Shenyang Institute of Automation

This paper develops a precise micro-amplitude force output device (PMAFOD) and its control strategy to meet the needs of precision-instrument environmental simulation and active vibration suppression. Building on adaptive inverse control (AIC) and active disturbance-rejection control (ADRC), a disturbance-compensation adaptive inverse control (DCAIC) scheme is proposed for fast time-domain force tracking. A linear extended state observer (LESO) is used to construct the disturbance-compensation loop, which explicitly targets the system’s frequency response, mitigates AIC divergence caused by PMAFOD phase lag, and preserves ADRC’s disturbance-rejection capability. Experiments on the PMAFOD show that fixed- and sweep-frequency tracking achieves an effective bandwidth of 20–500 Hz with tracking errors approaching the 1 mN measurement noise floor, while band-limited random-waveform tracking maintains errors below 10 mN. The proposed framework provides a practical solution for broadband micro-force generation and can be extended to other precision actuation platforms.

As the maritime industry transitions towards green shipping, operational sustainability and energy efficiency are increasingly crucial for long-endurance Unmanned Surface Vehicle (USV) missions. To this end, proactively adjusting driving strategies based on the prediction of other USVs’ motion is essential. This proactive approach directly minimizes carbon emissions and reduces high-energy driving behaviors resulting from passive sudden braking or sharp turns in unexpected situations. However, existing trajectory prediction methods are trained based on low-frequency automatic identification system data of large merchant vessels, which cannot be directly used on the highly dynamic USV data. To address this limitation, this study constructs a large-scale simulated USV scenario dataset grounded in nonlinear ship hydrodynamics, which contains complicated interactive scenarios with multiple USV agents. To effectively model the interaction among agents for accurate prediction, we further propose USV-Former, a hierarchical encoder-decoder architecture designed for proactive navigation. The framework integrates a symmetric encoding structure with a dual-stage pipeline: a Local Attention Module captures high-frequency dynamics, while a Global Graph Attention Module enforces COLREGs-compliant topological constraints. Experimental results demonstrate that the proposed model outperforms established baselines in prediction accuracy. Qualitative analysis further reveals that by accurately anticipating target intentions, the model minimizes unnecessary avoidance maneuvers, enabling more stable and momentum-conserving velocity profiles. Ultimately, this architecture exhibits high computational efficiency, reduces operational energy waste, and provides a robust, measurable algorithmic foundation for green autonomous shipping and marine environmental protection.

In smart grids, smart meters periodically collect users' fine-grained multi-dimensional energy data, which poses great concerns on users' privacy and security. Existing privacy preserving multi-dimensional aggregation schemes suffer from heavy computational burdens, especially for smart meters with limited computational resources. To address these limitations, in this paper we propose an efficient and flexible multi-dimensional data aggregation scheme called MDA-SMuSha, by which smart meters employ the Shamir's multi-secret sharing to generate a set of shared secrets, with the first one kept locally, while the remained ones are packaged and then uploaded to a control center via an aggregator. By the MDA-SMuSha scheme, aggregation results of smart meters' multi-dimensional energy data during multiple periods can be obtained, with only one time of Paillier encryption conducted on the smart meters. In addition, it allows the control center to send query requests flexibly, i.e., at a pre-specified frequency or whenever it wants to obtain statistical data of interests. Rigorous security analyses show that the MDA-SMuSha scheme satisfies security requirements of privacy-preservation, authenticity and data integrity as well as fault-tolerance. Both theoretical analyses and experiment results show that the MDA-SMuSha scheme outperforms state-of-the art methods in terms of computation costs, with comparable communication costs.

ABSTRACT Implantable bioelectronic devices demonstrate immense potential in health monitoring and therapeutic interventions, yet encounter formidable challenges in achieving biocompatibility and interfacial stability within complex biological environments. This study proposes a novel liquid metal‐hydrogel bonding strategy based on Cabrera–Mott oxidation kinetics regulation, which significantly enhances the printability of liquid metals on biocompatible hydrogel substrates through interfacial tension reduction and accelerated surface oxidation. Experimental findings revealed a 26.25% reduction in contact angle and a printing resolution improvement to 200 µm while maintaining superior electrical conductivity (3.83 × 10 5 S/m). Leveraging this advancement, we developed a flexible cardiac pacemaker integrating wireless energy transmission, pulse circuitry, and electrostimulation modules, which successfully achieved stable cardiac rhythm modulation in murine heart failure models. Histopathological analyses further corroborated the device's biosafety profile. This study presents a promising strategy for miniaturized implantable bioelectronics design and biointerface optimization, offering valuable insights for the development of future personalized bioelectronic systems.