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检索条件"机构=State Key Laboratory of Intelligent Control and Management of Complex Systems"

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Path Following and Obstacle Avoidance control Based on Different Fuzzy Grains

Path Following and Obstacle Avoidance Control Based on Diffe...

引用

2015年中国智能自动化学术会议

作者： Yifei Kong Chaoyi Chen Yuequan Yang Zhiqiang Cao College of Information Engineering Yangzhou University State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

This paper presented a hierarchical fuzzy path following control scheme based on different fuzzy grain size in a class of unknown environment with static *** employing fine-grained fuzzy division and design of fuzzy rule table for the rotation angle and speed of a robot,a more accurate path following control was achieved,while more effective fuzzy obstacle avoidance was realized with coarse-grained fuzzy division *** proposed controller was a two-leveled architecture in which the higher level was the decision-making of the sub-task switching of path following or obstacle avoidance,while the lower level was motion control of path following and fuzzy obstacle ***,the simulation experiments were carried out to demonstrate the feasibility and effectiveness of the proposed scheme.

关键词： Robot Fuzzy control Path following Obstacle avoidance

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Optimal Cooperative control for Residential Multi-Battery systems Using Iterative Adaptive Dynamic Programming

Optimal Cooperative Control for Residential Multi-Battery Sy...

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第27届中国控制与决策会议

作者： Qinglai Wei Guang Shi Yu Liu Qiang Guan Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Institute of Automation Chinese Academy of Sciences

In this paper,an iterative adaptive dynamic programming(ADP) algorithm is developed to solve the optimal cooperative control problems for residential multi-battery *** avoid solving high-dimensional optimal control problems,we first constrain all the batteries at their worst performance,which transforms the multi-input optimal control problem into a single-input *** on the worst-performance optimal control law,the optimal cooperative control law for the residential multi-battery systems is obtained,where in each iteration,only a single-input optimization problem is ***,numerical results are given to illustrate the performance of the developed algorithm.

关键词： Adaptive critic designs,Adaptive dynamic programming,Approximate dynamic programming,Smart grid,Smart home,Optimal control.

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A Pdf-Free Change Detection Test for Data Streams Monitoring

A Pdf-Free Change Detection Test for Data Streams Monitoring

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Li Bu Dongbin Zhao Cesare Alippi The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Politecnico di Milano Milano Italy

ISBN: (纸本)9781479975617

We experience changes in stationarity/time variance in many practical applications. Since changes modify the operational framework the application is working with, its accuracy performance is in turn affected. When changes can occur, we need to detect them as soon as possible, in general by inspecting features extracted from data, and afterwards intervene to mitigate their effects. In this paper, we propose a novel change detection test based on the least squares density difference estimation. Neither assumptions about the distribution of features are needed, nor the change types are made (the method is pdf-free and can handle arbitrary changes.). What here proposed requires limited data to become operational and thresholds needed to assess the change can be set met to predefined false positive rates. We show through comprehensive experiments the effectiveness of the detection method and point out how it outperforms other related methods.

关键词： Training Monitoring Feature extraction Probability density function Kernel Least squares approximations Estimation

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A New Second-order Fuzzy control Scheme for Dynamic Obstacle Avoidance

A New Second-order Fuzzy Control Scheme for Dynamic Obstacle...

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第27届中国控制与决策会议

ISBN: (纸本)9781479970186

For the dynamic obstacle avoidance problem in a unknown environment,a second-order fuzzy control strategy is proposed based on fuzzy *** the observation and analysis of the perception information of the delta speed and the delta deviation angle of a detected dynamic obstacle,the robot then make decision to efficiently avoid dynamical ***,a two hierarchical control scheme is designed,where the upper level is to determine the deflection angle according to delta of speed and direction of dynamic obstacles,and the lower one is to derive the speed of a robot by employing the output of the upper level and the distance between the robot and dynamic *** simulations are demonstrated that the proposed scheme is effective and efficient.

关键词： robot dynamic obstacle avoidance fuzzy control

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Shared control for teleoperation enhanced by autonomous obstacle avoidance of robot manipulator

Shared control for teleoperation enhanced by autonomous obst...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Xinyu Wang Chenguang Yang Hongbin Ma Long Cheng Centre for Robotics and Neural Systems Plymouth University Plymouth UK State Key Lab of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Ministry of Education South China University of Technology Guangzhou China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

In this paper, a human robot shared control strategy is developed and tested on a Baxter robot. Using the proposed method, the human operator only needs to consider the motion of the end-effector of the manipulator, while the manipulator will avoid obstacle by itself without sacrificing the end effector motion performance. An improved obstacle avoidance strategy based on the joint space redundancy of the manipulator is designed. A dimension reduction method is presented to solve the over defined problem of avoiding velocity to achieve a more efficient use of the redundancy. By employment of an artificial parallel system of the teleoperate manipulator and the task switching weighting factor, the proposed control method enable the robot restoring back to the commanded pose smoothly when the obstacle is removed. By implementing the dimension reduction method, the trajectory of each joint of the manipulator can be controlled at the same time to achieve the restoring task. Thus, the proposed control method can eliminate the impact of the obstacle on the remaining task. Satisfactory experiment results demonstrate the effectiveness of the proposed methods.

关键词： Manipulators Collision avoidance Robot kinematics Trajectory Kinematics Robot sensing systems

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Data-Driven Room Classification for Office Buildings Based on Echo state Network

Data-Driven Room Classification for Office Buildings Based o...

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第27届中国控制与决策会议

作者： Guang Shi Qinglai Wei Yu Liu Qiang Guan Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781479970186

In this paper,based on echo state network(ESN),a data-driven method is developed to solve the room classification problem of office *** developed method is divided into two *** the data of electricity consumption,which are classified into electricity consumption from sockets,lights and air-conditioners for a typical room in an office building,the first step is to reconstruct the behavior of electricity consumption in three types by using three *** second step is to classify the room into a certain category of office room,computer room,storage room and meeting room by establishing another *** developed method fully utilizes the outstanding performance of ESN in chaotic time-series prediction and *** study on an office building illustrates the accuracy and effectiveness of the developed method.

关键词： Data-driven room classification,Office buildings,Electricity consumption,Neural networks,Echo state network.

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On Finite-Horizon Optimal control of First-Order Plus Time Delay systems

On Finite-Horizon Optimal Control of First-Order Plus Time D...

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第27届中国控制与决策会议

作者： Dawei Shi Tongwen Chen State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Department of Electrical and Computer Engineering University of Alberta

In this work,a finite-horizon optimal control problem for first-order plus time delay(FOPTD) processes is *** show that if the control horizon is greater than three and the prediction horizon is great than the control horizon plus the time delay in discrete time,the optimal controller is not affected by either of the two ***,under these conditions,the controller parameters are explicitly calculated,the closed-loop system is shown to be stable,and the controller is *** problem considered is related to the results on linear quadratic regulation of linear systems with time delays;however,the detailed parameterization of the state-space model introduced by the FOPTD process provides an additional opportunity to investigate the exact controller structure and properties(e.g.,the locations of the closed-loop poles),which are also the major difficulties encountered and overcome in this *** problem is motivated from phenomena experienced in designing industrial model predictive control(MPC) tuning algorithms,and extensive numerical examples indicate that the proposed results speed up the MPC autotuning algorithms by 70%.

关键词： Optimal control First-order plus time delay process Performance visualization MPC tuning

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Multi-Scale Wavelet Kernel Extreme Learning Machine for EEG Feature Classification

Multi-Scale Wavelet Kernel Extreme Learning Machine for EEG ...

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IEEE International Conference on Cyber Technology in Automation, control, and intelligent systems

作者： Qi Liu Xiao-guang Zhao Zeng-guang Hou Hong-guang Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation CAS Institute of crime Chinese People's Public Security University

ISBN: (纸本)9781479987313

In this paper, the principle of the kernel extreme learning machine (ELM) is analyzed. Based on that, we introduce a kind of multi-scale wavelet kernel extreme learning machine classifier and apply it to electroencephalographic (EEG) signal feature classification. Experiments show that our classifier achieves excellent performance.

关键词： EEG classification ELM Multi-scale wavelet kernel Elm Ecosystem models Learning machines eeg feature Classifiers multi-scale Seeds wavelets Kernel

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RBF neural network identifier based constrained optimal guidance for Mars entry vehicles

RBF neural network identifier based constrained optimal guid...

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International Conference on Information Science and Technology (ICIST)

作者： Teng-Hai Qiu Biao Luo Huai-Ning Wu Lei Guo Science and Technology on Aircraft Control Laboratory Beijing University of Aeronautics and Astronautics Beijing China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

In this paper, a radial basis function (RBF) neural network (NN) identifier based approximate constrained optimal guidance law is proposed for Mars entry vehicles guidance. Firstly, an RBF NN identifier is used to identify the system uncertain parameters. With the identified parameters, the optimal guidance problem of Mars entry vehicles is transformed into an optimal tracking control one, which depends on the solution of the Hamilton-Jacobi-Bellman (HJB) equation. Due to the control input constraints, a generalized non-quadratic performance function is proposed. In general, the HJB equation is a nonlinear partial differential equation that is difficult or even impossible to be solved analytically. We use an NN to solve the HJB equation approximately. Finally, the Monte-Carlo simulation results on the Mars entry vehicles demonstrate the effectiveness of the proposed method.

关键词： Artificial neural networks Indexes Mathematical model

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A Vision-Based Recognition Method for Transformer Based on AdaBoost and Multi-Template Matching

A Vision-Based Recognition Method for Transformer Based on A...

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IEEE International Conference on Cyber Technology in Automation, control, and intelligent systems

作者： Yang Wu Hongkai Chen Xiaoguang Zhao Yongjie Zhai School of Control and Computer Engineering North China Electric Power University The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781479987313

With the smart monitoring being widely concerned recently, substations have been introducing smart monitoring system. In this paper, we propose a vision-based recognition method for transformers in substation via combining with AdaBoost and a multi-template matching method. The proposed method works by dividing the whole process into two parts, namely coarse detection and fine recognition. In coarse detection, haar features of training samples in each sub-region are extracted and then AdaBoost algorithm is utilized for training and detecting. After coarse detection, we then perform fine recognition using multi-template matching with histogram intersection. Experimental results demonstrate that our method has a higher recognition precision and it is superior and more effective than the conventional AdaBoost method.

关键词： Transformer recognition Haar-like features AdaBoost Multi-template matching Transformer ADABOOST Recognition (Psychology) TEMPLATE MATCHING subregion Substations monitoring systems

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