Search Results (912)

To enable safe cooperative flight of multi-UAV formations in urban 3-D airspace with wind-field disturbances, we develop an integrated planning-control framework.The planning layer uses an APF-guided RRT* with continuous collision prediction and explicit velocity/acceleration limits, and compensates wind online.The control layer adopts a dual-loop MA-AADRC-SMC design. An adaptive ESO estimates disturbances for feed-forward cancellation, and an SMC term improves robustness and tracking accuracy. By coupling the planned trajectory with speed-weighted repulsive fields, the framework coordinates path and attitude in closed loop, enabling collision-free and overshoot-free formation flight in wind and clutter. Simulations show higher tracking accuracy and better formation stability than ADRC, PID and SMC. A Lyapunov analysis proves uniform boundedness and asymptotic stability. The framework is scalable to applications such as disaster assessment and urban air transport. Full article

This study proposes a novel egg-crate honeycomb core sandwich panel (SP-EHC) that combines the structural advantages of conventional lattice and grid configurations while mitigating their limitations in stability and mechanical performance. The design employs chamfered intersecting grid walls to create a semi-enclosed honeycomb architecture, enhancing out-of-plane stiffness and buckling resistance and enabling ventilation and drainage. To facilitate efficient and accurate structural analysis, a two-dimensional equivalent plate model (2D-EPM) is developed using the variational asymptotic method (VAM). This model significantly reduces the complexity of three-dimensional elasticity problems while preserving essential microstructural characteristics. A Reissner–Mindlin-type formulation is derived, enabling local field reconstruction for detailed stress and displacement evaluation. Model validation is conducted through experimental testing and three-dimensional finite element simulations. The 2D-EPM demonstrates high accuracy, with static analysis errors in load–displacement response within 10% and a maximum modal frequency error of 10.23% in dynamic analysis. The buckling and bending analyses, with or without initial deformation, show strong agreement with the 3D-FEM results, with deviations in the critical buckling load not exceeding 5.23%. Local field reconstruction achieves stress and displacement prediction errors below 2.7%, confirming the model’s fidelity at both global and local scales. Overall, the VAM-based 2D-EPM provides a robust and computationally efficient framework for the structural analysis and optimization of advanced sandwich panels. Full article

In this study, we formulate and analyze a deterministic mathematical model describing the transmission dynamics of pneumonia. A comprehensive stability analysis is conducted for both the disease-free and endemic equilibrium points. The disease-free equilibrium is locally and globally asymptotically stable when the basic reproduction number R₀ < 1, while the endemic equilibrium is locally and globally asymptotically stable when R₀ > 1. To evaluate effective intervention strategies, an optimal control problem is formulated by introducing time-dependent control variables representing awareness campaigns, screening of carriers, and treatment of infected individuals. Applying Pontryagin’s Maximum Principle, the simulation results confirm the effectiveness of the proposed control strategies in reducing the number of infections and mitigating the overall disease burden. The findings offer valuable insights into the control of pneumonia and highlight the potential impact of strategic public health interventions. Full article

This paper presents a fully implicit finite difference scheme for the numerical approximation of a wave equation featuring strong damping and a distributed delay term. The discretization employs second-order accurate approximations in both time and space. Although implicit, the scheme does not ensure unconditional stability due to the nonlocal nature of the delayed damping. To address this, we perform a stability analysis based on Rouché’s theorem from complex analysis and derive a sufficient condition for asymptotic stability of the discrete system. The resulting criterion highlights the interplay among the discretization parameters, the damping coefficient, and the delay kernel. Two quadrature techniques, the composite trapezoidal rule (CTR) and the Gaussian quadrature rule (GQR), are employed to approximate the convolution integral. Numerical experiments validate the theoretical predictions and illustrate both stable and unstable dynamics across different parameter regimes. Full article

This paper investigates distributed optimization problems for multi-agent systems with parametric uncertainties over unbalanced directed communication networks. To settle this class of optimization problems, a continuous-time algorithm is proposed by integrating adaptive control techniques with an output feedback tracking protocol. By systematically employing Lyapunov stability theory, perturbed system analysis, and input-to-state stability theory, we rigorously establish the asymptotic convergence property of the proposed algorithm. A numerical simulation further demonstrates the effectiveness of the algorithm in computing the global optimal solution. Full article

The increasing demand for high-performance power converters for electric vehicle (EV) applications places a significant emphasis on developing effective and robust control strategies for DC-DC converter operation. This paper deals with the development, simulation, and experimental validation of an adaptive Lyapunov-type Nonlinear Sliding Mode Control (L-SMC) strategy for a DC–DC boost converter, addressing significant uncertainties caused by large variations in system parameters (R and L) and ensuring the tracking of a voltage reference. The proposed control strategy employs the Lyapunov stability theory to build an adaptive law to update the parameters of the sliding surface so the system can achieve global asymptotic stability in the presence of uncertainty in inductance, capacitance, load resistance, and input voltage. The nonlinear sliding manifold is also considered, which contributes to a more robust and faster convergence in the controller. In addition, a logic optimization technique was implemented that minimizes switching (chattering) operations significantly, and as a result of this, increases ease of implementation. The proposed L-SMC is validated through both simulation and experimental tests under various conditions, including abrupt increases in input voltage and load disturbances. Simulation results demonstrate that, whether under nominal parameters (R = 320 Ω, L = 2.7 mH) or with parameter variations, the voltage overshoot in all cases remains below 0.5%, while the steady-state error stays under 0.4 V except during the startup, which is a transitional phase lasting a very short time. The current responds smoothly to voltage reference and parameter variations, with very insignificant chattering and overshoot. The current remains stable and constant, with a noticeable presence of a peak with each change in the reference voltage, accompanied by relatively small chattering. The simulation and experimental results demonstrate that adaptive L-SMC achieves accurate voltage regulation, a rapid transient response, and reduces chattering, and the simulation and experimental testing show that the proposed controller has a significantly lower steady-state error, which ensures precise and stable voltage regulation with time. Additionally, the system converges faster for the proposed controller at conversion and is stabilized quickly to the adaptation reference state after the drastic and dynamic change in either the input voltage or load, thus minimizing the settling time. The proposed control approach also contributes to saving energy for the application at hand, all in consideration of minimizing losses. Full article

To address the challenge of low trajectory tracking accuracy for underactuated unmanned underwater vehicles (UUVs) under external disturbances, this study proposes a method integrating backstepping control with improved active disturbance rejection control (IADRC), which enhances high-precision trajectory tracking performance for UUV systems. Firstly, a five-degree-of-freedom dynamic model is established according to the symmetrical structure characteristics of an underactuated UUV, and virtual control inputs are designed using the backstepping method to address the underactuated characteristics. To improve convergence speed and tracking accuracy, a nonsingular terminal sliding mode control (NTSMC) is incorporated into the ADRC framework. Additionally, a parameter-adaptive tracking differentiator (PATD) is developed to mitigate the “differential explosion” problem inherent in backstepping virtual control inputs. A model-assisted extended state observer (ESO) is also designed to accurately estimate system disturbances. Stability analysis, grounded in Lyapunov theory, rigorously proves that all tracking errors converge asymptotically to a small bounded neighborhood of the origin. Simulation results demonstrate the effectiveness and superiority of the proposed control strategy. Full article

The Fermi condensation flows in the sine-Gordon–Thirring model with two impurities coupling are investigated in this paper; these matter flows can be induced by the Ricci flow perturbation in the two-dimensional string $\sigma$ model. The Ricci flow perturbation equations are derived according to the Gauss–Codazzi equations, and the two-loop asymptotic perturbation solution of the cigar soliton is reduced by using a small parameter expansion method. Moreover, the thermodynamic quantities on the cigar soliton background are obtained by using the variational functional integrals method. Subsequently, the Fermi condensation flows varying with the momentum scale $\lambda$ are analyzed and discussed. We find that the energy density, the correlation function, and the condensation fluctuations will decrease, but the entropy will increase monotonically. The Fermi condensed matter can maintain thermodynamic stability under the Ricci flow perturbation. Full article

Type 2 diabetes (T2D) is a chronic metabolic disorder requiring effective management to avoid complications. Metformin is a first-line drug agent and is routinely prescribed for the control of glycemia, but its underlying dynamics are complicated and not fully quantified. This paper formulates a control-oriented and interpretable mathematical model that integrates metformin dynamics into a classic beta-cell–insulin–glucose (BIG) regulation system. The paper’s applicability to theoretical and clinical settings is enhanced by rigorous mathematical analysis, which guarantees the model is globally bounded, well-posed, and biologically meaningful. One of the key features of the study is its global stability analysis using Lyapunov functions, which demonstrates the asymptotic stability of critical equilibrium points under realistic physiological constraints. These findings support the predictive reliability of the model in explaining long-term glycemic regulation. Bifurcation analysis also clarifies the dynamic interplay between glucose production and utilization by identifying parameter thresholds that signify transitions between homeostasis and pathological states. Residual analysis, which detects Gaussian-distributed errors, underlines the robustness of the fitting process and suggests possible refinements by including temporal effects. Sensitivity analysis highlights the predominant effect of the initial dose of metformin on long-term glucose regulation and provides practical guidance for optimizing individual treatment. Furthermore, changing the two considered metformin parameters from their optimal values—altering the dose by ±50% and the decay rate by ±20%—demonstrates the flexibility of the model in simulating glycemic responses, confirming its adaptability and its potential for optimizing personalized treatment strategies. Full article

An asymptotic stability velocity tracking controller is designed to enable the autonomous maneuvering flight of unmanned helicopters. Firstly, taking the UH-60A without pilots as the research object, a high-efficient rotor aerodynamic modeling is developed, which incorporates a free-wake vortex method with the flap response of blades. The consummate flight dynamic model is complemented by wind tunnel-validated fuselage/tail rotor load regressions. Secondly, a linear state–space equation is derived via the small perturbation linearization method based on the flight dynamic model within the body coordinate system. A decoupled model is formulated based on the linear state–space equation by employing the implicit model approach. Subsequently, a system of ordinary differential equations is constructed, which is related to the deviation between actual velocity and its expected value, along with higher-order derivatives of this discrepancy. The I&I (immersion and invariance) theory is then employed to facilitate the design of a non-cascade control loop. Finally, the response of desired velocity in longitudinal channel is simulated with step signal to compare the control effect with a PID (proportional–integral–derivative) controller. By adjusting the coefficients, the response progress of the PID controller is similar to the effect of adaptive controller with I&I theory. However, there is no obvious overshoot in the process with I&I adaptive controller, and the average response amplitude accounts for 16.69% of the random white noise, which is 7.38% of the oscillation level under the PID controller. The parameter tuning complexity when employing I&I theory is significantly lower than that of the PID controller, which is evaluated by mathematical derivations and simulations. Meanwhile, the sidestep and pirouette maneuvers are simulated and analyzed to examine the controller in accordance with the performance criteria outlined in the ADS-33E-REF standards. The simulation results demonstrate that the speed expectation-oriented asymptotic stability control can achieve a fast response. Both sidestep and pirouette maneuvers can satisfy the desired performance requirements stipulated by ADS-33E-REF. Full article

This paper investigates the stabilization problem of a class of nonlinear systems characterized by non-minimum phase behavior within each subsystem, with a focus on an application to a gantry crane system that employs friction to control its swing angle. In practical crane operations, the demand for accelerated system response is critical to improving productivity; however, this often induces significant variations in the swing angle, potentially destabilizing the system. To overcome this challenge, we propose a hybrid control approach that combines the concept of multi-diffeomorphism with symmetry considerations to enhance the smoothness of transient responses. Unlike classical input–output feedback linearization, which typically relies on a single diffeomorphism and may compromise the zero dynamics stability, the proposed method distributes the transformation across multiple diffeomorphisms, ensuring balanced and coordinated transient behavior. The design involves the simultaneous development of subsystem-dependent feedback controllers, which collaboratively guarantee the global stability of the overall closed-loop nonlinear gantry crane system. The Lyapunov stability framework is employed to rigorously demonstrate that the tracking errors converge asymptotically to meet the desired performance specifications. In addition, the simulation results demonstrate that the developed hybrid control approach notably enhances the system’s responsiveness while preserving both symmetry and the stability of the zero dynamics. Specifically, the swing angle decreases by over 90% in less than 2 s, highlighting the method’s efficiency in minimizing oscillations during fast operations. This study highlights the practical benefits of integrating symmetry-aware multi-diffeomorphism techniques into nonlinear control design. Such techniques are found to be particularly effective for underactuated mechanical systems like gantry cranes. Full article

Corporate Social Responsibility (CSR) actively enhances social, economic, and environmental well-being, increasingly impacting society. It plays a vital role in building a trustworthy and transparent image for the banking system’s relationship with the community. In this context, the paper aims to analyse the effects of delayed adaptation by the banking system to reporting requirements, as well as the reasons that may cause oscillating behaviour on their part. Accordingly, three scenarios are developed to describe the behaviour of banks that experience regular fluctuations in the level of external sustainability reporting requirements, meaning the pressure to comply with these requirements may vary over time. The research method employed involves a dynamic analysis, utilising a mathematical model described by a nonlinear system with time delay. The goal of the research is to identify the equilibrium point of the system and analyse its asymptotic stability. Moreover, the critical time delay is provided, beyond which banks’ responses become oscillatory rather than stable. Numerical simulations illustrate the theoretical findings and reveal a critical delay value under which banks can stabilise their resources to meet sustainability requirements. Full article

The control of many industrial processes, such as superheated steam temperature control, exhibits poor robustness and degraded accuracy in the presence of model parameter uncertainties. This paper addresses this issue by developing a novel interval power integration-based nonlinear suppression scheme for a class of uncertain nonlinear systems with unknown but bounded parameters. The efficacy of this approach is specifically demonstrated for the superheated steam temperature control in thermal power plants. By integrating Lyapunov stability theory and homogeneous system theory, this method extends the traditional homogeneous degree theory to the interval domain, establishes interval boundary conditions for time-varying parameters, and constructs a Lyapunov function with interval numbers to recursively design the controller. Furthermore, the interval monotonic homogeneous degree and an admissibility index are introduced to ensure system stability under parameter uncertainties. The effectiveness of the proposed method is verified through numerical simulations of superheated steam temperature control. Simulation results demonstrate that the method effectively suppresses nonlinearities and achieves robust asymptotic stability, even when model parameters vary within bounded intervals. In the varying-exponent scenario, the proposed controller achieved an Integral of Absolute Error (IAE) of 70.78 and a convergence time of 37s for the superheated steam temperature control. This represents a performance improvement of 42.79% in IAE and 53.16% in convergence time compared to a conventional PID controller, offering a promising solution for complex thermal processes with inherent uncertainties. Full article

This paper conducts a rigorous study on the spectral properties and operator-space distances of perturbed Dirichlet–Neumann tridiagonal (PDNT) Toeplitz matrices, with emphasis on their asymptotic behaviors. We establish explicit closed-form solutions for the eigenvalues and associated eigenvectors, highlighting their fundamental importance for characterizing matrix stability in the presence of perturbations. By exploiting the structural characteristics of PDNT Toeplitz matrices, we obtain closed-form expressions quantifying the distance to normality, the deviation from normality. Full article

As a typical porous medium, unsaturated loess demonstrates critical hydro-mechanical coupling properties that fundamentally influence geohazard mitigation, groundwater resource evaluation, and foundation stability in geotechnical engineering. This investigation develops a novel theoretical framework to overcome the limitations of existing models in converting electrical resistivity tomography (ERT) profiles into water content distributions for unsaturated loess through quantitative inversion modeling. Systematic laboratory investigations on remolded loess specimens with controlled density and water content conditions revealed distinct resistivity–water interaction mechanisms. A characteristic two-stage decay pattern was identified: resistivity exhibited an exponential decrease from 420 Ω·m (water saturation (S_w = 10%)) to 90 Ω·m (S_w = 40%), followed by asymptotic stabilization at S_w ≥ 40%. The derived quantitative correlation provides a robust mathematical basis for water content profile inversion. Field validation through integrated ERT and borehole data demonstrated exceptional predictive accuracy in shallow strata (<20 m depth), achieving mean absolute errors of <5%. However, inversion reliability decreased with depth (>20 m), primarily attributed to density-dependent charge transport mechanisms. This underscores the necessity of incorporating coupled thermo-hydro-mechanical processes for deep-layer characterization. This study provides a robust framework for engineering applications of ERT in loess terrains, offering significant advancements in geotechnical monitoring and geohazard prevention. Full article