Ebook: Mechatronics and Automation Technology

In recent years, the industrial automation industry has been developing rapidly; according to statistics, the global automation equipment market is growing at a rate of more than 10% per year. Mechatronics significantly contributes to attaining advanced levels of automation and intelligent control, which are both essential for the successful implementation of automated processes. With the continued growth in the market, led by technological innovation and the released potential of emerging markets, mechatronics looks set to usher in wider prospects for development.

To promote academic exchange and cooperation in mechatronics and automation technology, and share the latest research results and cutting-edge innovations, the 3rd International Conference on Mechatronics and Automation Technology (ICMAT 2024) was held in Wuhan, China on 25 and 26 October 2024. ICMAT 2024 brought together top scholars and researchers from all over the world to share their latest research results and practical experiences in mechatronics and automation technology applications. A number of speakers were specially invited to give keynote speeches at the conference: Zheng Hong (George) Zhu, Professor at York University and General Chair of ICMAT 2024; Ching-Chih Tsai, Professor at National Chung Hsing University, Taiwan, China; Shunli Wang, academician of the Russian Academy of Natural Sciences and Professor at the Smart Energy Storage Institute, China, as well as Program Chair of ICMAT 2024; and Li Guo, Professor at Hunan University, China. Together with the other contributors, their presentations shared achievements of scientific research and innovation in a number of fields. Special seminars were also set up to discuss some of the currently hot issues in the field, providing participants with an opportunity for in-depth exchanges and the collision of ideas. A total of 176 submissions were received for the conference, of which 98 papers were ultimately selected after a rigorous process of peer-review. The papers are divided into 6 sections: Mechatronics; Mechanical Manufacturing and Material Design; Robotics and Automation; Intelligent Control and System; Electronic, Electrical and Power Engineering, Sensors and wireless Sensor Networks. Topics covered include intelligent mechatronics, mechanical engineering, 3D printing technologies, robots, automation and control applications, electrical power, energy storage, industrial manufacturing, sensors, actuators, networks, communication and other related interdisciplinary technologies.

We would like to take this opportunity to express our appreciation for the efforts of all the speakers, editors, reviewers, contributors and participants.

Jinyang Xu

Taking the aircraft cabin door drive system as the focus of this research, this paper establishes a dynamic model that incorporates the rigid-flexible coupling of the drive mechanism, as well as a control system model for the permanent magnet synchronous motor. Building on this foundation, an integrated mechatronics simulation analysis model for the cabin door drive system is developed. In accordance with the actual operational requirements of the system, the effects of various driving forms on the cabin door drive system are analyzed. The research findings indicate that all dynamic responses of the cabin door drive system exhibit fluctuations. Under various driving forms, the speed of the cabin door and the power of the motor show the most significant differences, while there is no notable difference in the deployment angle of the cabin door and the output torque of the motor. Specifically, the maximum speed of the cabin door in driving form 1 is approximately 10.1 r/min, while the maximum power of the motor is around 2469 W. This study provides theoretical guidance for the design, speed regulation, and monitoring of cabin door drive systems.

The performance of sensorless control in synchronous reluctance motors (SynRMs) can be significantly affected by the nonlinear characteristics of inductance. To resolve this challenge, a method that employs high-frequency square-wave voltage signals for estimating inductance in real-time has been introduced. Considering the substantial variation of SynRM inductance with current, a motor model is developed that incorporates inductance variation as a function of current, providing a more accurate representation of real-world conditions. Injecting high-frequency voltages in the crossed and straight axes responds to corresponding high-frequency currents. A simple calculation of the current signal yields the inductance. The effectiveness for online inductance identification of the proposed method is validated through MATLAB simulations, demonstrating computational simplicity, accurate tracking, and high precision.

Water is a fundamental need for humans, comprising 70% of the human body. Dispensers are commonly used due to their convenience and hygienic nature for storing drinking water. Visually impaired individuals often face challenges in using conventional dispensers, which can lead to injuries when retrieving water. This study aims to design an automatic dispenser to assist the visually impaired, reducing the risk of injury when using dispensers. The dispenser is designed with two microcontrollers: Atmega32 and ESP8266. The ESP8266 microcontroller has a Wi-Fi feature, enabling it to connect to the internet. The dispenser uses two ultrasonic sensors to detect objects obstructing the sensor’s beam, helping control the flow of water. The system communicates between the two microcontrollers and connects to the Telegram app via Wi-Fi, allowing for remote monitoring and control. The Arduino Uno microcontroller serves as the system’s control center.

Edge caching is employed to solve the challenge of massive data requests, ensuring the quality of user experience. However, existed edge caching algorithms often overlook issues related to user mobility, and privacy protection, non-identically and independently distributed (non-i.i.d.) characteristics of content requests among base stations. To tackle these challenges, this paper proposes Federated Reinforcement Learning Algorithm with Fair Aggregation for Edge Caching (FFA-PPO) algorithm. This paper primarily focuses on scenario of non-i.i.d. content requests in multi-base-station and multi-mobile-user network. We model this problem as a Markov Decision Process (MDP) problem and propose a federated reinforcement learning method to solve MDP problem. The goal is to minimize the content transmission latency of base stations. FFA-PPO algorithm resolves gradient conflicts by seeking the optimal gradient vector within a local ball centered at the averaged gradient which ensures model’s fairness. In conclusion, simulation results prove that the proposed FFA-PPO algorithm outperforms other baseline algorithms in terms of content transmission latency, model’s fairness.

In order to solve the problems of large-scale factory workshop, such as large number of motors, changeable working conditions of motor bearings, frequent faults and difficulties in diagnosis, a distributed motor bearing health management system based on embedded edge and cloud platform is designed. This system uses Raspberry Pi and STM32 to build a low-cost embedded edge motor condition monitoring platform, and deploys the lightweight bearing fault diagnosis algorithm in it, and then uses the Internet of things technology to connect the edge end with the remote server cloud platform to make web pages to realize motor bearing fault diagnosis and motor running status monitoring. The test results show that the system can effectively realize the health management of the motor and facilitate the maintenance and management of the motor.

Surge is a parameter that has an important impact on the performance of aircraft engines, and also the main factor that restricts the performance of engines and affects flight safety. By studying the surge principle of turbine engine and the anti-surge principle of rescue aircraft turbo-shaft engine, the anti-surge measures of each type of engine are understood. To provide some help for the improvement of engine maintenance level in the future, so as to reduce the probability of the rescue aircraft engine surge effectively, further improve the reliability of the engine, and improve the airworthiness of the rescue helicopter.

This paper presents an optimal control framework tailored for redundant robotic manipulators, aiming to devise precise joint-space trajectories while minimizing control efforts. The core contribution is the formulation of trajectory planning as a multi-objective optimization problem, tackled through a Genetic Algorithm-based Model Predictive Control strategy, followed by Gradient Descent refinement. Moreover, we develop a strategy to apply the resulted high-level design of the joint-space trajectory into a dynamic time-series control strategy that respects the physical constraints of actuators in motion, speed, acceleration and jerk. Experimental results on a simulation model underscore the framework’s efficacy, demonstrating minimal positioning errors without the need for high computational resources for the trajectory design. Moreover, dynamical analysis of the actuators signals for the low-level phase demonstrates the ability of the overall framework to be applied on a real robotic manipulator.

Given the weight and corrosion resistance limitations of traditional steel gas cylinders, this study proposes the use of lightweight, high-strength, and corrosion-resistant aluminum alloy as an alternative material. The research specifically focuses on analyzing the impact of winding technology and materials on the stress and strain of the gas cylinder at different temperatures (600°C) and pressures (from 15Mpa to 22.5Mpa), with the aim of optimizing the design and manufacturing process of the gas cylinder to meet more stringent engineering requirements. The study indicates that under high temperature (600°C) and high pressure (15Mpa) conditions, Type B gas cylinders exhibit lower average equivalent stress (573.66Mpa) and average stress intensity (589.36Mpa) compared to Types A and C. The average deformation is 0.01313m/m, slightly higher than that of Type C, but overall, Type B performs better. When the gas cylinder’s volume increases, the average equivalent stress, stress intensity, and equivalent elastic strain all decrease, albeit with relatively minor overall changes. When the temperature rises to 1000°C, the average equivalent stress reaches 927.96Mpa, reflecting the impact of temperature on material expansion and internal stress. These findings are of significant practical importance for guiding the future design and manufacturing of high-pressure gas cylinders to meet higher performance and safety requirements.

According to the requirement for the concentration gradient generator (CGG) in the chip laboratory, a dose-modulated exposure from bottom-up technique was proposed to fabricate SU-8 microstructure. The SU-8 microstructure is used for PDMS CGG. For thick SU-8 photoresist layer, during a one-time exposure, it is easy to over-expose at the top and under-expose at the bottom, which then forms a T-shaped structure. The technique in this article using dose-modulated low power multiple exposure from bottom-up. At last, the photochemical reaction channel inside SU-8 is formed, and SU-8 is fully exposed. This technique effectively suppresses forming the T-shaped structure, and also suppress photoresist liftoff. In this work, after 55 times exposure, a right angle three-level SU-8 CGG structure with a height of 45 μm was fabricated. The width of the single microchannel is 50 μm. The PDMS CGG matches the SU-8 structure. The microchannels are clear with vertical sidewalls.

As industrial technology continues to evolve, synchronous machines powered by inverters are widely implemented to provide enhanced control performance. However, the inverter-fed systems can lead to asymmetries in the three-phase voltages, generating common-mode voltage (CMV) in machines with Y-winding connections configuration. Influenced by the parasitic capacitive effects between the internal conductors of the machine, the CMV results in a potential difference between the shaft and the housing, known as the common-mode shaft voltage (CMSV). When the CMSV exceeds a certain threshold, it can cause the lubricating film of the bearings to break down. To mitigate the risk of bearing failure due to the CMSV, this paper proposes a method for extending stator length, with the advantages of simpler and more cost-effective. This paper first presents the mechanism and mathematical model of CMSV generation, followed by an analysis of potential suppression measures. Furthermore, a method of extending the stator lamination length to reduce the coupling capacitance between the stator windings and the rotor is proposed, thereby achieving suppression of shaft voltage. Finally, a three-dimensional finite element analysis (3D-FEA) software is used to analyze and evaluate the model with different degrees of extending the axial length of the stator or rotor lamination and the machine with different stator inner diameter to axial length ratios. The longer the extension of the stator lamination length, the greater the suppression capability for CMSV. For machines with a larger stator inner diameter to axial length ratio, this method exhibits a more pronounced effect on attenuating the CMSV. Conversely, extending the axial length of the rotor significantly increases the CMSV.

Renewable energies are the key to sustainable development. They are the seat of a winning energy strategy. In particular, photovoltaic energy (PV) is one of the most widespread of these energies. But this energy suffers from its intermittency due to changing meteorological conditions, hence the need to follow the maximum power point of this energy at each moment. This paper focuses on the sliding mode control command to optimize the maximum power search. Thus we spread the evolved command on sliding mode control noted super twisting control as an MPPT approach. This latter is used in hybrid with the conventional incremental conductance similar method to the conventional hybridization incremental conductance-sliding mode control. The evolved approach is tested under MATLAB/Simulink with two other methods, such as the incremental conductance and its hybridization with sliding mode control. The results show a considerable minimization of the phenomena of ripple and chattering, thus improving MPPT efficiency.

The synchronous reluctance motor (SynRM) is gaining attention in various industrial applications due to its high efficiency and rugged rotor structure. This paper presents a comparative study of the performance of SynRM when driven by sine wave and square wave signals. The analysis covers key performance metrics including efficiency, power factor, torque ripple, noise, etc. The study summarizes the advantages and disadvantages of each driving method. And the findings provide insights for selecting the appropriate driving method for SynRMs in different application scenarios, balancing performance, complexity, and cost.

In the field of high-voltage three-phase asynchronous motor manufacturing, stator punching piece, rotor punching piece is a necessary part, rotor punching piece through the stacking, casting aluminium, wear shaft, manufactured into cast aluminium rotor, cast aluminium rotor machined with a lathe and then manufactured into a rotor, made from the cast aluminium rotor into a rotor, there will be a machining allowance, the size of the machining allowance determines the efficiency of the production, in order to improve the efficiency of the production, reduce machining allowances, when manufacturing stator punches and rotor punches,special stamping dies are required to ensure that processing allowances are reduced and production efficiency is increased.

In recent years, unmanned aerial vehicle (UAV) technology has made remarkable progress in many fields, especially in the path planning of fixed-wing UAVs. In the face of complex task scenarios, fixed UAVs need to consider various scenarios, generate conforms to aircraft performance, and make autonomous decision-making to evade and standby flight routes to meet the needs of load adaptation and performance guarantee. Especially for some specific load unmanned aerial vehicles (UAVs), the flight path planning is in advance before launch, so the ground stage of route planning is the key. This paper puts forward A kind based on A* heuristic search algorithm of the optimum path planning method, through the Alpha - Beta pruning to accelerate the search process, using Douglas-Peucker curve smoking loose to reduce cost, time and space combined with spline interpolation and polynomial fitting rounds of optimization, Finally, the critical routes with the ability to evade, wait and attack are generated. The experimental results show that the algorithm achieves 4.5% optimization in the path length, and the smoothness of the curve is improved by 36.71%. It has the planning ability to hover and wait in the mission area, effectively improving the path generation’s smoothness, effectiveness, and refinement. It also reduces the route length, showing good anti-data noise and long path planning ability.

A novel 3-CRS parallel mechanism with six degrees of freedom is proposed and the metamorphic characteristics of 3-CRS parallel mechanism are studied based on cylindrical motion variable locked in the sub-chain. Firstly, the kinematic parameters of 3-CRS parallel mechanism are analyzed, and the closed equations of the kinematic variable are obtained. Secondly, the screw system of the sub-chain of 3-CRS parallel mechanism is analyzed, and the motion characteristics of 3-CRS parallel mechanism are mastered. Thirdly, the sub-chain constraint-screw system of 3-CRS parallel mechanism is studied in detail when the moving or rotating variables of cylindrical pair are locked. Finally, the metamorphic characteristics of 3-CRS parallel mechanism are discussed when the moving or rotating variables of cylindrical pair are locked. The results show that the metamorphic characteristics of 3-CRS parallel mechanism can be obtained by locking the cylindrical pair parameters.

The current posture adjustment and docking of various engine models typically rely on rigid tooling for support and locking, with the position and posture of the engine being confirmed and adjusted manually. Such docking methods often come with issues such as intense labor, low assembly efficiency, and lengthy assembly cycles. To address these problems, this paper takes the common aircraft engine as the research object and builds an automatic engine docking system. In the AMESim software, a theoretical model of Diverter-regulated cylinder position control is established. Parameters are adjusted based on different working condition parameter scenarios, and the variation curves of parameters such as pressure and flow rate over time under different working conditions are measured to analyze the actual operating status of the system. In the Simulink software, the Diverter-regulated cylinder position control system is reestablished. Sensitivity is used to analyze the Diverter-regulated cylinder unit, and the first-order sensitivity equation and the first-order sensitivity matrix are established. The values of each state variable of the system are extracted in real time using the simulation platform to obtain the sensitivity of the system to each parameter and obtain the optimal solution for each parameter, ensuring the high-precision response of each adjusting leg. The high-precision automatic mounting of the engine is achieved through numerical simulation.

In this study, a robust finite-time (FnT) sliding mode attitude and position control is proposed for the precise tracking of an underactuated quadrotor unmanned aerial vehicle (QUAV) subjected to multiple sources of uncertainties, i.e., unmodeled dynamics, external perturbations, and parameter uncertainties. The proposed flight control system is based on the nonsingular integral terminal sliding control (NITSMC) to ensure rapid tracking of the targeted 3D trajectories while reducing the steady state-errors. The performances of the control system are enhanced through the introduction of a disturbance observer (DO) that estimates unknown external disturbances and enhances the system’s robustness. Stability analysis and FnT convergence are verified using the Lyapunov stability analysis. Finally, comparative simulations under different flight conditions are performed to assess the accuracy and robustness of the suggested controller. The obtained results highlight the improved performance of the suggested approach in terms of accuracy, rapidity, and robustness against wind disturbances.

A parameter identification scheme of permanent magnet synchronous motor(PMSM) is proposed, which is easy to implement in engineering. Firstly, a set of excitation with different frequency, phase and voltage combination is applied to the measured PMSM and the response signal is collected. The stator resistance and the inductance of direct and quadrature axis are obtained by least square curve fitting, then start the motor to the set frequency, suddenly block the output, collect the generation voltage of the PMSM. The algorithm is integrated in the inverter controlled by SVPWM, and the parameters of the controlled motor can be identified without additional equipment, so as to support the implementation of speed sensorless control. The simulation shows that the identification scheme has sufficient precision to meet the need of speed sensorless control, and has guiding and reference significance for practical engineering applications.

This study successfully develops a 7-axis suspended robotic arm for an automated spraying system, considering factors such as flexible operation modes, spray area dimensions, workpiece geometry, and the degrees of freedom required for effective operation. By using SolidWorks software for verification, the endpoints of the robotic arm can reach all positions within the workspace. The design and fabrication of the arm are completed according to specifications for structural strength, load capacity, rated torque output, and rotational speed. Kinematic analyses, both forward and inverse, are applied to determine the posture and position of the 7-axis robotic arm, facilitating the planning and design of the spraying trajectory. The control system architecture utilizes a multi-axis servo control board, integrated with a manifold deformation control method for trajectory tracking. Simulations and experiments are conducted to use a car shell workpiece provided by the manufacturer. The results from the simulations of MATLAB analyses show that the maximum tracking error is less than 0.4 mm. In experiments with the robotic arm, the maximum error is less than 0.7 mm. The results of the simulation and experiment are quite close, indicating that the deformation control method effectively operates the posture and movement of the 7-axis suspended robotic arm. Therefore, the 7-axis suspended robotic arm developed in this study will be effectively utilized in the production line of the automated spraying system.

This study discusses the development of a sensorless speed control method for induction motors using an adaptive PID Controller. An approach is proposed that utilizes a disturbance observer to estimate the speed of the induction motor. Subsequently, an adaptive PID Controller is implemented to regulate speed control with real-time parameter adjustments based on the motor’s operating conditions. Experimental results show that the combination of these two methods enhances dynamic response performance, particularly in avoiding overshoot and steady-state error. By applying this technique, effective control is achieved without the need for additional sensor devices, leading to reduced costs and system complexity. This research makes an important contribution to the development of more efficient and reliable induction motor technology and opens avenues for further research in sensorless control applications.

In view of the structural contradiction between heating and wind power consumption of thermoelectric units during heating period, a thermal power cooperative dispatching support system is established. Based on platform layer, computing layer and collaboration layer, data acquisition and processing, unit regulation capacity calculation and cooperative scheduling are realized respectively. On the premise of ensuring the quality of data collection, according to the set of unit operation constraints, the system constructs a calculation model of peak regulation margin based on the operation feasible region of cogeneration units, and realizes the deep mining of the peak regulation capacity of generating units under certain heat supply. Through collaborative optimization of power load distribution in the region, the level of wind power consumption can be improved. The operation results of the system in Liaoning Provincial dispatching Center show that the thermoelectric units can not only meet the heating demand, but also maintain safe operation at a lower generation load level. Through collaborative optimization of load distribution, the overall peak regulation capacity of thermoelectric units has been increased by 14.8%, and the absorption capacity of clean energy has been greatly improved.

Surface electromyography (sEMG) directly reflects muscle activity and has been widely applied in areas such as prosthetics, rehabilitation, exoskeletons, and human-computer interaction. However, traditional sEMG modeling methods are often constrained by the complexity of data and computation time, making it difficult to meet real-time control requirements. This paper proposes a rapid modeling method based on sEMG, exploring its application in hand assistive devices and medical rehabilitation. By designing sEMG datasets, extracting transient features, and using deep learning algorithms (Vision Transformer and ConvNext), the method effectively reduces modeling time and improves classification accuracy. Experimental results demonstrate that this method is both efficient and accurate in real-time control applications, making it suitable for various real-time interactive systems.

Permanent Magnet Synchronous Motor (PMSM) is a system with multivariable, nonlinear, and strong coupling characteristics. Due to the uncertainty of model parameters and external load disturbances, traditional linear control methods often struggle to achieve effective control. Considering the significant advantages of Nonlinear Model Predictive Control (NMPC) in handling complex constraint optimization of nonlinear systems, as well as its ability to reduce computational burden and improve system robustness, Nonlinear Model Predictive Control Method with Analytical Formal Control Law (ANMPC) in this paper is used to design PMSM controller, and conducts simulation analysis on the prediction time domain and control order. The ANMPC method behaves well in speed tracking behavior, and the system has strong anti-interference ability.