adaptive sliding mode control scheme is developed to handle the system lumped disturbance. Rigorous Lyapunov analyses are employed to ensure practical fixed-time closed-loop stability in the presence of system disturbance uncertainties and attitude pointing constraints. Therefore, the fixed-time stability, the feasibility of attitude pointing constraints and disturbance rejection are achieved simultaneously with the proposed controller. Numerical simulations are provided to demonstrate the effectiveness and superiority of the proposed method.

Identifying hotspots of water table depth change by coupling trend with time stability analysis in the North China Plain.

Many groundwater construction projects such as South-to-North Water Diversion Project (SNWDP) were conducted for controlling groundwater overexploitation in the North China Plain (NCP). However, more insight is required into the magnitude and distribution of water table depth (WTD) in time and space over the NCP. This study evaluated the variability and the hotspots of WTD based on 83 unconfined monitoring wells and took trend, breakpoint, and time stability into consideration. We found the average WTD of unconfined aquifer for the Southern Hebei Plain generally increased continuously from 1998 to 2020 in spite of the operation of the SNWDP since 2014. However, the rise rate of WTD slows down in recent years and the WTD has decreased in certain subregions. We further divided these groundwater wells into five groups: climb accelerating (Group 1), increase decelerating (Group 2), first rise then descend (Group 3), first descend then rise (Group 4), decrease decelerating (Group 5), and reduce accelerating (Group 6). Moreover, we found that the number of wells that divided into Group1 to Group 5 account for 15 %, 41 %, 25 %, 18 %, and 1 % of the total number of observation wells. The breakpoints of all the wells are from 2001 to 2017 and most of the breakpoints were found before 2014, which demonstrates that other groundwater management strategies implemented in the Southern Hebei Plain prior to the operation of the SNWDP plays a crucial part. The hotspots area for group 1 is mainly distributed in the north region of Shijiazhuang City, group 2 is in southern region of piedmont plain, group 3 is in northern region of Baoding and south-west region of Xingtai City, and group 4 is in Cangzhou City and eastern region of Xingtai City. The method and framework of this study can be applied in other regions suffering from groundwater depletion.

Design of A Finite-Time Adaptive Controller for Image-Based Uncalibrated Visual Servo Systems with Uncertainties in Robot and Camera Models.

Aiming at the time-varying uncertainties of robot and camera models in IBUVS (image-based uncalibrated visual servo) systems, a finite-time adaptive controller is proposed based on the depth-independent Jacobian matrix. Firstly, the adaptive law of depth parameters, kinematic parameters, and dynamic parameters is proposed for the uncertainty of a robot model and a camera model. Secondly, a finite-time adaptive controller is designed by using a nonlinear proportional differential plus a dynamic feedforward compensation structure. By applying a continuous non-smooth nonlinear function to the feedback error, the control quality of the closed-loop system is improved, and the desired trajectory of the image is tracked in finite time. Finally, using the Lyapunov stability theory and the finite-time stability theory, the global finite-time stability of the closed-loop system is proven. The experimental results show that the proposed controller can not only adapt to the changes in the EIH and ETH visual configurations but also adapt to the changes in the relative pose of feature points and the camera's relative pose parameters. At the same time, the convergence rate near the equilibrium point is improved, and the controller has good dynamic stability.

Scrutinization of finite time stability of fractional impulsive neutral model with disturbance.

Finite time stability practically examines the trajectories of a system which converge to equilibrium state in a short period of time. This notion requires predefined bounds on system parameters and bounded time interval. Considering the idea that many practical system often operates over time interval being finite rather than infinite, we explore the finite time stability concept of damped fractional system with neutral conditions and impulsive effects. The desired bounds for the stability of the system is derived by implementing Gronwall's inequality conditions. Further, the finite time stability conditions of the proposed fractional linear model is extended to nonlinearity term with disturbance. Finally, numerical simulations are given to show the effectiveness of the derived results.

Fixed-time periodic stabilization of discontinuous reaction-diffusion Cohen-Grossberg neural networks.

This paper aims to study the fixed-time stabilization of a class of delayed discontinuous reaction-diffusion Cohen-Grossberg neural networks. Firstly, by providing some relaxed conditions containing indefinite functions and based on inequality techniques, a new fixed-time stability lemma is given, which can improve the traditional ones. Secondly, based on state-dependent switching laws, the periodic wave solution of the formulated networks is transformed into the periodic solution of ordinary differential system. By utilizing differential inclusions theory and coincidence theorem, the existence of periodic solutions is obtained. Thirdly, based on the new fixed-time stability lemma, the periodic solutions are stabilized at zero in a fixed-time, which is a new topic on reaction-diffusion networks. Moreover, the established criteria are all delay-dependent, which are less conservative than the previous delay-independent ones for ensuring the stabilization of delayed reaction-diffusion networks. Finally, two examples give numerical explanations of the proposed results and highlight the influence of delays.

Distributed observer-based finite-time control of moving target tracking for UAV formation.

This paper disseminated two formation control strategies for multiple unmanned aerial vehicles (multi-UAV) system of moving target tracking in a windy environment. The communication among UAVs is modeled by a directed graph. The first control strategy proposes a distributed dynamic error observer and a guidance law to make the system global uniform asymptotic stability when the wind disturbance is a known constant. The second control strategy employs a distributed fixed-time observer and a finite-time stable guidance law to make the system globally finite-time stable with unknown wind disturbances. The stability of both formation control strategies is rigorous demonstrated mathematically. Finally, the excellent performance and reliability of the proposed guidance law for target tracking in a windy environment are verified through several simulation examples.

Finite-time stability analysis and control of stochastic SIR epidemic model: A study of COVID-19.

Finite-time stability analysis is a powerful tool for understanding the long-term behavior of epidemiological models and has been widely used to study the spread of infectious diseases such as COVID-19. In this paper, we present a finite-time stability analysis of a stochastic susceptible-infected-recovered (SIR) epidemic compartmental model with switching signals. The model includes a linear parameter variation (LPV) and switching system that represents the impact of external factors, such as changes in public health policies or seasonal variations, on the transmission rate of the disease. We use the Lyapunov stability theory to examine the long-term behavior of the model and determine conditions under which the disease is likely to die out or persist in the population. By taking advantage of the average dwell time method and Lyapunov functional (LF) method, and using novel inequality techniques the finite-time stability (FTS) criterion in linear matrix inequalities (LMIs) is developed. The finite-time stability of the resultant closed-loop system, with interval and linear parameter variation (LPV), is then guaranteed by state feedback controllers. By analyzing the modified SIR model with these interventions, we are able to examine the efficiency of different control measures and determine the most appropriate response to the COVID-19 pandemic and demonstrate the efficacy of the suggested strategy through simulation results.

Fixed-time fault-tolerant attitude control for rigid spacecraft with torque saturation.

This paper investigates the fixed-time attitude control problem for spacecraft under input saturation, actuator faults, and system uncertainties. Three novel saturated fixed-time nonsingular terminal sliding mode surfaces (NTSMSs) are designed, which can keep the system states fixed-time stable after the establishment of their sliding manifolds. Two of them are time-varying and firstly designed. Each of the two NTSMSs has an adjustment parameter that is adjusted dynamically and used to handle saturation and cancel the attitude dynamics. According to other related predesigned parameters, a conservative lower bound of this parameter is obtained. A saturated control scheme is then designed in conjunction with a newly proposed saturated reaching law. A modification strategy is carried out to facilitate the engineering applications of our methods. The fixed-time stability of the closed-loop systems is validated by Lyapunov stable theory. Simulation results validate the effectiveness and superiority of the proposed control scheme.

Continuous Adaptive Finite-Time Sliding Mode Control for Fractional-Order Buck Converter Based on Riemann-Liouville Definition.

This study proposes a continuous adaptive finite-time fractional-order sliding mode control method for fractional-order Buck converters. In order to establish a more accurate model, a fractional-order model based on the Riemann-Liouville (R-L) definition of the Buck converter is developed, which takes into account the non-integer order characteristics of electronic components. The R-L definition is found to be more effective in describing the Buck converter than the Caputo definition. To deal with parameter uncertainties and external disturbances, the proposed approach combines these factors as lumped matched disturbances and mismatched disturbances. Unlike previous literature that assumes a known upper bound of disturbances, adaptive algorithms are developed to estimate and compensate for unknown bounded disturbances in this paper. A continuous finite-time sliding mode controller is then developed using a backstepping method to achieve a chattering-free response and ensure a finite-time convergence. The convergence time for the sliding mode reaching phase and sliding mode phase is estimated, and the fractional-order Lyapunov theory is utilized to prove the finite-time stability of the system. Finally, simulation results demonstrate the robustness and effectiveness of the proposed controller.