Advanced Equipment

ISSN: 3007-5114 (Print)

ISSN: 3007-5122 (Online)

CODEN: AEABF4

About This Journal
Special Issues
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Advances in Precision Manufacturing and Instrumentation Technologies
Special Issue Editor:   Yanquan Geng, Jiqiang Wang, Yang He
Submission Deadline:  31 December 2026
Intelligent Fault Diagnosis under Complex and Uncertain Environments
Special Issue Editor:   Jiantao Lu, Jingsong Xie, Xiaoli Zhao
Submission Deadline:  31 December 2026
Latest Articles
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Adaptive asymptotic tracking control for active suspension systems: an event-triggered approach with input saturation
Yingjie Deng,Fangcheng Liu,Xiangyu Meng,Yuxin Wu,Dingxuan Zhao,Tao Ni,Namkyun Im
Article08 Jul 2026OPEN ACCESS

In this paper, an adaptive neural asymptotic tracking control scheme with the event-triggered mechanism is presented for a quarter-car active suspension system (ASS) with unknown road inputs and input saturation. In the control design, an auxiliary system is constructed to compensate for the input saturation of the actuator, and a linear filter is introduced to solve the chattering problem of the suspension system under the zero dynamics. By integrating integral-bounded functions into the adaptive law and control law, asymptotic convergence of the tracking error is achieved with high precision. Using the adaptive backstepping control method and introducing the command filter, an event-triggered adaptive neural asymptotic tracking control algorithm is developed, in which the radial basis function neural networks (RBFNNs) are used to approximate the unknown model dynamics. Considering the waste of communication resources in the controller, the event-triggered control (ETC) law in the controller-to-actuator channel is designed. Benefiting from the minimal learning parameters (MLP) technique, the proposed scheme requires updating only one parameter, which reduces computational complexity and saves communication resources. By using the Lyapunov’s method and the Barbalat’s lemma, the asymptotic stability of the closed-loop system is proved, and the constraint conditions for vehicle ride comfort are also guaranteed. Finally, the effectiveness of the proposed method is further verified through simulations and experimental results.

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Development of a 3D-printed hybrid compliant revolute joint with enhanced directional stiffness
Zhengyao Wang,Richard Kavanagh,Yancheng Zhang,Guangbo Hao
Article05 Jun 2026OPEN ACCESS

Compliant revolute joints (CRJs) offer advantages in terms of frictionless motion, compactness, and monolithic fabrication, but their practical application is often constrained by an inherent stiffness–flexibility trade-off. High rotational compliance is typically accompanied by insufficient resistance to off-axis deformation, leading to parasitic motion and reduced directional stability. To address this challenge, this study proposes a hybrid CRJ designed to enhance directional stiffness while maintaining large elastic rotational capability. The joint integrates stiff polylactic acid (PLA) reinforcement ribs within a compliant thermoplastic polyurethane (TPU) matrix, with material distribution strategically tailored to suppress off-axis deformation without compromising the intended rotational motion. The design is compatible with monolithic fabrication via dual-material fused deposition modelling (FDM). Finite element analysis, informed by experimentally characterised material and interfacial properties, is employed to evaluate the mechanical performance of the proposed joint. The results demonstrate that the hybrid joint exhibits a significantly higher ratio of off-axis to on-axis rotational stiffness compared with mono-material PLA and TPU joints, indicating effective suppression of parasitic deformation while preserving rotational compliance.

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Photopolymerisation-extrusion coupled moulding: a new paradigm and trend outlook for 3D printing of ceramic precursors
Linzhe Zhang,Zhen Wang,Chuanzhen Huang,Longhua Xu,Shuiquan Huang,Meina Qu,Zhengkai Xu,Dijia Zhang,Baosu Guo,Tianye Jin,Xiaodan Wang
Review05 Jun 2026OPEN ACCESS

Ceramic materials are indispensable in aerospace, energy, and biomedical fields due to their high hardness, heat resistance, and corrosion resistance. However, their inherent brittleness makes it difficult to fabricate complex structures via traditional forming methods. 3D printing provides an effective near-net-shape route, among which Polymer-Derived Ceramics (PDCs) have become a research hotspot owing to binder-free composition, molecular design flexibility, and low-temperature sinterability. This review focuses on photopolymerisation-extrusion coupled moulding as a core strategy to resolve the long-standing trade-off between high precision and low defects in PDC 3D printing. We systematically review the material systems of ceramic precursors, analyze the principles of photopolymerisation-based printing for PDCs, clarify the reaction mechanisms, volumetric shrinkage mechanisms, and extrusion flow behaviors of photopolymerisation-assisted extrusion 3D printing. Emphasis is placed on how coupling mitigates contradictions between precision and defects, improves interlayer bonding, and reduces warpage and cracking. Finally, we summarize key bottlenecks and propose targeted future development directions, providing a clear reference for advancing high-performance ceramic precursor additive manufacturing.

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Microstructure evolution and property improvement of Al–Zn–Mg–Cu alloy processed by laser-arc hybrid additive manufacturing
Dehua Liu,Jiang Bi,Zhuoyun Yang,Guojiang Dong
Article11 Aug 2025OPEN ACCESS
Recently, laser-arc hybrid additive manufacturing (LAHAM) has emerged as a promising strategy for fabricating components with favorable performance. In this paper, we compared the microstructure and mechanical properties of Al–Zn–Mg–Cu alloy manufactured by wire + arc additive manufacturing (WAAM) and LAHAM and obtained strengthening by means of heat treatment. The microstructure consisted of coarse columnar grains with an average grain size of 70.4 µm in the WAAM-processed Al–Zn–Mg–Cu alloy. Compared to the WAAM specimen, the grain size of LAHAM specimen was reduced by 68%, and the eutectics distribution was more uniform. The high-densities η′ precipitates with the length of 10–30 nm appeared in the processed by LAHAM. The key achievement indicated that the ultimate tensile strength (590 ± 9 MPa) and elongation (8.6 ± 0.2%) for LAHAM-processed Al–Zn–Mg–Cu alloy after heat treatment were enhanced by approximately 87% and 169% than those in the deposited specimen.
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Development of an integrated device for processing and detection of micro and nano structures on a miniaturized sphere utilizing atomic force microscopy
Jiqiang Wang,Ziwen Kang,Yongda Yan,Yanquan Geng
Article31 Jul 2025OPEN ACCESS
Microspheres, with diameters ranging from tens of microns to several millimeters, find extensive application in precision bearings, optical cameras, and lithography machines due to their unique mechanical and optical properties. Concurrently, the demand for improved dimensional accuracy and enhanced surface quality of these microspheres has significantly increased. As a result, the research focus has increasingly shifted towards micro-nano structuring and high-precision measurement of microspheres. In this study, an integrated device comprising a custom-developed AFM system, a control system, and proprietary software was established to achieve seamless integration of machining and measurement on the surface of microspheres. Moreover, the control system of the device has been established. The computer software is also developed based on the C++ graphical user interface (GUI) application development framework QT software. To achieve the center alignment between the micro-sphere and the air-bearing spindle, a strategy based on the device is proposed. Nanostructures, including square pit structures, triangular structures, and circular structures, are successfully machined and measured on the surface of GDP microspheres. Our findings provide a new approach for machining and measuring micro-nano structures on the surface of micro-target balls used in ICF.
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Event-triggered adaptive neural network asymptotic tracking control of intelligent vehicles with composite learning
Yingjie Deng,Fangcheng Liu,Songtao Wang,Yifei Xu,Tao Ni,Dingxuan Zhao
Article11 Jun 2025OPEN ACCESS
In the current epoch of intelligent transportation, achieving high-precision tracking control for autonomous vehicles is a crucial challenge due to the presence of system nonlinearities, uncertainties, and communication constraints. Traditional continuous control methods often lead to excessive communication traffic, while existing adaptive control techniques struggle to ensure asymptotic tracking accuracy under these constraints. To address these issues, this paper investigates the problem of high-precision tracking control for intelligent vehicles by designing an event-triggered asymptotic composite neural tracking control scheme. In the proposed framework, radial basis function neural networks are employed to compensate for system nonlinearities and uncertainties. By introducing integral-bounded functions into both the control laws and adaptive laws, the asymptotic convergence of positional tracking errors is ensured through the adaptive backstepping approach. To reduce communication traffic, an event-triggered control strategy is implemented in the controller-to-actuator channel, where variable threshold-based triggering conditions are designed. Furthermore, to enhance the approximation capability of neural networks, composite learning is incorporated into the control design. A novel serial-parallel estimation model is established to generate prediction errors while simultaneously ensuring asymptotic stability. The stability of the overall system is rigorously analyzed using Lyapunov’s direct method and the Barbalat lemma. Finally, numerical simulations are conducted to validate the effectiveness and superiority of the proposed control scheme.
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