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This article investigates the adaptive fuzzy prescribed time tracking control problem for a class of strict-feedback systems simultaneously considering the user-defined asymmetric tracking performance, input saturation, and external disturbances. From the perspective of ensuring the reliability for control implementation, a saturation-based fixed-time funnel boundary is constructed by embedding the modification signals related to input saturation errors into a funnel function, which is capable of automatically enlarging or recovering itself when input saturation occurs or disappears, thereby reducing the risk of system singularity. Subsequently, by constructing a fixed-time tracking performance function, any known bounded tracking error is recast into a new variable with a zero initial value. With such a treatment, funnel boundaries are no longer redeveloped for different initial tracking errors, and meanwhile the behavior of the tracking error is pre-specified as needed over a finite time interval. Also, auxiliary systems are devised to generate the aforesaid modification signals, while compensating for the adverse impact resulting from input saturation. Remarkably, by feat of the backstepping design based on the fuzzy approximation, it is proven that the tracking error converges to a user-defined region within a prescribed time (known as the practically prescribed time tracking), which is achieved without the fractional power feedback of system states. Finally, two simulation examples are presented to confirm the feasibility and effectiveness of the developed approach. • A novel fixed-time tracking performance function is designed to relax the initial condition. • By a simple variable transformation, the asymmetric performance constraint is handled. • A new form of self-adjustable performance funnel is constructed to enhance the reliability of control designs. • A class of the practically prescribed time tracking problems is solved. [ABSTRACT FROM AUTHOR]

This paper studies the congestion control problem of multiple bottleneck networks. First, this paper regards the routing nodes of the network as multi-agents, and considers its own dynamic process. For the first time, the time-varying characteristics of the number of sessions in the network transmission process and the mutual influence between nodes are considered into the model, and a queue utilization rate switching model is established to describe the dynamics of a single agent. Then, considering the boundedness of the control input, combined with the prescribed performance technique, two congestion controllers are designed by using the backstepping method according to whether the controller depends on the number of sessions. The designed congestion controllers improve the robustness of the TCP/AQM network system in the case of frequent and time-varying sessions in multiple bottleneck networks. In addition, the designed controllers can stabilize different routing nodes of multiple bottleneck networks under different queue lengths, thereby improving the utilization efficiency of the network. Finally, the effectiveness and superiority of the designed controllers are verified by simulation. • TCP/IP network node queue utilization switching model is built. • The controller design takes into account the input saturation characteristics. • Two prescribed performance congestion control algorithms are designed. [ABSTRACT FROM AUTHOR]

A neural network control strategy based on the immune algorithm is proposed to address the problem of chattering and trajectory tracking performance degradation of multi-joint manipulators due to unknown backlash-like hysteresis and system uncertainty. The controller is designed based on backstepping sliding mode technology and is suitable for Euler-Lagrange nonlinear systems. Firstly, to deal with the uncertainty problem of the manipulator model, we consider using radial basis function neural networks (RBFNN) to approximate, and on this basis, we add immune algorithms to optimize the RBFNN parameters to improve the approximation ability. Secondly, to compensate for the unknown backlash-like hysteresis error and RBFNN approximation error, an adaptive reaching law is designed to improve the control accuracy and reduce chattering to a certain extent. Finally, taking a 3-DOF manipulator as the research object, based on comparative simulation results, the feasibility and superiority of this control method can be proven. [ABSTRACT FROM AUTHOR]

This paper focuses on the mobile robot path planning problem of optimizing the performance metrics of bidirectional A* algorithm in randomized two-dimensional map environments. An algorithm called direction constraints adaptive extended bidirectional A* (DCAE-BA*), which is an improvement of the traditional target dynamic bidirectional A* algorithm (TTD-BA*), is proposed to improve the performance metrics of the algorithm. Regarding the improvement, we propose the adaptive extension method and the direction-constrained optimal node extension method (DCONE). Simulation experiments were conducted for DCAE-BA*, TTD-BA* and traditional A* algorithm (A*) in a large number of random two-dimensional map environments. The simulation experimental scenarios consider four types of start and end point relative directions and three obstacle proportions to objectively and comprehensively evaluate the performance of the proposed algorithms. The results show that different scenarios have a significant impact on the algorithm performance metrics. Finally, the overall performance of the proposed algorithm is evaluated with a large number of experiments in "random" scenarios, and the results show that DCAE-BA* obtains significantly better search time for all three obstacle proportions, and better path length and number of expanded nodes for 10% and 25% obstacle proportions. The effectiveness of the proposed DCAE-BA* algorithm is demonstrated, which provides an essential reference for the path planning of mobile robots in a random 2D map environment. • DCAE-BA* is improved by adaptive extension and direction-constrained optimal node extension (DCONE). • The Start-End Dir and obstacle proportions have a significant impact on the algorithm metrics. • Overall, the DCAE-BA* has the highest computational efficiency for all three types of obstacle proportion. • DCAE-BA* optimizes the path length in the "diagonal" scenario most significantly. • As the proportion of obstacles increases, the metric optimization effect decreases. [ABSTRACT FROM AUTHOR]

To study the influence of anisotropic transport properties of porous layers (PLs) on the dynamic performance (DP) of fuel cells (FC), a numerical model was developed. The model uses self-compiled codes to couple the actual structure of PLs with its transport capability, while introducing a non-homogeneous model that reflects the effect of the actual agglomerate structure of the catalyst layer on the electrochemical reaction, based on the consideration of the internal heat transport and external heat exchange of FC, the three-phase transformation of water, the change of momentum, energy, species, and water transport with time, and finally realizes the transient changes of complete transport and reaction process inside the FC. Using the current density as the input load, the law of the anisotropic transport properties of PLs on the FC's DP was explored. The results show that among all properties, the proton conductivity has the most significant influence on DP indexes such as steady-state transition time, over/undershoot amplitude, the electrical conductivity and diffusivity have similar and significant effects, the thermal conductivity and permeability have minor and most negligible effects, respectively. When designing the material, structure and composition of the PLs, the focus should be on protons, electron conductivity and diffusivity. • The effect of porous layers anisotropy on the transient behavior of FC was analyzed. • Coupled structural parameters and transport properties of the porous layers. • The effect of the CL's actual agglomerate structure on FC performance is considered. • Pointed out the porous layers transport capability that should be enhanced in focus. [ABSTRACT FROM AUTHOR]

In online battery model identification by recursive least squares (RLS), the identification biases are generated by the noises in the voltage and current measurements, further resulting in the accuracy degradation of model-based state of charge (SOC) estimation. Firstly, the detailed formula derivation presents the relationship between noise variances and identification biases in least squares. Then, through the practical identification on a general battery model, the consistent results from the formulas and simulations both adequately and quantitatively verify that the model identified by RLS is biased, when either only one of voltage and current measurements or both are corrupted by noises. To further assess the noise effects on SOC and parameter estimations, a conventional co-estimation algorithm joining RLS and extended Kalman filter (EKF) is applied into the simulations and experiments especially under noise corrupted measurements, the numerical results show that the estimation accuracy degradation generated by noises is quite considerable. Hence, bias compensation RLS and EKF co-estimation algorithms are proposed to alleviate the impact of the noises. Simulation and experiment studies show that the proposed algorithms can compensate the model identification biases caused by noises and can enhance SOC estimation accuracy under noise corrupted measurements. • Noise corruption on battery model identification bias in RLS is investigated. • Biases generated even only voltage or current measurement is corrupted by noise. • Noise effect on conventional RLS based co-estimation algorithm is investigated. • Three bias compensation RLS based co-estimation algorithms are proposed. • The superiority of the proposed methods is verified by simulations and experiments. [ABSTRACT FROM AUTHOR]

This article investigates the adaptive fuzzy prescribed time H ∞ congestion control problem for a class of high speed transmission control protocol/active queue management (HSTCP/AQM) systems subject to asymmetric input saturation and external disturbance. Firstly, a saturation-based finite-time performance function (SFTPF) is constructed by introducing a nonnegative modified signal associated with input saturation errors into user-defined performance boundaries, which features the capability of ensuring the user-appointed tracking performance when no saturation exists and degrading it once saturation occurs, thereby effectively increasing the flexibility and reliability of the control scheme. Then, by designing a novel shifting function, the condition that the initial value of the queue tracking error remains within that of SFTPF is relaxed, which avoids the SFTPF being redeveloped for different initial queue tracking errors. Thereafter, an auxiliary system and H ∞ control theory are employed to eliminate the adverse effect caused by input saturation and external disturbance, respectively. Moreover, through the Lyapunov stability analysis, it is proven that, under our proposed adaptive fuzzy congestion control scheme, all the closed-loop signals are bounded, and the connection between input saturation and performance-related constraint is established. Finally, a set of simulation results are presented to demonstrate the feasibility and effectiveness of the designed congestion controller. • A new shifting function is developed to relax the initial condition restriction. • An error transformation function is designed to solve asymmetric constrained issues. • The performance constraint boundaries can be resiliently enlarged and recovered. • An adaptive fuzzy practical prescribed time congestion control scheme is proposed. [ABSTRACT FROM AUTHOR]

• A semicircular baffle flow field with helical structure is proposed. • Considering the anisotropic mass and heat transfer properties of the porous layers. • Considering the actual agglomerate structure of the cathode catalyst layer. • The optimized flow field increases the fuel cell's net power density by 11.42 %. To effectively improve the fuel cell (FC) mass transport capacity, a new flow field (FF) design with helical baffle at the cathode is proposed, which facilitates gas flow and mass transfer in both through- and in-plane directions. To fully understand the influence of various design parameters on the FC performance, a series of studies were carried out with a semicircular baffle as an example. The effect of the baffle structure on the complex heat and mass transport process is studied in detail to obtain the optimal baffle structure parameters. To simulate the complete transport process, a three-dimensional, multiphase, non-isothermal steady-state model was developed, embedding the anisotropic transport properties caused by the porous layer structures and the heterogeneous model of the actual agglomerate structure of the catalyst layer in the model. The results show that the helical baffles induce cross flow under the ribs while inducing forced convection, enhancing the oxygen supply in both directions. The FF structure with baffle height and pitch of 0.4 mm and 1.0 mm respectively has the maximum net power density. Taking the relative humidity = 50 % and 100 % as an example, the net power density is increased by 11.42 % and 5.72 % respectively compared with the original FF. [ABSTRACT FROM AUTHOR]

Abstract: In the paper, crashworthiness of the S-shaped rail extracted from the frontal frame in a car is studied. In order to reduce the peak impact force while increasing the total absorbed energy, the hybrid materials are employed in that rail, where aluminum alloy is used for its front part and advanced high strength steel (AHSS) for its back part. By designing 16 experiments based on orthogonal experiment, the effect of five influence factors with four levels on the crash performance of the steel–aluminum hybrid S-shaped front rail is emphatically investigated. These influence factors include the different material types of aluminum alloy and AHSS, the sheet thicknesses of the two parts, and length proportion for the aluminum part. The AHSS includes dual-phase (DP) steel, transformation induced plasticity (Trip) steel and Mart steel; the aluminum alloy series include 5000 and 6000 series. The research result shows that the use of steel–aluminum hybrid materials can reduce the peak impact force and the total weight for the S-shaped front rail, while the total absorbed energy can be greatly increased, so the crashworthiness and lightweight of the S-shaped front rail are significantly improved. [Copyright &y& Elsevier]

The gas diffusion layer (GDL) is currently manufactured from randomly stacked carbon fibers, with each layer forming a different pore structure. This investigation attempts to know the effect of the random poral microstructures on the water transport capacity. The stochastic reconstruction approach to numerically establishes random fiber distributions in GDL and a three-dimensional two-phase volume of fluid model are developed and validated. By combining the two models the liquid water transporting inside the randomly different GDLs is numerically processed. Thus, those observed relations, such as the water coverage ratio (WCR) of the fiber layer (FL) plane and gas channel wall, saturation and pressure drop, are comparable in simulations. The results show that even if the porosity of each FL is the same, the uncertainty of liquid water movement due to the random structure can cause large state deviations with different GDLs, within the studied range. They can lead to significant differences in oxygen content within the same GDL volume and ultimately results in significantly different fuel cell performance. The mechanism of the effect of the randomness of GDL microstructure on water transport capacity is beneficial for further mining valid characteristic information of FLs and structure improvement. • The GDL pore structure was established using the stochastic reconstruction method. • A model that captures the behavior of liquid water through the pores was developed. • The effect of random stacking of fibers on liquid water transfer was investigated. • The effect of fiber layers' random arrangement on water transfer was investigated. [ABSTRACT FROM AUTHOR]

• An ultrasonic duplex model was developed for flaw detection in long butt-weld. • Floating potential can be used to parse several geometrical parameters of flaw. • Global energy vanishing time of flaw position exhibited an upward spiral. • Flaw length effects the peak number of floating potential upper envelope curve. • The energy decay rate increases with increasing flaw orientation angle. Non-destructive testing (NDT), as an indispensable technique for assessing welding quality, is expected to continuously improve. In this study, to obtain welding flaw geometrical parameters more simply and conveniently, their correlations with floating potential were explored using groups of simulation experiments. All the simulation experiments were performed with a well-designed duplex finite element model, which can simulate ultrasonic guided wave testing (UGWT) of flaws embedded in the metro traction beam butt weld. Experimental results proved that different geometrical parameters of welding flaws exhibited different traits on floating potential. Position, length and orientation parameters of flaw related individually to the energy vanishing point, the number of peaks, the travelling time between peaks, the energy decay rate and so on. Thus, recording the floating potential of the entire UGWT process shows great promise in elucidating flaw geometrical parameter information and makes the proposed approach possible for practical use. [ABSTRACT FROM AUTHOR]