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Optimal Switching Integrity Attacks on Sensors in Industrial control systems

Journal of systems Science and complexity 2019年第5期32卷 1290-1305页

作者： Wu, Guangyu Sun, Jian The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing100081 China

In this article, an optimal switching integrity attack problem is investigated to study the response of feedback control systems under attack. The authors model the malicious attacks on sensors as additive norm bounded signals. The authors consider an attacker who is only capable of launching attacks to limited number of sensors once a time and changing the combinations of attacked sensors all over the time. The objective of this paper is to find the optimal switching sequence of these combinations and the optimal attack input. The authors solve this problem by transforming it into a traditional optimal control problem with new control variables vary continuously in the range [0, 1]. The optimal solutions of the new control variables are of bang-bang-type. Therefore, an algebraic switching condition and an optimal attack input can be obtained. Finally, numerical results are provided to illustrate the effectiveness of the methods. © 2019, The Editorial Office of JSSC & Springer-Verlag GmbH Germany.

关键词： Adaptive control systems

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A memetic algorithm for path planning of curvature-constrained UAVs performing surveillance of multiple ground targets

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Chinese Journal of Aeronautics 2014年第3期27卷 622-633页

作者： Zhang Xing Chen Jie Xin Bin Peng Zhihong School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles （UAVs） performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs＇ minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood （DTSPN）. Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants （multi-UAV scenario and multiple groups of targets scenario）. The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.

关键词： Approximate gradient Dubins traveling salesmanproblem with neighborhood Local search Memetic algorithm Unmanned aerial vehicles

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Further results on cloud control systems

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Science China(Information Sciences) 2016年第7期59卷 232-236页

作者： Yuanqing XIA Yongming QIN Di-Hua ZHAI Senchun CHAI School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology

This paper is devoted to further investigating the cloud control systems(CCSs). The benefits and challenges of CCSs are provided. Both new research results of ours and some typical work made by other researchers are p... 详细信息

关键词： cloud control systems cloud computing cyber-physical systems networked control systems big data

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Interactive multiobjective evolutionary algorithm based on decomposition and compression

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Science China(Information Sciences) 2021年第10期64卷 166-181页

作者： Lu CHEN Bin XIN Jie CHEN School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Many real-world optimization problems involve multiple conflicting objectives. Such problems are called multiobjective optimization problems(MOPs). Typically, MOPs have a set of so-called Pareto optimal solutions rather than one unique optimal solution. To assist the decision maker(DM) in finding his/her most preferred solution, we propose an interactive multiobjective evolutionary algorithm(MOEA)called iDMOEA-εC, which utilizes the DM's preferences to compress the objective space directly and progressively for identifying the DM's preferred region. The proposed algorithm employs a state-of-the-art decomposition-based MOEA called DMOEA-εC as the search engine to search for solutions. DMOEA-εC decomposes an MOP into a series of scalar constrained subproblems using a set of evenly distributed upper bound vectors to approximate the entire Pareto front. To guide the population toward only the DM's preferred part on the Pareto front, an adaptive adjustment mechanism of the upper bound vectors and two-level feasibility rules are proposed and integrated into DMOEA-εC to control the spread of the population. To ease the DM's burden, only a small set of representative solutions is presented in each interaction to the DM,who is expected to specify a preferred one from the set. Furthermore, the proposed algorithm includes a two-stage selection procedure, allowing to elicit the DM's preferences as accurately as possible. To evaluate the performance of the proposed algorithm, it was compared with other interactive MOEAs in a series of experiments. The experimental results demonstrated the superiority of iDMOEA-εC over its competitors.

关键词： multiobjective optimization interactive decision making preference incorporation decomposition compression

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Online adaptive Q-learning method for fully cooperative linear quadratic dynamic games

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Science China(Information Sciences) 2019年第12期62卷 164-177页

作者： Xinxing LI Zhihong PENG Lei JIAO Lele XI Junqi CAI School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

A model-based offline policy iteration(PI) algorithm and a model-free online Q-learning algorithm are proposed for solving fully cooperative linear quadratic dynamic games. The PI-based adaptive Q-learning method can learn the feedback Nash equilibrium online using the state samples generated by behavior policies, without sending inquiries to the system model. Unlike the existing Q-learning methods, this novel Q-learning algorithm executes both policy evaluation and policy improvement in an adaptive *** prove the convergence of the offline PI algorithm by proving its equivalence to Newton's method while solving the game algebraic Riccati equation(GARE). Furthermore, we prove that the proposed Q-learning method will converge to the Nash equilibrium under a small learning rate if the method satisfies certain persistence of excitation conditions, which can be easily met by suitable behavior policies. Our simulation results demonstrate the good performance of the proposed online adaptive Q-learning algorithm.

关键词： adaptive dynamic programming reinforcement learning Q-learning fully cooperative linear quadratic dynamic games policy iteration off-policy

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Moving object detection in framework of compressive sampling

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Journal of systems Engineering and Electronics 2010年第5期21卷 740-745页

作者： Jing Li JunzhengWang Wei Shen Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing 100081 P. R. China

Compressive sensing is a revolutionary idea proposed recently to achieve much lower sampling rate for *** the image application with limited resources the camera data can be stored and processed in compressed *** algorithm for moving object and region detection in video using a compressive sampling is *** algorithm estimates motion information of the moving object and regions in the video from the compressive measurements of the current image and background *** algorithm does not perform inverse compressive operation to obtain the actual pixels of the current image nor the estimated *** leads to a computationally efficient method and a system compared with the existing motion estimation *** experimental results show that the sampling rate can reduce to 25% without sacrificing performance.

关键词： compressive sampling compressive measurements moving object detection.

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Dynamic image stabilization precision test system based on the Hessian matrix

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Science China(Information Sciences) 2012年第9期55卷 2056-2074页

作者： LI Jing ,WANG JunZheng,WANG ShouKun,MA LiLing & SHEN Wei key laboratory of complex system intelligent control and decision,School of Automation,Beijing Institute of Technology,Beijing 100081,China Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing China

Dynamic image stabilization precision of an optical image-stable device is a key technical ***,a fast dynamic image stabilization precision test system for an optical image-stable device is developed.A large-aperture collimator with a designed cross divisional board is used to simulate the infinity *** image-stable device is installed on the motion simulator with six degrees of freedom which is used to simulate the moving state of the *** CCD camera installed behind the eyepiece lens of the image-stable device acquires images rapidly and in real *** local energy maxima center of the cross light spot can be acquired accurately through the proposed algorithm using the Hessian *** addition,to deal with the CCD non-uniformity,an adaptive non-uniformity correction algorithm based on bi-dimensional empirical mode decomposition is *** actual test results for the proposed method show that the test error of dynamic image stabilization is less than 0.7,and the time for the frame image acquisition and processing is less than 10 ms,which demonstrates the effectiveness of the test system.

关键词： image stabilization precision adaptive non-uniformity correction empirical mode decomposition local energy maxima Hessian matrix

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Positioning accuracy of IGPS

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Journal of Harbin Institute of Technology(New Series) 2010年第2期17卷 219-224页

作者：于淼陈杰窦丽华甘明刚 School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

The positioning accuracy of a short-haul target-locating system,the inverse-GPS(IGPS) ,was analyzed in detail. The relationship between IGPS and the positioning error was discussed. The multiplicative error minimal bound of the geometric dilution of precision (GDOP) about the four-base-station IGPS was also investigated. In order to clarify the practical implementation of IGPS,the multiplicative and additive error factors which affect the positioning accuracy and theoretical estimation of positioning accuracy were presented. By analyzing the experiments of locating a target's position in virtual three-dimensional areas,the positioning performance of IGPS was illustrated. The results show that the multiplicative and additive error factors should be eliminated in IGPS to improve the positioning accuracy.

关键词： inverse-GPS(IGPS) GDOP positioning accuracy

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Safe RL-based Adaptive Cooperative Game control of Wing Deformation and Flight State Tracking for Morphing Hypersonic Vehicles

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Wang, Jun-Wei Wang, Feng Wu, Huai-Ning Liu, Zhou-Yang University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Hangzhou International Innovation Institute Hangzhou311115 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China

This study addresses the issue of adaptive cooperative game control (ACGC) design for wing deformation and flight state tracking of morphing hypersonic vehicles (MHVs) with variable wing shapes, input constraints and state constraints. To access a better flight control performance, the wing deformation parameter is extended in this work as an auxiliary control input. An oriented-coordinated-control nonlinear differential equation model is first established to describe the complicated longitudinal flight state tracking error dynamics of the MHV. Then, a control barrier function (CBF) is introduced and incorporated into the value function as a risk penalty term of state security constraint. Based on the differential game (DG) theory, the optimal coordinated control problem for the MHV with input constraints and state constraints is treated as a constrained cooperative DG that is further formulated as a Hamilton-Jacobi-Bellman (HJB) equation with barrier and hyperbolic functions. A safe RL algorithm is proposed to solve the above HJB equation and an online Pareto joint control strategy is achieved thereby. Hereafter the stability analysis of the closed-loop state tracking error system is done by the Lyapunov technique. Meanwhile, both state and input constraints are met during the the parameter learning regulation process. At last, a simulation study is performed to support the proposed safe RL-ACGC algorithm. © 2025 IEEE.

关键词： Hyperbolic functions

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Distributed stereoscopic rotating formation control of networks of second-order agents

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Journal of systems Engineering and Electronics 2013年第3期24卷 480-487页

作者： Li Song Qinghe Wu Di Yu Yinqiu Wang Key Laboratory of Complex System Intelligent Control and Decision(Ministry of Education) School of AutomationBeijing Institute of Technology School of Automation Beijing Institute of Technology

Distributed stereoscopic rotating formation control of networks of second-order agents is investigated. A distributed control protocol is proposed to enable all agents to form a stereoscopic formation and surround a common axis. Due to the existence of the rotating mode, the desired relative position between every two agents is time-varying, and a Lyapunov-based approach is employed to solve the rotating formation control problem. Finally, simulation results are provided to illustrate the effectiveness of the theoretical results.

关键词： multi-agent system collective motion stereoscopic rotating formation control.

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