Fault evolution law and diagnosis method of chassis hydraulic steering system based on AMESim simulation

Driving torque for a steer-by-wire system hand wheel actuator based on the reference driving torque from an electric power steering system

Inspired by the exceptional control over molecular motion in biological machinery, artificial molecular motors capable of unidirectional rotation have been developed. However, achieving two actively powered rotations at different frequencies within a single molecule has remained elusive. Here molecular motors are presented incorporating two structurally distinct rotors, each operating at a unique rotational frequency-resembling a molecular steering system. The rotor activation preference arises from differences in photochemical, rather than thermal, behaviour and can be tuned by the rotor structure, solvent and light source. This discovery of controlling mixed rotor systems could, in principle, be applied to other rotors, combinations thereof and even to other classes of molecular motors, and thus could serve as a blueprint for the construction of future advanced synthetic molecular machines.

User-friendly robust control for driver-automation shared steering system based on driver group characteristics

Head-mounted displays (HMDs) based on the well-established rectilinear sampling method are subject to the inherent trade-off between wide field of view (FOV) and high spatial resolution. This challenge limits their broader application due to constraints in manufacturing high-resolution displays and the substantial data bandwidth required for rendering, storage, and transmission. Foveated display technology alleviates this issue by allocating resources differently between the region of interest and the peripheral region. However, most existing solutions rely on dynamic dual-resolution schemes that are costly and complex, requiring multiple displays or optical paths, two-dimensional steering mechanisms, and eye-tracking systems. We propose and demonstrate a perception-driven approach to the design of a three-element freeform eyepiece featuring spatially varying optical power. The novel eyepiece enables the creation of a statically foveated optical see-through HMD, yielding a display of an 80° diagonal FOV and a peak resolution density of 60 pixels per degree with a 4 K display panel. The system offers high perceived resolution across the FOV with imperceptible or minimal degradation and resolution discontinuity with eye movements. Our approach eliminates the need for eye tracking, scanning mechanisms, or multiple displays, significantly reducing hardware complexity. Compared to the rectilinear sampling scheme offering the same peak resolution density and FOV, our system reduces pixel usage by more than 35% or equivalently 4.4 million fewer pixels.

Tilt-to-length (TTL) coupling is a critical noise source in high-precision interferometric measurements, particularly in systems involving angular actuation and beam steering. This paper proposes a nonlinear cyclic modulation method to identify lateral misalignment and suppress the associated TTL coupling. By applying controlled sinusoidal angular excitation and evaluating the complex modulus ratio between the optical path difference (OPD) and the beam angle at the modulation frequency, the TTL noise induced by the point-ahead angle mechanism (PAAM) is separated and quantified in the frequency domain. Experimental results demonstrate that lateral offset correction reduces TTL noise by 94%, corresponding to a suppression factor of 15.5 and enabling pointing control better than 21 µm/rad. Meanwhile, the parasitic displacement noise of the PAAM is reduced from 10 pm/Hz1/2 to below 4 pm/Hz1/2. These results validate the effectiveness of the proposed modulation-based identification framework and demonstrate its applicability to precision interferometric systems.

Synergistic hydro-thermal performance enhancement of micro pin-fin heat sinks via improved pitch angle, perforations, and flow steering mechanisms

A sliding mode active disturbance rejection tracking control scheme based on the Smith predictive control structure is proposed for the front steering wheel of tractors, aiming to address the challenges of time delay and unknown disturbances in the angle tracking process. In the control system design, the effects of time delay and disturbances on the angle tracking performance are thoroughly considered, based on the established steering system model. A time delay processing structure is designed based on the Smith predictive control principle, and linear extended state observer is designed to realize synchronous estimation for the un-delayed angle output and the controller output. A simple Sliding Mode Controller (SMC) is introduced to replace the linear feedback controller in active disturbance rejection control (ADRC) to improve the accuracy and disturbance rejection performance. Simulation charts and performance evaluating indexes show that the proposed control method has obvious advantages in tracking accuracy, robustness and disturbance rejection in comparison with other methods. The angle tracking error is no more than 0.055rad even under the interference of white noise signal. The proposed method effectively mitigates the impact of time delay and disturbance, it can significantly enhance the dynamic response performance of the steering system.

A feasibility study on a machine-learning-based quality assurance tool for spot-scanning proton therapy using delivery log files and treatment plans\u2606

Mobile Edge Computing (MEC) has become increasingly critical for latency-sensitive applications, including Augmented/Extended Reality (AR/XR), Cloud Gaming, Real-Time Video Analytics, and Interactive Enterprise Services. Existing edge steering mechanisms remain largely reactive by relying on static policies, nearest-edge selection, or compute-only information that usually fail under user mobility, fluctuating radio conditions, dynamic user-plane paths, and edge resource contention rather than being more proactive. This paper presents SCONE-AEGIS framework that extends the Standard Communication with Network Elements (SCONE) paradigm beyond throughput advisories to support joint network-compute steering of MEC applications. SCONE-AEGIS introduces an Edge Steering Advice (ESA) that communicates recommendations that can be consumed by the applications, which have been derived from a combination of RAN, UPF, and MEC telemetry. The framework is a combination of a two-stage AI/ML engine, the first being a Spatio-Temporal Graph Predictor that is uncertaintyaware and models the evolving relationships among radio access network nodes, user-plane functions, edge sites, and mobile users, and the second stage is a Safe Contextual Bandit Steering Policy (SCBSP) that selects execution sites subject to SLA constraints, migration hysteresis, and prediction confidence. The proposed framework provides a standards-compatible, privacypreserving path for exposing joint network-compute intelligence to applications without breaking transport encryption.

The synchronous belt is a key transmission component in automotive steering gears, and its dynamic characteristics significantly impact the NVH (Noise, Vibration, and Harshness) performance of the steering system. To investigate the vibration characteristics of the synchronous belt under pre-tension, this study takes the steering gear synchronous belt as the research object. A three-dimensional finite element model of the synchronous belt-pulley system, considering its layered structure, is established. Pre-tension is applied using the displacement loading method, and prestressed modal simulation analysis is conducted. The results show that the system’s low-order modes are primarily characterized by overall vertical bending and torsion, while medium- and high-order modes exhibit combined mode shapes and localized vibration features. When the pre-tension displacement increases from 2 mm to 4 mm, the first-order natural frequency rises from 340.69 Hz to 464.88 Hz, but the impact on the mode shape morphology of the synchronous belt is minimal. The relative error between the simulation and experimental results for the first six natural frequencies is less than 1 %, verifying the accuracy of the established model.

With the rapid advancement of vehicle intelligence and electrification, the Active Front Steering (AFS) system has emerged as a pivotal technology for enhancing vehicle handling stability and safety. However, the performance of Sliding Mode Control (SMC), which is widely applied in AFS, is heavily contingent upon controller parameters. Conventional manual tuning methods are empirical, laborious, and often fail to guarantee optimal robustness across diverse driving conditions. To address these limitations and bridge the gap between theoretical control design and engineering application, this study aims to develop a novel autonomous parameter tuning strategy for AFS systems. A co-design optimization framework is established by integrating a linear two-degree-of-freedom (2-DOF) vehicle dynamics model with an SMC controller. The Runge-Kutta Optimizer (RUN) is employed to precisely optimize the sliding surface and reaching law parameters by minimizing a stability-based objective function. The proposed strategy is validated through a MATLAB/Simulink and CarSim co-simulation platform under a double lane change scenario. Comparative results demonstrate that the proposed RUN-based approach significantly outperforms benchmark algorithms. Specifically, compared to Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO), the convergence speed is accelerated by 42.3% and 35.7%, while the solution accuracy is enhanced by 28.6% and 21.4%, respectively. These findings confirm that the proposed methodology substantially elevates the dynamic stability of the vehicle.

Against the backdrop of the rapid iteration of intelligent connected vehicles and autonomous driving technologies, Steer-by-Wire (SBW) has become the core technical direction for the upgrading of automotive steering systems. As a global leader in the electric power steering sector, as well as a pioneer and mass-production promoter of SBW technology, JTEKT has laid out a large number of core patents worldwide, forming significant technological barriers and intellectual property advantages. Based on global SBW patent data, this paper combs the technical architecture, analyzes the patent application trends, and dissects the competitive landscape of major applicants. It focuses on the patent application status, subdivided technical layout characteristics, and technological route evolution of JTEKT in the SBW field, summarizes its patent layout strategy and core technical advantages, and puts forward targeted suggestions for technological R&D and patent layout combined with the current situation of China's automotive industry, so as to provide a reference for domestic automakers and component enterprises to break through foreign technological blockades and achieve independent control of SBW technology.

Although extensive research has been conducted on peristaltic robots, early designs are often constrained by mechanical configurations and material constraints, which restrict kinematic capability, particularly steering control. In contrast, snails steer by modulating mucus secretion to redistribute ventral friction along the foot. Inspired by this strategy, we propose a friction-differential steering mechanism and develop a novel crawler that implements it. The crawler is integrated with a peristaltic robot, and three experiments are conducted to evaluate steering performance. We further establish a physical model of friction-differential steering, including cases identified from the experiments. The proposed model captures the experimentally observed trend that the steering response increases with the friction differential and provides a qualitative physical interpretation of the steering mechanism. Finally, the method is generalized by analyzing its limiting behavior, thereby clarifying the operating bounds of the proposed approach. This work provides a principled framework for steering control in peristaltic robots and offers a promising direction for improving their motion controllability.

This study investigates the dimensional synthesis and optimization of multi-link steering mechanisms—namely, the leading and mixed-leading double four-bar configurations—for front-wheel-drive vehicles. To overcome the accuracy limitations of conventional steering at large angles (up to 70°), a comparative metaheuristic approach is employed, utilizing two popular metaheuristic optimizations, Improved Particle Swarm Optimization (IPSO) and Differential Evolution with golden ratio (DE-gr), to optimize the geometric parameters of these complex eight-bar steering systems. Using a track-to-wheelbase ratio of 0.5, the optimization minimizes a mean-squared structural-error objective function integrated with Grashof mobility constraints. The optimized mechanisms are validated via ADAMS kinematic simulations and further analyzed in MATLAB R2021 regarding steering accuracy, transmission angles, and mechanical advantage. The results reveal a distinct performance trade-off: mixed-leading configurations achieve superior geometric precision and mass reduction due to shorter link lengths, with IPSO yielding the highest accuracy. Conversely, leading-type mechanisms provide a more linear and stable mechanical advantage, ensuring predictable force transmission. While DE-gr exhibits faster convergence across both variants, both algorithms effectively exploit the complex parameter space of multi-link systems. Ultimately, this metaheuristic optimization-based approach offers a superior and robust framework for the dimensional synthesis of high-performance multi-link steering mechanisms, surpassing the constraints of traditional gradient-based methods. Our findings recommend the mixed-leading configuration for precision-focused applications and the leading configuration for scenarios requiring consistent mechanical performance.

Navigating confined and complex environments, such as pipes, biological tissues, and collapsed debris, has remained a challenge for conventional robotic systems, which often struggle with maneuverability and adaptability. Soft toroidal robots offer a promising alternative, with a compact and lightweight toroidal shape that allows continuous movement without requiring bulky external equipment. However, the lack of a steering mechanism has limited their applicability in dynamic and complex terrains. To overcome this, we developed a steering mechanism that leverages the bistable characteristics inherent in the toroidal structure to enable curvature formation. By adjusting the position of the tail within the structure, the robot can change its direction of bending, enabling flexible and responsive steering. To achieve this bistable behavior, we utilized the orthotropic properties of ripstop nylon fabric, reducing the robot's bending stiffness and enhancing its steering capabilities. Through theoretical modeling and experimental validation, we identified key design parameters, such as optimal operating pressure and steering device length. The proposed soft toroidal robot, with a diameter of 70 mm and a total length of 400 mm, achieves 1-degree of freedom (DOF) steering by exploiting this bistable deformation. Our experiments demonstrated its ability to navigate a T-shaped pipe and climb vertically in confined spaces, achieving a maximum curvature of 13.4 m-1. These findings highlight the potential of soft toroidal robots for maneuvering through both confined and open environments with enhanced adaptability and efficiency.

Magnetic soft fiber robots have demonstrated significant potential in minimally invasive medicine due to their superior navigability in confined lumens. However, integrating functional end-effectors into these systems often leads to control coupling, where the actuation of distal modules inadvertently interferes with the robot's navigation posture. Herein, we propose a decoupled actuation strategy by integrating a photothermal MXene/reduced graphene oxide (RGO) gripper onto a magnetically steerable fiber robot. The distal gripper features a bilayer architecture, comprising a functional MXene@RGO/elastomer composite layer and a passive substrate layer. Leveraging the high photothermal conversion efficiency of MXene nanosheets, the gripper generates significant bending deformation driven by the thermal expansion mismatch under near-infrared (NIR) irradiation. This optical actuation mechanism is physically independent of the magnetic steering system, effectively eliminating signal crosstalk. We demonstrate that the fiber robot can perform precise magnetic navigation through complex tortuous paths and execute on-demand optical grasping of small objects without compromising its structural flexibility. This work presents a robust material interface-based solution for enabling multimodal control in soft robotics, expanding their capabilities for precise remote operations in restricted environments.

Wireless Capsule Endoscopy (WCE) is a minimally invasive technology for imaging the gastrointestinal (GI) tract, particularly the small intestine, where conventional endoscopy faces accessibility limitations. Traditional capsule endoscopes rely on passive motion driven by natural peristalsis, which limits controllability and may increase the risk of capsule retention. To address these challenges, this study presents the design and experimental validation of a compliant active capsule endoscope actuated by four Shape Memory Alloy (SMA) spring actuators. A key feature of the proposed system is a steering mechanism that reuses the same SMA actuators responsible for locomotion, enabling control of the camera orientation without increasing system complexity, size, or weight. The capsule architecture consists of rigid polylactic acid (PLA) links connected through thermoplastic polyurethane (TPU) flexure hinges, fabricated using dual-material 3D printing. Nonlinear finite element analysis (FEA) was employed to optimize the flexure hinge geometry for maximum displacement while maintaining safe stress levels. To validate the concept, a 3.5× scaled prototype was fabricated and integrated with SMA actuators and an Arduino-based control system. The experimental results demonstrate effective locomotion and steering capabilities, achieving a maximum stroke of approximately 5.4 mm and a steering angle of 24° for the 3.5× scaled prototype, corresponding to an estimated stroke of approximately 1.98 mm (Based on the FEA) at the intended clinical scale. Thermal characterization of the SMA actuators was also conducted to identify suitable operating current ranges for future biomedical deployment. The results demonstrate the feasibility of integrating locomotion and steering within a compact compliant capsule architecture, representing a step toward next-generation capsule endoscopy systems with improved navigation and diagnostic capability.

Despite significant advances in our understanding of human hearing and assistive hearing technologies, the benefits of hearing loss compensation continue to vary widely across individuals. A central challenge is the complexity and heterogeneity of hearing loss, whose perceptual consequences often extend far beyond reduced sensitivity. Conventional strategies rely on signal processing algorithms-such as spatial filtering, noise reduction, and dynamic range compression-to improve audibility and enhance target signals. These components are usually optimized in isolation, yet their combined effects may interfere with one another and therefore do not necessarily yield an overall benefit. More recently, machine learning techniques have been used to further improve the performance of individual components. To tailor compensation strategies to specific acoustic environments or listeners, various steering mechanisms have also been proposed, guided by acoustic cues, audiovisual input, or listener attention. While these approaches show promise, a consistent and objective computational target for optimization has yet to be established. As an alternative, auditory model-based strategies, increasingly combined with machine learning, have emerged. These approaches aim to minimize the discrepancy between simulated auditory representations of normal and impaired hearing, thereby providing a physiologically motivated optimization goal. Although both categories of strategies offer considerable potential, achieving effective compensation under real-time, real-world conditions remains a major challenge. This paper reviews opportunities and limitations of these approaches for individualized hearing aid compensation.

To address the inherent nonlinearity and time-varying dynamics of tractor steer-by-wire (SbW) hydraulic systems, as well as the inadequacies of empirical PID tuning in achieving rapid dynamic response and high tracking accuracy during headland maneuvers, continuous steering, and stochastic field operations, this study proposes an Improved Sparrow Search Algorithm (ISSA)-PID control strategy. Initially, an SbW hydraulic test bench was established, and an asymmetric dynamic transfer function model of the steering system was identified utilizing the Nelder–Mead simplex method. To overcome the susceptibility of the conventional Sparrow Search Algorithm (SSA) to local optima entrapment and its insufficient population diversity, the Circle chaotic map was employed to enhance the initial population distribution. Furthermore, an adaptive t-distribution mutation strategy was incorporated to coordinate global exploration and local exploitation, facilitating the optimization of the PID parameters. Hardware-in-the-loop (HIL) bench tests were conducted to evaluate the performance of the different control algorithms. With the proposed ISSA-PID controller, under step response conditions, accounting for the inherent dynamics of the asymmetric steering cylinder, the response times for left and right turns were reduced to 0.77 s and 0.98 s, respectively. During random signal tracking tests that emulate stochastic field operations, the average tracking error was minimized to 0.75°, with a maximum deviation restricted to 1.27°. These results demonstrate that the proposed ISSA-PID strategy addresses parameter tuning challenges, improving control precision and dynamic response. Consequently, it offers a practical control strategy for tractor SbW hydraulic systems.