Hasil untuk "Control engineering systems. Automatic machinery (General)"

TS Amer, Galal M. Moatimid, SK Zakria et al.

This study introduces a novel approach to analyzing a four-degree-of-freedom (DoF) nonlinear system by leveraging advanced numerical and analytical techniques to comprehensively examine its dynamic behavior. The system’s nonlinear differential equations (DEs) are obtained through the application of Lagrange’s equations (LE). The solutions are obtained using the fourth-order Runge–Kutta method (4-RKM). The investigation involves analyzing the relationships between the angular solutions and their corresponding first-order derivatives, commonly referred to as phase plane analysis. The study aims to examine bifurcation diagrams and Lyapunov exponent spectra to reveal the various modes of motion within the system and visualize Poincaré maps. These tools are used to analyze a unique system configuration. Lastly, the conditions for solvability and the characteristic exponents are identified by examining resonance scenarios. The examination of resonance scenarios through characteristic exponents and solvability conditions, coupled with the application of Routh-Hurwitz criteria (RHC) for stability evaluation, provides an innovative framework for understanding frequency response and nonlinear stability across stable and unstable ranges. By exploring both theoretical and practical aspects of vibrational dynamics in applications like aviation, robotics, and underwater exploration, this work offers a significant advancement in analyzing complex systems, with wide-ranging implications for various engineering fields, including aerospace, structural mechanics, and energy harvesting.

Pingping Xie, Yang Liu, Qiuyu Lu et al.

The dependence of wind power on the natural environment leads to volatility, which can cause hidden dangers to the safe and stable operation of the power grid. In this work, a deep learning-based GoogLeNet-embedded no-pooling dimension fully-connected prediction network is proposed for the short-term prediction issue of wind power generation, and the deep learning-based GoogLeNet-embedded no-pooling dimension fully-connected network is compared with five algorithms including long short-term memory network and NasNet. The dataset was collected in Natal. The six algorithms employed predicted the value of wind power for the coming day. Among all, the deep learning-based GoogLeNet embedded no-pooling dimension fully-connected network achieved the optimal prediction results and evaluation metrics. The percentage reduction of each metric value from the second smallest long short-term memory network for the deep learning-based GoogLeNet-embedded no-pooling dimension fully-connected network is 27.0% for mean absolute error, 27.2% for mean absolute percentage error, 34.8% for mean squared error, 19.9% for root mean square error and 21.6% for symmetric mean absolute percentage error.

Sheng Qian, Fusheng Wang, Haihong Huang et al.

Modular Multilevel Converters (MMCs) play a crucial role in high-voltage DC (HVDC) systems due to their adaptable control and swift response capabilities. However, AC side faults could introduce asymmetric double-line frequency components into the MMC's circulating current, jeopardizing DC bus stability. Although strategies to mitigate DC side fluctuations are well-established, a detailed comparison of their operational impacts remains unexplored. The operational effects of MMCs under AC side faults are firstly examined in this study, including issues related to grid-connected current asymmetry and DC bus current fluctuations. Subsequently, two targeted control schemes are devised based on the goals of suppressing the double-line frequency components and only the zero-sequence components of circulating current. Through simulation, these approaches are contrasted, delineating their advantages and disadvantages in terms of circulating current suppression, submodules(SMs) capacitance voltage fluctuation, and other performance metrics, which could provide a foundational reference for designing and selecting MMC control strategies under AC side faults.

Yalin Gui, Lixin Gao, Zhitao Li

Abstract In the realm of evolutionary game theory, the majority of scenarios involve players with incomplete knowledge, specially regarding their opponents' actions and payoffs compounded by the ever‐shifting landscape of players' interactions. These dynamics present formidable challenges in both the analysis and optimization of game evolution. To address this, a novel model named the networked evolutionary game (NEG) is proposed based on incomplete information with switched topologies. This model captures situations where players possess limited insight into their opponents' benefits, yet make decisions based on their own payoffs while adapting to different networks and new players. To bridge the gap between incomplete and complete information games, R. Selten's transformation method is leveraged, a renowned approach that converts an incomplete information game into an interim agent game, thereby establishing the equivalence of pure Nash equilibria (NE) in both scenarios. Employing the semi‐tensor product (STP) of matrices, a powerful tool in logistic system, the evolution of the model is articulated through algebraic relationships. This enables to unravel the patterns of game evolution and identify the corresponding pure Nash equilibria. By introducing control players, strategically positioned within the game, optimized control is facilitated over the evolutionary trajectory, ultimately leading to convergence towards an optimal outcome. Finally, these concepts are illustrated with a practical example within the paper.

Yifeng Hao, Xiaomei Wang, Xiaoqi Song et al.

Compact, low‐inertia, and soft compliant robotic joint mechanisms are in great demand for ensuring safe interactions in human–robot collaborative tasks. Tensegrity, of which the structural integrity is constrained by tension, does not involve static/sliding friction among the rigid components. However, this mechanical stability is very susceptible to actuation errors. It requires complex kinematics modeling and sophisticated control model with sensing feedback. Herein, a low‐inertia tensegrity joint that is covered/protected by a fiber Bragg grating (FBG)‐embedded silicone sheath is proposed, with the aim to reinforce the joint motion stability and enable self‐contained sensing feedback. A learning‐based closed‐loop controller is also designed and trained with the proper joint configurations selected by a two‐step sampling method. Both the kinematics and static equilibriums of such configurations can be well satisfied. The experiments demonstrate that the joint can follow paths accurately in 2D by compensating manipulation error shortly under the closed‐loop control. The joint stiffness can also be varied against the external/impulsive disturbances. It can be foreseen that this primitive robot joint component with 2 degrees of freedom (DoFs) can provide safe, compliant interaction with human, for which a simple test of maneuvering a portable ultrasound probe (≈210 g) for abdominal imaging is demonstrated.

Yujiang Gou, Hui-Bo He, Huaying Li et al.

In order to solve the problems of low efficiency of fertilization and spraying in the hilly mountains of China, a vehicle-mounted fertilization and spraying machine was designed. The whole structure and working principle of the machine were described, and the key components of fertilization and spraying are designed. The kinetics and kinematics of fertilizer particles and droplets were modeled by theoretical analysis of their motion characteristics in the air. The fertilization and variable spraying control system based on the core controller MCU (Microcontroller Unit) was set up. And the system can adjust the rotational speed of the disc and can automatically change the spraying volume by real-time detection of forward speed to achieve a constant spraying volume per unit area. The test results showed that: when the disc speed was greater than 90 r/min, the uniformity coefficient of variation was less than 15%, which satisfied the operational requirements; the uniformity coefficient of variation reached the minimum value of 10.03% when the disc rotation speed was 180 r/min, and the best fertilization performance was achieved at this time. In the spraying system, the actual spraying volume increased with the increased forward speed, and the relative error between the theoretical flow rate and the actual flow rate was 6.25% at most, and the average error was 5.94%, which could achieve the purpose of variable spraying. The research results can provide technical reference for the design and development of fertilization and spraying machinery in hilly areas.

Wei‐ren Kong, De‐yun Zhou, Yong‐jie Du et al.

Abstract The close‐range autonomous air combat has gained significant attention from researchers involved in applications related to artificial intelligence (AI). A majority of the previous studies on autonomous air combat were focused on one‐on‐one air combat scenarios, however, the modern air combat is mostly conducted in formations. With regard to the aforementioned factors, a novel hierarchical maneuvering control architecture is introduced that is applied to the multi‐aircraft close‐range air combat scenario, which can handle air combat scenarios with variable‐size formation. Subsequently, three air combat sub‐tasks are designed, and recurrent soft actor‐critic (RSAC) algorithm combined with competitive self‐play (SP) is incorporated to learn the sub‐strategies. A novel hierarchical multi‐agent reinforcement learning (HMARL) algorithm is proposed to obtain the high‐level strategy for target and sub‐strategy selection. The training performance of the training algorithm of sub‐strategies and high‐level strategy in different air combat scenarios is evaluated. The obtained strategies are analyzed and it is found that the formations exhibit effective cooperative behavior in symmetric and asymmetric scenarios. Finally, the ideas of engineering implementation of the maneuvering control architecture are given. The study provides a solution for future multi‐aircraft autonomous air combat.

Kexin Fan, Weiran Liu, Yuchen Miao et al.

The use of smartphone‐based analysis systems has been increasing over the past few decades. Among the important reasons for its popularity are its ubiquity, increasing computing power, relatively low cost, and capability to acquire and process data simultaneously in a point‐of‐need fashion. Furthermore, smartphones are equipped with various sensors, especially a complementary metal–oxide–semiconductor (CMOS) sensor. The high sensitivity of the CMOS sensor allows smartphones to be used as a colorimeter, fluorimeter, and spectrometer, constituting the essential part of point‐of‐care testing contributing to E‐health and beyond. However, despite its myriads of merits, smartphone‐based diagnostic devices still face many challenges, including high susceptibility to illumination conditions, difficulty in adapter uniformization, low interphone repeatability, and et al. These problems may hinder smartphone‐enabled diagnosis from passing the FDA regulations of medical devices. This review discusses the design and application of current smartphone‐based diagnostic devices and highlights challenges associated with existent methods and perspectives on how to deal with those challenges from engineering aspects on constant color signal acquisition, including smartphone adapter design, color space transformation, machine learning classification, and color correction.

LI Qihe

Intelligent driving system is the development direction of heavy haul railway,automatic train protection (ATP) system to ensure the safety of train is the basis of intelligent driving system and radio block center (RBC) is the wayside ATP core equipment used in high speed railway. Different from the existing RBC, this paper proposes a new type of RBC which aims at heavy haul railway. Based on the characteristics of the heavy haul railway intelligent system, the RBC core functions such as radio communication, train location, movement authority, temporary speed restriction, etc. are improved. Wireless interface with LKJ is added, so the control command can be sent from wayside to LKJ instantly; LTE wireless network is used for onboard-wayside communication to replace GSM-R in order to adapt to the requirement of moving block which need higher frequency communication session; virtual balise technology based on Beidou GNSS is used for train location, which can save cost and avoid ambiguous train position; configuration function is used for switching between fixed block and moving block; temporary speed restriction command is issued based on the format of LKJ to adaption the custom of drivers;and a new function called shunting protection is added. The RBC has been successfully applied to Shenhua locomotive intelligent driving system, its vehicle control rate is more than 90% and the number of operated heavy haul railway trains is 5~6 more than normal, which helps improve the operation efficiency of Shenshuo heavy haul railway.

LU Xiangyang, CAI Jianye, LAN Deshao et al.

This paper summarizes the most recent development and progress of the open-pit mine autonomous haulage operation system in abroad and the development from scratch in domestic, and gives a brief introduction of the standardization work in the industry sector. On this basis, the key technical issues or the key requirements of open-pit mine autonomous haulage operation system is comprehensively described at systematical level,including nine core technical issues such as environment awareness and path planning,and five related technical issues such as line reconstruction and roadside monitoring. The system structure that satisfies the requirements is presented, consisting of ground management and supervision system, vehicle automation package onboard automated dumper, auxiliary operation package onboard collaborative machinery, data communication system and road side system. Eleven further research aspects including enhancement of automation grade, more comprehensive scenario description of event detection and response, as well as optimization of operation plan and regulation are proposed. The future of open-pit mine autonomous haulage operation system is prospected finally.

LIN Xuerong, XIE Heping, XU Biao et al.

Due to the strictly restricted free area, vehicles have difficulties to pass through mine narrow corridors. To solve this problem, this paper presents a trajectory planning method based on optimal control. Narrow corridor model and vehicle single-track kinematics model are adopted to construct the trajectory planning model based on optimal control with an approximate space-discretization strategy considering factors like vehicle passage time, vehicle-boundary collision and vehicle actuator range. By vehicle kinematics integral, the control variable sequence solved by the above trajectory planning model leads to an initial optimal trajectory. Taking the discretization impact on trajectory continuity into account, the final target trajectory is formed after smooth the initial optimal trajectory by quadratic programming. Simulation results show that the trajectory generated by the proposed method is effective in narrow corridor scene, and the generated trajectory is continuous and smooth. Compared with the baseline method, the average maximum curvature reduces from 0.094 m^-1 to 0.040 m^-1 and the average passing time reduces from 6.18 s to 4.80 s in evaluate scenarios.

Woongbae Kim, Jaemin Eom, Kyu-Jin Cho

Soft fluidic actuators produce continuous and life‐like motions that are intrinsically safe, but current designs are not yet mature enough to enable large deployment with high force and low‐cost fabrication methods. Herein, soft fluidic actuators with two superimposed origami architectures are reported. Driven by a fluid input, the presented dual‐origami soft actuators produce quasisequential deployment and bending motion that is guided by unsymmetric unfolding of low‐stretchable origami components. The dominance between the deployment and bending can be shifted by varying the unfolding behavior, enabling preprogramming of the motion. The proposed origami‐inspired soft actuators are directly fabricated by low‐cost fused deposition modeling 3D printing and subjected to heat treatment postprocessing to enhance the fluid sealing performance. Finally, soft gripper applications are presented and they successfully demonstrate gripping tasks where each requires strength, delicacy, precision, and dexterity. The dual‐origami approach offers a design guidance for soft robots to embody grow‐and‐retract motion with a small initial form factor, promising for applications in next‐generation soft robotic systems. An interactive preprint version of the article can be found here: https://www.authorea.com/doi/full/10.22541/au.163698906.68661340.

Z. Pu, Jinlin Sun, Jianqiang Yi et al.

It is commonly believed that observer-based compensation is an effective way for disturbance rejection. A less talked about fact is that such disturbance rejection control technique may also degrade control performance. In this article, we present a typical cross-coupling system to reveal this problem and, more importantly, propose a new design principle of conditional disturbance negation (CDN) to eliminate its potential drawbacks of disturbance observer-based compensation. Qualitative analysis is first given for a general form of such cross-coupling systems, indicating the necessity of CDN. The analysis and control design principle of CDN is then exemplified through two applications. A numerical linear application produces abundant quantitative results through the powerful transfer function and frequency domain tools. A more complex nonlinear flexible air-breathing hypersonic vehicle application shows how conventional compensation deteriorates the couplings between rigid and flexible modes, and validates the effectiveness of CDN through comprehensive model analysis and simulation results. The proposed CDN design principle also arouses awareness of the importance of: 1) understanding the characteristics of the plant to be controlled and 2) recognizing the critical role the information plays in engineering practice.

A. V. Hoegen, R. D. Doncker, M. Bragard et al.

During the Covid-19 pandemic, vocational colleges, universities of applied science and technical universities often had to cancel laboratory sessions requiring students’ attendance. These above of all are of decisive importance in order to give learners an understanding of theory through practical work.This paper is a contribution to the implementation of distance learning for laboratory work applicable for several upper secondary educational facilities. Its aim is to provide a paradigm for hybrid teaching to analyze and control a non-linear system depicted by a tank model. For this reason, we redesign a full series of laboratory sessions on the basis of various challenges. Thus, it is suitable to serve different reference levels of the European Qualifications Framework (EQF).We present problem-based learning through online platforms to compensate the lack of a laboratory learning environment. With a task deduced from their future profession, we give students the opportunity to develop own solutions in self-defined time intervals. A requirements specification provides the framework conditions in terms of time and content for students having to deal with the challenges of the project in a self-organized manner with regard to inhomogeneous previous knowledge. If the concept of Complete Action is introduced in classes before, they will automatically apply it while executing the project.The goal is to combine students’ scientific understanding with a procedural knowledge. We suggest a series of remote laboratory sessions that combine a problem formulation from the subject area of Measurement, Control and Automation Technology with a project assignment that is common in industry by providing extracts from a requirements specification.

Rini Akmeliawati

Ko-Feng Lee, Yen-Lin Chen, Chao-Wei Yu et al.

In this study, a head-mounted camera was used to track eye behaviors and estimate the gaze point on the user’s visual plane. The integration of the elastic mechanism design makes the headset adaptable for various users. The wearable cases were prototyped with low-cost cameras to produce an efficient eye tracking solution. This proposed system can effectively extract and estimate pupil ellipse from a few camera images of an eye and compute the corresponding three-dimensional eye model. The system can match later images of the same pupil ellipse from a head-mounted camera to give the possible visual angles. To estimate the gaze point, the system uses multiple-point calibration to solve the related polynomial formula for future angle-to-gaze mapping. The proposed eye-tracking algorithms can provide a low-complexity solution with high accuracy, precision, and speed. This tracking system is a low-cost and promising system that can be used in headsets for virtual reality, auxiliary equipment, interactive machine, and human–machine interface applications. The proposed eye-tracking algorithm can achieve satisfactory performance without using a high-end high-speed camera and can be detected under different lighting sources, and the average errors of the detection results are stably within 9 pixels and at a distance of 50 cm from the screen; while the average error of the fixation mapping results is within 3°.

Heiko Koziolek, Andreas Burger, Marie Platenius-Mohr et al.

Software development for industrial automation applications is a growing market with high economic impact. Control engineers design and implement software for such systems using standardized programming languages (IEC 61131-3) and still require substantial manual work causing high engineering costs and potential quality issues. Methods for automatically generating control logic using knowledge extraction from formal requirements documents have been developed, but so far only been demonstrated in simplified lab settings. We have executed four case studies on large industrial plants with thousands of sensors and actuators for a rule-based control logic generation approach called CAYENNE to determine its practicability. We found that we can generate more than 70 percent of the required interlocking control logic with code generation rules that are applicable across different plants. This can lead to estimated overall development cost savings of up to 21 percent, which provides a promising outlook for methods in this class.

Dean Ho

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), the virus that led to the COVID‐19 (Coronavirus Disease 2019) pandemic, has resulted in substantial overburdening of healthcare systems as well as an economic crisis on a global scale. This has in turn resulted in widespread efforts to identify suitable therapies to address this aggressive pathogen. Therapeutic antibody and vaccine development are being actively explored, and a phase I clinical trial of mRNA‐1273 which is developed in collaboration between the National Institute of Allergy and Infectious Diseases and Moderna, Inc. is currently underway. Timelines for the broad deployment of a vaccine and antibody therapies have been estimated to be 12–18 months or longer. These are promising approaches that may lead to sustained efficacy in treating COVID‐19. However, its emergence has also led to a large number of clinical trials evaluating drug combinations composed of repurposed therapies. As study results of these combinations continue to be evaluated, there is a need to move beyond traditional drug screening and repurposing by harnessing artificial intelligence (AI) to optimize combination therapy design. This may lead to the rapid identification of regimens that mediate unexpected and markedly enhanced treatment outcomes.

J. Rossiter, B. Pasik-Duncan, A. Visioli et al.

activities of the IEEE Control Systems Society Technical Committee on Control Education (TC-CE) are focused on 1) promoting control with its cross-boundary nature as a field that spans science, technology, engineering, and mathematics (STEM); 2) providing students at all levels, including precollege, undergraduate, graduate, and postgraduate, with the opportunity to explore the world of control engineering; 3) organizing workshops and special sessions on education that unite members from academia and industry to facilitate learning experiences and attract students to control engineering; 4) communicating to the public at large about the control field; and 5) engaging all TCs in control education issues and activities. TC-CE currently has 30 members. Bozenna Pasik-Duncan chaired the TC from January 2012 to December 2014. Ljubo Vlacic was the chair in 2015, and Sebastian Dormido held the position from January 2016 to September 2017. Anthony Rossiter is the new chair. Among the topics of interest currently pursued by the membership are university education and continuing education issues in control; methodologies for improving the theory, practice, and accessibility of control systems education; control education laboratories; experiments; computer-aided design (CAD); distance and virtual education technologies; and a general awareness among precollege students and teachers of the importance of systems and control technology and its cross-disciplinary nature. This column summarizes the 2016 activities.

DENG Xiaoxiang, LI Peng, DAI Chaofan et al.

In order to analyze the causes and correlations of gate drive loss and switching loss of GaN MOSFET and Si MOSFET, a single-phase full-bridge inverter topology was proposed to build a power switch device efficiency test platform and the working efficiencies of GaN MOSFET and Si MOSFET at different switching frequencies and different temperatures were tested using the test platform. The experimental results show that the efficiecies of the inverter with enhanced GaN MOSFETs are respectively 1.47% and 1.6% higher than that of the inverter with Si MOSFETs at the switching frequencies of 50 kHz and 120 kHz . The efficiencies of the inverter with enhanced GaN MOSFETs are respectively 1.8%, 1.9%, 2.0% and 2.1% higher than that of the inverter with Si MOSFETs at different operating temperatures of 40 ℃ , 50 ℃ , 60 ℃ 70 ℃ . The results showed that the efficiency of enhanced GaN MOSFET is higher, with increasing switching frequency and higher working temperature.