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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 33286

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Prof. Dr. Syuan-Yi Chen

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Department of Electrical Engineering, National Taiwan Normal University, Taipei, Taiwan
Interests: intelligent control; artificial intelligence; mechatronics; vehicle power management and control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Mechatronics is an engineering discipline integrating the fields of mechanics, electronics, control, and computer science. Many modern systems and products such as robots, manipulators, autonomous vehicles, electronic instruments, manufacturing equipment, and energy systems are designed and constructed by using mechatronic systems. The main characteristic of these systems is the progressively tighter coupling of mechanisms and an increasing number of electrical or electronic components with software. The arrangements of these components and software ensure their functions, specifically in terms of their reliability, stability, and performance. From the point of view of dynamics, mechatronic systems can be characterized by model uncertainties, high nonlinearities, complicated coupling, and stringent performance requirements, among others. To deal with the abovementioned facts, strong research activity is still ongoing that aims to design efficient controllers that can guarantee high performance control despite the presence of system uncertainties and external disturbances. Among the various control strategies, intelligent control (IC) methods with artificial intelligence have been widely studied and developed for mechatronic systems in terms of direct control, parameter optimization, system identification, uncertainty estimation, and compensation. With the help of IC methods, it is possible to achieve better accuracy, robustness, reliability, and implementation simplicity. In addition, the learning algorithms can adapt the control parameters to ensure stability and efficiency for mechatronic systems in diverse applications under adverse conditions.

Hence, the objective of this Special Issue of the Applied Sciences Journal is to provide a forum for the presentation of new and recent developments in IC methods as applied to mechatronics systems. This Special Issue will consider high-quality research and review papers that deal with theoretical and application aspects of IC methods in mechatronic systems. Specific topics of interest for this Special Issue include but are not limited to the following or related topics:

Mechanical and mechatronic systems;
Robotics and automation systems;
Industry and manufacturing applications;
Transportation and energy systems;
Intelligent systems design and control;
Neural- and fuzzy-based control systems;
Machine learning in control applications;
Knowledge-based control systems;
Information-based models for control;
Data-driven control and applications;
Artificial intelligence and soft computing;
Evolutionary, echanism-based control;
Biologically inspired algorithms in control;
Hierarchical intelligent control systems;
Hybrid learning and control techniques;
Reinforcement learning for control;
Adaptive signal processing and control;
Observation and approximation techniques;
Uncertainty estimation and compensation;
Systems modelling and simulation;
Intelligent surveillance, fault detection, and diagnosis;
Real-time and hardware-in-the-loop simulation.

Prof. Dr. Syuan-Yi Chen
Guest Editor

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Published Papers (9 papers)

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Research

19 pages, 1060 KiB

Open AccessArticle

End-to-End Deep Reinforcement Learning for Decentralized Task Allocation and Navigation for a Multi-Robot System

by Ahmed Elfakharany and Zool Hilmi Ismail

Appl. Sci. 2021, 11(7), 2895; https://doi.org/10.3390/app11072895 - 24 Mar 2021

Cited by 11 | Viewed by 3383

Abstract

In this paper, we present a novel deep reinforcement learning (DRL) based method that is used to perform multi-robot task allocation (MRTA) and navigation in an end-to-end fashion. The policy operates in a decentralized manner mapping raw sensor measurements to the robot’s steering [...] Read more.

T A I

), which measures the performance of a method that performs MRTA and navigation from end-to-end in performing MRTA. The policy was trained on a simulated gazebo environment. The centralized learning and decentralized execution paradigm was used for training the policy. The policy was evaluated quantitatively and visually. The simulation results showed the effectiveness of the proposed method deployed on multiple Turtlebot3 robots. Full article

(This article belongs to the Special Issue Applications of Intelligent Control Methods in Mechatronic Systems)

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17 pages, 5006 KiB

Open AccessArticle

Robust Optimal Tracking Control of a Full-Bridge DC-AC Converter

by En-Chih Chang, Chun-An Cheng and Rong-Ching Wu

Appl. Sci. 2021, 11(3), 1211; https://doi.org/10.3390/app11031211 - 28 Jan 2021

Cited by 4 | Viewed by 2604

Abstract

This paper develops a full-bridge DC-AC converter, which uses a robust optimal tracking control strategy to procure a high-quality sine output waveshape even in the presence of unpredictable intermissions. The proposed strategy brings out the advantages of non-singular fast convergent terminal attractor (NFCTA) and chaos particle swarm optimization (CPSO). Compared with a typical TA, the NFCTA affords fast convergence within a limited time to the steady-state situation, and keeps away from the possibility of singularity through its sliding surface design. It is worth noting that once the NFCTA-controlled DC-AC converter encounters drastic changes in internal parameters or the influence of external non-linear loads, the trembling with low-control precision will occur and the aggravation of transient and steady-state performance yields. Although the traditional PSO algorithm has the characteristics of simple implementation and fast convergence, the search process lacks diversity and converges prematurely. So, it is impossible to deviate from the local extreme value, resulting in poor solution quality or search stagnation. Thereby, an improved version of traditional PSO called CPSO is used to discover global optimal NFCTA parameters, which can preclude precocious convergence to local solutions, mitigating the tremor as well as enhancing DC-AC converter performance. By using the proposed stable closed-loop full-bridge DC-AC converter with a hybrid strategy integrating NFCTA and CPSO, low total harmonic distortion (THD) output-voltage and fast dynamic load response are generated under nonlinear rectifier-type load situations and during sudden load changes, respectively. Simulation results are done by the Matlab/Simulink environment, and experimental results of a digital signal processor (DSP) controlled full-bridge DC-AC converter prototype confirm the usefulness of the proposed strategy. Full article

(This article belongs to the Special Issue Applications of Intelligent Control Methods in Mechatronic Systems)

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22 pages, 3617 KiB

Open AccessArticle

High Performance of an Adaptive Sliding Mode Controller under Varying Loads for Lifting-Type Autonomous Grounded Robot

by Van Ngoc Son Huynh, Ha Quang Thinh Ngo, Thanh Phuong Nguyen and Hung Nguyen

Appl. Sci. 2020, 10(17), 5858; https://doi.org/10.3390/app10175858 - 24 Aug 2020

Cited by 6 | Viewed by 1884

Abstract

To work in shared space with humans, autonomous systems must carry unknown loads in predefined missions. With the conventional control scheme, the grounded robot would suffer unstable motion and imprecise tracking performance. To overcome these challenges, in this paper, a novel controller using an adaptive sliding mode for autonomous grounded robots (AGR) is proposed. This control strategy takes into consideration uncertain characteristics, varying loads, and external disturbances. To analyze the tracking performance precisely, the overall error of motion system is decoupled into two subsystems where the second-order system is related to the angular tracking error and the third-order system is associated with the linear one. Initially, the dynamics model of the grounded robot is established containing different elements of nonlinear forces in order to address the technical problems. Then, the system state equation of the autonomous system is mentioned to indicate the theoretical characteristics. Based on the proposed controller, the stability of the system is validated by the Lyapunov theorem. From the results of numerical tests, three practical situations consisting of separately linear and circular trajectories with varying loads and an S-curve trajectory of a working map are suggested. The tracking performance validates that the proposed control scheme is, in various scenarios, robust, effective, and feasible. From these superior outcomes, it can be determined obviously the property of our works in accommodating the variations of cargo from applications in distribution centers, material transportation, or handling equipment. Full article

(This article belongs to the Special Issue Applications of Intelligent Control Methods in Mechatronic Systems)

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17 pages, 4254 KiB

Open AccessArticle

Optimal Fuzzy Impedance Control for a Robot Gripper Using Gradient Descent Iterative Learning Control in Fuzzy Rule Base Design

by Ba-Phuc Huynh and Yong-Lin Kuo

Appl. Sci. 2020, 10(11), 3821; https://doi.org/10.3390/app10113821 - 30 May 2020

Cited by 7 | Viewed by 4946

Abstract

This paper proposes a novel control approach for a robot gripper in which the impedance control, fuzzy logic control, and iterative learning control are combined in the same control schema. The impedance control is used to keep the gripping force at the desired value. The fuzzy impedance controller is designed to estimate the best impedance parameters in real time when gripping unknown objects. The iterative learning control process is employed to optimize the sample dataset for designing the rule base to enhance the effectiveness of the fuzzy impedance controller. Besides, the real-time gripping force estimator is designed to keep an unknown object from sliding down when picking it up. The simulation and experiment are implemented to verify the proposed method. The comparison with another control method is also made by repeating the experiments under equivalent conditions. The results show the feasibility and superiority of the proposed method. Full article

(This article belongs to the Special Issue Applications of Intelligent Control Methods in Mechatronic Systems)

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21 pages, 11028 KiB

Open AccessArticle

Development of A Linear Delta Robot with Three Horizontal-Axial Pneumatic Actuators for 3-DOF Trajectory Tracking

by I-Hsum Li, Hsin-Han Chiang and Lian-Wang Lee

Appl. Sci. 2020, 10(10), 3526; https://doi.org/10.3390/app10103526 - 20 May 2020

Cited by 12 | Viewed by 5366

Abstract

This paper focuses on developing a pneumatic-driven and horizontal-structure linear delta robot (PH-LDR) and increasing its trajectory tracking performance on the three-degrees-of-freedom (3-DOF) space. With the investigation of inverse and forward kinematics, the parallel mechanism of PH-LDR is designed by using three high-power and low-cost rod-less pneumatic actuators (PAs) to track 3-DOF motion, and this has a horizontal structure to enlarge the workspace. Since the PH-LDR features nonlinear coupling among its three axes and is disturbed by the three high-nonlinear rod-less PAs, the tracking control performance is significantly decreased, subject to uncertain nonlinearity and parametric uncertainty. Therefore, a fuzzy-PID controller is used to achieve highly accurate 3-DOF trajectory tracking, and furthermore, this study exploits neural networks (NNs) to pre-compensate the impacts arising from the compressibility of air and temperature change. The control system for the PH-LDR also features an embedded controller that allows real-time control. Experimental demonstration verifies the developed PH-LDR with the proposed controller, and the dynamic tracking accuracy in 3-DOF trajectory can be achieved. Full article

(This article belongs to the Special Issue Applications of Intelligent Control Methods in Mechatronic Systems)

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25 pages, 2409 KiB

Open AccessArticle

Optimal Design of Adaptive Robust Control for the Delta Robot with Uncertainty: Fuzzy Set-Based Approach

by Linlin Wu, Ruiying Zhao, Yuyu Li and Ye-Hwa Chen

Appl. Sci. 2020, 10(10), 3472; https://doi.org/10.3390/app10103472 - 18 May 2020

Cited by 17 | Viewed by 5155

Abstract

An optimal control design for the uncertain Delta robot is proposed in the paper. The uncertain factors of the Delta robot include the unknown dynamic parameters, the residual vibration disturbances and the nonlinear joints friction, which are (possibly fast) time-varying and bounded. A fuzzy set theoretic approach is creatively used to describe the system uncertainty. With the fuzzily depicted uncertainty, an adaptive robust control, based on the fuzzy dynamic model, is established. It designs an adaptation mechanism, consisting of the leakage term and the dead-zone, to estimate the uncertainty information. An optimal design is constructed for the Delta robot and solved by minimizing a fuzzy set-based performance index. Unlike the traditional fuzzy control methods (if-then rules-based), the proposed control scheme is deterministic and fuzzily optimized. It is proven that the global solution in the closed form for this optimal design always exists and is unique. This research provides the Delta parallel robot a novel optimal control to guarantee the system performance regardless of the uncertainty. The effectiveness of the proposed control is illustrated by a series of simulation experiments. The results reveal that the further applications in other robots are feasible. Full article

(This article belongs to the Special Issue Applications of Intelligent Control Methods in Mechatronic Systems)

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17 pages, 3517 KiB

Open AccessArticle

Safe and Policy Oriented Secure Android-Based Industrial Embedded Control System

by Raimarius Delgado, Jaeho Park, Cheonho Lee and Byoung Wook Choi

Appl. Sci. 2020, 10(8), 2796; https://doi.org/10.3390/app10082796 - 17 Apr 2020

Cited by 4 | Viewed by 2694

Abstract

Android is gaining popularity as the operating system of embedded systems and recent demands of its application on industrial control are steadily increasing. However, its feasibility is still in question due to two major drawbacks: safety and security. In particular, ensuring the safe operation of industrial control systems requires the system to be governed by stringent temporal constraints and should satisfy real-time requirements. In this sense, we explore the real-time characteristics of Xenomai to guarantee strict temporal deadlines, and provide a viable method integrating Android processes to real-time tasks. Security is another issue that affects safety due to the increased connectivity in industrial systems provoking a higher risk of cyber and hardware attacks. Herein, we adopted a hardware copy protection chip and enforced administrative security policies in the booting process and the Android application layer. These policies ensure that the developed system is protected from physical tampering and unwanted Android applications. The articulacy of the administrative policies is demonstrated through experiments. The developed embedded system is connected to an industrial EtherCAT motion device network exhibiting operability on an actual industrial application. Real-time performance was evaluated in terms of schedulability and responsiveness, which are critical in determining the safety and reliability of the control system. Full article

(This article belongs to the Special Issue Applications of Intelligent Control Methods in Mechatronic Systems)

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15 pages, 2524 KiB

Open AccessArticle

Adaptive Sliding Mode PID Control for Underwater Manipulator Based on Legendre Polynomial Function Approximation and Its Experimental Evaluation

by Chao Yang, Feng Yao, Mingjun Zhang, Zhiqiang Zhang, Zhenzhen Wu and Peijian Dan

Appl. Sci. 2020, 10(5), 1728; https://doi.org/10.3390/app10051728 - 3 Mar 2020

Cited by 21 | Viewed by 2998

Abstract

The joint control problem of the underwater manipulator is addressed in this paper, under the influence of uncertainty factors such as model uncertainty, external disturbance, and manipulator joint lag. In general, for the uncertainty factors, it is usually approximated online, but it is difficult to select a reasonable value for the approximation error boundary, too conservative estimated values would cause chattering problem easily. And the influence of joint lag on the manipulator control should be considered in actual work. Unlike most previous control method, in this paper, the function approximation technique (FAT), which uses the Legendre polynomial, is adopted to approximate the uncertainty factors online. Then, based on the proportion integral differential (PID) sliding manifold with the integral and differential of tracking error, a sliding model PID controller is designed to speed up the response and reduce the effects of joint lag. For the error boundary, the adaptive law is proposed, and it will reduce chattering of the control quantity under the steady state of the system. It was proved that the joint error of the control system is uniformly asymptotic convergence through the stability analysis. Finally, the effectiveness of the proposed approach is demonstrated with pool comparison experiments of the underwater manipulator installed in the autonomous underwater vehicles (AUVs). Full article

(This article belongs to the Special Issue Applications of Intelligent Control Methods in Mechatronic Systems)

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17 pages, 5796 KiB

Open AccessArticle

Development of a Low Cost and Path-free Autonomous Patrol System Based on Stereo Vision System and Checking Flags

by Chien-Wu Lan and Chi-Yao Chang

Appl. Sci. 2020, 10(3), 974; https://doi.org/10.3390/app10030974 - 2 Feb 2020

Cited by 6 | Viewed by 3321

Abstract

Nowadays, security guard patrol services are becoming roboticized. However, high construction prices and complex systems make patrol robots difficult to be popularized. In this research, a simplified autonomous patrolling robot is proposed, which is fabricated by upgrading a wheeling household robot with stereo vision system (SVS), radio frequency identification (RFID) module, and laptop. The robot has four functions: independent patrolling without path planning, checking, intruder detection, and wireless backup. At first, depth information of the environment is analyzed through SVS to find a passable path for independent patrolling. Moreover, the checkpoints made with RFID tag and color pattern are placed in appropriate positions within a guard area. While a color pattern is detected by the SVS, the patrolling robot is guided to approach the pattern and check its RFID tag. For more, the human identification function of SVS is used to detect an intruder. While a skeleton information of the human is analyzed by SVS, the intruder detection function is triggered, then the robot follows the intruder and record the images of the intruder. The recorded images are transmitted to a server through Wi-Fi to realize the remote backup, and users can query the recorded images from the network. Finally, an experiment is made to test the functions of the autonomous patrolling robot successfully. Full article

(This article belongs to the Special Issue Applications of Intelligent Control Methods in Mechatronic Systems)

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