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Novel algorithm of gait planning of hydraulic quadruped robot to avoid foot slidingand reduce impingement

Journal of Beijing Institute of Technology 2016年第1期25卷 91-99页

作者：马立玲杨超峰王立鹏王军政 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

In order to solve kinematic redundancy problems of a hydraulic quadruped walking robot,which include leg dragging,sliding,impingement against the ground,an improved gait planning algorithm for this robot is proposed in this ***,the foot trajectory is designated as the improved composite cycloid foot ***,the landing angle of each leg of the robot is controlled to satisfy friction cone to improve the stability performance of the *** with the controllable landing angle of quadruped robot and a geometry method,the kinematic equation is derived in this ***,agait planning method of quadruped robot is proposed,a dynamic co-simulation is done with ADAMS and MATLAB,and practical experiments are *** validity of the proposed algorithm is confirmed through the co-simulation and *** results show that the robot can avoid sliding,reduce impingement,and trot stably in trot gait.

关键词： landing angle gait planning foot trajectory friction cone sliding impingement

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Localization and mapping in urban area based on 3D point cloud of autonomous vehicles

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Journal of Beijing Institute of Technology 2016年第4期25卷 473-482页

作者：王美玲李玉杨毅朱昊刘彤 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

In order to meet the application requirements of autonomous vehicles, this paper proposes a simultaneous localization and mapping （SLAM） algorithm, which uses a VoxelGrid filter to down sample the point cloud data, with the combination of iterative closest points （ICP） algorithm and Gaussian model for particles updating, the matching between the local map and the global map to quantify particles＇ importance weight. The crude estimation by using ICP algorithm can find the high probability area of autonomous vehicles＇ poses, which would decrease particle numbers, increase algorithm speed and restrain particles＇ impoverishment. The calculation of particles＇ importance weight based on matching of attribute between grid maps is simple and practicable. Experiments carried out with the autonomous vehicle platform validate the effectiveness of our approaches.

关键词： simultaneous localization and mapping （SLAM） Rao-Blackwellized particle filter （ RB-PF） VoxelGrid filter ICP algorithm Gaussian model urban area

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Optimal Tuning of Plant-Friendly PID controllers

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Journal of Beijing Institute of Technology 2010年第3期19卷 331-336页

作者：史大威王军政马立玲 Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology

A plant-friendly proportional-integral-derivative （PID） controller optimization framework is proposed to make tradeoffs among set-point response,controller output variations and *** objective function is chosen as the weighted sum of the integral of squared time-weighted error and the integral of squared timeweighted derivative of the control variable with respect to set-point response,while the robustness of the system is guaranteed by constraints on gain and phase *** to the complex structure of the constraints,the problem is solved by genetic *** analysis show the proposed method could efficiently reduce the controller output variations while maintaining a short settling *** on the simulation results,iterative tuning rules for the weighting factor in the objective function are obtained,which allows efficient simple proportional-integral（PI） tuning formulae to be derived.

关键词： PID control plant-friendliness genetic algorithm constrained optimization

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Deep reinforcement learning for optimal denial-of-service attacks scheduling

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Science China(Information Sciences) 2022年第6期65卷 98-106页

作者： Fangyuan HOU Jian SUN Qiuling YANG Zhonghua PANG State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology

We consider an optimal denial-of-service(DoS) attack scheduling problem of N independent linear time-invariant processes, where sensors have limited computational capability. Sensors transmit measurements to the remote estimator via a communication channel that is exposed to DoS attackers. However,due to limited energy, an attacker can only attack a subset of sensors at each time step. To maximally degrade the estimation performance, a DoS attacker needs to determine which sensors to attack at each time step. In this context, a deep reinforcement learning(DRL) algorithm, which combines Q-learning with a deep neural network, is introduced to solve the Markov decision process(MDP). The DoS attack scheduling optimization problem is formulated as an MDP that is solved by the DRL algorithm. A numerical example is provided to illustrate the efficiency of the optimal DoS attack scheduling scheme using the DRL algorithm.

关键词： optimal denial-of-service attack scheduling optimization limited energy deep reinforcement learning

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Spiking Neural Network for Intra-cortical Brain Signal Decoding

arXiv

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arXiv 2025年

作者： Yang, Song Fu, Haotian Zhang, Herui Zhang, Peng Li, Wei Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Brain-inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China Department of Biomedical Engineering College of Life Science and Technology Huazhong University of Science and Technology Wuhan430074 China

Decoding brain signals accurately and efficiently is crucial for intra-cortical brain-computer interfaces. Traditional decoding approaches based on neural activity vector features suffer from low accuracy, whereas deep learning based approaches have high computational cost. To improve both the decoding accuracy and efficiency, this paper proposes a spiking neural network (SNN) for effective and energy-efficient intra-cortical brain signal decoding. We also propose a feature fusion approach, which integrates the manually extracted neural activity vector features with those extracted by a deep neural network, to further improve the decoding accuracy. Experiments in decoding motor-related intra-cortical brain signals of two rhesus macaques demonstrated that our SNN model achieved higher accuracy than traditional artificial neural networks;more importantly, it was tens or hundreds of times more efficient. The SNN model is very suitable for high precision and low power applications like intracortical brain-computer interfaces. © 2025, CC BY.

关键词： Deep neural networks

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control of Bilateral Teleoperation with Time Delay Considering Operator Force Sending 34

Control of Bilateral Teleoperation with Time Delay Consideri...

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第三十四届中国控制会议

作者： QIN Yongming XIA Yuanqing School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology

ISBN: (纸本)9781467374439

Force reflection methods are widely used in teleoperation with force sensors on slave manipulator. However, force sensors would impair manipulator structure and may be installed or maintained difficultly on slave site. Additionally, in some tasks operator pays more attention to control the exerted force on environment than to fell the reflection force. Considering these factors, a force sending method is proposed in this paper with force sensors installed only on master manipulator. Adjusted virtual force is provided to operator on master site. Operator force sending and slave manipulator position tracking are achieved without conflict on slave site. Stability analysis is presented based on ISS(input-to-state stability) method and numerical simulations are given to show the effectiveness.

关键词： bilateral teleoperation,time delay,force sending,position tracking,contact force

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A Mobility Based Clustering Algorithm in MANETs Utilizing Learning Automata

A Mobility Based Clustering Algorithm in MANETs Utilizing Le...

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第三十二届中国控制会议

作者： GAO Xun School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (纸本)9781479900305

There being ample research in cluster-based Media Access control(MAC) protocols for Mobile Ad Hoc Networks (MANETs) recently makes it necessary having a stable clustering algorithm developed for *** in MANETs often have highly mobility and sometimes present the characteristic of group *** the innovation perspective,we proposed a clustering algorithm by employing Learning Automata(LA) in a distributed manner considering nodes distance and nodes mobility to produce stable *** utilizing LA nodes can make intelligent and adaptive decisions based on the local information collected in the past *** to another mobility based clustering algorithm,simulation results present us the superior performance of the proposed algorithm.

关键词： Ad Hoc clustering mobility Learning Automata

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Multi-sensor optimal distributed weighted Kalman filter fusion over unreliable networks 35

Multi-sensor optimal distributed weighted Kalman filter fusi...

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第35届中国控制会议

作者： XING Zirui XIA Yuqing Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

ISBN: (纸本)9781509009107

This paper presents the problem of optimal distributed weighted Kalman filter fusion for a class of multi-sensor unreliable networked systems with uncorrelated *** distributed multi-sensor data fusion system suffers measurements delay or loss due to unreliability of networked systems with uncorrelated *** the addressed model,an optimal local Kalman filter with a finite buffer is derived for each subsystem,which can also be used as a centralized optimal Kalman filter fusion *** on the new optimal local Kalman filter,multi-sensor optimal distributed weighted Kalman filter fusion with finite buffers has been ***,compared with the centralized optimal Kalman filter fusion algorithm,the proposed distributed weighted Kalman filter fusion algorithm developed in this paper has stronger fault-tolerance *** results are provided to illustrate the effectiveness of the proposed approaches.

关键词： Multi-sensor unreliable networked systems Distributed weighted Kalman filter fusion Network delay Buffers

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The Forecasting Research on the Model of the Hysteresis Brake based on Elman Multi-Hidden Layers Neural Network Algorithm with the Speed and Directional Factor 35

The Forecasting Research on the Model of the Hysteresis Brak...

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第35届中国控制会议

作者： ZHANG Bo SHEN Wei WANG Junzheng Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

ISBN: (纸本)9781509009107

Hysteresis brake,which provides for step-less torque and high speed,is a stable and reliable device used for loading,but with some problems,such as the large time-lag,strong nonlinearity,and difficulty in modeling et *** to the above-mentioned issues,the special working conditions of hysteresis brake developed by our project team and the advantage of the dynamical performance of the Elman Multi-Hidden Layers Neural Network,this paper employs modified neural network algorithm with Elman dynamic recursive structure to accomplish the model of hysteresis brake,and guarantees the accuracy of output loaded *** this algorithm,we introduce the speed,the given and desired torque,and a directivity factor respectively as a disturbance variable and two input vectors of the system,and then train the model and *** numerical results validate the effectiveness of the algorithm proposed.

关键词： Hysteresis brake strong nonlinearity neural network algorithm with Elman dynamic recursive structure

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Optimal Design of controllers Based on Libraries and Differential Evolution 34

Optimal Design of Controllers Based on Libraries and Differe...

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第三十四届中国控制会议

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

ISBN: (纸本)9781467374439

This paper presents a new method for optimal design of controllers based on a "library" thought and differential *** first an extensible component library and a performance criteria library are established in the *** component library contains different types of system components which may be essential for controller *** components can be selected from the library and then combined to form a controller with richer *** performance criteria library includes some common control performance *** can choose one from it according to performance ***,the differential evolution algorithm is utilized to optimize the parameters of each component in order to find the optimal solution and ultimately obtain the controller structure and parameters which meet *** were done on different types of control *** results show that the controllers designed by the proposed method for different types of control objects generally have better comprehensive performance than the PID controllers designed by conventional methods,differential evolution and genetic ***,stability and generalizability of the proposed method were also tested and verified.

关键词： controller Design Differential Evolution Component Library Performance Criteria Library

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