Search Results (29)

To address the robustness limitations of three-vector model predictive current control (TV-MPCC) in permanent magnet synchronous motor (PMSM) drives under parameter variations and external disturbances, this paper proposes an improved sliding mode observer (SMO) based on a novel dual power-rate reaching law combined with a hyperbolic tangent function (PTHSMO) for back-EMF estimation and feedforward compensation. The proposed reaching law integrates a terminal attractor term and a nonlinear power-rate term to achieve fast convergence, while the tanh-based switching term continuously approximates the sign function to suppress chattering without requiring a downstream low-pass filter. The estimated back-EMF, which encapsulates the combined effect of parameter mismatch and actual back-EMF, is fed forward into the TV-MPCC prediction model to actively compensate for residual disturbances (denoted PTHESMO). The stability of the observer is verified via the Lyapunov method. Compared with the traditional SMO-based TV-MPCC, the proposed method reduces startup overshoot by approximately 46%, decreases speed recovery time under a 0.3 Nm load disturbance from 46.2 ms to 24.5 ms, and reduces rotor position error from 0.1358 rad to 0.1266 rad, providing an effective solution for high-performance sensorless PMSM drive control. Full article

Endoplasmic reticulum (ER) stress is a common state of cellular adversity experienced by tumor cells under unfavorable conditions such as hypoxia, nutrient deprivation, and oncogene activation. As the most conserved signaling branch of the unfolded protein response (UPR), the inositol-requiring enzyme 1α (IRE1α)- X-box-binding protein 1 (XBP1) pathway plays a central role in sustaining tumor cell survival, driving malignant progression, and remodeling the tumor microenvironment (TME). XBP1, the terminal transcription factor of this pathway, finely orchestrates tumor cell fate through both its canonical and non-canonical functions. This review systematically summarizes the dual mechanisms of XBP1 in cancer: within cancer cells, XBP1 promotes proliferation, metastasis, and chemoresistance via metabolic reprogramming, anti-apoptotic proteins, and DNA repair; within immune cells (macrophages, dendritic cells, T cells), XBP1 fosters an immunosuppressive microenvironment, while also modulating cancer-associated fibroblasts, endothelial cells, and osteoclasts. Despite its therapeutic promise, several major unresolved questions remain, including the precise molecular switch governing XBP1’s pro-tumorigenic versus anti-tumorigenic functions, the functional divergence between XBP1u and XBP1s isoforms in different cellular contexts, and the lack of reliable predictive biomarkers for patient stratification. Key translational challenges involve the on-target toxicity of systemic XBP1/IRE1α inhibition due to its essential roles in normal tissues, the cell-type-specific and context-dependent effects that complicate therapeutic outcomes, and the limited selectivity and off-target effects of current inhibitors, as well as compensatory activation of other UPR branches that may drive adaptive resistance. Finally, this review discusses XBP1-targeted therapeutic strategies, including small-molecule inhibitors, nucleic acid-based drugs, immunotherapeutic combination approaches, and XBP1-based tumor vaccines, and provides perspectives on future research directions, aiming to establish a theoretical foundation for the development of more effective and precise XBP1-targeted therapies for tumorigenesis and cancer progression. Full article

Multi-terminal voltage-source-converter-based HVDC (VSC-MTDC) systems are increasingly used to integrate renewable energy and interconnect asynchronous AC grids, but conventional fixed-coefficient droop control cannot simultaneously limit DC-voltage deviations, reduce operating losses, and preserve converter power margins during operating-point switching. This paper hypothesizes that a rule-based fuzzy adjustment of the droop slope can provide smooth multi-objective coordination without inter-station communication. A dual Mamdani fuzzy controller is developed: one controller adjusts the weighting between loss-oriented and power-margin-oriented droop coefficients according to converter power margin, while the other introduces a voltage-deviation correction according to DC-bus voltage. The controller is implemented and verified in a five-terminal MMC-based VSC-MTDC model built in PSCAD/EMTDC, where simulation data are generated under heavy-load, light-load, and power-reference switching scenarios using specified line and converter parameters. Compared with conventional droop control, the proposed strategy improves power-margin utilization, reduces operating-point discontinuities, and raises the minimum DC voltage from 370.2 kV to 381.4 kV in the severe switching case. The results confirm that fuzzy-slope droop control can achieve smoother operating-point switching and better coordinated optimization among voltage stability, operating loss, and converter reserve margin. Full article

Executing multi-UAV cooperative pursuit in complex public domains requires balancing interception efficiency with flight safety under strict micro-platform constraints. Existing planners often struggle with high computational overhead or lack kinodynamic adaptability in heterogeneous environments. To address this, we propose AC2F, a lightweight Adaptive Coarse-to-Fine hybrid framework featuring a bidirectional state-switching mechanism. The framework utilizes the Apollonius circle for efficient global guidance during the coarse phase, dynamically transitioning to a Dynamic Window Approach (DWA) upon detecting path oscillations or entering terminal capture zones. To ensure robustness, a dual-layer parameter paradigm integrates offline Bayesian optimization for globally optimal baselines with online real-time weight adaptation based on target distance. Extensive simulations show that AC2F effectively escapes local minima, such as urban-style U-shaped traps. Real-world suburban validation confirms an 86% capture rate with minimal computational overhead, demonstrating AC2F’s suitability for public domain protection and civil security. Full article

Decoupled maximum power point tracking control and output voltage control can be accomplished simultaneously using dual-duty cycle control. However, developed triple switch triple mode (TSTM) exhibits absence of the common ground between the solar panel and output load therefore causing the leakage current to flow which creates safety concern especially for household electrification. In addition to having a negative effect on the solar panel, leakage current increases power losses. Thus, this work proposes a unique TSTM dc-dc converter. The suggested converter has the following advantages: (1) The presence of a common ground between the output load and the solar panel eliminates the leakage current. (2) Reduced electromagnetic interference issues present due to leakage current. (3) Enhanced voltage gain over wider duty cycle. (4) Enables simultaneous decoupled control of MPPT and output voltage. (5) Absence of voltage oscillation across the switches. The proposed TSTM converter is an unique combination of switched inductor and switched capacitor. Both inductor and capacitors are connected in order to boost the level of voltage at the output terminal. The operating principle, design equations and device stress are analyzed in detail for the proposed TSTM. The comparison over existing converter in terms of voltage gain and switch stresses are highlighted in details. Lastly, a laboratory prototype (40/400 V) for 400 W is created and thoroughly tested in order to validate mathematical calculations. Full article

Deploying unmanned aerial vehicles (UAVs) cooperatively with legged robots for disaster response and inspection requires autonomous docking on miniature walking platforms. This study addresses the problem of landing a foldable quadrotor onto the back of a trotting wheel-legged robot ($300\times 180$ mm) and subsequently taking off while carrying it as a payload. Four tightly coupled challenges distinguish this task from conventional mobile-platform landing: (i) an extremely small landing surface, (ii) gait-induced periodic vibrations at $2.5$ Hz, (iii) continuous platform translation at $0.3$–$0.8$ m/s, and (iv) surface docking that requires simultaneous position and attitude matching rather than mere point tracking. The proposed framework comprises four components: (1) a novel single-servo crank-rocker folding mechanism that reduces the folded body footprint by 48.5% and the maximum linear dimension from 590 mm to 309 mm (↓47.6%) compared with the prior dual-servo design; (2) a staged Continuous Fast Nonsingular Terminal Sliding Mode (CFNTSM) controller combined with a Gait-Frequency-Aware Finite-time Extended Observer (GFA-FEO); (3) a Feature-wise Linear Modulation Soft Actor-Critic (FiLM-SAC) residual reinforcement-learning policy conditioned on physical states and mission phase, with an adaptive trust weight $\lambda \left(t\right)$; and (4) a payload-adaptive takeoff strategy with parameter hot-switching to handle the twofold mass increase. Extensive Monte Carlo simulations and ablation studies across three experiment groups demonstrate that the proposed hierarchical framework achieves sub-centimetre (<10 mm) position accuracy and <3° attitude matching on a walking platform. Quantitatively, the full method reduces docking RMSE by 42% relative to the model-based CFNTSM + GFA-FEO controller without residual RL (4.2 vs. 7.2 mm) and reduces post-lock takeoff RMSE by 63% through FEO hot-switching (16.2 vs. 44.2 mm). Full article

Binary cell fate decisions in the Drosophila retina generate R8 photoreceptor subtypes that express either blue-sensitive Rh5 or green-sensitive Rh6 opsins. These choices are governed by a Hippo pathway–dependent bistable switch, yet the mechanisms that couple pathway output to terminal opsin expression remain unclear. Here, we identify miR-927 as a regulator that biases R8 subtype fate. Loss of miR-927 increases Rh5-positive pR8 cells, whereas its overexpression promotes Rh6-positive yR8 identity. Mechanistically, miR-927 directly represses the terminal differentiation gene Rh5 and is capable of repressing the Hippo pathway effector yki through its 3′UTR. This dual targeting couples pathway output to terminal gene expression, providing a mechanism to bias and stabilize subtype identity. More broadly, our findings illustrate how microRNAs can be integrated into bistable signaling networks to modulate binary cell fate decisions. Full article

To address the deteriorated control performance of permanent magnet synchronous motor (PMSM) drive systems for new energy vehicles (NEVs) under complex conditions caused by multi-source disturbances (internal parameter perturbations and external load mutations), this paper proposes an improved terminal integral sliding mode control (ITISMC-ADERL) strategy integrating a piecewise adaptive terminal integral sliding mode surface and an ADERL. The proposed sliding mode surface adopts interval-adaptive switching between high- and low-order power terms, completely eliminating singularity and integral saturation defects of traditional terminal sliding mode control while ensuring fast convergence, and achieving an optimal structural balance between convergence speed and chattering suppression. The state-dependent ADERL leverages the synergy of error-sliding variable coupled dynamic gain adjustment and variable exponential power compensation, realizing dual-mode adaptive switching of “strong driving for fast approaching far from the sliding surface, weak gain for smooth regulation near the sliding surface”, which significantly improves control accuracy and anti-disturbance robustness. The finite-time convergence of the closed-loop system is rigorously proved via Lyapunov stability theory. Full-operating-condition comparative tests on a TMS320F28379D DSP platform show that the proposed strategy outperforms SMC-ERL, ISMC-ERL and ITISMC-ERL in all test scenarios (no-load startup, acceleration/deceleration, sudden load changes, flux linkage perturbation), meeting the requirements of high-performance NEV drive systems and possessing important engineering application potential. Full article

Conventional multispectral photodetectors typically rely on multiple electrical terminals to discriminate different wavelengths, which inevitably increases structural complexity. Here, we break this paradigm by demonstrating a dual-color visible–infrared photodetector based on a simple two-terminal Au/MoS₂/Te heterostructure. The device operates through a bias-switching mechanism: reversing the voltage polarity selectively activates either the MoS₂/Au Schottky junction for visible-light detection (520 nm) or the Te/MoS₂ heterojunction for infrared detection (1550 nm). This bias-controlled wavelength selectivity is unambiguously verified by scanning photocurrent mapping. Beyond dual-color discrimination, an adaptive convolutional neural network is employed to decode the nonlinear current–voltage characteristics and enable precise spectral identification, achieving a reconstruction error of approximately 4.5%. Furthermore, high-fidelity dual-color imaging is demonstrated at room temperature. These results establish a hardware–algorithm co-design strategy based on a minimalist two-terminal architecture, providing a viable route toward compact and intelligent spectral-sensing systems. Full article

State-of-charge (SOC) estimation for lithium-ion batteries in smartphones is complicated by nonlinear load variation, electro-thermal coupling, aging effects, and heterogeneous user behaviors. This study proposes a multi-physics coupled SOC estimation framework, termed the Multi-Physics Thermo-Electrochemical Coupled SOC Model (MTEC-SOC), to characterize battery behavior under representative user-load conditions within controlled ambient thermal boundaries. The model combines system-level power profiling, thermal evolution, voltage dynamics, and aging-related capacity correction within a unified framework. To support model development and validation, a dual-source dataset is established using laboratory battery characterization data and real-world smartphone behavioral data, from which users are classified into light, heavy, and mixed usage patterns. Comparative results against four benchmark models (M1–M4) show that MTEC-SOC achieves the highest overall accuracy, with average MAE, RMSE, and TTE error values of 0.0091, 0.0118, and 0.08 h, respectively. The results suggest distinct degradation tendencies across user types: calendar aging dominates under prolonged high-voltage dwell in light-use scenarios, whereas, within the tested thermal range, heavy-use scenarios exhibit stronger voltage sag, relative temperature rise, and polarization-related stress; mixed-use scenarios are characterized by transient responses induced by abrupt load switching. Sensitivity analysis further indicates that the predictive behavior of the model is strongly scenario-dependent, with higher-load operation within the calibrated range amplifying parameter perturbations. Overall, the proposed MTEC-SOC framework provides accurate SOC estimation and physically interpretable insight within the evaluated dataset and operating conditions, offering potential guidance for battery management and energy optimization in intelligent mobile terminals. Full article

Mitogen-activated protein kinase kinase kinase 1 (MAP3K1) possesses dual enzymatic functions, i.e., kinase and E3 ubiquitin ligase activities, orchestrating proliferation, survival, apoptosis, DNA damage response, and immune modulation. Recent genomic and mechanistic studies have revealed MAP3K1’s paradoxical, context-dependent roles as both an oncogene and a tumor suppressor. We discuss MAP3K1’s multidomain architecture, featuring an N-terminal RING and PHD domain (E3 ligase activity), a TOG domain (microtubule dynamics), and a C-terminal kinase domain, enabling the integration of c-jun N-terminal kinase (JNK), p38 mitogen-activated protein kinase (p38 MAPK), extracellular signal-regulated kinase (ERK), and nuclear factor kappa B (NF-κB) signaling pathways. MAP3K1 functions as a molecular switch balancing survival and apoptosis, with caspase-3 cleavage at Asp878 activating pro-apoptotic JNK/p38 signaling. Genomic analyses across >35 cancer types reveal MAP3K1 alterations at frequencies of <1–14%, highest in breast and endometrial cancers. These alterations show tissue specificity: loss-of-function mutations predominate in hormone receptor-positive breast cancer with a favorable prognosis, whereas gain-of-function mutations in melanoma activate oncogenic ERK signaling. MAP3K1 mutations predict response to mitogen-activated protein kinase kinase (MEK) and phosphoinositide 3-kinase (PI3K) inhibitors, with mutant cancers showing higher MEK inhibitor response than wild-type tumors. Despite substantial progress, critical gaps remain regarding MAP3K1’s E3 ligase substrates, context-dependent activity determinants, and therapeutic strategies. Addressing these through inhibitor development, biomarker validation, and mechanistic studies will accelerate potential clinical translation of MAP3K1 biology. Full article

Reliable state-of-charge (SoC) estimation is crucial for safe and efficient battery management. However, it is challenging in practice. Terminal-voltage sensitivity becomes weak in open-circuit-voltage (OCV) plateau regions. Model uncertainty also persists at practical sampling periods. To tackle this issue, this paper proposes a discrete-time, model-based SoC estimation framework. This framework combines a dual-polarization equivalent-circuit model with a tuning-light sliding-mode observer. It is specifically designed for digitally sampled battery management systems. The modeling stage includes: (i) a discrete-time DP representation suitable for embedded use, (ii) a shape-preserving PCHIP reconstruction of the OCV–SoC curve and its derivative, and (iii) an effective-slope regularization mechanism that maintains non-vanishing output sensitivity even in flat OCV regions. On top of this structure, a boundary-layer SMO is developed with output-error shaping, model-driven gain scaling, and simple bias-compensation terms based on integral correction and leaky Coulomb counting. A discrete-time Lyapunov analysis is conducted directly on the surface dynamics. This analysis shows finite-time reaching to the boundary layer and a practical limit on the steady-state error that depends on the sampling period, disturbance level, and boundary-layer width. Numerical tests on a DP model identified from experimental data indicate that the proposed method achieves SoC accuracy similar to a switching-gain adaptive SMO. The results confirm the benefits of a model-centric design. The discrete-time formulation and convergence proof, which do not depend on high sampling rates, provide robustness advantages over traditional sliding-mode methods. The proposed method also performs better than a tuned EKF in plateau regions, requiring much less tuning effort. Full article

Most electric vehicles use 400 V batteries, while some companies are moving to 800 V to reduce current in electric drives. More cars are expected to adopt 800 V at the DC terminals of the batteries, but 400 V will remain common for the duration of this transition, so future off-board chargers must support a wide voltage output range. Silicon carbide switches are used to keep the power–electronics interface compact and scalable. The AC/DC stage of a modular silicon carbide-based interface is designed using a T-type active front end and a dual active bridge. The T-type front end is optimized with a genetic algorithm. The resulting model is used to tune the inner current and outer voltage controllers. Bode analysis shows an inner current loop bandwidth of 4.25 kHz with a phase margin of ${53}^{°}$ and a gain margin of 30 dB. The outer voltage loop reaches 50 Hz with a phase margin of ${108}^{°}$ and a gain margin of 33 dB. The controller is implemented on a dSPACE MicroLabBox. Tests show peak efficiency of 98.5% in G2V mode and 98.3% V2G mode. THD stays under 5% above 4 kW and reaches 3% at peak power. Full article

Aiming at the problem of model parameter perturbation in vehicle trajectory tracking control, an improved robust model predictive control (RMPC) method is proposed. Based on the two-degree-of-freedom vehicle model and Serret Frenet error model, a multi-cell hypercube vertex modeling is adopted to map the disturbance range of parameters such as vehicle speed and lateral stiffness to a set of vertices, and dynamic linear combination is achieved through normalized weights. The algorithm design mainly focuses on the dual-layer optimization of the switching mechanism, decomposing the infinite time domain problem into finite time domain optimization and terminal constraints. At the same time, it dynamically updates the vertex parameters to match time-varying uncertainties and then combines Lyapunov theory to design a control invariant set. The results show that in complex road conditions and vehicle state transitions, RMPC can reduce the peak lateral deviation from 1.0 m to 0.2 m, converge the heading deviation to within 2 deg, and significantly reduce the mean and root mean square values of control errors compared to traditional MPC, under the influence of vehicle model parameter perturbations. RMPC has good robustness and real-time performance. Full article

Magnetically levitated artificial hearts impose stringent requirements on the blood-pump motor: zero friction, minimal heat generation and full biocompatibility. Traditional mechanical-bearing motors and permanent-magnet bearingless motors fail to satisfy all of these demands simultaneously. A bearingless switched reluctance motor (BSRM), whose rotor contains no permanent magnets, offers a simple structure, high thermal tolerance, and inherent fault-tolerance, making it an ideal drive for implantable circulatory support. This paper proposes an 18/15/6-pole dual-stator BSRM (DSBSRM) that spatially separates the torque and levitation flux paths, enabling independent, high-precision control of both functions. To suppress torque ripple induced by pulsatile blood flow, a variable-overlap TSF-PWM-DITC strategy is developed that optimizes commutation angles online. In addition, a grey-wolf-optimized fast non-singular terminal sliding-mode controller (NRLTSMC) is introduced to shorten rotor displacement–error convergence time and to enhance suspension robustness against hydraulic disturbances. Co-simulation results under typical artificial heart operating conditions show noticeable reductions in torque ripple and speed fluctuation, as well as smaller rotor radial positioning error, validating the proposed motor and control scheme as a high-performance, biocompatible, and reliable drive solution for next-generation magnetically levitated artificial hearts. Full article