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Research Square 2021年

作者： Yi, Ming Dai, Shiqi Lu, Lulu Wei, Zhouchao Zhu, Yuan School of Mathematics and Physics China University of Geosciences Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences Hubei Wuhan430074 China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Ministry of Education Fudan University Shanghai200433 China

Temperature is an important environmental factor that all creatures depend on. Under the appropriate temperature, the neural system shows good biological performance. Based on an improved Hodgkin-Huxley (HH) neuron model considering temperature and noise, the ten-layers pure excitatory feedforward neural network and the ten-layers excitatory-inhibitory (EI) neural network are constructed to study the subthreshold signal propagation. It’s found that increasing temperature can restrain the signal propagation, and raise the noises intensity threshold where the failed signal propagation can transform into succeed signal propagation. Under the large noise, the signal propagation in network in different temperatures exhibits different anti-noise capabilities. There exists the saturation value of interlayer connection probability, that is, the signal propagation maintains constant when interlayer connection probability beyond a certain value. Moreover, in EI network with large noise, the network’s intrinsic oscillation activity will completely cover subthreshold signal, and block the signal propagation. The jumping phenomenon in the value of fidelity, which measures the similarity between input signal and output signal, appears in both pure excitatory network and EI network. This paper provides potential value for understanding the regulation of both temperature and noise in information propagation in neural network. © 2021, CC BY.

关键词： Backpropagation

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Design of a novel flexible assistive hand exoskeleton

Design of a novel flexible assistive hand exoskeleton

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Youth Academic Annual Conference of Chinese Association of automation (YAC)

作者： Guotao Li Long Cheng Zhengrun Gao Jilong Lu Yanjiang Zhao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The National Clinical Research Center for Aging and Medicine Fudan University Shanghai China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Harbin China Intelligent Machine Institute Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781665465373

Hand paralysis caused by stroke, spinal cord injury, or neurological trauma has a significant impact on the independence and quality of life of the patients. The hand exoskeleton can provide hand assistance and improve the patient’s grasp. In this article, a novel wearable flexible hand exoskeleton is proposed to assist users in activities of daily life. To create a simple and lightweight assistive hand exoskeleton, 3D printing is used to manufacture most of the components, and a remote drive system is designed to reduce the weight of the hand exoskeleton. A ball pair device and a slider device are used to ensure the freedom of the thumb and the adaptability of the hand exoskeleton to different hand sizes. Finally, the experiments are conducted to verify that the hand exoskeleton can achieve motion assistance.

关键词： Exoskeletons Thumb Metals Stroke (medical condition) Three-dimensional printing Motion capture Paralysis

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Interval prediction model of blast furnace gas utilization rate based on multi-time-scale

Interval prediction model of blast furnace gas utilization r...

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第三十九届中国控制会议

作者： Feng Yin Jianqi An Xiaoling Shen Takao Terano School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Chiba University of Commerce

Gas utilization rate（GUR） is an important indicator that reflects the state of a blast furnace（BF）. However, most researches only predict the point values of GUR, it is difficult for the operator to make corresponding operations. This paper presents an interval prediction model based on multi-time-scale to predict the GUR. First, this paper analyzes the impact of the burden distribution and the hot-blast supply on multi-time-scale of the blast furnace. Then, we build a multi-time-scale point prediction model based on support vector regression（SVR）. Next, an interval prediction model of multi-objective optimization based on interval prediction indicators and the point prediction model was proposed. Finally, some experiment results base on actual run data shows that the method predicts the GUR more effectively than the point prediction model based on single time scale.

关键词： Blast furnace Gas utilization rate Interval prediction Multi-time-scale Multi-objective optimization

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A Deep Reinforcement Learning Method with Action Switching for Autonomous Navigation

A Deep Reinforcement Learning Method with Action Switching f...

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第40届中国控制会议

作者： Zuowei Wang Xiaozhong Liao Fengdi Zhang Min Xu Yanmin Liu Xiangdong Liu Xi Zhang Rui wei Dong Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control Capital Aerospace Machinery Co. Ltd.

Stochastic policy-based deep reinforcement learning（DRL） has successfully gained the widespread application but demands plenty of stochastic exploration to learn the environment at the initial training *** the agent is exposed to more complex environment,not only is the methodology inefficient,but its performance may also suffer from the issue of high *** paper develops a framework to accelerate the training procedure and reduce the variance by introducing a stochastic switching network,which specifically allows the agent to choose between heuristic actions and actions output by proximal policy optimization（PPO） *** of starting from the random actions,the agent can be effectively guided by the heuristic actions so that the navigation capability of the agent can be rapidly *** vanilla policy gradient（VPG） algorithm is further utilized to train the switching network,which can be jointly trained with the baseline *** the experimental comparison with the baseline PPO in the customized maze environment with openAI Gym toolkit,our method greatly contributes to the more efficient execution of navigation task by means of the heuristic actions for guidance.

关键词： Robot navigation proximal policy optimization（PPO） deep reinforcement learning（DRL） Vanilla policy gradient（VPG） action switching

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A comparative study on evolutionary algorithms for the agent routing problem in multi-point dynamic task

A comparative study on evolutionary algorithms for the agent...

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作者： Lu, Sai Xin, Bin Dou, Lihua Wang, Ling School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Department of Automation Tsinghua University Beijing China

The agent routing problem in multi-point dynamic task (ARP-MPDT) proposed recently is a novel permutation optimisation problem. In ARP-MPDT, a number of task points are located at different places and their states change over time. The agent must go to the task points in turn to execute the tasks, and the execution time of each task depends on the task state. The optimisation objective is to minimise the time for the agent to complete all the tasks. In this paper, five evolutionary algorithms are redesigned and tried to solve this problem, including a permutation genetic algorithm (GA), a variant of the particle swarm optimisation (PSO) and three variants of the estimation of distribution algorithm (EDA). In particular, a dual-model EDA (DM-EDA) employing two probability models was proposed. Finally, comparative tests confirm that the DM-EDA has a stronger adaptability than the other algorithms though GA performs better for the large-scale instances. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Genetic algorithms

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Distributed Event-Triggered Algorithm for Convex Optimization with Coupled Constraints

arXiv

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arXiv 2022年

作者： Huang, Yi Zeng, Xianlin Meng, Ziyang Sun, Jian School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Precision Instrument Tsinghua University Beijing100084 China Chongqing Innovation Center Beijing Institute of Technology Chongqing401120 China

This paper develops a distributed primal-dual algorithm via event-triggered mechanism to solve a class of convex optimization problems subject to local set constraints, coupled equality and inequality constraints. Different from some existing distributed algorithms with the diminishing step-sizes, our algorithm uses the constant step-sizes, and is shown to achieve an exact convergence to an optimal solution with an O(1/k) convergence rate for general convex objective functions, where k > 0 is the iteration number. Moreover, by applying event-triggered communication mechanism, the proposed algorithm can effectively reduce the communication cost without sacrificing the convergence rate. Finally, a numerical example is presented to verify the effectiveness of the proposed algorithm. Copyright © 2022, The Authors. All rights reserved.

关键词： Convex optimization

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Calibration of agent-based model using reinforcement learning 1

Calibration of agent-based model using reinforcement learnin...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Song, Bing Xiong, Gang Yu, Songmin Ye, Peijun Dong, Xisong Lv, Yisheng Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China Fraunhofer Institute for Systems and Innovation Research Breslauer Germany

ISBN: (纸本)9781665433372

In the research and application of Agent-Based Models (ABM), parameter calibration is an important content. Based on the existing state transfer equations that link the micro-parameters and macro-states of the multi-agent system, this paper further proposes to introduce Reinforcement Learning when calibrating the parameters. The state transfer of the agent after learning is used to calibrate the micro-parameters of ABM, and the interaction between each agent and multiple other agents is expressed as the parameters of the agent. The application case study of population migration demonstrates that our method can achieve high accuracy and low computational complexity. © 2021 IEEE.

关键词： Autonomous agents

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Stacked Sparse Autoencoder based Automatic Detection of Ripples and Fast Ripples in Epilepsy

Stacked Sparse Autoencoder based Automatic Detection of Ripp...

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第三十九届中国控制会议

作者： Hongzhen Qin Min Wu Xiongbo Wan Yuxiao Du School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation Guangdong University of Technology

High frequency oscillations(HFOs) have been acknowledged as a putative biomarker of epileptic seizure onset zones(SOZs). Accurate detection of HFOs is significant for the preoperative localization of epileptic SOZs. In this paper, a new method is proposed to automatically detect ripples(Rs) and fast ripples(FRs) from intracranial electroencephalography(iEEG)in epilepsy. A moving-window technique is utilized to segment the filtered signals which are obtained by filtering the raw iEEG signals using two Chebyshev band-pass filters. Two stacked sparse autoencoder(SSAE) models are proposed to automatically detect Rs and FRs, respectively. By optimizing the parameters of the two SSAE models, our method yields higher sensitivity(88.9±2.4% for Rs and 83.2±2.5% for FRs) and higher specificity(92.3±2.8% for Rs and 86.1±2.8% for FRs) than other three methods do.

关键词： Epilepsy Intracranial electroencephalography Ripples Fast ripples Stacked sparse autoencoder

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Extended Dissipative control for Drill-String systems with Input Time-Varying Delays 38

Extended Dissipative Control for Drill-String Systems with I...

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第三十八届中国控制会议

作者： Chengda Lu Min Wu Luefeng Chen Aoxue Yang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Software and Electrical Engineering Swinburne University of Technology

ISBN: (纸本)9781728123295;9789881563972

The objective of this paper is to design an extended dissipative controller for drill-string systems by taking into account input time-delays. A multi-degree-of-freedom lumped parameter model is established for the drill-string and a state space model in perturbation coordinates is derived correspondingly. By using the Lyapunov-Krasovskii functional method, two sufficient conditions are provided to make extended dissipativity analysis of the drill-string and design a suitable extended dissipative controller for the system. The effectiveness of our results is verified through a numerical example.

关键词： Drill-string extended dissipative control time-delay

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Research on trajectory planning and motion control of 7-DoF sawyer manipulator 1

Research on trajectory planning and motion control of 7-DoF ...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Luo, Kun Xiong, Gang Wang, Yuxiao Hu, Bin Liu, Sheng Chen, Shichao Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijng China School of Artificial Intelligence University of Chinese Academy of Sciences Beijng China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Beijng China Qingdao Academy of Intelligent Industries Chinese Academy of Sciences Beijng China

ISBN: (纸本)9781665433372

Regarding human-machine collaborative task, generated trajectories of a robot manipulator should be able to avoid joint limits and singularities, but the 6 Degrees of Freedom(DoF) or lower DoF manipulators encounter difficulties in many schemes. In this paper, research is implemented on the methods of trajectory planning and motion control on the newly human-machine collaborative 7-DoF Sawyer manipulator. We try to pay more attention to these approaches and find a better combination between trajectory planners and motion controllers for Sawyer manipulator. First of all, comparison is proposed between the methods about trajectory planning in task space and joint space, drawing a conclusion that the latter has the advantage of quickness and smoothness on trajectories in real time. Next, we choose to plan trajectory in the joint space by interpolating positions and orientations. Three approaches, i.e., trapezoidal velocity trajectory, cubic polynomial trajectory and basic spline trajectory, are applied to interpolate positions. Experimental results show that it results in the smoothest trajectory using basic spline trajectory planning. We also compare linear and nonlinear orientation interpolations to address the angle wrapping issue, which leads to difficulties in smooth orientation interpolation between several waypoints. Combining polynomial trajectory planning methods with the proportional-derivative (PD) motion controller and the computed-torque motion controller, we focus on the performance of the two different combinations. It is found that trajectories with computed-torque controller have shorter path with a congruous convergence on joint position, and more accurate trajectories with less overshoots in position than others. © 2021 IEEE.

关键词： Motion control

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