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Journal of Systems engineering and Electronics 2023年第4期34卷 992-1006页

作者： NAN Yi YI Guoxing HU Lei WANG Changhong TU Zhenbiao department of control Science and engineering Harbin Institute of TechnologyHarbin 150001China Beijing Electro-mechanical engineering Institute Beijing 100074China

The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation,while its influencing factors are complex and mutually coupled.Existing calculation methods have very limited analysis of the influence mechanism of influencing factors,and none of them has analyzed the influence of the guidance law.This paper considers the influencing factors of both the interceptor and the target more comprehensively.Interceptor parameters include speed,guidance law,guidance error,fuze error,and fragment killing ability,while target performance includes speed,maneuverability,and vulnerability.In this paper,an interception model is established,Monte Carlo simulation is carried out,and the influence mechanism of each factor is analyzed based on the model and simulation results.Finally,this paper proposes a classification-regression neural network to quickly estimate the interception probability based on the value of influencing factors.The proposed method reduces the interference of invalid interception data to valid data,so its prediction accuracy is significantly better than that of pure regression neural networks.

关键词： interception probability simulation modeling analysis of influencing factors probability estimation neural networks

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A logical network approximation to optimal control on a continuous domain and its application to HEV control

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Science China(Information Sciences) 2022年第11期65卷 178-195页

作者： Yuhu WU Jiangyan ZHANG Tielong SHEN School of control Science and engineering Dalian University of Technology College of mechanical and Electronic engineering Dalian Minzu University department of engineering and Applied Sciences Sophia University

The finite-time horizon optimal control problem is investigated for discrete-time dynamical systems defined on a continuous domain. First, the original optimal control problem in the continuous domain is approximated as one on a finite-valued domain based on a special quantification process. Under suitable assumptions, convergence analysis of the approximate optimal cost of the quantified system to the optimal cost of the original system was established with error estimation. Thereafter, the approximate problem is solved using a logical network-based method that is proposed based on the semi-tensor product of the matrix.Finally, the proposed scheme is applied to deal with the optimal control problem of a hybrid electric vehicle(HEV) powertrain system, and its effectiveness is shown by a series of simulation results.

关键词： finite horizon optimal control logical networks semi-tensor product quantification HEV control

A hybrid genetic algorithm for the electric vehicle routing problem with time windows

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control Theory and Technology 2022年第2期20卷 279-286页

作者： Qixing Liu Peng Xu Yuhu Wu Tielong Shen School of control Science and engineering Dalian University of TechnologyDalian 116024China department of mechanical engineering Sophia UniversityTokyo 102-8554Japan

Driven by the new legislation on greenhouse gas emissions,carriers began to use electric vehicles(EVs)for logistics transportation.This paper addresses an electric vehicle routing problem with time windows(EVRPTW).The electricity consumption of EVs is expressed by the battery state-of-charge(SoC).To make it more realistic,we take into account the terrain grades of roads,which affect the travel process of EVs.Within our work,the battery SoC dynamics of EVs are used to describe this situation.We aim to minimize the total electricity consumption while serving a set of customers.To tackle this problem,we formulate the problem as a mixed integer programming model.Furthermore,we develop a hybrid genetic algorithm(GA)that combines the 2-opt algorithm with GA.In simulation results,by the comparison of the simulated annealing(SA)algorithm and GA,the proposed approach indicates that it can provide better solutions in a short time.

关键词： Electric vehicles Vehicle routing Battery SoC Hybrid genetic algorithm

The dynamic relaxation form finding method aided with advanced recurrent neural network

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 635-644页

作者： Liming Zhao Zhongbo Sun Keping Liu Jiliang Zhang department of mechanical and Electrical engineering Changchun University of TechnologyChangchunChina department of control engineering Changchun University of TechnologyChangchunChina department of Electronic and Electrical engineering The University of SheffieldSheffieldEngland

How to establish a self‐equilibrium configuration is vital for further kinematics and dynamics analyses of tensegrity mechanism.In this study,for investigating tensegrity form‐finding problems,a concise and efficient dynamic relaxation‐noise tolerant zeroing neural network(DR‐NTZNN)form‐finding algorithm is established through analysing the physical properties of tensegrity structures.In addition,the non‐linear constrained opti-misation problem which transformed from the form‐finding problem is solved by a sequential quadratic programming algorithm.Moreover,the noise may produce in the form‐finding process that includes the round‐off errors which are brought by the approximate matrix and restart point calculating course,disturbance caused by external force and manufacturing error when constructing a tensegrity structure.Hence,for the purpose of suppressing the noise,a noise tolerant zeroing neural network is presented to solve the search direction,which can endow the anti‐noise capability to the form‐finding model and enhance the calculation capability.Besides,the dynamic relaxation method is contributed to seek the nodal coordinates rapidly when the search direction is acquired.The numerical results show the form‐finding model has a huge capability for high‐dimensional free form cable‐strut mechanisms with complicated topology.Eventually,comparing with other existing form‐finding methods,the contrast simulations reveal the excellent anti‐noise performance and calculation capacity of DR‐NTZNN form‐finding algorithm.

关键词： dynamic relaxation form‐finding noise‐tolerant zeroing neural network sequential quadratic programming Tensegrity

Analysis and Optimization of Operational and Pollutant Attributes of Diesel Engine with CNT-Infused Orange Peel Biodiesel-Diesel Blend Fuel

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Journal of Thermal Science 2024年第2期33卷 761-778页

作者： Ranjeet RAI R.R.SAHOO mechanical engineering department GLA UniversityMathura281406India mechanical engineering department IIT(BHU)Varanasi221005India

The current study is performed to find sustainable solutions for the future of transportation and environmental well-being.Both conventional methods and experimental design table(L16 Orthogonal Array)techniques have been employed to examine and optimize a diesel-powered engine's operational and pollutant parameters.The L16 Orthogonal Array is obtained through Taguchi's experimental design approach using Minitab 16 software.The experimental design incorporated three control variables,namely engine speed,fuel type,and engine load,each with four levels.The operational parameters,namely brake thermal efficiency(BTE)and brake specific fuel consumption(BSFC),as well as the emission characteristics,including hydrocarbon(HC),carbon monoxide(CO),nitrogen oxide(NO),and smoke emissions,were acquired using the L16 orthogonal array(OA) and subsequently examined.The utilization of methodologies such as signal-to-noise(S/N) ratio and grey analysis was employed to determine the optimal operational state of the engine to achieve maximum performance while minimizing emissions.The engine's ideal state of operation,in terms of BTE and BSFC,was determined to be at 75% engine load,1000 r/min engine speed,and using 10^(-4)(in vol) carbon nanotube incorporated 20% orange peel biodiesel(OPB20CNT100) blended fuel(A3-B1-C4).The study indicated that engine load significantly influenced BTE and BSFC,with 84.05% and 87.79% contribution factors,respectively.At 25% engine load,1000 r/min,and OPB20CNT100 fuel(A1-B1-C4) CO,smoke,NO,and HC emissions were the lowest.Engine load affects emissions the most.Engine BSFC increased 3.10% and NO emissions 1.77%.BTE,CO,smoke,and HC emissions decreased by 1.9%,12.29%,47.05%,and 47.22%,respectively,at optimal operating conditions concerning diesel fuel.This study shows that Taguchi-Grey's experimental design optimizes diesel engine operational and pollutant attributes.The outcomes revealed that orange peel biodiesel infused with CNT can replace diesel fuel in an environmentally friendly way.This alternative

关键词： Taguchi-Grey method OPB20CNT100 transesterification S/N ratio GRG HC CO and NO

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Event-triggered robust MPC of nonlinear cyber-physical systems against DoS attacks

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Science China(Information Sciences) 2022年第1期65卷 22-38页

作者： Qi SUN Jicheng CHEN Yang SHI department of mechanical engineering University of Victoria

This paper proposes an event-triggered robust nonlinear model predictive control(NMPC) framework for cyber-physical systems(CPS) in the presence of denial-of-service(Do S) attacks and additive disturbances. In the framework, a new robustness constraint is introduced to the NMPC optimization problem in order to deal with additive disturbances, and a packet transmission strategy is designed for NMPC such that Do S attacks can be tackled. Then, an event-triggered mechanism, which accommodates Do S attacks occurring in the communication network, is proposed to reduce the communication cost for resource-constrained CPSs. Besides, we prove that the NMPC algorithm is recursively feasible and the closed-loop system is input-to-state practical stable under some sufficient conditions. Simulation examples and comparisons are conducted to show the effectiveness of the proposed NMPC algorithm.

关键词： cyber-physical systems nonlinear model predictive control event-triggered mechanism robust control denial-of-service attacks

Robotic mobile and mirror milling of large-scale complex structures

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National Science Review 2023年第5期10卷 10-13页

作者： Zenghui Xie Fugui Xie Limin Zhu Xin-Jun Liu State Key Laboratory of Tribology in Advanced Equipment Department of Mechanical Engineering(DME) Tsinghua University Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and control Tsinghua University State Key Laboratory of mechanical System and Vibration School of Mechanical EngineeringShanghai Jiao Tong University

Large-scale complex structures,such as spacecraft cabins,aircraft composite skins and launch vehicle fuel tanks,are the core components of the equipment in aerospace,energy,shipbuilding and other fields.Their milling quality and efficiency are factors directly affecting the performance and productivity of spacecraft,aircraft and other key equipment.This kind of structure generally features large dimension,high accuracy,

关键词： COMPENSATION PARTS

Model Predictive control Coupled with Artificial Intelligence for Eddy Current Dynamometers

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Computer Systems Science & engineering 2023年第1期44卷 221-234页

作者： İhsan Uluocak Hakan Yavuz Çukurova University Ceyhan Engineering FacultyMechanical Engineering DepartmentAdanaTurkey Çukurova University Faculty of EngineeringMechanical Engineering DepartmentAdanaTurkey

The recent studies on Artificial Intelligence(AI)accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing adap-tiveness and fast responding features.The Model Predictive control(MPC)tech-nique is a widely used,safe and reliable control method based on constraints.On the other hand,the Eddy Current dynamometers are highly nonlinear braking sys-tems whose performance parameters are related to many processes related vari-ables.This study is based on an adaptive model predictive control that utilizes selected AI methods.The presented approach presents an updated the mathema-tical model of an Eddy Current Dynamometer based on experimentally obtained system operational data.Finally,the comparison of AI methods and related learn-ing performances based on the assessment technique of mean absolute percentage error(MAPE)issues are discussed.The results indicate that Single Hidden Layer Neural Network(SHLNN),General Regression Neural Network(GRNN),Radial Basis Network(RBNN),Neuro Fuzzy Network(ANFIS)coupled MPC have quite satisfying performances.The presented results indicate that,amongst them,GRNN appears to provide the best performance.

关键词： Model predictive control eddy current dynamometer artificial intelligence GRNN RBNN ANFIS

Development of a Hand Exoskeleton System for Quantitative Analysis of Hand Functions

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Journal of Bionic engineering 2018年第5期15卷 783-794页

作者： Jeongsoo Lee Minhyuk Lee Joonbum Bae Bio-Robotics and control (BiRC) Laboratory Department of Mechanical Engineering UNIST Ulsan Republic of Korea

This paper proposes a hand exoskeleton system for evaluating hand functions. To evaluate hand functions, the hand exoskeleton system must be able to pull each finger joint, measure the finger joint angle and exerted force on the finger simultaneously. The proposed device uses serially connected 4-bar linkage structures, which have two embedded actuators with encoders and two loadcells per finger, to move each phalanx independently and measure the finger joint angles. A modular design was used for the exoskeleton, to facilitate the removal of unnecessary modules in different experiments and improve convenience. Silicon was used on the surface of the worn part to reduce the skin irritation that results from prolonged usage. This part was also designed to be compatible with various finger thicknesses. Using the proposed hand exoskeleton system, finger independence, multi-finger synergy, and finger joint stiffness were determined in five healthy subjects. The finger movement and force data collected in the experiments were used for analyzing three hand functions based on the physical and physiological phenomena.

关键词： evaluation of hand function hand rehabilitation wearable system exoskeleton

Adaptive Fuzzy Dynamic Surface control of Flexible-Joint Robot Systems With Input Saturation

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 97-107页

作者： Song Ling Huanqing Wang Peter X.Liu the School of mechanical Electronic and Control EngineeringBeijing Jiaotong University the department of Mathematics Bohai University IEEE the department of Systems and Computer engineering Carleton University

In this paper, we propose an adaptive fuzzy dynamic surface control(DSC) scheme for single-link flexible-joint robotic systems with input saturation. A smooth function is utilized with the mean-value theorem to deal with the difficulties associated with input saturation. An adaptive DSC design with an auxiliary first-order filter is used to solve the "explosion of complexity"problem. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood around zero. The main advantage of the proposed method is that only one adaptation parameter needs to be updated,which reduces the computational burden significantly. Simulation results demonstrate the feasibility of the proposed scheme and the comparison results show that the improved DSC method can reduce the computational burden by almost two thirds in comparison with the standard DSC method.

关键词： Adaptive fuzzy control dynamic surface control (DSC) flexible-joint (FJ) robots single-link tracking control

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