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Actuators
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Intelligent and Precision Control for Mechatronic/Electro-Hydraulic Systems—Second Edition
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Intelligent and Precision Control for Mechatronic/Electro-Hydraulic Systems—Second Edition

A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Control Systems".

Deadline for manuscript submissions: 30 October 2026 | Viewed by 3546

Special Issue Editors

Dr. Bobo Helian

E-Mail Website
Guest Editor
Institute of Mobile Machines, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
Interests: advanced controls of mechatronic and electro-hydraulic systems; motion control; constrained control; nonlinear adaptive robust control; machine learning; pump control; independent metering control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zheng Chen

E-Mail Website
Guest Editor
The State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
Interests: advanced control of robotic and mechatronic systems; nonlinear adaptive robust control; motion control; trajectory planning; telerobotics; hydraulic system; precision mechatronic system; soft actuator and robot; mobile manipulator; underwater robot; exoskeleton
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of the previous Special Issue “Intelligent and Precision Control for Mechatronic/Electro-Hydraulic Systems” (https://www.mdpi.com/journal/actuators/special_issues/83519I456E), we are pleased to announce the next in the series, entitled “Intelligent and Precision Control for Mechatronic/Electro-Hydraulic Systems—Second Edition”.

Precision is a core requirement of industrial machines, including mechatronic and electro-hydraulic systems. Advanced control techniques are extensively utilized for high-performance operations in the fields of manufacturing, mobile machines, industrial robots, etc. In addition, control difficulties that challenge the precision of control are prevalent in many mechatronic and electro-hydraulic systems. These control difficulties can be summarized as dynamic non-linearities, parametric uncertainties, constraints, time-varying working conditions, unknown workloads, disturbances, friction, vibration, etc. To overcome these control difficulties and enhance the accuracy of control, intelligent and precision control strategies can be employed, including non-linear model-based control and machine learning. Therefore, this Special Issue aims to provide an opportunity for international researchers to present recent research regarding intelligent and precision control for mechatronic/electro-hydraulic systems. The scope of this Special Issue includes, but is not limited to, the following topics：

  • Control of mechatronic systems;
  • Control of electro-hydraulic systems;
  • Intelligent control;
  • Data-driven modelling, diagnosis, optimization, and control;
  • Machine learning;
  • model-based non-linear control;
  • precision motion control;
  • modelling and identification;
  • adaptive robust control;
  • robotic control.

Dr. Bobo Helian
Prof. Dr. Zheng Chen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Actuators is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • control
  • mechatronics
  • electro-hydraulic systems
  • intelligent control
  • machine learning
  • motion control
  • non-linear control

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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (5 papers)

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Research

24 pages, 1967 KB  
Article
Command-Filtered Adaptive Prescribed-Time Tracking Control with Application to Output-Constrained Hydraulic Servo Systems
by Pengfei Li, Jianyong Yao and Xiaowei Yang
Actuators 2026, 15(5), 238; https://doi.org/10.3390/act15050238 - 28 Apr 2026
Abstract
In this paper, a command filter-based adaptive prescribed-time control method is proposed for hydraulic servo systems subject to time-varying parameters, external disturbances and output constraints. Firstly, a state-based nonlinear transformation function is introduced to convert the output-constrained problem into a boundedness problem. Then, [...] Read more.
In this paper, a command filter-based adaptive prescribed-time control method is proposed for hydraulic servo systems subject to time-varying parameters, external disturbances and output constraints. Firstly, a state-based nonlinear transformation function is introduced to convert the output-constrained problem into a boundedness problem. Then, an auxiliary system is constructed to compensate for command filtering errors. Subsequently, to handle the uncertainties from time-varying parameters and external disturbances, a smooth nonlinear term featuring an updated gain and incorporating a prescribed-time function is designed. Based on the transformed system, a novel control framework integrating command filtering, adaptive control, and the prescribed-time function is developed. Consequently, the complexity explosion is avoided, and the system output is guaranteed to converge to a small bounded interval near zero while strictly satisfying the output constraints. Moreover, this prescribed convergence time can be independently set by the designer. Furthermore, both the transient convergence performance within the prescribed time and the bounded convergence performance afterward are guaranteed by Lyapunov stability analysis. Finally, the effectiveness of the proposed method is verified by simulation results. Full article
(This article belongs to the Special Issue Intelligent and Precision Control for Mechatronic/Electro-Hydraulic Systems—Second Edition)
30 pages, 40596 KB  
Article
Three-Vector-Based Model Predictive Direct Speed Control Strategy for Enhanced Target Tracking in Risley Prism Systems
by Hao Lu, Bo Liu, Jianwen Guo, Yuqi Shan, Hao Yi, Yun Jiang, Lan Luo, Feifan He, Taibei Liu, Zixun Wang and Yongqi Yang
Actuators 2026, 15(4), 213; https://doi.org/10.3390/act15040213 - 11 Apr 2026
Viewed by 399
Abstract
When the Risley prism pair is used for target tracking, the nonlinear relationship between beam deflection and prism rotation makes tracking performance highly dependent on precise and stable motor control over a wide speed range. Although the brushless DC motor serves as the [...] Read more.
When the Risley prism pair is used for target tracking, the nonlinear relationship between beam deflection and prism rotation makes tracking performance highly dependent on precise and stable motor control over a wide speed range. Although the brushless DC motor serves as the preferred drive source, its inherent commutation torque ripples directly induce beam pointing jitter, severely degrading overall tracking accuracy and stability. To address these issues, this paper proposes a three-vector-based model predictive direct speed control method. This approach establishes a direct speed-to-torque control channel by generating reference active power through dynamic equations, eliminating the need for fitting a constant flux linkage and parameter tuning. Simultaneously, combined with three-vector optimization and seven-segment modulation strategies, it achieves a dynamic balance between high-frequency, instantaneous electromagnetic power fine-tuning and inherent mechanical inertia of the rotor. Simulation results demonstrate that the proposed method exhibits superior speed stability compared to the conventional double-vector-based model predictive power control method and maintains high-precision dynamic tracking over a wide speed range. Ultimately, it leads to an average reduction of over 60% in the time-weighted absolute tracking error integral under various target trajectories, providing an effective solution for drive control of target tracking in Risley prism systems. Full article
(This article belongs to the Special Issue Intelligent and Precision Control for Mechatronic/Electro-Hydraulic Systems—Second Edition)
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20 pages, 4228 KB  
Article
Design and Application of an Automated Microinjection System Combining Deep Learning Vision Positioning and Neural Network Sliding Mode Motion Control
by Zhihao Deng, Yifan Xu and Shengzheng Kang
Actuators 2026, 15(4), 208; https://doi.org/10.3390/act15040208 - 5 Apr 2026
Viewed by 321
Abstract
Microinjection is one of the most established and effective techniques for introducing foreign substances into cells. However, issues such as cumbersome procedures, low success rates, and poor repeatability in manual cell microinjection have seriously restricted its practical applications in biomedical research and engineering. [...] Read more.
Microinjection is one of the most established and effective techniques for introducing foreign substances into cells. However, issues such as cumbersome procedures, low success rates, and poor repeatability in manual cell microinjection have seriously restricted its practical applications in biomedical research and engineering. Responding to such problems, this paper designs an automated microinjection system that combines deep learning visual positioning and adaptive neural network sliding-mode motion control. The machine vision solution based on the deep learning YOLOv8 target detection algorithm is utilized by the system to provide positional prerequisites for automated microinjection. Then, stable and fast puncture is completed by controlling the end effector (composed of a piezoelectric actuator and a displacement amplification mechanism). Since the piezoelectric actuator has strong nonlinearity, the motion control of the end effector adopts the control strategy combining sliding mode variable structure and adaptive neural networks to meet the requirements of precise displacement output of microinjection. At the same time, a host computer control system is developed to integrate hardware equipment, visual positioning algorithms and motion control algorithms to achieve corresponding automated microinjection tasks. Finally, the effectiveness of the designed automated microinjection system is successfully verified on zebrafish embryos. Full article
(This article belongs to the Special Issue Intelligent and Precision Control for Mechatronic/Electro-Hydraulic Systems—Second Edition)
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24 pages, 1435 KB  
Article
Robust Sliding Mode Motion Control for an Integrated Hydromechatronic Actuator
by Dom Wilson, Andrew Plummer and Ioannis Georgilas
Actuators 2025, 14(9), 435; https://doi.org/10.3390/act14090435 - 3 Sep 2025
Viewed by 820
Abstract
Electro-hydraulic servoactuators have great potential in mobile robotics due to their robustness, high bandwidth and power density, but compared with electromechanical actuators, they can be inefficient and more difficult to integrate into systems. The Integrated Smart Actuator (ISA) developed by Moog Controls Ltd. [...] Read more.
Electro-hydraulic servoactuators have great potential in mobile robotics due to their robustness, high bandwidth and power density, but compared with electromechanical actuators, they can be inefficient and more difficult to integrate into systems. The Integrated Smart Actuator (ISA) developed by Moog Controls Ltd. is a hydromechatronic device that aims to address these issues by combining a novel efficient servovalve, cylinder, sensors and control electronics into a single component. The aim of this work was to develop a robust motion control algorithm that can make integration of the ISA into a robotic system straightforward by requiring minimal controller set-up despite variations in the load characteristics. The proposed controller is a sliding mode controller with a varying boundary layer that contains two robustness parameters and a single bandwidth parameter that defines the response. The controller outperforms a conventional high-performance linear controller in terms of tracking performance and its robustness to variations in the load mass and fluid bulk modulus. The response when the system was subject to some unachievable demand trajectories, such as large step demands, was found to be poor, and an online velocity, acceleration and jerk limited trajectory filter was demonstrated to rectify this issue. The successful implementation of a robust motion controller enables this highly novel integrated actuator to live up to its ‘smart’ epithet. Full article
(This article belongs to the Special Issue Intelligent and Precision Control for Mechatronic/Electro-Hydraulic Systems—Second Edition)
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20 pages, 3835 KB  
Article
Fuzzy PD-Based Control for Excavator Boom Stabilization Using Work Port Pressure Feedback
by Joseph T. Jose, Gyan Wrat, Santosh Kr. Mishra, Prabhat Ranjan and Jayanta Das
Actuators 2025, 14(7), 336; https://doi.org/10.3390/act14070336 - 4 Jul 2025
Cited by 4 | Viewed by 1067
Abstract
Hydraulic excavators operate in harsh environments where direct measurement of actuator chamber pressures and boom displacement is often unreliable or infeasible. This study presents a novel control strategy that estimates actuator chamber pressures from work port pressures using differential equations, eliminating the need [...] Read more.
Hydraulic excavators operate in harsh environments where direct measurement of actuator chamber pressures and boom displacement is often unreliable or infeasible. This study presents a novel control strategy that estimates actuator chamber pressures from work port pressures using differential equations, eliminating the need for direct pressure or position sensors. A fuzzy logic-based proportional–derivative (PD) controller is developed to mitigate boom oscillations, particularly under high-inertia load conditions and variable operator inputs. The controller dynamically adjusts gains through fuzzy logic-based gain scheduling, enhancing adaptability across a wide range of operating conditions. The proposed method addresses the limitations of classical PID controllers, which struggle with the nonlinearities, parameter uncertainties, and instability introduced by counterbalance valves and pressure-compensated proportional valves. Experimental data is used to design fuzzy rules and membership functions, ensuring robust performance. Simulation and full-scale experimental validation demonstrate that the fuzzy PD controller significantly reduces pressure overshoot (by 23% during extension and 32% during retraction) and decreases settling time (by 31.23% and 28%, respectively) compared to conventional systems. Frequency-domain stability analysis confirms exponential stability and improved damping characteristics. The proposed control scheme enhances system reliability and safety, making it ideal for excavators operating in remote or rugged terrains where conventional sensor-based systems may fail. This approach is generalizable and does not require modifications to the existing hydraulic circuit, offering a practical and scalable solution for modern hydraulic machinery. Full article
(This article belongs to the Special Issue Intelligent and Precision Control for Mechatronic/Electro-Hydraulic Systems—Second Edition)
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