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Distributed collaborative complete coverage path planning based on hybrid strategy

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Journal of Systems Engineering and Electronics 2024年第2期35卷 463-472页

作者： ZHANG Jia DU Xin DONG Qichen XIN Bin School of automation Beijing Institute of TechnologyBeijing 100081China National key laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China

Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm is proposed for the urban rescue search or military search in outdoor environment.Due to flexible control of small UAVs, it can be considered that all UAVs fly at the same altitude, that is, they perform search tasks on a two-dimensional plane. Based on the agents’ motion characteristics and environmental information, a mathematical model of CCPP problem is established. The minimum time for UAVs to complete the CCPP is the objective function, and complete coverage constraint, no-fly constraint, collision avoidance constraint, and communication constraint are considered. Four motion strategies and two communication strategies are designed. Then a distributed CCPP algorithm is designed based on hybrid strategies. Simulation results compared with patternbased genetic algorithm(PBGA) and random search method show that the proposed method has stronger real-time performance and better scalability and can complete the complete CCPP task more efficiently and stably.

关键词： multi-agent cooperation unmanned aerial vehicles(UAV) distributed algorithm complete coverage path planning(CCPP)

Prediction and Output Estimation of Pattern Moving in Non-Newtonian Mechanical Systems Based on Probability Density Evolution

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 515-536页

作者： Cheng Han Zhengguang Xu School of automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China key laboratory of Knowledge automation for Industrial Processes University of Science and Technology BeijingBeijing100083China

A prediction framework based on the evolution of pattern motion probability density is proposed for the output prediction and estimation problem of non-Newtonian mechanical systems,assuming that the system satisfies the generalized Lipschitz condition.As a complex nonlinear system primarily governed by statistical laws rather than Newtonian mechanics,the output of non-Newtonian mechanics systems is difficult to describe through deterministic variables such as state variables,which poses difficulties in predicting and estimating the system’s output.In this article,the temporal variation of the system is described by constructing pattern category variables,which are non-deterministic variables.Since pattern category variables have statistical attributes but not operational attributes,operational attributes are assigned to them by posterior probability density,and a method for analyzing their motion laws using probability density evolution is proposed.Furthermore,a data-driven form of pattern motion probabilistic density evolution prediction method is designed by combining pseudo partial derivative(PPD),achieving prediction of the probability density satisfying the system’s output uncertainty.Based on this,the final prediction estimation of the system’s output value is realized by minimum variance unbiased estimation.Finally,a corresponding PPD estimation algorithm is designed using an extended state observer(ESO)to estimate the parameters to be estimated in the proposed prediction method.The effectiveness of the parameter estimation algorithm and prediction method is demonstrated through theoretical analysis,and the accuracy of the algorithm is verified by two numerical simulation examples.

关键词： Non-newtonian mechanical systems prediction and estimation pattern moving probability density evolution pseudo partial derivative

Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

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Journal of Systems Engineering and Electronics 2024年第2期35卷 361-373页

作者： CHEN Chen QUAN Wei SHAO Zhuang School of automation Beijing Institute of TechnologyBeijing 100081China State key laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081China

Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.

关键词： target threat assessment gated recurrent unit(GRU) self-attention(SA) fractional Fourier transform(FRFT)

Security-constrained Transmission Maintenance Optimization Considering Generation and Operational Risk Costs

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 767-781页

作者： Dan Xu Zhi Cai Qian Cheng Guodong Huang Jingyang Zhou Junjie Tang beijing key laboratory of Research and System Evaluation of Power Dispatching automation technology China Electric Power Research Institute State key laboratory of Power Transmission Equipment & System Security and New technology Chongqing University

With the large-scale integration of renewable energy, the traditional maintenance arrangement during the load valley period cannot satisfy the transmission demand of renewable energy generation. Simultaneously, in a market-oriented operation mode, the power dispatching control center aims to reduce the overall power purchase cost while ensuring the security of the power system. Therefore, a security-constrained transmission maintenance optimization model considering generation and operational risk costs is proposed herein. This model is built on double-layer optimization framework, where the upper-layer model is used for maintenance and generation planning, and the lowerlayer model is primarily used to address the operational security risk arising from the random prediction error and N-1 transmission failure. Correspondingly, a generation-maintenance iterative algorithm based on a defined cost feedback is included to increase solution efficiency. Generation cost is determined using long-term security-constrained unit commitment, and the operational risk cost is obtained using a double-layer N-1 risk assessment model. An electrical correlation coupling coefficient is proposed for the solution process to avoid maintenance of associated equipment simultaneously, thereby improving model convergence efficiency. The IEEE 118-bus system is used as a test case for illustration, and test results suggest that the proposed model and algorithm can reduce the total cost of transmission maintenance and system operation while effectively improving the solution efficiency of the joint optimization model.

关键词： Maintenance engineering Costs Optimization Power systems Renewable energy sources Power grids Load modeling

Prescribed Performance Evolution Control for Quadrotor Autonomous Shipboard Landing

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1151-1162页

作者： Yang Yuan Haibin Duan Zhigang Zeng State key laboratory of Virtual Reality technology and Systems the School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China State key laboratory of Virtual Reality technology and Systems the School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083 Virtual Reality Fundamental Research laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China School of Artificial Intelligence and automation Huazhong University of Science and TechnologyWuhan 430074China

The shipboard landing problem for a quadrotor is addressed in this paper,where the ship trajectory tracking control issue is transformed into a stabilization control issue by building a relative position model.To guarantee both transient performance and steady-state landing error,a prescribed performance evolution control(PPEC)method is developed for the relative position control.In addition,a novel compensation system is proposed to expand the performance boundaries when the input saturation occurs and the error exceeds the predefined threshold.Considering the wind and wave on the relative position model,an adaptive sliding mode observer(ASMO)is designed for the disturbance with unknown upper bound.Based on the dynamic surface control framework,a shipboard landing controller integrating PPEC and ASMO is established for the quadrotor,and the relative position control error is guaranteed to be uniformly ultimately bounded.Simulation results have verified the feasibility and effectiveness of the proposed shipboard landing control scheme.

关键词： error integrating stabilization

Three-Rigid-Body-Particle Modeling and Optimization of Trajectory and Posture for Alpine Skiing

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Journal of Systems Science & Complexity 2024年第2期37卷 581-608页

作者： ZHANG Yijia FEI Qing YAO Xiaolan SUN Jian ZHANG Yanjun CHEN Zhen School of automation Beijing Institute of TechnologyBeijing 100081China

This paper presents a new study on modeling and optimization of trajectory and posture for the super-giant(SG)slalom of alpine skiing.It is the first time that a Three-Rigid-Body-Particle model based on rigorous derivations and stability analysis is established to represent skiers trajectory and posture characteristics,as it is more accurate than the single-rigid-body model which is commonly used in existing studies.In addition,the Radau pseudospectral method is applied to solve the trajectory and posture optimization problem in order to obtain better skiing trajectory,skiing posture,and some key kinematic parameters of skiers.Moreover,this paper analyzes the effects of different body types,minimum turning radii,and flexor and extensor strength of knees and hip joint on skiing performance.Finally,based on the findings of the study,some advice about how to improve the performance of the SG slalom in view of science and technology is given to skiers and coaches for reference.

关键词： Alpine skiing modeling posture optimization Three-Rigid-Body-Particle model trajectory optimization

Extremum seeking control for UAV close formation flight via improved pigeon-inspired optimization

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Science China(Technological Sciences) 2024年第2期67卷 435-448页

作者： YUAN GuangSong DUAN HaiBin State key laboratory of Virtual Reality technology and Systems School of Automation Science and Electrical EngineeringBeihang University(BUAA)Beijing 100083China

This paper proposes a comprehensive design scheme for the extremum seeking control(ESC)of the unmanned aerial vehicle(UAV)close formation flight.The proposed design scheme combines a Newton-Raphson method with an extended Kalman filter(EKF)to dynamically estimate the optimal position of the following UAV relative to the leading UAV.To reflect the wake vortex effects reliably,the drag coefficient induced by the wake vortex is considered as a performance function.Then,the performance function is parameterized by the first-order and second-order terms of its Taylor series expansion.Given the excellent performance of nonlinear estimation,the EKF is used to estimate the gradient and the Hessian matrix of the parameterized performance function.The output feedback of the proposed scheme is determined by iterative calculation of the Newton-Raphson method.Compared with the traditional ESC and the classic ESC,the proposed design scheme avoids the slow continuous time integration of the gradient.This allows a faster convergence of relative position extremum.Furthermore,the proposed method can provide a smoother command during the seeking process as the second-order term of the performance function is taken into account.The convergence analysis of the proposed design scheme is accomplished by showing that the output feedback is a supermartingale sequence.To improve estimation performance of the EKF,a improved pigeon-inspired optimization(IPIO)is proposed to automatically tune the noise covariance matrix.Monte Carlo simulations for a three-UAV close formation show that the proposed design scheme is robust to the initial position of the following UAV.

关键词： unmanned aerial vehicle close formation extremum seeking control Newton-Raphson method improved pigeon-inspired optimization

Data-Driven Adaptive Predictive Control Method With Autotuned Weighting Factor for Nonlinear Systems Using Triangular Dynamic Linearization

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IEEE/CAA Journal of Automatica Sinica 2024年第8期 1880-1882页

作者： Zhong-Hua Pang Yumo Zhang Xueyuan Sun Shengnan Gao Guo-Ping Liu IEEE the key laboratory of fieldbus technology and automation of beijing North China University of Technology the School of Data Science Capital University of Economics and Business the Center for Control Science and technology Southern University of Science and Technology

Dear Editor,In this letter, a novel data-driven adaptive predictive control method is proposed using the triangular dynamic linearization technique. The proposed method only contains one time-varying parameter with explicit physical meaning, which can prevent severe deviation in parameter estimation. Specifically, a triangular dynamic linearization (TDL) data model is employed to predict future system outputs, and then to correct inaccurate predictive outputs, a feedback regulator is designed.

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Control of 2-D Semi-Markov Jump Systems:A View from Mode Generation Mechanism

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 258-260页

作者： Yunzhe Men Jian Sun Jie Chen the National key laboratory of Autonomous Intelligent Unmanned Systems the School of AutomationBeijing Institute of TechnologyBeijing 100081 the beijing Institute of technology Chongqing Innovation Center Chongqing 401120China the Department of Control Science and Engineering Tongji UniversityShanghai 201804 the National key laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China

Dear Editor,Two-dimensional(2-D) systems have wide applications in image data processing,gas absorption and fluid dynamics analysis [1]-[3].When there exist abrupt changes in 2-D systems,they are usually modeled by 2-D Markov jump systems(MJSs) or 2-D semi-Markov jump systems(SMJSs).This letter investigates the control of 2-D SMJSs based on a novel mode generation mechanism,which could avoid mode ambiguousness phenomenon caused by the evolution of system mode in two different directions.The criterion that guarantees the almost surely exponential stability of the system is obtained.A thermal process is studied to demonstrate the availability of the proposed method.

关键词： Markov mode system