Actuators

24 pages, 3447 KB

Open AccessArticle

Stability Optimization of an Oil Sampling Machine Control System Based on Improved Sparrow Search Algorithm PID

by Pan Zhang, Changwei Yang, Min Liao, Junmin Li, Simon X. Yang, Peisong Jiang, Yangxin Teng and Xiaolong Wu

Actuators 2025, 14(9), 419; https://doi.org/10.3390/act14090419 - 28 Aug 2025

Abstract

This paper presents an automatic oil sampling system designed for vertical cylindrical oil tanks on land, focusing primarily on the structural design and control optimization for oil level measurement and liquid sampling inside the tank. First, the key structure and control architecture of [...] Read more.

This paper presents an automatic oil sampling system designed for vertical cylindrical oil tanks on land, focusing primarily on the structural design and control optimization for oil level measurement and liquid sampling inside the tank. First, the key structure and control architecture of the automatic sampler are introduced, explaining the collaborative working principles of its components to ensure good stability in system structure and motion control. On this basis, an improved Sparrow Search Algorithm (CSSA) is proposed, which integrates the Coati Optimization Algorithm (COA) and the traditional Sparrow Search Algorithm (SSA). This algorithm is used to optimize the parameters of the Proportional–Integral–Derivative (PID) control system in the oil sampler, aiming to address issues such as response delay, large overshoot, and insufficient stability that commonly occur in traditional PID control under complex conditions. This method achieves consistent response behavior over time and adaptiveness in the control process by dynamically adjusting the PID parameters in real time. To verify the effectiveness of the proposed control strategy, system simulations were conducted in the MATLAB 2024B environment, and a physical experimental platform was built for testing. The simulation compares the CSSA-PID controller with traditional PID, COA-PID, and SSA-PID control methods. In addition, a load disturbance was introduced at 300 ms to perform anti-interference comparative simulations. The results show that under CSSA-PID control, the system response time was shortened by up to 112 ms, the convergence speed improved by 72.3%, the global optimization capability was significantly enhanced, and the anti-interference ability was stronger. In the actual tests, the average error was reduced by approximately 45.3%. These results indicate that CSSA-PID can significantly enhance the stability and response speed of the control system. The efficient control of the automatic oil sampler will greatly enhance the intelligence and efficiency of oil level detection in tanks and reduce labor costs, having significant implications for the development of the grain and oil storage industry. Full article

(This article belongs to the Section Control Systems)

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17 pages, 28985 KB

Open AccessArticle

Design, Performance Testing, and Experimental Validation of Modular Soft Robots Based on Thin-Film Actuators

by Anqi Guo, Zhiwei Ji, Siqi Yu, Wenlong Xie, Xiangchen He and Guoqing Jin

Actuators 2025, 14(9), 418; https://doi.org/10.3390/act14090418 - 27 Aug 2025

Abstract

Currently, soft robots face challenges such as low motion efficiency, susceptibility to damage in traditional silicone materials, and difficulty in achieving reproducible manufacturing. To address these issues, we integrate flexible film materials with modular design principles and apply them to soft robotics. Based [...] Read more.

Currently, soft robots face challenges such as low motion efficiency, susceptibility to damage in traditional silicone materials, and difficulty in achieving reproducible manufacturing. To address these issues, we integrate flexible film materials with modular design principles and apply them to soft robotics. Based on the concept of modularity, this study simplifies and decomposes the robot’s motion into three fundamental modules: a thin-film elongation actuator module, a thin-film deflection actuator module, and a connection module. Inspired by the Miura-fold origami technique and traditional lantern contraction, the elongation actuator is designed to produce axial extension of varying lengths under different air pressures. The deflection actuator is modeled after the head expansion mechanism of the pelican eel, enabling deflection movement. The connection module integrates the elongation and deflection modules into a unified structure. The research results show that the elongation actuator achieves an extension length of 118 mm under 50 kPa and can pull a 500 g load during horizontal contraction. The two-layer deflection actuator achieves a deflection angle of 56° at 40 kPa, while the three-layer version reaches 98°. For further demonstration, we subsequently conducted peristaltic soft robot experiments and obstacle avoidance experiments. This study holds significant potential for the development of next-generation multifunctional soft robots. Full article

(This article belongs to the Section Actuators for Robotics)

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14 pages, 1776 KB

Open AccessArticle

A Fluid Elastomeric Actuator Design for Soft Robots

by Dennis Els, Theo van Niekerk, Paolo Mercorelli and Jacques Welgemoed

Actuators 2025, 14(9), 417; https://doi.org/10.3390/act14090417 - 25 Aug 2025

Abstract

The field of robotics faces significant challenges in creating adaptable and flexible end-effectors. Soft robotics, specifically soft robotic end-effectors, offer an innovative solution. This paper focuses on designing fluid elastomeric actuators (FEAs) for soft robotic end-effectors. The study presents key design considerations and [...] Read more.

The field of robotics faces significant challenges in creating adaptable and flexible end-effectors. Soft robotics, specifically soft robotic end-effectors, offer an innovative solution. This paper focuses on designing fluid elastomeric actuators (FEAs) for soft robotic end-effectors. The study presents key design considerations and evaluates the use of Finite Element Method (FEM) simulations for optimizing FEA performance. The study then concludes by proposing design guidelines for developing application-specific fluid elastomeric actuators. Full article

(This article belongs to the Special Issue Actuator Technologies and Control: Materials, Devices and Applications)

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15 pages, 5053 KB

Open AccessArticle

Master Cylinder Pressure Control Based on Piecewise-SMC in Electro-Hydraulic Brake System

by Cong Liang, Xing Xu, Hui Deng, Chuanlin He, Long Chen and Yan Wang

Actuators 2025, 14(9), 416; https://doi.org/10.3390/act14090416 - 24 Aug 2025

Abstract

This paper focuses on enhancing master cylinder pressure control in pressure-sensorless Electro-Hydraulic Brake (EHB) systems. A novel control strategy is developed, integrating a Piecewise Sliding Mode Controller (Piecewise-SMC) with an Extended Sliding Mode Observer (ESMO) based on a newly derived pressure–position–velocity model that [...] Read more.

This paper focuses on enhancing master cylinder pressure control in pressure-sensorless Electro-Hydraulic Brake (EHB) systems. A novel control strategy is developed, integrating a Piecewise Sliding Mode Controller (Piecewise-SMC) with an Extended Sliding Mode Observer (ESMO) based on a newly derived pressure–position–velocity model that accounts for rack position and velocity effects. To handle external disturbances and parameter uncertainties, the ESMO provides accurate pressure estimation. The nonlinear EHB model is approximated piecewise linearly to facilitate controller design. The proposed Piecewise-SMC regulates motor torque to achieve precise pressure tracking. Experimental validation under step-change braking conditions demonstrates that the Piecewise-SMC reduces response time by 31.8%, overshoot by 35.8%, and tracking root mean square error by 9.6% compared to traditional SMC, confirming its effectiveness and robustness for pressure-sensorless EHB applications. Full article

(This article belongs to the Special Issue Actuator Fault Diagnosis, State Detection and Fault Tolerant Control for Ground and Rail Vehicles)

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24 pages, 1538 KB

Open AccessArticle

Intelligent Fault Diagnosis for Rotating Machinery via Transfer Learning and Attention Mechanisms: A Lightweight and Adaptive Approach

by Zhengjie Wang, Xing Yang, Tongjie Li, Lei She, Xuanchen Guo and Fan Yang

Actuators 2025, 14(9), 415; https://doi.org/10.3390/act14090415 - 23 Aug 2025

Abstract

Fault diagnosis under variable operating conditions remains challenging due to the limited adaptability of traditional methods. This paper proposes a transfer learning-based approach for bearing fault diagnosis across different rotational speeds, addressing the critical need for reliable detection in changing industrial environments. The [...] Read more.

Fault diagnosis under variable operating conditions remains challenging due to the limited adaptability of traditional methods. This paper proposes a transfer learning-based approach for bearing fault diagnosis across different rotational speeds, addressing the critical need for reliable detection in changing industrial environments. The method trains a diagnostic model on labeled source-domain data and transfers them to unlabeled target domains through a two-stage adaptation strategy. First, only the source-domain data are labeled to reflect real-world scenarios where target-domain labels are unavailable. The model architecture combines a convolutional neural network (CNN) for feature extraction with a self-attention mechanism for classification. During source-domain training, the feature extractor parameters are frozen to focus on classifier optimization. When transferring to target domains, the classifier parameters are frozen instead, allowing the feature extractor to adapt to new speed conditions. Experimental validation on the Case Western Reserve University bearing dataset (CWRU), Jiangnan University bearing dataset (JNU), and Southeast University gear and bearing dataset (SEU) demonstrates the method’s effectiveness, achieving accuracies of 99.95%, 99.99%, and 100%, respectively. The proposed method achieves significant model size reduction compared to conventional TL approaches (e.g., DANN and CDAN), with reductions of up to 91.97% and 64%, respectively. Furthermore, we observed a maximum reduction of 61.86% in FLOPs consumption. The results show significant improvement over conventional approaches in maintaining diagnostic performance across varying operational conditions. This study provides a practical solution for industrial applications where equipment operates under non-stationary speeds, offering both computational efficiency and reliable fault detection capabilities. Full article

(This article belongs to the Section Actuators for Manufacturing Systems)

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21 pages, 3369 KB

Open AccessArticle

Event-Triggered Fixed-Time Consensus Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Dead-Zone Input

by Zian Wang, Yixiang Gu, Jiarui Liu, Yue Zhang, Kai Feng, Jietao Dai and Guoxiong Zheng

Actuators 2025, 14(9), 414; https://doi.org/10.3390/act14090414 - 22 Aug 2025

Abstract

This study explores the issue of fixed-time dynamic event-triggered consensus control for uncertain nonlinear multi-agent systems (MASs) within directed graph frameworks. In practical applications, the system encounters multiple constraints such as unknown time-varying parameters, unknown external disturbances, and input dead zones, which may [...] Read more.

This study explores the issue of fixed-time dynamic event-triggered consensus control for uncertain nonlinear multi-agent systems (MASs) within directed graph frameworks. In practical applications, the system encounters multiple constraints such as unknown time-varying parameters, unknown external disturbances, and input dead zones, which may increase the communication burden of the system. Therefore, achieving fixed-time consensus tracking control under the aforementioned conditions is challenging. To address these issues, an adaptive fixed-time consensus tracking control method based on boundary estimation and fuzzy logic systems (FLSs) is proposed to achieve online compensation for the input dead zone. Additionally, to optimize the utilization of communication resources, a periodic adaptive event-triggered control (PAETC) is designed. The mechanism dynamically adjusts the frequency at which the trigger is updated in real time, reducing communication resource usage by responding to changes in the control signal. Finally, the efficacy of the proposed approach is confirmed via theoretical evaluation and simulation. Full article

(This article belongs to the Special Issue Analysis and Design of Linear/Nonlinear Control System)

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27 pages, 8503 KB

Open AccessArticle

Design and Implementation of an Autonomous Intelligent Fertigation System for Cross-Regional Applications

by Ruizhi Tang, Hanhong Hu, Hai Lin, Jiahao Li, Zian Wang, Guanquan Zhu, Ziyou Mei and Jietao Dai

Actuators 2025, 14(9), 413; https://doi.org/10.3390/act14090413 - 22 Aug 2025

Abstract

Conventional fertigation systems suffer from limited cross-regional adaptability, mainly due to unstable fertilizer flow from fixed-aperture units, poor terrain adaptability, and an inadequate response to environmental heterogeneity. This study proposes an autonomous, cross-regional intelligent fertigation system based on an STM32F1 microcontroller and UART [...] Read more.

Conventional fertigation systems suffer from limited cross-regional adaptability, mainly due to unstable fertilizer flow from fixed-aperture units, poor terrain adaptability, and an inadequate response to environmental heterogeneity. This study proposes an autonomous, cross-regional intelligent fertigation system based on an STM32F1 microcontroller and UART communication protocols. The system integrates a mechanically adjustable iris fertilizer delivery unit, a dual-axis fertigation module, a data interconnection unit, and comprehensive control software with dynamic calibration capabilities. Prototype evaluations conducted on both sloped terrain (up to 38°) and flat surfaces demonstrate a stable performance, achieving fertilizer flow control errors below 3%, irrigation deviation under 5%, and fertilization deviation within 2%. Real-time data acquisition, remote monitoring, and intelligent operation are supported by a YOLOv5s-based visual recognition system, which attains an mAP@0.5 of 92.5%. This integrated solution offers a robust approach to precision agriculture across diverse environmental conditions. Full article

(This article belongs to the Special Issue Adaptive Fault-Tolerant Control Strategies for Uncertain Nonlinear Systems: Mitigating Actuator Faults)

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21 pages, 854 KB

Open AccessArticle

An Event-Triggered Observer-Based Control Approach for Enhancing Resilience of Cyber–Physical Systems Under Markovian Cyberattacks

by Eya Hassine, Assem Thabet, Noussaiba Gasmi and Ghazi Bel Haj Frej

Actuators 2025, 14(8), 412; https://doi.org/10.3390/act14080412 - 21 Aug 2025

Abstract

This paper presents a resilient observer-based and event-triggered control scheme for discrete-time Cyber–Physical Systems (CPS) under Markovian Cyber-Attacks (MCA). The proposed framework integrates a Luenberger observer for cyberattack detection with a state-feedback controller designed to preserve system stability in the presence of Denial-of-Service [...] Read more.

This paper presents a resilient observer-based and event-triggered control scheme for discrete-time Cyber–Physical Systems (CPS) under Markovian Cyber-Attacks (MCA). The proposed framework integrates a Luenberger observer for cyberattack detection with a state-feedback controller designed to preserve system stability in the presence of Denial-of-Service (DoS) and False Data Injection (FDI) attacks. Attack detection is achieved through residual signal generation combined with Markovian modeling of the attack dynamics. System stability is guaranteed by formulating relaxed Linear Matrix Inequality (LMI) conditions that incorporate relaxation variables, a diagonal Lyapunov function, the S-procedure, and congruence transformations. Moreover, the Event-Triggered Mechanism (ETM) efficiently reduces communication load without degrading control performance. Numerical simulations conducted on a three-tank system benchmark confirm enhanced detection accuracy, faster recovery, and strong robustness against uncertainties. Full article

(This article belongs to the Special Issue Actuator Technologies and Control: Materials, Devices and Applications)

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18 pages, 13640 KB

Open AccessArticle

Nonlinearity Characterization of Flexible Hinge Piezoelectric Stages Under Dynamic Preload via a Force-Dependent Prandtl–Ishlinskii Model with a Force-Analyzed Finite Element Method

by Xuchen Wang, Dong An, Zicheng Qin, Chuan Wang, Yuping Liu and Yixiao Yang

Actuators 2025, 14(8), 411; https://doi.org/10.3390/act14080411 - 19 Aug 2025

Abstract

The operational performance of Flexible Hinge Piezoelectric Stages (FHPSs), essential components in precision engineering, is fundamentally constrained by the inherent hysteresis of the piezoelectric actuator (PEA). A significant deficiency in prevailing characterization methods is their failure to consider the dynamic nature of the [...] Read more.

The operational performance of Flexible Hinge Piezoelectric Stages (FHPSs), essential components in precision engineering, is fundamentally constrained by the inherent hysteresis of the piezoelectric actuator (PEA). A significant deficiency in prevailing characterization methods is their failure to consider the dynamic nature of the mechanical preload exerted by the flexible hinge. This position-dependent preload induces substantial deviations in the PEA’s response characteristics, thereby compromising the predictive accuracy of conventional design frameworks. To address this limitation, this paper proposes a Force-Dependent Prandtl–Ishlinskii (FPI) model that explicitly formulates the PEA’s hysteretic behavior as a function of variable preload conditions. The FPI model is subsequently integrated into a comprehensive FPI-FFEM characterization framework. Within this framework, a Force-analyzed Finite Element Method (FFEM) is utilized to compute the dynamic preload throughout the actuator’s operational stroke. This information, notably neglected in conventional FEM analysis, is essential to the fidelity of the proposed FPI model. Experimental validation demonstrates the superior fidelity of the FPI model in comparison to the traditional PI model for tracking preload-induced nonlinearities. Furthermore, the complete FPI-FFEM framework exhibits substantially enhanced prediction accuracy relative to both conventional PI-FEM and advanced LDPI-FEM methodologies, as demonstrated by a significant reduction in the Mean Absolute Error (MAE). Full article

(This article belongs to the Special Issue Piezoelectric Actuators and Motors: State-of-the-Art and Perspectives for Actuators)

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26 pages, 3443 KB

Open AccessArticle

Intelligent Soft Sensors for Inferential Monitoring of Hydrodesulfurization Process Analyzers

by Željka Ujević Andrijić, Srečko Herceg, Magdalena Šimić and Nenad Bolf

Actuators 2025, 14(8), 410; https://doi.org/10.3390/act14080410 - 19 Aug 2025

Abstract

This work presents the development of soft sensor models for monitoring the operation of online process analyzers used to measure the sulfur content in the product of the refinery hydrodesulfurization process. Since sulfur content often fluctuates over time, soft sensor models must account [...] Read more.

This work presents the development of soft sensor models for monitoring the operation of online process analyzers used to measure the sulfur content in the product of the refinery hydrodesulfurization process. Since sulfur content often fluctuates over time, soft sensor models must account for these frequency fluctuations. We have therefore developed dynamic data-driven models based on linear and nonlinear system identification techniques (finite impulse response—FIR, autoregressive with exogenous inputs—ARX, output error—OE, nonlinear ARX—NARX, Hammerstein–Wiener—HW) and machine learning techniques, including models based on long short-term memory (LSTM) and gated recurrent unit (GRU) networks, as well as artificial neural networks (ANNs). The core steps in model development included the selection and preprocessing of continuously measured plant process data, collected from a full-scale industrial hydrodesulfurization unit under normal operating conditions. The developed soft sensor models are intended to support or replace process analyzers during maintenance periods or equipment failures. Moreover, these models enable the application of inferential control strategies, where unmeasured process variables—such as sulfur content—can be estimated in real time and used as feedback for advanced process control. Full article

(This article belongs to the Special Issue Analysis and Design of Linear/Nonlinear Control System)

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22 pages, 2994 KB

Open AccessArticle

Servo State-Based Polynomial Interpolation Model Predictive Control for Enhanced Contouring Control

by Shisheng Lv, Qiang Liu, Yiqing Yang, Yanqiang Liu, Liuquan Wang, Chenxin Zang and Zhiwei Ning

Actuators 2025, 14(8), 409; https://doi.org/10.3390/act14080409 - 19 Aug 2025

Abstract

To further improve machining accuracy under the constrained conditions of multi-axis dynamic response, current research is focusing on the control of CNC machine toolpaths, with contour error as the target. While extant approaches analyze positions solely at PLC sampling nodes, they neglect inter-sample [...] Read more.

To further improve machining accuracy under the constrained conditions of multi-axis dynamic response, current research is focusing on the control of CNC machine toolpaths, with contour error as the target. While extant approaches analyze positions solely at PLC sampling nodes, they neglect inter-sample toolpath fluctuations induced by velocity deviations. This paper proposes a servo state-based polynomial interpolation model predictive control that predicts real-time toolpath behavior by utilizing servo axis states. The polynomial interpolation of servo states (e.g., position/velocity feedback) enables high-fidelity toolpath prediction between PLC nodes, overcoming the limitation imposed by the sampling gap. Experimental validation on a five-axis motion platform with S-shaped trajectories demonstrates that, without extending the prediction horizon of the model predictive control method, the proposed method reduces contour error by approximately 20% at the tool tip and 40% in tool orientation, while decreasing contour error fluctuations by around 60% compared to conventional model predictive control method. Full article

(This article belongs to the Section Control Systems)

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24 pages, 2404 KB

Open AccessSystematic Review

A Systematic Review on Smart Insole Prototypes: Development and Optimization Pathways

by Vítor Miguel Santos, Beatriz B. Gomes, Maria Augusta Neto, Patrícia Freitas Rodrigues and Ana Martins Amaro

Actuators 2025, 14(8), 408; https://doi.org/10.3390/act14080408 - 15 Aug 2025

Abstract

This review synthesizes research on smart insole prototypes and their designs, focusing on those incorporating artificial intelligence (AI) and a wireless communication/transmission system. The main objective of this work is to summarize existing studies, identify key trends, evaluate the performance of these innovative [...] Read more.

This review synthesizes research on smart insole prototypes and their designs, focusing on those incorporating artificial intelligence (AI) and a wireless communication/transmission system. The main objective of this work is to summarize existing studies, identify key trends, evaluate the performance of these innovative biomechanical tools, and recognize the factors that could lead to optimization. This comprehensive analysis includes studies from PubMed, Scopus, and Web of Science databases and other investigations on the critical themes to consider. It follows strict inclusion and exclusion criteria, ensuring the quality and accuracy of the overview. The findings emphasize significant progress in smart insoles, particularly in AI-enhanced prototypes, while addressing existing challenges and problems. This review helps guide potential future research and define practical application directions. The growing importance of biomechanics, especially on smart insoles, underscores the considerable potential of these innovations to monitor and improve human movement in both clinical and non-clinical settings, promising a future of more effective and personalized health and performance interventions. This protocol was registered with the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) on 6 February 2025 and was last updated on 6 February 2025. Full article

(This article belongs to the Special Issue Actuator Technologies and Control: Materials, Devices and Applications)

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30 pages, 35408 KB

Open AccessArticle

Robustness Analysis of the Model Predictive Position Control of an Electro-Mechanical Actuator for Primary Flight Surfaces

by Marco Lucarini, Gianpietro Di Rito, Marco Nardeschi and Nicola Borgarelli

Actuators 2025, 14(8), 407; https://doi.org/10.3390/act14080407 - 14 Aug 2025

Abstract

This paper deals with the design and the robustness analysis of a model predictive control (MPC) for the position tracking of primary flight movables driven by electro-mechanical actuators. This study is, in particular, focused on a rotary electro-mechanical actuator (EMA) by UMBRAGROUP, employing [...] Read more.

This paper deals with the design and the robustness analysis of a model predictive control (MPC) for the position tracking of primary flight movables driven by electro-mechanical actuators. This study is, in particular, focused on a rotary electro-mechanical actuator (EMA) by UMBRAGROUP, employing a patented mechanical transmission based on a differential ball-screw mechanism characterized by a huge gear ratio. To obtain a baseline reference, conventional PID regulators were initially optimized by using multi-objective cost functions based on tracking accuracy, load disturbance rejection, and power consumption. The position regulator was then replaced by an MPC regulator, designed to balance performance, computational resources, and safety constraints. A nonlinear physics-based simulation model of the EMA, entirely developed in the Matlab–Simulink environment and validated with experiments, was used to compare the two control strategies. The simulation results in both the time and frequency domains highlight that the MPC solution provides faster and more accurate position tracking, improved dynamic stiffness, and reduced power absorption. Finally, the robustness against model uncertainties of the MPC was addressed by imposing random and combined deviations of model parameters from the nominal values (via Monte Carlo analysis). The results demonstrate that the implementation of MPC control laws could enhance the stability and the reliability of EMAs, thus supporting their application for safety-critical flight control functions. Full article

(This article belongs to the Special Issue Flight Control Systems and Dynamic Simulation for Aerospace Applications)

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29 pages, 30370 KB

Open AccessArticle

A Data-Driven Global Load Case Analysis Method for Aircraft Structural Design

by Yongbin Liu, Kaiyi Zheng, Xichang Liang and Qianqian Xin

Actuators 2025, 14(8), 406; https://doi.org/10.3390/act14080406 - 13 Aug 2025

Abstract

Aircraft encounter complex ground and air scenarios during service, necessitating a comprehensive analysis of extensive global load cases during the design phase to ensure structural reliability and safety. While high-fidelity finite element analysis enables precise assessment of load case criticality, its prohibitive human [...] Read more.

Aircraft encounter complex ground and air scenarios during service, necessitating a comprehensive analysis of extensive global load cases during the design phase to ensure structural reliability and safety. While high-fidelity finite element analysis enables precise assessment of load case criticality, its prohibitive human and computational costs constrain aircraft iterative development. To overcome this challenge, this study proposes a Global Load Case Analysis (GLCA) system for identifying critical load cases across structural sections. The method is driven by aerodynamic load data and structural response data from coarse-grid models. First, it achieves a quantitative ranking of global load case criticality, providing engineers with a standardized severity metric. Second, based on defined criticality relationships, it identifies coverage, coupling, and differentiation patterns among load cases to establish criticality hierarchies. Finally, a novel 1DCNN architecture with specialized training strategies learns the GLCA system’s behavioral patterns, enabling accurate prediction of criticality for newly added load cases without computationally intensive reanalysis. The results demonstrate strong agreement between GLCA and high-fidelity model analyses: quantitative ranking achieves 95.98% average accuracy with complete identification of critical load cases. Predictions for new load cases yield coefficients of determination (R²) > 0.98 and 97.91% average criticality classification accuracy. Furthermore, GLCA operates 335 times more efficiently than high-fidelity finite element analysis. This approach effectively substitutes high-fidelity modeling during load development, reducing human effort and shortening aircraft design iteration cycles. Full article

(This article belongs to the Section Aerospace Actuators)

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19 pages, 7157 KB

Open AccessArticle

Fault Diagnosis Method of Micro-Motor Based on Jump Plus AM-FM Mode Decomposition and Symmetrized Dot Pattern

by Zhengyang Gu, Yufang Bai, Junsong Yu and Junli Chen

Actuators 2025, 14(8), 405; https://doi.org/10.3390/act14080405 - 13 Aug 2025

Abstract

Micro-motors are essential for power drive systems, and efficient fault diagnosis is crucial to reduce safety risks and economic losses caused by failures. However, the fault signals from micro-motors typically exhibit weak and unclear characteristics. To address this challenge, this paper proposes a [...] Read more.

Micro-motors are essential for power drive systems, and efficient fault diagnosis is crucial to reduce safety risks and economic losses caused by failures. However, the fault signals from micro-motors typically exhibit weak and unclear characteristics. To address this challenge, this paper proposes a novel fault diagnosis method that integrates jump plus AM-FM mode decomposition (JMD), symmetrized dot pattern (SDP) visualization, and an improved convolutional neural network (ICNN). Firstly, we employed the jump plus AM-FM mode decomposition technique to decompose the mixed fault signals, addressing the problem of mode mixing in traditional decomposition methods. Then, the intrinsic mode functions (IMFs) decomposed by JMD serve as the multi-channel inputs for symmetrized dot pattern, constructing a two-dimensional polar coordinate petal image. This process achieves both signal reconstruction and visual enhancement of fault features simultaneously. Finally, this paper designed an ICNN method with LeakyReLU activation function to address the vanishing gradient problem and enhance classification accuracy and training efficiency for fault diagnosis. Experimental results indicate that the proposed JMD-SDP-ICNN method outperforms traditional methods with a significantly superior fault classification accuracy of up to 99.2381%. It can offer a potential solution for the monitoring of electromechanical structures under complex conditions. Full article

(This article belongs to the Section Actuators for Manufacturing Systems)

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15 pages, 2952 KB

Open AccessArticle

Electrochemical Properties and Electromechanical Analysis of a Stacked Polyvinyl Chloride (PVC) Gel Actuator

by Kinji Asaka, Zicai Zhu and Minoru Hashimoto

Actuators 2025, 14(8), 404; https://doi.org/10.3390/act14080404 - 13 Aug 2025

Abstract

We investigated the electrochemical properties of and conducted an electromechanical analysis on a stacked polyvinyl chloride (PVC) gel actuator, comprising a PVC gel plasticized with dibutyl adipate (DBA) sandwiched between a metal mesh and a metal disk electrode. In this study, we examined [...] Read more.

We investigated the electrochemical properties of and conducted an electromechanical analysis on a stacked polyvinyl chloride (PVC) gel actuator, comprising a PVC gel plasticized with dibutyl adipate (DBA) sandwiched between a metal mesh and a metal disk electrode. In this study, we examined the electrochemical impedance, displacement, and electric current responses to square-wave voltage inputs. The linear motion of PVC gel actuators with and without ionic liquid (IL) additives was analyzed in relation to the mesh size and metal composition of the mesh electrode. The displacement increased with decreasing mesh numbers, indicating that displacement increases with increasing wire diameter and space length. The linear motion of the stacked PVC gel actuators with and without IL additives depended on the metal species of the mesh electrodes. The electrochemical impedance of the stacked PVC gel actuators under DC voltage application was analyzed with and without the IL. Based on the electromechanical and electrochemical results, a deformation model was developed to describe the linear motion of stacked PVC gel actuators in response to the applied voltage. The model attributed this motion to the deformation induced by Maxwell stress in the solvent-rich layer, successfully accounting for the experimental observations. Full article

(This article belongs to the Special Issue Actuators in 2025)

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17 pages, 3842 KB

Open AccessArticle

A Novel Kinematic Calibration Method for Industrial Robots Based on the Improved Grey Wolf Optimization Algorithm

by Bingzhang Cao, Jiuwei Yu, Yi Zhang, Peijun Liu, Yifan Zhang, Hongwei Sun, Peng Jin, Jie Lin and Lei Wang

Actuators 2025, 14(8), 403; https://doi.org/10.3390/act14080403 - 13 Aug 2025

Abstract

Due to insufficient absolute positioning accuracy, industrial robots frequently face challenges in efficiently performing drilling and riveting operations during the assembly of aircraft and other large-scale workpieces. To enhance the absolute positioning accuracy of industrial robots, this paper proposes a novel kinematic calibration [...] Read more.

Due to insufficient absolute positioning accuracy, industrial robots frequently face challenges in efficiently performing drilling and riveting operations during the assembly of aircraft and other large-scale workpieces. To enhance the absolute positioning accuracy of industrial robots, this paper proposes a novel kinematic calibration method for industrial robots based on the Improved Grey Wolf Optimization (IGWO) algorithm. Specifically, the method employs an enhanced selection and update strategy to avoid convergence stagnation and local optimum traps. The proposed method features a novel boundary search strategy, which leverages the Dimension-oriented Learning (DL) search strategy to enhance search speed and stability. Through parameter identification and calibration experiments, the effectiveness of the method was validated using an ABB IRB4600 industrial robot and a Leica laser tracker. Additionally, compared with the Levenberg–Marquardt (LM) algorithm, Particle Swarm Optimization (PSO), and Genetic Algorithm (GA), the IGWO algorithm demonstrates faster convergence and superior optimization performance. According to the calibration experimental results, by applying the IGWO algorithm, the absolute positioning accuracy of the industrial robot is ultimately improved from 1.918 mm to 0.475 mm and the absolute positioning accuracy is improved by 75.2%. Full article

(This article belongs to the Special Issue Intelligent Sensing, Control and Actuation in Networked Systems)

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28 pages, 6025 KB

Open AccessArticle

Reliable Neural Network Control for Active Vibration Suppression of Uncertain Structures

by Jinglei Gong and Xiaojun Wang

Actuators 2025, 14(8), 402; https://doi.org/10.3390/act14080402 - 13 Aug 2025

Abstract

This paper proposes a novel reliable neural network control (NNC) method for active vibration control of uncertain structures. First, reliable model predictive control (MPC) was established by introducing nonprobabilistic reliability constraints into traditional MPC. An importance sampling strategy was established to improve the [...] Read more.

This paper proposes a novel reliable neural network control (NNC) method for active vibration control of uncertain structures. First, reliable model predictive control (MPC) was established by introducing nonprobabilistic reliability constraints into traditional MPC. An importance sampling strategy was established to improve the efficiency of the entire training process to achieve sufficient accuracy. An adaptive nonprobabilistic Kalman filter was further proposed for estimating the uncertain region of system states. Compared to existing reliability-based control methods, the proposed reliable NNC ensured structural safety across broader loads. Compared with reliable MPC, reliable NNC significantly reduced the online computational load, making it suitable for vibration control of high-frequency complex structural systems. The effectiveness and superiority of the proposed reliable NNC were validated through two numerical examples and experimental verification. Full article

(This article belongs to the Section Control Systems)

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25 pages, 3078 KB

Open AccessArticle

Research on Hierarchical Composite Adaptive Sliding Mode Control for Position and Attitude of Hexarotor UAVs

by Xiaowei Han, Hai Wang, Nanmu Hui and Gaofeng Yue

Actuators 2025, 14(8), 401; https://doi.org/10.3390/act14080401 - 12 Aug 2025

Abstract

This study proposes a hierarchical composite adaptive sliding-mode control strategy to address the strong nonlinear dynamics of a hexarotor Unmanned Aerial Vehicle (UAV) and the external disturbances encountered during flight. First, within the position-control loop, a Terminal Sliding Mode Control (TSMC) is designed [...] Read more.

This study proposes a hierarchical composite adaptive sliding-mode control strategy to address the strong nonlinear dynamics of a hexarotor Unmanned Aerial Vehicle (UAV) and the external disturbances encountered during flight. First, within the position-control loop, a Terminal Sliding Mode Control (TSMC) is designed to guarantee finite-time convergence of the system states, thereby significantly improving the UAV’s rapid response to complex trajectories. Concurrently, an online Adaptive rates mechanism is introduced to estimate and compensate unknown disturbances and modeling uncertainties in real time, further enhancing disturbance rejection. In the attitude-control loop, a Super-twisting Sliding Mode Control (STSMC) method is employed, where an Adaptive rate law dynamically adjusts the sliding gain to prevent overestimation and high-frequency chattering, while ensuring fast convergence and smooth response. To comprehensively validate the feasibility and superiority of the proposed scheme, a representative helical trajectory-tracking experiment was conducted and systematically compared, via simulation, against conventional control methods. Experimental results demonstrate that the proposed approach achieves stable control within 0.15 s, with maximum position and attitude tracking errors of 0.05 m and 0.15°, respectively. Moreover, it exhibits enhanced robustness and adaptability to external disturbances and parameter uncertainties, effectively improving the motion-control performance of hexacopter UAVs in complex missions. Full article

(This article belongs to the Section Aerospace Actuators)

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