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arXiv 2023年

作者： Deng, Boyuan Sun, Jian Li, Zhuo Wang, Gang School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing100081 China

Continuous trajectory tracking control of quadrotors is complicated when considering noise from the environment. Due to the difficulty in modeling the environmental dynamics, tracking methodologies based on conventional control theory, such as model predictive control, have limitations on tracking accuracy and response time. We propose a Time-attenuating Twin Delayed DDPG, a model-free algorithm that is robust to noise, to better handle the trajectory tracking task. A deep reinforcement learning framework is constructed, where a time decay strategy is designed to avoid trapping into local optima. The experimental results show that the tracking error is significantly small, and the operation time is one-tenth of that of a traditional algorithm. The OpenAI Mujoco tool is used to verify the proposed algorithm, and the simulation results show that, the proposed method can significantly improve the training efficiency and effectively improve the accuracy and convergence stability. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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Supplier Selection Considering Interrelated Practices of Resilience and Sustainability: An Approach Based on Rough Set and Prospect Theory

SSRN

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SSRN 2023年

作者： Song, Wenyan Rong, Wan School of Economics and Management Beihang University Beijing100191 China Key Laboratory of Complex System Analysis Management and Decision Beihang University Ministry of Education Beijing100191 China

As the global risk of uncertainty continues to increase and the problem of environmental pollution and resource constraints intensifies, the modern supply chain requires even greater resilience and sustainability to withstand disruptions. This research develops a novel hybrid approach that uses sustainability and resilience practices as supplier selection criteria. Most of the previous supplier selection methods may neglect the correlations between sustainability and resilience practices, and they often ignore the bounded rationality and ambiguity of decision-makers' judgments, leading to inaccurate supplier selection results. To address these challenges, this paper proposes a novel framework for resilient sustainable supplier selection that integrates variable precision rough set theory, prospect theory, Choquet integral, and TOPSIS. The new method combines the strength of Choquet integral in modeling the interaction relationships between sustainability and resilience practices, the advantages of prospect theory in dealing with bounded rationality of decision-makers, and the superiority of variable precision rough set theory in flexibly handling vagueness. Finally, the proposed approach is validated by applying it to a real case study of selecting a resilient sustainable chip supplier for a communications equipment manufacturer. © 2023, The Authors. All rights reserved.

关键词： Sustainable development

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Data-Driven Discovery of Nonlinear Dynamical systems from Noisy and Sparse Observations

Data-Driven Discovery of Nonlinear Dynamical Systems from No...

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New Trends in Computational Intelligence (NTCI), International Conference on

作者： Wei Zhu Chao Pei Yulan Liang Zhang Chen Jingsui Li School of Science Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing China College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9798331517021

ISBN: (纸本)9798331517038

Sparse Identification of Nonlinear Dynamics (SINDy) is a data-driven algorithm for interpretability mod-eling. SINDy has a strong ability to learn dynamical systems from time series data. Sparse Identification of Nonlinear Dynamics (SINDy) can extract equations from data, but its performance will degrade when data has noise or sparse. In order to deal with this case, the idea of Monte Carlo Markov Chain (MCMC) is introduced, which is used to optimally select models. The SINDy with MCMC (MCMC-SINDy) can comprehensively discover model structures by employing random samples in data space. Simulation results show that MCMC-SINDy is more robust than SINDy with 1 % -15 % levels of noise or sparse 0.5. These results are promising for the discovery of governing equations for complex systems in neuroscience, power grids, epidemiology, finance or ecology, where governing equations have remained elusive. mportantly, compared to existing machine learning methods, the accuracy of modeling using MCMC SINDy is higher.

关键词： Neuroscience Biological system modeling Simulation Noise Time series analysis Mathematical models Power grids Nonlinear dynamical systems Noise measurement Periodic structures

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Asymptotic stability of fractional linear discrete-time equations with arbitrary time delays

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The European Physical Journal Special Topics 2025年 1-18页

作者： Liu, Chong Wu, Guo-Cheng Hou, Hu-Shuang School of Mathematics and Statistics Guizhou University Guiyang People’s Republic of China Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Chongqing People’s Republic of China School of Mathematical Sciences Sichuan Normal University Chengdu People’s Republic of China

This paper introduces a class of Caputo fractional difference equations with arbitrary time delays. It provides non-negative conditions of the Mittag-Leffler function solutions. Exact solutions of fractional linear difference equations are obtained by Picard’s method, and stability conditions are given by the Z-transform. Finally, such results are extended to h-fractional difference equations. This study reveals the time delay’s effect on the dynamics of fractional difference equations and the stable regions. It also provides necessary and sufficient conditions for neural networks and control.

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Identifying hidden critical elements in interconnected systems: An influence dynamics analysis approach considering structural constraints

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European Journal of Operational Research 2025年

作者： Zhou, Caibo Song, Wenyan Wang, Huiwen Wang, Lihong School of Economics and Management Beihang University Beijing 100191 China MOE Key Laboratory of Complex System Analysis and Management Decision Beihang University Beijing 100191 China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing 100029 China

The systems analysis field has traditionally focused on identifying the essential elements within an interconnected system and analyzing the cause-and-effect relationships among them. However, most decision-making methods in system analysis have been one-sided. They primarily rely on the interactions between elements to make decisions, neglecting to account for the non-uniform influence attenuation among elements and unequal importance diffusion. Furthermore, these two factors are closely tied to the topological structure of systems, which has been an often-overlooked aspect in previous research, leading to inaccurate identification and omission of hidden key elements. In response to these challenges, this paper introduces a novel method called SIDA (Structural-constrained Influence Dynamic analysis). We utilize structural constraint coefficients derived from structural hole theory to describe the non-uniform attenuation. Furthermore, we integrate an influence and distance-weighted PageRank algorithm to manage the unequal importance diffusion taking into account both the influence and the distance between elements within systems. We validated our proposed method through a comprehensive analysis of a pharmaceutical industry ecosystem, comparing its performance with previous approaches to validate its effectiveness and practicality. The case study results demonstrate that SIDA produces more reasonable element analysis and ranking outcomes. © 2025 Elsevier B.V.

关键词： systems analysis

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Manual Alignment of Dual End-Effectors for Piezo-Driven Microhand

Manual Alignment of Dual End-Effectors for Piezo-Driven Micr...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Jichao Pang Dan Liu Xiaoqing Tang Yan Chen Qiang Huang Tatsuo Arai Xiaoming Liu Beijing Advanced Innovation Center for Intelligent Robots and Systems and School of Mechatronical EngineeringBeijing Institute of Technology Key Laboratory of Biomimetc Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing China Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

In recent years, micromanipulator with dual end-effectors called microhand has been widely used in industrial and biological fields. Whether the tip positions of the two end-effectors of the microhand can be accurately aligned seriously affects the precise grasping of the microhand. However, few researchers have presented practical ways for precisely aligning the tip positions of a 6-DOF microhand’s two end- effectors. This paper proposes a novel, inexpensive, lightweight, robust, and easy-to-use microhand dual end-effectors clamping device that can precisely and quickly align the two end-effectors of a 6-DOF microhand. First, we describe the microhand dual end-effectors clamping device’s lightweight structural design. After that, we simplify the microhand dual end-effectors clamping device model and create a mathematical model to determine the relationship between the end-effectors’ tip position and the rotation angles of screw No.1, screw No.2, screw No.3 of the microhand dual end-effectors clamping device. Through experimentation, we are able to attain precise alignment of the two end-effectors tip positions of the 6-DOF microhand, so we confirm that our mathematical model is true. Finally, we use the impulse response of PZT in the microhand’s lower module to confirm the stability of the microhand dual end- effectors clamping device. We believe that the proposed the microhand dual end-effectors clamping device has great potential in industrial and biological applications as a universal tool for precise alignment of the tip positions of the two end-effectors of a 6-DOF microhand.

关键词： Costs Accuracy Fasteners End effectors 6-DOF Mathematical models Biology

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Self-Attention based Temporal Intrinsic Reward for Reinforcement Learning

Self-Attention based Temporal Intrinsic Reward for Reinforce...

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2021 China Automation Congress, CAC 2021

作者： Jiang, Zhuo Tian, Daiying Yang, Qingkai Peng, Zhihong The School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing China Peng Cheng Laboratory Guangdong Shenzhen China

ISBN: (纸本)9781665426473

This paper proposes a self-attention based temporal intrinsic reward model for reinforcement learning (RL), to synthesize the control policy for the agent constrained by the sparse reward in partially observable environments. This approach can solve the problem of temporal credit assignment to some extent and deal with the low efficiency of exploration. We first introduce a sequence-based self-attention mechanism to generate the temporary features, which can effectively capture the temporal property of the task for the agent. During the training process, the temporary features are employed in each sampled episode to elaborate the intrinsic rewards, which is combined with the extrinsic reward to help the agent learn a feasible policy. Then we use the meta-gradient to update this intrinsic reward model in order that the agent can achieve better performance. Experiments are given to demonstrate the superiority of the proposed method. © 2021 IEEE

关键词： Reinforcement learning

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Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation

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Chinese Journal of Electronics 2023年第3期19卷 451-456页

作者： Bo Li Wenju Liu Lihua Dou School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.

关键词： Training Image segmentation Analytical models Parameter estimation Estimation Probability density function Speech processing

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Acoustically Driven Micropipette for Hydrodynamic Manipulation of Mouse Oocytes

Acoustically Driven Micropipette for Hydrodynamic Manipulati...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Zhaofeng Zuo Xiaoming Liu Zhuo Chen Yuyang Li Xiaoqing Tang Dan Liu Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Micromanipulation techniques that can achieve controlled fine operations at the micro scale play an important role in biomedical fields including embryo engineering, gene engineering, drug screening, and cell analysis. However, micromanipulation of biological micro-objects, such as cells and micro tissues, suffers from mechanical damage and low efficiency. Several techniques have been introduced to manipulate cells more easily, but most of them are restricted by expensive devices, limited work area, and potential damage to cellular structure. Here we develop a hydrodynamic manipulation method to rotate and transport mouse oocytes, which utilizes acoustic waves and micropipette to generate acoustic radiation force and excite microstreaming. This method can accomplish rotational and translational operations precisely and controllably. We tested the process of trapping, rotation, and transportation of the mouse oocytes, and measured rotational and translational speed with a range of applied voltage. The method was able to shorten the cost time of delivery and posture adjustment before oocyte injection. Our study provides an easy-to-use technique for oocyte manipulation without contact, and it has the potential to be universally applied in many cellular studies.

关键词： Visualization Voltage measurement Three-dimensional displays Force Transportation Hydrodynamics Biology

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Exponential p-stability of stochastic impulsive fuzzy reaction-diffusion Cohen-Grossberg neural networks with mixed delays

Exponential p-stability of stochastic impulsive fuzzy reacti...

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Chinese Control and decision Conference, CCDC

作者： Weisong Zhou Sa Xiao Wei Zhu Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Chongqing P. R. China

ISBN: (纸本)9781665478977

In this paper, the pth moment exponential stability of a class of stochastic impulsive fuzzy reaction-diffusion Cohen-Grossberg neural networks (CGNNs) with mixed delays is studied. By means of the property of "M-cone", Lyapunov functional, Itô formula and Hanalay inequality techniques, sufficient conditions for exponential p-stability of our model are obtained. Finally, a simulation example is given to verify the validity of our result.

关键词： Sufficient conditions Stability Neural networks Switches Markov processes Control systems Delays

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