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arXiv 2023年

作者： Zheng, Zhi Cai, Qifeng Wang, Jin Xu, Xinhang Cao, Muqing Yu, Huan Li, Jihao Meng, Jun Lu, Guodong State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Institute of Zhejiang University Zhejiang University Hangzhou310027 China Robotics Research Center of Yuyao City Ningbo315400 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh15217 United States Center for Data Mining and Systems Biology College of Electrical Engineering Zhejiang University Hangzhou310027 China

This paper presents the design, modeling, and experimental validation of CapsuleBot, a novel hybrid aerial-ground bi-copter robot designed for long-endurance and low-noise operations. CapsuleBot combines the maneuverability of a bi-copter in the air with the low power consumption and low noise of a two-wheel self-balancing robot on the ground. To achieve this, we design an innovative mechanical structure named the actuated-wheel-rotor, which uses a servo motor and a brushless motor to function as both a tilting rotor in the air and an actuated wheel on the ground. CapsuleBot is equipped with two actuated-wheel-rotors, enabling it to achieve hybrid aerial-ground propulsion using only four motors, with no additional motors required compared to a bi-copter. Additionally, we develop comprehensive dynamics and control systems for both air and wheel mode, based on the bi-copter model and the two-wheel self-balancing robot model. A prototype of CapsuleBot is constructed, and its performance in terms of low power consumption and low noise is validated through experiments. Challenging tasks demonstrate CapsuleBot’s capability to climb steep, fly over cliffs, and traverse rough terrains. Copyright © 2023, The Authors. All rights reserved.

关键词： Antenna grounds

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Detection of stealthy false data injection attacks against networked control systems via active data modification

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Information Sciences 2021年 546卷 192-205页

作者： Zhong-Hua Pang Lan-Zhi Fan Jian Sun Kun Liu Guo-Ping Liu Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology Beijing 100144 China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing 100081 China Department of Artificial Intelligence and Automation Wuhan University Wuhan 430072 China

This paper investigates the design and detection problems of stealthy false data injection (FDI) attacks against networked control systems from the different perspectives of an attacker and a defender, respectively. First, a Kalman filter-based output tracking control system is presented, where stealthy FDI attacks are designed for its feedback and forward channels so as to destroy the system performance while bypassing a traditional residual-based detector. Second, to successfully detect such two-channel stealthy attacks, an active data modification scheme is proposed, by which the measurement and control data are amended before transmitting them through communication networks. Theoretical analysis is then carried out for both ideal and practical cases to evaluate the effectiveness of the detection scheme. An interesting finding is that the attacks designed based on a false model obtained from those modified data can remain stealthy. Finally, simulation results are provided to validate the proposed attack design and detection schemes.

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Generalized Multi-kernel Maximum Correntropy Kalman Filter for Disturbance Estimation

arXiv

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arXiv 2023年

作者： Li, Shilei Shi, Dawei Lou, Yunjiang Zou, Wulin Shi, Ling The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The School of Automation Beijing Institute of Technology China The State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen518055 China Xeno Dynamics Control Department Xeno Dynamics Co. Ltd Shenzhen518055 China

Disturbance observers have been attracting continuing research efforts and are widely used in many applications. Among them, the Kalman filter-based disturbance observer is an attractive one since it estimates both the state and the disturbance simultaneously, and is optimal for a linear system with Gaussian noises. Unfortunately, The noise in the disturbance channel typically exhibits a heavy-tailed distribution because the nominal disturbance dynamics usually do not align with the practical ones. To handle this issue, we propose a generalized multi-kernel maximum correntropy Kalman filter for disturbance estimation, which is less conservative by adopting different kernel bandwidths for different channels and exhibits excellent performance both with and without external disturbance. The convergence of the fixed point iteration and the complexity of the proposed algorithm are given. Simulations on a robotic manipulator reveal that the proposed algorithm is very efficient in disturbance estimation with moderate algorithm complexity. Copyright © 2023, The Authors. All rights reserved.

关键词： Kalman filters

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An Improved Upper Bound on the Maximum Eigenvalue of Exponential Model Based Spatial Correlation Matrices in Massive MIMO systems 19

An Improved Upper Bound on the Maximum Eigenvalue of Exponen...

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19th IEEE International Conference on Communication Technology, ICCT 2019

作者： Gong, Tierui Yang, Guang Mu, Ke Zhao, Chun Yang, Zhijia Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781728105352

Massive Multiple-Input, Multiple-Output (MIMO) communications are considered as one of the most promising directions for the next generation communications and have attracted extensive research interests. The using of exponential model is recognized as an effective manner to describe the spatial correlation matrix in a spatially correlated MIMO channel for its simple form and accurate fitting on the experimental measurements. Based on this useful exponential model, an improved upper bound on the maximum eigenvalue of the spatial correlation matrix is given in this paper. Complying with the existing results, the proposed upper bound is also a function of the number of antennas and the absolute value of correlation coefficient. However, the proposed upper bound is obtained using a trace-based derivation, which is tighter than existing results in high spatial correlation massive MIMO systems. Simulations show that the proposed upper bound is closer to the true maximum eigenvalues for both uniform linear array and uniform planar array scenarios, which is expected to be widely used in massive MIMO systems. © 2019 IEEE.

关键词： Eigenvalues and eigenfunctions

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Locomotion control of a hybrid propulsion biomimetic underwater vehicle via deep reinforcement learning

Locomotion control of a hybrid propulsion biomimetic underwa...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Zhang, Tiandong Wang, Rui Wang, Yu Wang, Shuo Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9781665436786

This paper presents a novel deep reinforcement learning (DRL) method to solve the locomotion control problem of the biomimetic underwater vehicle (BUV) with hybrid propulsion, in order to meet the challenge of intractable multi-fins coordination and the complex hydrodynamic model. The system overview of the BUV, named RoboDact, with two flexible long fins and a double-joint fishtail as hybrid propulsion, is introduced. After that, the locomotion control problem is modeled as a Markov decision process (MDP) to be solved. Therefore, the locomotion control method based on soft actor-critic (SAC, a novel DRL algorithm) is proposed. The simulation environment is established based on the kinetic model for interaction. Finally, the feasibility and effectiveness of the proposed control method is demonstrated after extensive simulations. It will provide rich insights into the coordination control of biomimetic underwater vehicles. © 2021 IEEE.

关键词： Reinforcement learning

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Antenna Cross-correlation based Compressive Subspace Learning for Wideband Spectrum Sensing 19

Antenna Cross-correlation based Compressive Subspace Learnin...

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19th IEEE International Conference on Communication Technology, ICCT 2019

作者： Gong, Tierui Liu, Zhifeng Yang, Zhijia Wang, Gengshan Key Laboratory of Networked Control Systems State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781728105352

To address the performance degradation of wide-band spectrum sensing by sub-Nyquist sampling (SNS) in wireless fading channels, two compressive subspace learning (CSL) algorithms are proposed for signal subspace learning based on antenna cross-correlations for further improving the sensing performance. Both algorithms are developed based on different organizations of SNS samples, and both exploit space diversity and noise uncorrelations between antennas. We further establish the expressions for statistical covariance matrices (SCMs) obtained by SNS samples in the multi-antenna SNS cognitive radio system. Based on the derived SCM expressions, conditions to ensure SCMs without noise contamination are given. Simulations validate the derived conditions and show the improvement on sensing performance over related works. © 2019 IEEE.

关键词： Covariance matrix

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On the Robustness of Power IOT against Attack Based on General Framework

On the Robustness of Power IOT against Attack Based on Gener...

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Power and Energy Engineering (ICPEE), International Conference on

作者： Tianyu Wang Weiwei Miao Jianming Zhao Bowen Zhang Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China State Grid Jiangsu Electric Power Co. Ltd Information & Telecommunication Branch Nanjing China

ISBN: (纸本)9781665420471

Power Internet of Things (IOT) is the application of Internet of things in smart grid and the result of the development of information and communication technology to a certain stage. It will effectively integrate communication infrastructure resources and power system infrastructure resources, and improve the informationize level of power system. However, real-world complex systems are often vulnerable under disruptions. Power IOT is facing with different types of attack, which contains natural disasters and human intentional attacks. Motivated by this point, we propose a general framework of Power IOT robustness with different structures against diverse attacks. Evaluation on example IOT networks shows the effectiveness of our framework, and the characteristics of different structure against attacks. Our study contributes to a better understanding of Power IOT robustness, and reveals the designation of the Power IOT network improves the robustness of the network.

关键词： Robustness Power systems Smart grids Information and communication technology Internet of Things Complex systems

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Observer-based Dynamic Surface control for Robotic Manipulator with Fixed-time Convergence 7

Observer-based Dynamic Surface Control for Robotic Manipulat...

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7th International Conference on Information, Cybernetics, and Computational Social systems, ICCSS 2020

作者： Zhu, Chengzhi Zuo, Lei Wang, Ning Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou510640 China School of Electronic and Control Engineering Chang'an University Xi'an710064 China School of Information Engineering Chang'an University Xi'an710064 China

ISBN: (纸本)9781728162461

A state feedback dynamic surface tracking control algorithm is proposed for parametric linearized manipulator model in this paper. Different from ordinary finite-time control schemes, fixed-time convergence can be achieved in the proposed algorithm via both of high and low-degree terms in the controller such that the settling time can be preestablished by the designed parameters independent of the system initial conditions. Moreover, the problem of the 'explosion of complexity' and the singularity can be avoided by constructing an auxiliary controller with a first-order filter. The semi-global fixed-time uniform convergence of all the signals in the closed-loop system can be proved by Lyapunov theorem. In order to avoid the employment of acceleration signals and obtain better tracking performance during the procedure, a kind of observer based on uniform exact differentiators was used to compensate the uncertainties online. Finally the superiority of the proposed method has been verified by simulations based on a 2-DOF robot manipulator. © 2020 IEEE.

关键词： state feedback

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Multivariate time series forecast in industrial process based on XGBoost and GRU 9

Multivariate time series forecast in industrial process base...

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9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Zhai, Naiju Yao, Peifu Zhou, Xiaofeng Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China China Copper Co.LTD Kunming China

In this paper, a time series prediction model that merges eXtreme Gradient Boosting (XGBoost) and Gate Recurrent Unit (GRU), XGB-GRU model, is proposed for multivariate time series prediction in industry. The XGB-GRU model uses XGBoost's strong feature extraction capabilities to extract the hidden information of multiple control variables in industrial data. Next, the model uses GRU's unique gating unit to extract the timing information in the industrial data. Finally, the importance of XGBoost output variables to guide actual production and solve the problem of inexplicability of neural networks. Predicting the temperature of the heating furnace verifies that the proposed XGB-GRU is better than a single XGBoost and GRU model. And the model has a good fit to the predicted value. © 2020 IEEE.

关键词： Time series

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Low-noise analysis and design for the sensing system of the nanomanipulation robot by AFM

Low-noise analysis and design for the sensing system of the ...

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IEEE International Conference on robotics and Biomimetics

作者： Shuai Yuan Boyu Wu Kaixuan Wang Peng Yu school of Information & Control Engineering Shenyang Jianzhu University Shenyang Liaoning Province China Shenyang Jianzhu University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665481106

In this paper, through the noise analysis of the signal processing circuit of the photoelectric sensor, two noise reduction methods are proposed by reducing the feedback resistance of the transimpedance amplifier and integrating the overall signal processing circuit. These two noise reduction methods can reduce noise and improve the signal-to-noise ratio while ensuring that the topography signal of the item is unchanged. To verify the method in this paper, the scanning head design was optimized, the feasibility of the proposed scheme was verified by the thermal noise method and the 0-range scanning method, and finally, the roughness specification was analyzed.

关键词： Noise reduction Force Signal processing Robot sensing systems Thermal noise Thermal analysis Noise measurement

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