Search Results (249)

This paper examines the rotational motion of a compound mechanical system comprising a rigid carrier body equipped with internal gyroscopic devices and a point mass that moves along a prescribed trajectory relative to the body. The system undergoes free motion in a uniform gravitational field. We derive the complete equations of motion accounting for the constant gyrostatic torque (GT) generated by internal rotors. Using asymptotic methods, we develop approximate dynamical equations valid under two distinct physical scenarios: (i) when the moving mass is small relative to the carrier mass and executes rapid oscillations and (ii) when the mass oscillates with small amplitude near a fixed location within the body, regardless of mass ratio. The accuracy and validity range of these approximations are rigorously established. For the first scenario, we have approached the idea that gyrostatic coupling fundamentally alters the system’s integrability properties while introducing beneficial stabilization mechanisms. We characterize families of permanent rotational states and analyze their stability using linear perturbation theory. The second scenario reveals that the approximate dynamics correspond to gyrostat motion rather than the classical Euler–Poinsot case. Comprehensive numerical simulations validate theoretical predictions and demonstrate applications to spacecraft attitude control problems. The results provide practical design guidelines for gyrostabilized systems with internal moving components. Full article

Contact–impact phenomena caused by joint clearances can significantly alter the dynamic response of high-speed mechanical systems, yet fewer studies combine analytical impact-force modeling, virtual prototyping, and experimental observations for multi-cylinder internal combustion engine mechanisms within a unified framework. This problem is scientifically important because the piston–connecting rod–crankshaft chain is subjected to rapid motion reversals, high transmitted loads, and local clearances that may generate shocks, force amplification, and vibration growth. The objective of this study is to evaluate the influence of mechanical impact on the dynamic response of a three-cylinder inline engine mechanism by combining analytical modeling, MSC Adams virtual prototyping, and experimental investigation. The mechanism was analyzed in two operating conditions: under load, using an experimentally derived gas pressure input, and without load at low speed imposed on the crankshaft, using a sectioned engine test bench. The loaded virtual model was studied at a crankshaft speed of 6000 rpm, with cylinder gas pressure peaks above 90 bar and engine torque oscillating around 170 Nm. A radial clearance of 0.03 mm was introduced in the connecting rod–piston joint to evaluate clearance-induced impacts. The results showed that the damping coefficient strongly influences the amplitude and harmonic content of the impact force. For the analyzed no-load case at low speed, the simulated impact force reached a maximum value of 3000 N. Experimentally, the worn connecting rod with 0.03 mm clearance exhibited markedly higher dynamic response than the clearance-free case, with the maximum longitudinal acceleration increasing from 17.77 to 48.26 m/s² at 1.341 Hz. The novelty of the study lies in the integrated analytical–virtual–experimental investigation of clearance-induced impact in a three-cylinder inline engine mechanism and in the comparative evaluation of its effects on joint forces and vibration signatures. In addition, compared to other models, the novelty lies in introducing and adapting the impact force damping component for mechanisms with rapid motion and high dynamic loads. Full article

The rotational evolution of pulsars is governed by torque mechanisms whose mathematical structure encodes fundamental symmetries of the underlying physics. We demonstrate that the standard spin-down equation $\dot{f}=-sf-r{f}^3-g{f}^5$ derives from a discrete antisymmetry requirement, namely invariance of the torque under reversal of rotation sense, which restricts the frequency dependence to odd integer powers. We show that physically motivated plasma processes systematically break this symmetry, introducing fractional frequency exponents: viscous Ekman pumping at the crust–superfluid boundary layer ($f^{3/2}$), magnetohydrodynamic turbulent dissipation via Kolmogorov and Sweet–Parker cascades ($f^{10/3}$, $f^{11/3}$), non-linear superfluid vortex dynamics ($f^{5/2}$), and saturated r-mode oscillations ($f^{7-2\beta }$). The central result is an exact analytical resolution of the long-standing Crab pulsar braking index puzzle: the observed $n=2.51\pm 0.01$, which has defied explanation for nearly four decades, emerges naturally from the superposition of magnetic dipole radiation ($\dot{f}\propto f^3$) and boundary layer Ekman pumping ($\dot{f}\propto f^{3/2}$), with analytically derived coefficients yielding a dipole-component surface field $B_p=6.2\times {10}^{12}$ G—higher than the standard $\sqrt{P\dot{P}}$ estimate of $3.8\times {10}^{12}$ G, because that formula conflates dipole and non-dipole torques, but lower than applying the Larmor formula to the full spin-down rate ($7.6\times {10}^{12}$ G), since $32.7\%$ of the total torque is non-radiative boundary-layer dissipation. We develop the Riemann–Liouville fractional calculus formalism for these equations, showing that fractional derivatives break time-translation symmetry through intrinsic memory effects, with solutions expressed in terms of Mittag-Leffler and Fox H-functions that interpolate continuously between exponential (fully symmetric) and power-law (scale-free symmetric) relaxation. Lambert–Tsallis $W_q$ functions with non-extensive parameter q encoding broken statistical symmetry enable equation-of-state-independent inference of neutron star compactness and tidal deformability. Our framework establishes a unified symmetry-based classification of pulsar spin-down mechanisms and predicts frequency-dependent braking indices evolving at rate $\mathrm{d}n/\mathrm{d}t\sim 2\times {10}^{-4}$ yr⁻¹, yielding $\mathrm{\Delta }n\approx 0.01$ over 50 years—testable with current pulsar timing programmes. The formalism provides a coherent theoretical foundation connecting plasma microphysics at the neutron star interior to macroscopic observables in electromagnetic and gravitational wave channels. Full article

This paper proposes a Black Kite Algorithm (BKA)-based hyperparameter optimization method for Artificial Neural Network (ANN) training, mitigating local minimum issues associated with conventional training techniques. The resulting BKA-ANN model is then employed to estimate PID controller parameters for DC motor speed regulation. A large-scale dataset of 100,000 samples was generated via MATLAB simulation, with reference speed and load torque stochastically varied, and optimal PID parameters determined by minimizing the ITAE criterion for each operating condition. The optimized controller was evaluated under various operating conditions including transient response, frequency domain analysis (phase margin and bandwidth), parametric robustness, and load disturbance suppression, along with control effort and energy consumption assessments. The proposed BKA-ANN approach was benchmarked against nine algorithms: hybrid atom search optimization-simulated annealing (hASO-SA), harris hawks optimization (HHO), Henry gas solubility optimization with opposition-based learning (OBL/HGSO), atom search optimization (ASO), henry gas solubility op-timization (HGSO), stochastic fractal search(SFS), grey wolf optimization (GWO), sine–cosine algorithm (SCA), and Standard ANN. Simulation results indicate that BKA-ANN achieves stable performance across all tested scenarios, with minimal oscillation and competitive settling time compared to the evaluated algorithms. Full article

Precise and smooth actuation is a central requirement in surgical robotics, where small tracking errors or oscillations can directly affect task quality and safety. This paper studies the control of an induction-motor-driven surgical joint using a sliding-mode strategy enhanced by fractional-order operators and implemented within a DTC–SVM structure. The motivation is to improve motion smoothness and disturbance rejection without sacrificing the fast dynamic response offered by direct torque control. A dynamic model of the actuator is developed by combining the electrical equations of the induction motor with the mechanical dynamics of a robotic joint, including inertia, viscous friction, gravity-induced torque, and Coulomb friction. Fractional-order sliding surfaces are introduced for both position and flux regulation, and the closed-loop stability is examined through Lyapunov-based arguments. Simulation results show accurate trajectory tracking with limited overshoot and smooth transient responses. The motor speed remains well regulated, while stator flux and currents stay within admissible bounds. The electromagnetic torque adapts to load variations with reduced ripple, and the rotor pulsation remains bounded. Within the limits of numerical evaluation, these results indicate that the proposed fractional-order sliding-mode DTC–SVM scheme is suitable for precision-oriented surgical robotic actuation. Full article

High-temperature, high-pressure (HTHP) hard-rock drilling frequently causes chamfer spalling of polycrystalline diamond compact (PDC) cutters, leading to ~20% loss in the rate of penetration (ROP) and large torque oscillations. We propose a surface-gradient chamfer comprising a thin SiC interlayer (t_SiC ≈ 0.7 μm) and a nanocrystalline diamond topcoat (t_D ≈ 5 μm, d_D ~100 nm), combined with shallow cobalt leaching (L_deCo ≈ 100 μm). The structure was verified by microscopy/spectroscopy and evaluated by scratch adhesion, SEVNB toughness, instrumented impact, thermal shock, 400 °C pin-on-disc wear, and bench-scale granite drilling with vibration/torque monitoring. A coupled thermo-mechanical finite-element model, calibrated with Raman stress maps and thermal measurements, was used to interpret failure trends. Relative to untreated cutters, the gradient design reduced peak tensile residual stress by ~45% and lowered high-temperature wear volume by ~40%. In the present impact dataset (limited cutters per condition), the observed spall incidence at 1.0 J decreased from 2/3 (baseline) to 1/5 (gradient-treated). Short bench drilling runs suggested improved signal separability between healthy and pre-spall states (ROC-AUC ≈ 0.85 vs. ~0.65 for baseline, evaluated using a leave-one-cutter-out protocol); these drilling results should be interpreted as trend-level evidence given the limited number of cutters. These gains arise from mitigated thermal mismatch and residual stresses at the chamfer. Full article

This paper investigates the dynamics of a permanent magnet synchronous motor (PMSM) and controls its chaotic speed behavior using the synergetic control technique (SCT). The model includes electrical dynamics in the dq frame and mechanical speed dynamics, with a scalar parameter $\gamma$ capturing cross-coupling effects. The equilibrium structure and local stability properties of the PMSM are analyzed. For zero input voltages and zero load torque, the system exhibits a pitchfork-type bifurcation in the electrical–mechanical equilibrium as $\gamma$ crosses a critical value. Explicit expressions are derived for all equilibria, and their stability is characterized using eigenvalue analysis and the Routh–Hurwitz criterion, and a secondary loss of stability via a Hopf-type mechanism is identified. The case of nonzero input voltages with zero load torque is also discussed. Numerical simulations confirm the analytical results and highlight the parameter regions that admit stable operation. Bifurcation diagrams show the different PMSM behaviors as the parameter $\gamma$ varies. For a certain interval of $\gamma$, the PMSM speed undergoes chaotic oscillations. The SCT is introduced to control the chaos. Macro variables are chosen to design the SCT. The derived SCT is implemented to eliminate the chaotic speed. The controller provides good performance in suppressing the chaos. The controller is tested under sudden reference speed change where the controller gets the new reference speed accurately. It is also evaluated under sudden and sinusoidal load torque variations. Full article

An integrated nonlinear dynamic model was developed to investigate resonance in a four-cylinder engine mounted on a viscoelastic foundation. A coupled lumped-parameter formulation captures vertical and torsional responses under unbalanced inertial forces, combustion torque, and stochastic base excitation. Time-domain simulations show that at low rotational speeds the vertical displacement reaches transient amplitudes before converging to periodic oscillations, whereas higher excitation speeds reduce steady-state amplitudes. Torsional motion exhibits initial angles near 0.05 rad that decay below 0.01 rad in steady state, with further reduction at higher speeds. Frequency-domain analysis indicates that vibration energy is concentrated in engine-order harmonics between approximately 8 and 50 Hz, while components above 60 Hz are strongly attenuated, yielding a dynamic range exceeding 50 dB. Finite element modal analysis identifies the first four structural modes between 18 Hz and 666 Hz, revealing an increasingly dominant overall translational mode and a localized directional behavior at higher frequencies. A high-dimensional kernel density spectrogram integrates modal and spectral features to map resonance regions. Results indicate that increasing rotational excitation enhances inertial stiffening, systematically reduces displacement amplitudes, and preserves bounded periodic dynamics without instability. Full article

As robotic manipulators evolve toward lightweight and long-link structures, flexibility increasingly affects dynamic response and trajectory tracking accuracy. However, existing studies often lack a consistent coupling mechanism between finite element structural models and control models, and flexible effects are typically treated as disturbances, limiting the direct use of structural parameters for control prediction and optimization. This paper proposes a structure–control collaborative co-simulation framework for a six-degree-of-freedom (6-DOF) flexible-joint manipulator. ANSYS-based finite element analysis (FEA) is integrated with the MATLAB/Simulink control environment to extract joint-level equivalent stiffness, inertia, modal frequencies, and damping parameters, which are embedded into a rigid–flexible coupled dynamic model. A regression-based representation is introduced to capture unmodeled flexible residual dynamics, and a regression-compensated adaptive PID torque controller with σ-modification and a dead-zone mechanism is developed to ensure bounded adaptation and closed-loop stability. Simulation results under no-load and payload conditions demonstrate improved oscillation suppression and tracking accuracy. By establishing a unified coupling mechanism from structural parameters to the control model, the proposed method achieves consistent co-modeling of the structural and control domains and provides an engineering-feasible co-simulation approach for dynamic prediction and control optimization of multi-DOF flexible manipulators under varying operating conditions. Full article

The aerodynamic behavior of small-scale UAV propellers operating under non-axial inflow conditions poses a significant prediction challenge due to the presence of strong azimuthal asymmetries, inherently unsteady flow phenomena, and Reynolds number effects that dominate forward flight conditions. Although numerical models based on the Moving Reference Frame (MRF) formulation combined with steady RANS solvers are widely used in engineering practice because of their low computational cost, the precise limits of their applicability in crossflow configurations remain poorly defined. This work conducts a comprehensive numerical investigation that systematically compares steady RANS–MRF predictions against time-accurate URANS simulations across a wide range of advanced ratios and rotor tilt angles. Rigorous validation of the computational framework against experimental data in axial and near-axial regimes demonstrates excellent agreement, with deviations below 5% in propulsive efficiency. The results clearly identify the operational envelope within which MRF-based steady models remain valid under non-axial inflow. In particular, the steady approach exhibits robust performance for low-to-moderate advance ratios, where global errors in thrust and power remain below 10% for $\mu =0.40$. However, the fidelity of the method deteriorates sharply under extreme edgewise-flight conditions ($\mu =0.70)$, in which the crossflow component dominates the aerodynamic field, the “frozen-rotor” assumption progressively loses mathematical consistency, and the solver may converge toward steady solutions that no longer represent a physically meaningful flow state. The URANS analysis further reveals two critical phenomena that cannot be captured by steady-state models. First, at high advance ratios, the retreating blade encounters an extensive region of reverse flow, which induces negative sectional thrust and strongly anharmonic load waveforms. This behavior has direct implications for structural design: the peak-to-peak amplitude of thrust oscillation in edgewise flight can exceed the mean thrust level, implying extreme cyclic loading and a high risk of high-cycle fatigue. Second, the simulations quantify the emergence of off-axis parasitic moments (pitching and rolling), which are negligible in vertical flight but reach magnitudes comparable to the total aerodynamic torque in forward-flight conditions. Taken together, these findings highlight the need for a hybrid-fidelity strategy in UAV propulsion analysis: employing steady RANS–MRF within the validated domain for energetic assessments, while relying on time-accurate URANS for mandatory evaluation of structural loading, vibration, and control logic in critical high-speed regimes. Full article

We show that the Zitterbewegung of the electron arises as a real internal motion when spin is treated as a classical bivector rather than as a point fermion of the Dirac equation. In the Bivector Standard Model, physically meaningful dynamics reside in the body-fixed frame where two orthogonal internal angular momentum vectors counter-precess about a torque axis. Their rigid rotation generates a time-dependent chord whose magnitude oscillates at twice the Compton frequency, $2{\omega }_C$, and whose orientation precesses at ${\omega }_C$. When projected into a laboratory-fixed frame, this internal rotor produces the characteristic trembling motion of the Zitterbewegung and traces a horn torus envelope without additional assumptions. The internal clock defined by this cyclic bivector motion unifies the origin of spin properties and the de Broglie modulation. It distinguishes complementary parity domains that cannot be related by Lorentz transformations. The Zitterbewegung is therefore not an interference between positive- and negative-energy spinors, but rather the visible shadow of a real, energy-conserving internal rotation inherent to the bivector structure. Full article

This paper presents a torque oscillation attenuation method for permanent magnet synchronous motors (PMSMs) based on the combination of sliding-mode control (SMC) and the equivalent input disturbance (EID) approach. To deal with the changes in PMSM parameters, we explored a continuous-domain ant colony optimization (CDACO) method to design a control system for such a plant. This is the first application of SMC-EID to uncertain PMSM plants, with CDACO enabling robust parameter tuning in continuous spaces. First, we designed an EID estimator to estimate the disturbance caused by torque oscillation. Next, we added the estimated disturbance to the sliding-mode controller to improve disturbance attenuation performance. Then, we extended an ant colony optimization (ACO) algorithm to the continuous domain to optimize controller parameters for an uncertain plant. Finally, a speed control experiment was carried out on a two-mass experimental system for PMSMs to demonstrate the validity of the method. The experimental results show that our method yields better control performance than the SMC. Full article

Kaolin is an abundant, low-cost filler for elastomeric compounds. The kaolin used here is primarily kaolinite, chemically clean, and contains a fine particle population. Although agglomeration is evident, it can be mitigated by appropriate physical processing and, when desired, by chemical coupling. This study evaluates kaolin in natural rubber (NR) and examines how adding bis(triethoxysilylpropyl) tetrasulfide (TESPT) during mixing affects filler–matrix compatibility, viscoelastic response, cure stability, and mechanical performance. Kaolin was structurally and morphologically characterized, and the compounds were prepared in a closed mixer coupled to a torque rheometer under controlled dispersion conditions. Part 1 assessed NR with kaolin without a coupling agent, and Part 2 assessed the NR–kaolin with TESPT added during mixing (0.5 and 5 phr). Small-amplitude oscillatory shear (SAOS) was used to probe viscoelastic behavior, while oscillating disk rheometry (ODR) and tensile tests quantified cure and mechanical properties. In Part 1, kaolin increased NR stiffness in SAOS and raised the 100% and 300% moduli by about 40% and 50%, respectively, relative to the unfilled NR compound, while reducing cure reversion from 30% to 10% at 150 °C. In Part 2, TESPT produced a threshold-like response: 0.5 phr caused only minor changes, whereas 5 phr led to pronounced stiffening and cure stabilization. At 5 phr, a low-frequency plateau in G′ below 0.1 Hz with no G′–G″ crossover was observed, accompanied by higher M_H and ΔM in ODR and reversion suppressed to 1% after 30 min. These trends indicate the formation of a more connected filler-rubber network, promoted by TESPT-assisted interfacial coupling/adhesion, while also reflecting the ability of TESPT (tetrasulfide) to contribute sulfur and modify the curing chemistry. Mechanically, kaolin produced marked stiffness increases, with the 100% and 300% moduli increasing by an additional 9% and 36%, respectively, at 5 phr TESPT. At the same time, ultimate tensile strength remained lower than that of neat NR, and elongation at break decreased slightly. Overall, adding TESPT during mixing enhances interfacial coupling and network connectivity and, at higher loading, also influences cure chemistry, yielding higher modulus and strongly improved reversion resistance without increasing ultimate tensile strength relative to neat NR. Full article

Insects achieve millisecond sensor–motor loops with tiny sensors, compact neural circuits, and powerful actuators, embodying the principles of Edge AI. We present a comprehensive architectural blueprint translating insect neurobiology into a hardware–software stack: a latency-first control hierarchy that partitions tasks between a fast, dedicated Reflex Tier and a slower, robust Policy Tier, with explicit WCET envelopes and freedom-from-interference boundaries. This architecture is realized through a neuromorphic Reflex Island utilizing spintronic primitives, specifically MRAM synapses (for non-volatile, innate memory) and spin-torque nano-oscillator (STNO) reservoirs (for temporal processing), to enable instant-on, memory-centric reflexes. Furthermore, we formalize the biological governance mechanisms, demonstrating that, unlike conventional ICEs and miniturbines that exhibit narrow best-efficiency islands, insects utilize active thermoregulation and DGC (Discontinuous Gas Exchange) to maintain nearly constant energy efficiency across a broad operational load by actively managing their thermal set-point, which we map into thermal-debt and burst-budget controllers. We instantiate this integrated bio-inspired model in an insect-like IFEVS thruster, a solar cargo e-bike with a neuromorphic safety shell, and other safety-critical edge systems, providing concrete efficiency comparisons, latency, energy budgets, and safety-case hooks that support certification and adoption across autonomous domains. Full article

With the rapid development of mobile robotics, wheeled bipedal robots, which combine the terrain adaptability of legged robots with the high mobility of wheeled systems, have attracted increasing research attention. To address the balance control problem during both standing and locomotion while reducing the influence of noise on control performance, this paper proposes a balance control framework based on a Linear Quadratic Regulator integrated with an Extended Kalman Filter (KLQR). Specifically, a baseline LQR controller is designed using the robot’s dynamic model, where the control input is generated in the form of wheel-hub motor torques. To mitigate measurement noise and suppress oscillatory behavior, an Extended Kalman Filter is applied to smooth the LQR torque output, which is then used as the final control command. Filtering experiments demonstrate that, compared with median filtering and other baseline methods, the proposed EKF-based approach significantly reduces high-frequency torque fluctuations. In particular, the peak-to-peak torque variation is reduced by more than 60%, and large-amplitude torque spikes observed in the baseline LQR controller are effectively eliminated, resulting in continuous and smooth torque output. Static balance experiments show that the proposed KLQR algorithm reduces the pitch-angle oscillation amplitude from approximately ±0.03 rad to ±0.01 rad, corresponding to an oscillation reduction of about threefold. The estimated RMS value of the pitch angle is reduced from approximately 0.010 rad to 0.003 rad, indicating improved convergence and steady-state stability. Furthermore, experiments involving constant-speed straight-line locomotion and turning indicate that the KLQR algorithm maintains stable motion with velocity fluctuations limited to within ±0.05 m/s. The lateral displacement deviation during locomotion remains below 0.02 m, and no abrupt acceleration or deceleration is observed throughout the experiments. Overall, the results demonstrate that applying Extended Kalman filtering to smooth the control torque effectively improves the smoothness and stability of LQR-based balance control for wheeled bipedal robots. Full article