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Machines
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Design and Control of Advanced Mechatronics Systems
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Design and Control of Advanced Mechatronics Systems

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: closed (28 September 2021) | Viewed by 42207

Special Issue Editors

Prof. Dr. Mingcong Deng

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan
Interests: nonlinear safety control and fault detection; real time estimation of human arm impedance; smart material actuators; micro hands; wireless power transfer systems; micro reactors
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Hongnian Yu

E-Mail Website
Guest Editor
School of Computing, Engineering and the Built Environment, Edinburgh Napier University, Edinburgh EH10 5QT, UK
Interests: robotics and intelligent control; applied artificial intelligence; data analysis; data sciences with applications in digital healthcare and manufacturing systems; applications of emerging technology, such as RFID, wireless technology, etc. into healthcare and manufacturing systems
Special Issues, Collections and Topics in MDPI journals
Dr. Changan Jiang

E-Mail Website
Guest Editor
Department of Robotics, Osaka Institute of Technology, Osaka 535-8585, Japan
Interests: robotics; smart material actuators; robust control; intelligent mechanics; mechanical systems; control engineering; system engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Research and experiments on mechatronics systems, which are a synergistic integration of mechanical engineering, electronic control, and systems concepts, have contributed significantly to the design of systems, devices, processes, and products. Effective systematic methods are still a challenging topic for the design and control of advanced mechatronics systems—especially for the potential of machine learning and optimal operation in engineering applications. This Special Issue will provide an international forum for professionals, academics, and researchers to present the latest developments from theoretical studies, computational algorithm development, and applications of advanced mechatronic systems.

This Special Issue will accept contributions describing innovative research and developments in “Design and Control of Advanced Mechatronics Systems”. The Special Issue will cover a wide range of disciplines, including mechatronic systems, robotics and advanced machines, automation and control systems, new energy systems, and manufacturing systems. It particularly welcomes those emerging methodologies and techniques which bridge theoretical studies and applications in advanced mechatronic systems. Novel quantitative engineering and science studies may be considered as well.

The proposed Special Issue particularly fits the following scopes of MDPI’s Machines journal:
  • Intelligent mechatronics, robotics, automation, and control systems
  • Control system modeling and simulation techniques and methodologies
  • Industrial automation, process control, manufacturing process and automation
  • Manufacturing systems, technologies and applications
  • AI, big data, intelligent computation, and their applications
  • Signal and image processing and pattern recognition in mechatronic systems
  • New energy systems, simulation and optimization
  • Fault diagnosis and tolerance of mechatronic systems

Prof. Dr. Mingcong Deng
Prof. Dr. Hongnian Yu
Dr. Changan Jiang
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Machines 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

  • Automation and control systems 
  • Robotics and advanced machines 
  • Machine learning 
  • Computer vision 
  • Intelligent computation 
  • Optimal operation

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

Published Papers (12 papers)

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Editorial

Jump to: Research

4 pages, 169 KiB  
Editorial
Design and Control of Advanced Mechatronics Systems
by Mingcong Deng, Hongnian Yu and Changan Jiang
Machines 2022, 10(7), 539; https://doi.org/10.3390/machines10070539 - 4 Jul 2022
Viewed by 2519
Abstract
Research and experiments on mechatronics systems, which are a synergistic integration of mechanical engineering, electronic control, and systems concepts, have contributed significantly to the design of systems, devices, processes, and products [...] Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)

Research

Jump to: Editorial

17 pages, 2189 KiB  
Article
Human Gait Data Augmentation and Trajectory Prediction for Lower-Limb Rehabilitation Robot Control Using GANs and Attention Mechanism
by Yan Wang, Zhikang Li, Xin Wang, Hongnian Yu, Wudai Liao and Damla Arifoglu
Machines 2021, 9(12), 367; https://doi.org/10.3390/machines9120367 - 18 Dec 2021
Cited by 17 | Viewed by 3979
Abstract
To date, several alterations in the gait pattern can be treated through rehabilitative approaches and robot assisted therapy (RAT). Gait data and gait trajectories are essential in specific exoskeleton control strategies. Nevertheless, the scarcity of human gait data due to the high cost [...] Read more.
To date, several alterations in the gait pattern can be treated through rehabilitative approaches and robot assisted therapy (RAT). Gait data and gait trajectories are essential in specific exoskeleton control strategies. Nevertheless, the scarcity of human gait data due to the high cost of data collection or privacy concerns can hinder the performance of controllers or models. This paper thus first creates a GANs-based (Generative Adversarial Networks) data augmentation method to generate synthetic human gait data while still retaining the dynamics of the real gait data. Then, both the real collected and the synthesized gait data are fed to our constructed two-stage attention model for gait trajectories prediction. The real human gait data are collected with the five healthy subjects recruited from an optical motion capture platform. Experimental results indicate that the created GANs-based data augmentation model can synthesize realistic-looking multi-dimensional human gait data. Also, the two-stage attention model performs better compared with the LSTM model; the attention mechanism shows a higher capacity of learning dependencies between the historical gait data to accurately predict the current values of the hip joint angles and knee joint angles in the gait trajectory. The predicted gait trajectories depending on the historical gait data can be further used for gait trajectory tracking strategies. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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23 pages, 7961 KiB  
Article
Hydrodynamic Bearing Structural Design of Blood Pump Based on Axial Passive Suspension Stability Analysis of Magnetic–Hydrodynamic Hybrid Suspension System
by Peng Shen, Yiwen Wang, Yun Chen, Pengqiang Fu, Lijie Zhou and Lijia Liu
Machines 2021, 9(11), 255; https://doi.org/10.3390/machines9110255 - 27 Oct 2021
Cited by 5 | Viewed by 2976
Abstract
Rotor suspension stability is one of the important performance indexes of a blood pump and the basis of determining whether the blood pump can be used in a clinic. Compared with the traditional magnetic suspension system, a single-winding, bearingless motor has the advantages [...] Read more.
Rotor suspension stability is one of the important performance indexes of a blood pump and the basis of determining whether the blood pump can be used in a clinic. Compared with the traditional magnetic suspension system, a single-winding, bearingless motor has the advantages of a compact structure, simple control system and low power consumption. In this pursuit, the present study aimed to envisage and design the magnetic suspension system coupled with a single-winding bearingless motor and permanent magnet bearings, establish the theoretical models of axial force and electromagnetic torque, and calculate the stiffness of the magnetic suspension system at the equilibrium point. Addressing the problem of the negative axial stiffness of the magnetic suspension system being negative, which leads to the instability of the suspension rotor, the hydrodynamic bearing structure was proposed and designed, and the critical stiffness to realize the stable suspension of the rotor was obtained based on the stability criterion of the rotor dynamics model. The optimal structural parameters of the hydrodynamic bearing are selected by integrating various factors based on the solution of the Reynolds equation and a stiffness analysis. Furthermore, the vibration experiment results proved that the blood pump rotor exhibited a good suspension stability, and the maximum offset under the impact external fluid was no more than 2 μm. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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15 pages, 14750 KiB  
Article
Design and Analysis of a Lower Limb Rehabilitation Training Component for Bedridden Stroke Patients
by Xusheng Wang, Yongfei Feng, Jiazhong Zhang, Yungui Li, Jianye Niu, Yandong Yang and Hongbo Wang
Machines 2021, 9(10), 224; https://doi.org/10.3390/machines9100224 - 30 Sep 2021
Cited by 7 | Viewed by 3714
Abstract
Carrying out the immediate rehabilitation interventional therapy will better improve the curative effect of rehabilitation therapy, after the condition of bedridden stroke patients becomes stable. A new lower limb rehabilitation training module, as a component of a synchronous rehabilitation robot for bedridden stroke [...] Read more.
Carrying out the immediate rehabilitation interventional therapy will better improve the curative effect of rehabilitation therapy, after the condition of bedridden stroke patients becomes stable. A new lower limb rehabilitation training module, as a component of a synchronous rehabilitation robot for bedridden stroke patients’ upper and lower limbs, is proposed. It can electrically adjust the body shape of patients with a different weight and height. Firstly, the innovative mechanism design of the lower limb rehabilitation training module is studied. Then, the mechanism of the lower limb rehabilitation module is simplified and the geometric relationship of the human–machine linkage mechanism is deduced. Next, the trajectory planning and dynamic modeling of the human–machine linkage mechanism are carried out. Based on the analysis of the static moment safety protection of the human–machine linkage model, the motor driving force required in the rehabilitation process is calculated to achieve the purpose of rationalizing the rehabilitation movement of the patient’s lower limb. To reconstruct the patient’s motor functions, an active training control strategy based on the sandy soil model is proposed. Finally, the experimental platform of the proposed robot is constructed, and the preliminary physical experiment proves the feasibility of the lower limb rehabilitation component. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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12 pages, 3119 KiB  
Communication
Continuous Control of an Underground Loader Using Deep Reinforcement Learning
by Sofi Backman, Daniel Lindmark, Kenneth Bodin, Martin Servin, Joakim Mörk and Håkan Löfgren
Machines 2021, 9(10), 216; https://doi.org/10.3390/machines9100216 - 27 Sep 2021
Cited by 24 | Viewed by 4470
Abstract
The reinforcement learning control of an underground loader was investigated in a simulated environment by using a multi-agent deep neural network approach. At the start of each loading cycle, one agent selects the dig position from a depth camera image of a pile [...] Read more.
The reinforcement learning control of an underground loader was investigated in a simulated environment by using a multi-agent deep neural network approach. At the start of each loading cycle, one agent selects the dig position from a depth camera image of a pile of fragmented rock. A second agent is responsible for continuous control of the vehicle, with the goal of filling the bucket at the selected loading point while avoiding collisions, getting stuck, or losing ground traction. This relies on motion and force sensors, as well as on a camera and lidar. Using a soft actor–critic algorithm, the agents learn policies for efficient bucket filling over many subsequent loading cycles, with a clear ability to adapt to the changing environment. The best results—on average, 75% of the max capacity—were obtained when including a penalty for energy usage in the reward. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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18 pages, 2682 KiB  
Article
A Performance-Driven MPC Algorithm for Underactuated Bridge Cranes
by Hanqiu Bao, Qi Kang, Jing An, Xianghua Ma and Mengchu Zhou
Machines 2021, 9(8), 177; https://doi.org/10.3390/machines9080177 - 20 Aug 2021
Cited by 15 | Viewed by 3206
Abstract
A crane system often works in a complex environment. It is difficult to model or learn its true dynamics by traditional system identification approaches. If a dynamics model is created by minimizing its prediction error, its use tends to introduce inaccuracies and thus [...] Read more.
A crane system often works in a complex environment. It is difficult to model or learn its true dynamics by traditional system identification approaches. If a dynamics model is created by minimizing its prediction error, its use tends to introduce inaccuracies and thus lead to suboptimal performance. Is it possible to learn the dynamics model of a crane that can achieve the best performance, instead of learning its true dynamics? This work answers the question by presenting a performance-driven model predictive control (P-MPC) algorithm for a two-dimensional underactuated bridge crane. In the proposed dual-layer control architecture, an inner-loop controller uses a proportional–integral–derivative controller to achieve anti-sway rapidly. An outer-loop controller uses MPC to ensure accurate trolley positioning under control constraints. Compared with classical MPC, this work proposes a data-driven method for plant modeling and controller parameter updating. By considering the control target at the learning stage, the method can avoid adjusting the controller to deal with uncertainty. We use Bayesian optimization in an active learning framework where a locally linear dynamics model is learned with the intent of maximizing control performance and then used in conjunction with optimal control schemes to efficiently design a controller for a given task. The model is updated directly based on the performance observed in experiments on the physical system in an iterative manner till a desired performance is achieved. The controller parameters and prediction models of the best closed-loop performance can be found through continuous experiments and iterative optimization. Simulation and experiment results show that we can explicitly find the dynamics model that produces the best performance for an actual system, and the method can quickly suppress swing and realize accurate trolley positioning. The results verified its effectiveness, feasibility, and superior performance on comparing it with state-of-the-art methods. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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24 pages, 940 KiB  
Article
A Unified Framework for the H∞ Mixed-Sensitivity Design of Fixed Structure Controllers through Putinar Positivstellensatz
by Valentino Razza and Abdul Salam
Machines 2021, 9(8), 176; https://doi.org/10.3390/machines9080176 - 20 Aug 2021
Cited by 1 | Viewed by 2518
Abstract
In this paper, we present a novel technique to design fixed structure controllers, for both continuous-time and discrete-time systems, through an H∞ mixed sensitivity approach. We first define the feasible controller parameter set, which is the set of the controller parameters that [...] Read more.
In this paper, we present a novel technique to design fixed structure controllers, for both continuous-time and discrete-time systems, through an H∞ mixed sensitivity approach. We first define the feasible controller parameter set, which is the set of the controller parameters that guarantee robust stability of the closed-loop system and the achievement of the nominal performance requirements. Then, thanks to Putinar positivstellensatz, we compute a convex relaxation of the original feasible controller parameter set and we formulate the original H∞ controller design problem as the non-emptiness test of a set defined by sum-of-squares polynomials. Two numerical simulations and one experimental example show the effectiveness of the proposed approach. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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17 pages, 1419 KiB  
Article
Operator-Based Nonlinear Control of Calorimetric System Actuated by Peltier Device
by Ryo Chikaraishi and Mingcong Deng
Machines 2021, 9(8), 174; https://doi.org/10.3390/machines9080174 - 18 Aug 2021
Cited by 3 | Viewed by 2135
Abstract
Recently, the development of SiC and GaN high-performance semiconductor devices has led to higher efficiency in power conversion equipment. In order to perform thermal design of power conversion equipment and evaluation of the equipment, it is necessary to measure the power loss of [...] Read more.
Recently, the development of SiC and GaN high-performance semiconductor devices has led to higher efficiency in power conversion equipment. In order to perform thermal design of power conversion equipment and evaluation of the equipment, it is necessary to measure the power loss of the equipment with high accuracy. In a previous study, a system to measure the power loss from the amount of heat emitted from power conversion devices using a Peltier device was proposed. In this study, aiming to improve the measurement accuracy, the temperature dependence of the thermal conductivity of a Peltier device, which was treated as a constant value in the previous study, was considered. The control system considering the temperature dependence of the thermal conductivity was designed based on operator theory, which is a nonlinear control theory. The simulation and experimental results show that the measurement accuracy was improved when the power loss was 10 W and 15 W compared to the case without considering the temperature dependence. In addition, the measurement time was reduced by about 100 s by considering the temperature dependence. The effectiveness of the proposed system was shown when the power loss was 10 W and 15 W. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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22 pages, 11441 KiB  
Article
A Redundantly Actuated Chewing Robot Based on Human Musculoskeletal Biomechanics: Differential Kinematics, Stiffness Analysis, Driving Force Optimization and Experiment
by Haiying Wen, Ming Cong, Zhisheng Zhang, Guifei Wang and Yan Zhuang
Machines 2021, 9(8), 171; https://doi.org/10.3390/machines9080171 - 18 Aug 2021
Cited by 9 | Viewed by 2941
Abstract
Human masticatory system exhibits optimal stiffness, energy efficiency and chewing forces needed for the food breakdown due to its unique musculoskeletal actuation redundancy. We have proposed a 6PUS-2HKP (6 prismatic-universal-spherical chains, 2 higher kinematic pairs) redundantly actuated parallel robot (RAPR) based on its [...] Read more.
Human masticatory system exhibits optimal stiffness, energy efficiency and chewing forces needed for the food breakdown due to its unique musculoskeletal actuation redundancy. We have proposed a 6PUS-2HKP (6 prismatic-universal-spherical chains, 2 higher kinematic pairs) redundantly actuated parallel robot (RAPR) based on its musculoskeletal biomechanics. This paper studies the stiffness and optimization of driving force of the bio-inspired redundantly actuated chewing robot. To understand the effect of the point-contact HKP acting on the RAPR performance, the stiffness of the RAPR is estimated based on the derived dimensionally homogeneous Jacobian matrix. In analyzing the influence of the HKP on robot dynamics, the driving forces of six prismatic joints are optimized by adopting the pseudo-inverse optimization method. Numerical results show that the 6PUS-2HKP RAPR has better stiffness performance and more homogenous driving power than its non-redundant 6-PUS counterpart, verifying the benefits that the point-contact HKP brings to the RAPR. Experiments are carried out to measure the temporomandibular joint (TMJ) force and the occlusal force that the robot can generate. The relationship between these two forces in a typical chewing movement is studied. The simulation and experimental results reveal that the existence of TMJs in human masticatory system can provide more homogenous and more efficient chewing force transmission. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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17 pages, 3330 KiB  
Article
Adaptive Data-Driven Control for Linear Time Varying Systems
by Talal Abdalla
Machines 2021, 9(8), 167; https://doi.org/10.3390/machines9080167 - 13 Aug 2021
Cited by 2 | Viewed by 3373
Abstract
In this paper, we propose an adaptive data-driven control approach for linear time varying systems, affected by bounded measurement noise. The plant to be controlled is assumed to be unknown, and no information in regard to its time varying behaviour is exploited. First, [...] Read more.
In this paper, we propose an adaptive data-driven control approach for linear time varying systems, affected by bounded measurement noise. The plant to be controlled is assumed to be unknown, and no information in regard to its time varying behaviour is exploited. First, using set-membership identification techniques, we formulate the controller design problem through a model-matching scheme, i.e., designing a controller such that the closed-loop behaviour matches that of a given reference model. The problem is then reformulated as to derive a controller that corresponds to the minimum variation bounding its parameters. Finally, a convex relaxation approach is proposed to solve the formulated controller design problem by means of linear programming. The effectiveness of the proposed scheme is demonstrated by means of two simulation examples. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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19 pages, 11442 KiB  
Article
Adaptive Direct Teaching Control with Variable Load of the Lower Limb Rehabilitation Robot (LLR-II)
by Xincheng Wang, Hongbo Wang, Xinyu Hu, Yu Tian, Musong Lin, Hao Yan, Jianye Niu and Li Sun
Machines 2021, 9(8), 142; https://doi.org/10.3390/machines9080142 - 27 Jul 2021
Cited by 6 | Viewed by 3041
Abstract
Most lower limb rehabilitation robots use fixed training trajectories and lack participation of physiotherapists. In addition, there is a lack of attention on combining direct teaching function with rehabilitation robots, which enables physiotherapists to plan trajectories directly. In this paper, an adaptive direct [...] Read more.
Most lower limb rehabilitation robots use fixed training trajectories and lack participation of physiotherapists. In addition, there is a lack of attention on combining direct teaching function with rehabilitation robots, which enables physiotherapists to plan trajectories directly. In this paper, an adaptive direct teaching function with variable load that can be applied to the sitting/lying lower limb rehabilitation robot-II (LLR-II) is proposed. First, the structural design and electrical system of LLR-II are introduced. The dynamic equation of LLR-II considering joint flexibility is derived and analyzed. Then, the impact of joint flexibility on LLR-II is reduced by introducing the intermediate input variables. Based on this, the control law of the dragging teaching stage and the replay stage in the direct teaching function with variable load is designed and the adaptive control strategy eliminates the influence of different patients. In addition, the control law is simulated and verified. Finally, some preliminary experiments of the adaptive direct teaching function with variable load on LLR-II are carried out, and the results showed that the control law has good performance, which lays the foundation for future work. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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19 pages, 47974 KiB  
Article
Mechanical Design and Analysis of the End-Effector Finger Rehabilitation Robot (EFRR) for Stroke Patients
by Yu Tian, Hongbo Wang, Baoshan Niu, Yongshun Zhang, Jiazheng Du, Jianye Niu and Li Sun
Machines 2021, 9(6), 110; https://doi.org/10.3390/machines9060110 - 26 May 2021
Cited by 9 | Viewed by 4644
Abstract
Most existing finger rehabilitation robots are structurally complex and cannot be adapted to multiple work conditions, such as clinical and home. In addition, there is a lack of attention to active adduction/abduction (A/A) movement, which prevents stroke patients from opening the joint in [...] Read more.
Most existing finger rehabilitation robots are structurally complex and cannot be adapted to multiple work conditions, such as clinical and home. In addition, there is a lack of attention to active adduction/abduction (A/A) movement, which prevents stroke patients from opening the joint in time and affects the rehabilitation process. In this paper, an end-effector finger rehabilitation robot (EFRR) with active A/A motion that can be applied to a variety of applications is proposed. First, the natural movement curve of the finger is analyzed, which is the basis of the mechanism design. Based on the working principle of the cam mechanism, the flexion/extension (F/E) movement module is designed and the details used to ensure the safety and reliability of the device are introduced. Then, a novel A/A movement module is proposed, using the components that can easily individualized design to achieve active A/A motion only by one single motor, which makes up for the shortcomings of the existing devices. As for the control system, a fuzzy proportional-derivative (PD) adaptive impedance control strategy based on the position information is proposed, which can make the device more compliant, avoid secondary injuries caused by excessive muscle tension, and protect the fingers effectively. Finally, some preliminary experiments of the prototype are reported, and the results shows that the EFRR has good performance, which lays the foundation for future work. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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