Magnitude Of Input Research Articles

Discrete-time partial control of transiently chaotic systems under stochastic perturbations.

Stochastic perturbations can steer the response of a nonlinear system to specific regions of the system state space, including equilibrium points, periodic solutions, and aperiodic (including chaotic) solutions. This study constructs a discrete partial control scheme to confine the response trajectories of a forced Duffing oscillator, showing transient chaos, within a chaotic attractor, thereby avoiding undesired behavior. The system is analyzed in the presence of white noise, using a minimally bounded control input. The primary motivation is to evaluate the viability of applying bounded control inputs at discrete time instants over intervals differing from the forcing period and to examine the required control input magnitude for response confinement. Results demonstrate that the system can be effectively controlled with relatively small magnitude control inputs applied at discrete time instants. A careful selection of time steps is crucial to ensure that the response trajectory remains within the desired region. The scheme's formulation and the associated algorithm are independent of the system dimension.

Geographic Information System and Contamination Indices for Environmental Risk Assessment of Landfill Disposal Sites in Central Saudi Arabia

Landfills pollute air, soil, and surface and groundwater worldwide. The present work aims to assess the environmental risks of three landfills in southern Riyadh using GIS, soil quality guidelines, and contamination indices. GIS tools indicated an increase in the area of the landfill sites with time. The concentration of heavy metals (HMs) in the investigated landfills had the following descending order: Fe (11,532 mg/kg) ˃ Al (5405 mg/kg) ˃ Pb (561.7 mg/kg) ˃ Zn (356.8 mg/kg) ˃ Mn (165 mg/kg) ˃ Cr (74.8 mg/kg) ˃ Cu (42.7 mg/kg) ˃ Ni (22.4 mg/kg) ˃ V (21.8 mg/kg) ˃ As (5.16 mg/kg) ˃ Co (4.08 mg/kg). The highest values of Al, As, Co, Ni, Pb, V, and Zn were recorded from Al Kharj road landfill (RL3). However, the average values of all HMs were lower than those from most worldwide soils and backgrounds, except for Zn, Cu, Cr, and Pb. Results of enrichment factor and statistical analysis indicated deficiency to minimal enrichment and geogenic sources for Al, Co, Mn, and V, while those of As, Cr, Pb, Zn, and Cu showed EF ˃ 2, which might be indicative of anthropogenic activities, especially in RL3. Additionally, very high contamination and a high effects range—median were reported in individual samples, especially for Pb, As, and Zn, indicating frequent adverse effects for these HMs. The difference in contamination for the HMs in the studied landfill sites might be attributed to the difference in the magnitude of input for each metal into the landfill site and/or the difference in the removal rate of each metal from it.

Neural Network-Based Nonconservative Predefined-Time Backstepping Control for Uncertain Strict-Feedback Nonlinear Systems.

To handle the tracking problem of uncertain strict-feedback nonlinear systems with matched and mismatched composite disturbances, this article studies a predefined-time backstepping controller by resorting to a Lyapunov-based predefined-time dynamic paradigm, a regulation function, and neural networks (NNs). Moreover, an adding-absolute-value (ADV) technique is adopted in the design process to remove the control singularity. Theoretical analyses prove the boundedness of all closed-loop system signals and the predefined-time convergence of the tracking error into an arbitrarily small vicinity of the origin. The proposed controller exhibits four advantages: 1) the actual convergence time is precisely predefined by only one design parameter irrespective of the initial conditions, and the control energy is economized; 2) no unbounded terms are adopted for predefining the actual convergence time, thus avoiding numerical overflow problem under limited memory space and gaining strong noise-tolerant ability; 3) the peaking tracking error and control input magnitude can be effectively reduced by appropriately setting parameters of the regulation function; and 4) the controller is continuous and nonsingular everywhere. Finally, a practical example of a single-link manipulator is presented to validate the efficacy and superiority of our predefined-time controller.

Consensus tracking control for nonlinear second-order multi-agent systems with input magnitude and rate constraints

In this study, consensus tracking control is considered for a class of nonlinear second-order multi-agent systems in an undirected communication topology subject to input magnitude and rate constraints (MRCs). Initially, the control inputs are designed directly using the smooth hyperbolic tangent function. Subsequently, some auxiliary signals are developed to guarantee input rate constraints simultaneously. By employing the backstepping method, the proposed control scheme can ensure uniform ultimate boundedness of the closed-loop system, and the consensus tracking error of each agent can converge to a small neighborhood near zero. Finally, the single-link robot manipulator multi-agent system model is used to perform numerical simulations to demonstrate the control effect further.

Nonlinear steering control law under input magnitude and rate constraints with exponential convergence

A ship steering control law is designed for a nonlinear maneuvering model whose rudder manipulation is constrained in both magnitude and rate. In our method, the tracking problem of the target heading angle with input constraints is converted into the tracking problem for a strict-feedback system without any input constraints. To derive this system, hyperbolic tangent (tanh\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ anh$$\\end{document}) function and auxiliary variables are introduced to deal with the input constraints. Furthermore, using the feature of the derivative of tanh\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ anh$$\\end{document} function, auxiliary systems are successfully derived in the strict-feedback form. The backstepping method is utilized to construct the control input for the resulting cascade system. The proposed steering control law is verified in numerical experiments, and the result shows that the tracking of the target heading angle is successful using the proposed control law.

Backstepping control of hypersonic vehicles under input and output constraints with model uncertainties and disturbances

In this paper, considering the physical restriction of hypersonic vehicle systems in a practical flight environment, the altitude tracking problem is studied with input magnitude, input rate, output constraints, system parameter uncertainties and disturbances, which expands the traditional considerations of control methods in the hypersonic vehicle field. The hyperbolic tangent function is employed to address the system input constraints. Furthermore, the incorporation of barrier Lyapunov function serves to ensure that the system output is limited in the prescribed limitations. In particular, two extended state observers are integrated to eliminate errors from model uncertainties and disturbances. Based on the effective combination of these techniques and auxiliary variable designs, a novel backstepping controller is proposed to simultaneously handle problems of input and output constraints, model uncertainties and disturbances. The closed-loop system stability is demonstrated using the Lyapunov theory. Simulation results show the effectiveness and superiority of the proposed controller compared with the traditional backstepping controller.

Wire arc additive manufacturing of ZL205A: Heat input effect on the forming quality, pore defects and mechanical properties

The magnitude of heat input (HI) plays a pivotal role in determining the deposition quality of wire arc additive manufacturing (WAAM) components. This article studies the effects of high and low HI on the forming quality, microstructure, pore defects, and mechanical properties of ZL205A parts, providing a theoretical foundation for choosing optimal HI parameters in the utilization of WAAM technology to fabricate ZL205A structural components. In this study, four thin-walled walls, SP1, SP2, SP3, and SP4, were manufactured with HI of 300.12, 200.08, 163.70, and 138.51 J/mm, respectively. The findings show that the SP4 has the least side forming error, and the maximum deposition efficiency, resulting in the best forming quality. From microstructural studies，SP4 has the lowest average grain size, 72μm. The quantity of θ phases (Al2Cu) on the grain boundary and the quantity and size of θ' phases in the middle and bottom grains both diminish with decreasing HI. As the HI decreases, the porosity of the four samples shows a trend of first decreasing and then increasing, with the highest being 1.41 % of the SP1. This change is explained from the four stages of bubble nucleation, growth, detachment, and escape. Reducing HI can significantly improve the ultimate tensile strength (UTS), and yield strength (YS) of the specimen. The SP4 has the highest UTS and YS, which are 232.99 MPa and 101.20 MPa, respectively.

A Curvilinear Transfer Function for Wide Dynamic Range Compression with Expansion

Wide Dynamic Range Compression in hearing aids is becoming increasingly more complex as the number of channels and adjustable parameters grow. At the same time, there is growing demand for customization and user self-adjustment of hearing aids, necessitating a balance between complexity and user accessibility. Compression in hearing aids is governed by the input-output transfer function, which relates input magnitude to output magnitude, and is typically defined as a combination of linear piecewise segments resembling logarithmic behavior. This work presents an alternative to the conventional compression transfer function that consolidates multiple compression parameters and revisits expansion in hearing aids. The curvilinear transfer function is a continuous curve with logarithm-like behavior, governed by two parameters—gain and compression ratio. Experimental results show that curvilinear compression reduces the amplification of low-level noise, improves signal-to-noise ratio by up to 1.0 dB, improves sound quality as measured by the Hearing Aids Speech Quality Index by up to 6.7%, and provides comparable intelligibility as measured by the Hearing Aids Speech Perception Index, with simplified parameterization compared to conventional compression. The consolidated curvilinear transfer function is highly applicable to over-the-counter hearing aids and offers more capabilities for customization than current prominent over-the-counter and self-adjusted hearing aids.

Joint Characteristics of Cu-Ni Alloy Fabricated by GTAW and MPAW Processes: A Comparative Study

The current work presents a comparative analysis of the joint behavior of Cu-Ni alloy weldments fabricated by Micro-Plasma Arc Welding (MPAW) and Gas Tungsten Arc Welding (GTAW) processes. The Cu-Ni alloy thin sheets are fabricated at different values of heat input (~40-135 J/mm) by MPAW and GTAW processes, respectively. Further, to evaluate their characteristics, joints are subjected to metallurgical, mechanical, and electrochemical testing. The joints fabricated with a higher magnitude of heat input resulted in deteriorated surface quality with a value of Ra~ 6.13 μm. The increased surface roughness value of the joints resulted in a higher corrosion rate (1.273 mm/year). A finer microstructural morphology is achieved for lower heat input condition. Accordingly, the weldment exhibited higher joint efficiency of ~91%.The prominent reason for achieving higher joint strength is related to the presence of lower secondary dendritic arm spacing (SDAS), which enhances the joint strength and ductility for the joints as compared to higher SDAS value. Further, the micro-fractography analysis reveals the presence of micro/macro-voids for high heat input, whereas the existence of numerous dimples of varying size and depth is observed for low heat input condition, implying the role of heat input of utmost importance.

Switching Anti-windup Synthesis for Linear Systems Subject to Asymmetric Input Magnitude and Rate Saturation: Application to Aircraft Engines

Switching Anti-windup Synthesis for Linear Systems Subject to Asymmetric Input Magnitude and Rate Saturation: Application to Aircraft Engines

Asymmetric integral barrier Lyapunov function-based three-dimensional integrated guidance and control design with field-of-view constraint and input saturation

This paper proposes an adaptive integrated guidance control (IGC) scheme for the flight vehicle intercepting the maneuvering target with asymmetric field-of-view angle constraint, input magnitude and rate saturation, and system uncertainties. A novel nonlinear three-dimensional IGC model is established in the body line-of-sight (LOS) coordinate system by employing the dual-integral control law. Based on this model, the input magnitude and rate saturation for the conventional IGC system can be converted to the limitations of the new augmented states. Asymmetric integral barrier Lyapunov function and dynamic surface control approach are applied to deal with the asymmetric state constraints of the proposed IGC model, and adaptive control laws are designed to compensate for model uncertainties. Furthermore, based on the Lyapunov stability theory, it is proved that all signals in the closed-loop system are bounded while the constrained states are not violated. Finally, the effectiveness and robustness of the proposed IGC scheme are illustrated with numerical simulations.

Minimal learning parameters-based simplified robust adaptive saturated control for dynamic positioning ship with input magnitude and rate saturations

In this study, a simplified robust adaptive saturated control strategy based on minimal learning parameters is developed for the dynamic positioning of ship with input magnitude and rate saturations, unknown external environment disturbance and dynamic uncertainties. Firstly, an augment model is developed to restrict the boundedness of the actuators while the input magnitude and rate saturations can be shown in a high-order model. Then, radial basis function neural networks are applied to formulate a new control law via the velocities backstepping method to hand with the dynamic uncertainties. In particular, the minimal learning parameters method is used to reduce the computational complexity, with a single parameter needing to be updated in each step of backstepping. Meanwhile, robust adaptive compensation terms are introduced into the design of virtual and actual control while the error caused by neural networks is mitigated. In line with the Lyapunov theory, the uniformly ultimately boundedness of all signal in closed-loop control system is demonstrated. Finally, simulation is performed to illustrate the advantage and effectiveness of the proposed control strategy.

Fixed-Time Consensus Based on a Fractional Adaptive Gain for Multi-Agent Systems

In this article, a fractional adaptive gain is adopted to solve fixed-time consensus problem. Both leaderless and leader-following consensus based on different communication topologies are considered and the stability is proved by Lyapunov analysis. With the help of the adaptive gain, the settling time is related to the first zero of a Mittag-Leffler function. Theoretical analysis demonstrates that the proposed protocol has smoother control input since the fractional gain is adaptive, and it is more robust since it is not time-based. The results of the simulation show that the convergence rate is faster and both the initial and the magnitude of the control input are smaller under our protocols. In addition, the basis of selecting parameters in the proposed method is also presented, which is consistent with the simulation results.

Three-dimensional transient heat transfer analysis of micro-plasma arc welding process using volumetric heat source models

Abstract The micro plasma arc welding process is associated with different physical phenomena simultaneously. This results in complexities to comprehend the actual mechanism involved during the process. Therefore, a robust numerical model that can compute the weld pool shape, temperature distribution, and thermal history needs to be addressed. Unlike, other arc welding processes, the micro plasma arc welding process utilizes thin sheets of thickness between 0.5 and 2 mm. However, joining thin sheets using a high-density arc welding process quickens the welding defects such as burn-through, thermal stresses, and welding-induced distortions. The incorporation of a surface heat source model for computational modeling of the high energy density welding process impedes heat transfer analysis. In that respect, researchers have developed numerous volumetric heat source models to examine the welding process holistically. Although, selecting volumetric heat source models for miniature welding is a significant task. The present work emphasis developing a rigorous yet efficient model to evaluate weld pool shape, temperature distribution, and thermal history of plasma arc welded Ti6Al4V sheets. The computational modeling is performed using a commercially available COMSOL Multiphysics 5.4 package with a finite element approach. Two different prominent thermal models, namely, Parabolic Gaussian and Conical power energy distribution models are used. A comparative analysis is carried out to determine the most suitable heat source model for evaluating temperature distribution, peak temperature, and thermal history. The analysis is done by juxtaposing the simulated half-cross-section weld macrographs with the published experimental results from independent literature. The numerical results showed that the proximity of top bead width magnitude was obtained using the Parabolic Gaussian heat source model for low heat input magnitude of 47.52 and high heat input magnitude of 65.47 J·mm−1, respectively. In terms of percentage error, the maximum top bead width percentage error for the Parabolic heat source model is 13.26%. However, the maximum top bead width percentage error for the Conical heat source model is 18.36%. Likewise, the maximum bottom bead width percentage error for the Parabolic heat source model and the Conical heat source model is 12.3 and 25.8%, respectively. Overall, it was observed that the Parabolic heat source model produces the least deviating outcomes when compared with the Conical distribution. It was assessed that the Parabolic Gaussian heat source model can be a viable heat source model for numerically evaluating micro-plasma arc welded Ti6Al4V alloy of thin sheets.

Shaking table tests of a full-scale base-isolated flat-bottom steel silo equipped with curved surface slider bearings

This paper presents a series of shaking table tests on a full-scale flat-bottom steel silo filled with soft wheat, under isolated-base conditions. The tested specimen is a 3.64 m-diameter 5.50 m-height corrugated-wall cylindrical silo, representing the smallest manufactured silo available in the catalogue of an Italian commercial silo provider. Curved Surface Slider isolators were introduced between the shaking table and the reinforced-concrete plate, on which the silo was mounted, to realize the isolated configuration where the main results have been investigated and compared with other results for the same silo specimen under fixed-base conditions. A detailed description of the silo components, the filling bulk material properties as well as the test setup is provided, including the full testing protocol. Multiple sensors were used to monitor the dynamic response of the filled silo system, including accelerometers, pressure cells, LVDT displacement transducers. Numerous unidirectional dynamic tests were conducted consisting of random signals, sinusoidal inputs, pulse-like inputs, and both artificial and real earthquake records. The results were processed to evaluate the performance of the isolators and their effectiveness on the silo response in terms of measured accelerations and dynamic overpressures. The efficiency of the isolation on the reduction of both acceleration amplifications over the silo wall height as well as the captured dynamic overpressures were detected in the range 30%–80% depending on the input type and magnitude.

Event-based adaptive fuzzy tracking control for nonlinear systems with input magnitude and rate saturations

In this paper, an event-based adaptive fuzzy tracking control strategy for a class of uncertain nonlinear systems with limited control input and its rate of change is proposed. The unknown nonlinear function of the considered system is approximated by a fuzzy logic system (FLS). Furthermore, an event-triggered control method is developed to save the computing resources, in which the controller parameters are adaptively adjusted by a fuzzy controller. Moreover, it is proved by designing the Lyapunov function that the event-based controller can ensure that all signals of the controlled system are bounded. In addition, the tracking error can converge to a preset domain. Meanwhile, two practical simulations are given to demonstrate the effectiveness of the proposed method.

Electrical conductivity as a reliable indicator for assessing land use effects on stream N2O concentration

While it is widely acknowledged that different categories of terrestrial land use significantly affect N2O emissions from streams and rivers, a suitable indicator to comprehensively reflect such influences is still lacking. This study examined the effectiveness of stream environmental and microbial factors in reflecting the influence of land use types on stream N2O concentrations, taking into account both endogenous N2O production and exogenous N2O inputs. Our results showed that human-disturbed (urban and agricultural) streams had nearly four times higher excess N2O concentrations (ΔN2O) than forest streams (5.01 versus 1.32 nmol/L N2O). By combining our observations with previous studies, we identify electrical conductivity as a significant and even the strongest predictor of (excess) N2O concentration and flux in streams across different land uses, surpassing the predictive power of nitrogen content. Elevated ΔN2O was observed at higher conductivities (r = 0.69, p < 0.01), which coincided with higher carbon and nutrient levels across different types of land use. Also, conductivity was positively correlated with the abundance of N2O-producing microbes (p < 0.05), including both nitrifying and denitrifying microbes. Denitrifiers adapted to human disturbance and the genetic potential for net N2O production, as evidenced by the positive correlation between conductivity and nir:nosZ ratio, were enhanced under high-conductivity conditions (p < 0.05). Furthermore, electrical conductivity had great potential to qualitatively indicate the magnitude of exogenous N2O input across different land uses. Overall, our results highlight the value of electrical conductivity as a reliable indicator for assessing the effect of land use types on stream N2O concentrations. This opens opportunities for the development of simple field-based assessments of riverine N2O emissions across regional landscapes.

An Improved Design of Absolute-value Detector by Using Optimized Ripple Adder

Absolute-value detector (AVD) is one of the most basic bit-operating devices, which compares the magnitude of two inputs. However, the traditional 4-bit AVD is not only time-consuming but also has a high energy consumption. This paper uses a hybrid design to optimize the 4-bit AVD by introducing an improved ripple adder in the absolute value extraction part, which then can be less energy-consuming and requires fewer transistors. The paper divides the design of AVD into an absolute value extraction part and a comparator. The input (2’s complement) can be positive or negative numbers in the absolute value extraction part. By observing the most significant bit (MSB) of the input, the design can determine the sign of input and output magnitude. For the comparator, this paper uses a logic of step-by-step comparison from the most to the least significant bits. Then, this paper finds the minimum delay of the design by critical path analysis and gate sizing. The final delay is set at 1.5 times its minimum. Device voltage optimization is applied for calculating the energy consumption. Finally, with 1.5 times the minimum delay, the energy consumption is 40% less than the consumption when the delay is the minimum.

Eruptive dynamics reflect crustal structure and mantle productivity beneath volcanoes

Abstract Volcanoes exhibit a wide range of eruptive and geochemical behavior, which has significant implications for their associated risk. The suggested first-order drivers of intervolcanic diversity invoke a combination of crustal and mantle processes. To better constrain mantle-crustal-volcanic coupling, we used the well-studied Lesser Antilles island arc. Here, we show that melt flux from the mantle, identified by proxy in the form of boron isotopes in melt inclusions, correlates with the long-term volcanic productivity, the volcanic edifice height, and the geophysically defined along-arc crustal structure. These features are the consequence of a variable melt flux modulating the pressure-temperature-composition structure of the crust, which we inverted from xenolith mineral chemistry. Mafic to intermediate melts reside at relatively constant temperature (981 ± 52 °C; 2σ) in the middle crust (3.5–7.1 kbar), whereas chemically evolved (rhyolitic) melts are stored predominantly in the upper crust (&amp;lt;3.5 kbar) at maximum depths that vary geophysically along the arc (6–15 km). Our findings are applicable worldwide, where we see similar correlations among average magma geochemistry, eruptive magnitude, and rate of magma input.

Building Intelligence in the Mechanical Domain—Harvesting the Reservoir Computing Power in Origami to Achieve Information Perception Tasks

Herein, the cognitive capability of a simple, paper‐based Miura‐ori—using the physical reservoir computing framework—is experimentally examined to achieve different information perception tasks. The body dynamics of Miura‐ori (aka its vertices displacements), which is excited by a simple harmonic base excitation, can be exploited as the reservoir computing resource. By recording these dynamics with a high‐resolution camera and image processing program and then using linear regression for training, it is shown that the origami reservoir has sufficient computing capacity to estimate the weight and position of a payload. It can also recognize the input frequency and magnitude patterns. Furthermore, multitasking is achievable by simultaneously applying two targeted functions to the same reservoir state matrix. Therefore, it is demonstrated that Miura‐ori can assess the dynamic interactions between its body and ambient environment to extract meaningful information—an intelligent behavior in the mechanical domain. Given that Miura‐ori has been widely used to construct deployable structures, lightweight materials, and compliant robots, enabling such information perception tasks can add a new dimension to the functionality of such a versatile structure.