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Initial attitude calibration is a critical yet challenging phase in hardware-in-the-loop (HIL) testing for space docking, often hindered by cumbersome procedures, safety concerns, and reliance on external equipment. This paper introduces a human–robot collaborative calibration method based on H∞ robust control. The core objective is to achieve symmetric pose alignment between docking mechanisms by allowing the operator to manually guide the test device, thereby rapidly obtaining initial attitude calibration results. An interactive model incorporating a time delay is established. Using H∞ synthesis, a stabilizing controller is designed to accurately track low-frequency operator commands while strongly suppressing high-frequency disturbances. Notably, the H∞ framework reconstructs an ideal interactive symmetry in human–robot collaboration by compensating for delays and disturbances. The solution to the Riccati equation within a game-theoretic framework effectively achieves symmetric optimization that balances tracking accuracy with safety constraints. Experimental results demonstrate that the method successfully compensates for system delays, enabling symmetric pose alignment while maintaining smooth and continuous motion of the docking mechanism. It also faithfully translates the operator’s low-frequency traction intent into motion. By retaining contact forces/torques within safe thresholds, the method balances interaction safety with operational precision, ultimately providing a reliable solution for initial attitude calibration in space docking HIL tests.

To meet the in-orbit performance verification requirements of a drag-free control system for gravitational wave detection satellites, this study develops a ground simulation platform using the H-infinity (H∞) control method in Simulink. The FPGA implementation accelerates the core algorithm of drag-free control. A frequency-domain linear robust control design is employed, with a frequency pre-warped bilinear transformation method used to discretize the multi-degree-of-freedom controller. The established control system model includes 18 degrees of freedom, with 12 from the dual test masses (TM) and 6 from the satellite body. The two test masses are spatially arranged in a symmetric configuration, and their control structure also exhibits symmetry. A rapid reconfigurable hardware architecture is utilized, and the Vitis Model Composer tool is employed to efficiently translate the Simulink algorithm model into hardware description language, reducing the processing delay of the core control algorithm to the nanosecond level. Through a 15-channel gradient test comparison, the FPGA platform maintains numerical equivalence with the Simulink platform (maximum error of 10−13). Experimental results show that the hardware acceleration improves dynamic response speed by an order of magnitude, achieving position control accuracy of ±5 μm and attitude accuracy of ±10 μrad, with overall processing latency at the microsecond level. This method provides a reliable engineering validation approach for ultra-precision control systems in gravitational wave detection.

In this paper, a robust control algorithm is designed to achieve a finite-time vehicle height and posture control through electronically controlled air suspension (ECAS) system subject to actuator faults, uncertainties under non-stationary condition. To achieve simultaneous position control of four corners of vehicle, synchronization errors between corners are taken to form a synchronization control strategy. Furthermore, to improve the system convergence speed and robustness, finite-time stability constrain is applied and H ∞ index is designed strategically in order to develop a novel robust finite-time controller. Since the solenoid valves in the ECAS system may degrade with the frequent switching, actuator fault and uncertain parameters are considered in this study to design the proposed fault-tolerant control methodology. Meanwhile, road disturbance is applied to the vehicle with the ECAS system to provide a non-stationary condition. Several software-in-the-loop tests and hardware-in-the-loop test are conducted to illustrate the effectiveness of the proposed controller.

To further improve the multi-objective comprehensive vibration isolation performance of commercial vehicles and save network resource occupation, this paper proposes a new configuration of semi-active quasi-zero stiffness air suspension (QZSAS) with network communication architecture, and a matching dynamic output feedback control (DOFC) strategy considering event-triggered mechanism. The semi-active QZSAS is mainly composed of a positive stiffness air spring, a pair of negative stiffness double-acting cylinders and two continuous damping controlled (CDC) dampers. Event-triggered mechanism determines whether the control signal is updated by judging the measured signal to save communication resources. Firstly, the nonlinear stiffness of the suspension system is regarded as an uncertain parameter and processed by constructing a Takagi–Sugeno (T-S) fuzzy controller model. Then, the Lyapunov–Krasovskii functional method is employed to design the dynamic output feedback controller under the linear matrix inequality constraint to ensure system stability with H ∞ performance index. Finally, the co-simulation and hardware-in-the-loop (HiL) test results show that the presented new semi-active QZSAS structure and the DOFC method considering event-triggered mechanism can significantly improve the multi-objective performance of commercial vehicles under different driving conditions with significantly reducing the network communication burden.

The connectivity of a network is an important indicator to its reliability and fault tolerability. Since the faulty elements in the network may have some special structures, two new kinds of conditional connectivity, called h -restricted H -structure connectivity and h -restricted H -substructure connectivity, are proposed as a generalization of conditional connectivity, where h ≥ 1 , and H is some special structure. In this paper, we establish both h -restricted H -structure connectivity and h -restricted H -substructure connectivity for the hypercube Q n , where the special structures are K 1 , K 1 , 1 , K 1 , 2 , respectively.

Motion estimation (ME) as a process in H.264 coding basically deals with huge number of image data and needs a lot of calculation so that it should be considered to improve by hardware implementation and data redundancy reduction. This paper proposes an H.264 coding-based motion estimation architecture for video broadcasting from a studio. To implement a hardware of motion estimation, parallel processing is logically applied in the preprocessing and keypoint finding processes, and time-domain based algorithm is replaced by the frequency-domain based algorithm in order to filter the informative data in the low frequency range. The experimental results show that the proposed H.264 coding-based motion estimation architecture achieved significant improvement while maintaining the signal quality.

To reduce the hardware implementation resource consumption of the two-dimensional transform component in H.266 VVC, a unified hardware structure is proposed that supports full-size Discrete Cosine Transform (DCT), Discrete Sine Transform (DST), and full-size Low-Frequency Non-Separable Transform (LFNST). This paper presents an area-efficient hardware architecture for two-dimensional transforms based on a general Regular Multiplier (RM) and a high-throughput hardware design for LFNST in the context of H.266/VVC. The first approach utilizes the high-frequency zeroing characteristics of VVC and the symmetric properties of the DCT-II matrix, allowing the RM-based architecture to use only 256 general multipliers in a fully pipelined structure with a parallelism of 16. The second approach optimizes the transpose operation of the input matrix for LFNST in a parallelism of 16 architecture, aiming to save storage and logic resources.

Traditional multilevel inverter topologies, such FC, NPC, and CHB, have a few significant disadvantages. They need a great number of parts, which raises the complexity, expense, and switching losses. Furthermore, their intricate control schemes make voltage balancing and synchronization challenging. Lastly, under some circumstances, they experience severe harmonic distortion, necessitating the inclusion of expensive filters to enhance signal quality. This paper proposes a novel multilevel converter topology that uses the phase-disposition PWM (PD-PWM) technique to control a 19-level output. This new configuration maintains performance comparable to the CHB-MLI reference while using fewer switches, simplifying control, and reducing costs. Our approach is based on extensive simulations conducted in the MATLAB Simulink environment, with results compared to the CHB-MLI. A low-pass filter is added to improve the output voltage quality, reducing the THD% to 1.33%. This strategy offers several advantages, including simpler control, lower costs, increased reliability, and higher-quality output. The system was replicated using MATLAB Simulink and validated through hardware-in-the-loop (HIL) testing. The HIL method ensures real-world testing without causing damage to the hardware. The integrated system includes sensors and necessary hardware for a comprehensive energy management solution.

This article presents a novel hardware-assisted distributed ledger-based solution for simultaneous device and data security in smart healthcare. This article presents a novel architecture that integrates PUF, blockchain, and Tangle for Security-by-Design (SbD) of healthcare cyber–physical systems (H-CPSs). Healthcare systems around the world have undergone massive technological transformation and have seen growing adoption with the advancement of Internet-of-Medical Things (IoMT). The technological transformation of healthcare systems to telemedicine, e-health, connected health, and remote health is being made possible with the sophisticated integration of IoMT with machine learning, big data, artificial intelligence (AI), and other technologies. As healthcare systems are becoming more accessible and advanced, security and privacy have become pivotal for the smooth integration and functioning of various systems in H-CPSs. In this work, we present a novel approach that integrates PUF with IOTA Tangle and blockchain and works by storing the PUF keys of a patient’s Body Area Network (BAN) inside blockchain to access, store, and share globally. Each patient has a network of smart wearables and a gateway to obtain the physiological sensor data securely. To facilitate communication among various stakeholders in healthcare systems, IOTA Tangle’s Masked Authentication Messaging (MAM) communication protocol has been used, which securely enables patients to communicate, share, and store data on Tangle. The MAM channel works in the restricted mode in the proposed architecture, which can be accessed using the patient’s gateway PUF key. Furthermore, the successful verification of PUF enables patients to securely send and share physiological sensor data from various wearable and implantable medical devices embedded with PUF. Finally, healthcare system entities like physicians, hospital admin networks, and remote monitoring systems can securely establish communication with patients using MAM and retrieve the patient’s BAN PUF keys from the blockchain securely. Our experimental analysis shows that the proposed approach successfully integrates three security primitives, PUF, blockchain, and Tangle, providing decentralized access control and security in H-CPS with minimal energy requirements, data storage, and response time.