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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Chen, Guangrong Wang, Junzheng Wang, Lipeng Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology BeijingCO 100081 China

ISBN: (纸本)9783902823625

For biped robot, friendly environment interaction makes sense. In this paper, a new method to plan the gait and control a biped robot on stairs with desired ZMP is proposed first. The desired ZMP derived from an iterative optimal algorithm not only has enough stability margin and satisfies actuator specifications, but also is available to implement and energy saving. Then, a controller with force sensing and variable impedance is proposed, which can sense and compensate the environmental disturbance well. Finally, the effectiveness of the proposed methods is confirmed by simulation examples. © IFAC.

关键词： Compliance control

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Artillery position control through auto disturbance rejection controller based on fuzzy control

Artillery position control through auto disturbance rejectio...

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2013 5th International Conference on intelligent Human-Machine systems and Cybernetics, IHMSC 2013

作者： Peng, Ning Bai, Yongqiang Luo, Hao Bai, Junlong Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology School of Automation Beijing China

ISBN: (纸本)9780769550114

Considering the characteristics of manipulation and collimation control in traction artillery control system, complex mathematic model, uncertainty and nonlinearity, ADRC (Active Disturbance Rejection controller) with Fuzzy control strategy as position controller was adopted and solved the difficult to adjust the parameters and weak anti-interference in practical engineering application. Through tests, it was shown that the controller was robust and met with the requirement of campaign system to quickly move the target to the given position with high reliability and high precision. © 2013 IEEE.

关键词： controllers

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Event-Trigger Extended Kalman Filter Design for Distributed Generation Network with Limited Communication 36

Event-Trigger Extended Kalman Filter Design for Distributed ...

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第36届中国控制会议

作者： Xing Xin Luyu Li Sen Li Zhen Li Jian Li Zhen Chen Xiangdong Liu Beijing Institute of Electronic System Engineering School of Automation & Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781538629185

For distributed generation(DG) network, it is important to estimate the real-time states. The information-centric networking(ICN) is established to take charge of the communication of DG network. However, the assumption of ideal communication between sensors and the estimation center cannot be guaranteed due to the communication constraints of ICN with the increasing DG network. A conventional algorithm, which reduces the communication burden in ICN, is to drop the observation of each smart grid in a random way. However, the accuracy of this algorithm recession decays rapidly with the increasing drop rate. To guarantee an appropriate estimation accuracy when the drop rate increases, this paper introduces the event-trigger strategy into the estimation algorithm. An event-trigger extended kalman filter(ET-EKF) is established in this paper to adapt the nonlinearity of DG system. ET-EKF reduces the communication burden and achieves an appropriate estimation accuracy at the same time. Finally, its feasibility and performance are demonstrated using the standard IEEE 39-bus system with phasor measurement units(PMUs).

关键词： Event-trigger extended Kalman filter(ET-EKF) real-time estimation distributed generation network smart grids phasor measurement unit(PMU)

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Evolutionary decision-makings for the dynamic weapon-target assignment problem

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Science in China(Series F) 2009年第11期52卷 2006-2018页

作者： CHEN Jie1,2, XIN Bin1,2, PENG ZhiHong1,2, DOU LiHua1,2 & ZHANG Juan1,2 1 School of Automation, Beijing Institute of Technology, Beijing 100081, China 2 key laboratory of complex system intelligent control and decision, Ministry of Education, Beijing 100081, China School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

The dynamic weapon-target assignment （DWTA） problem is an important issue in the field of military command and control. An asset-based DWTA optimization model was proposed with four kinds of constraints considered, including capability constraints, strategy constraints, resource constraints and engagement feasibility constraints. A general ＂virtual＂ representation of decisions was presented to facilitate the generation of feasible decisions. The representation is in essence the permutation of all assignment pairs. A construction procedure converts the permutations into real feasible decisions. In order to solve this problem, three evolutionary decision-making algorithms, including a genetic algorithm and two memetic algorithms, were developed. Experimental results show that the memetic algorithm based on greedy local search can generate obviously better DWTA decisions, especially for large-scale problems, than the genetic algorithm and the memetic algorithm based on steepest local search.

关键词： decision-making dynamic weapon-target assignment （DWTA） military command and control evolutionary computation memetic algorithms constraints handling

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New advances in complex motion control for single robot systems and multi-agent systems

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Science China(Technological Sciences) 2016年第12期59卷 1963-1964页

作者： FANG Hao LU Shao Lei CHEN Jie School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081China

CHEN Jie,email：chenjie@***

关键词： robot advances email cooperation simplified decomposed scenarios classic climbing obstacles

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A Dual-Motor Joint Model for Humanoid Robots

A Dual-Motor Joint Model for Humanoid Robots

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第25届中国控制与决策会议

作者： Jingtao Xue Xiaopeng Chen Ye Tian Zhangguo Yu Fei Meng Qiang Huang IRI School of Mechatronic Engineering Beijing Institute of Technology Key Laboratory of Biomimetic Robots and Systems Ministry of Education Key Laboratory of Intelligent Control and Decision of Complex System

ISBN: (纸本)9781467355339

To make humanoid robots walking fast, it's important to improve driving force of their leg joints. Usually, each joint of humanoid robots is driven by a single motor. Dual-motor joint, on the other hand, is one of the candidate solutions to meet the power requirement needed for fast walking. This paper proposed a new dual-motor control model. In the model, two motors are treated as a single control plant instead of two parallel control plants. With the usage of current distributor, the control model can pump different current to each motor freely so as to eliminate the unbalance of the load imposed on each motor. Simulation and experiment show that the proposed model works well under high joint load and it can be used on a fast walking humanoid robot.

关键词： Humanoid robot, dual motor, control model

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Trajectory Tracking Strategy for Gliding Hypersonic Vehicle with Aileron Stuck at an Unknown Angle

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Journal of Beijing Institute of Technology 2019年第3期28卷 447-455页

作者： Haibo Ji Lei Wang School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Intelligent Control and Decision of Complex Systems Ministry of EducationBeijing 100081China

A nonlinear robust trajectory tracking strategy for a gliding hypersonic vehicle with an aileron stuck at an unknown position is presented in this paper. First, the components of translational motion dynamics perpendicular to the velocity are derived, and then a guidance law based on a time-varying sliding mode method is used to realize trajectory tracking. Furthermore, the rotational equations of motion are separated into an actuated subsystem and an unactuated subsystem. And an adaptive time-varying sliding mode attitude controller is proposed based on the actuated subsystem to track the command attitude and the tracking performance and robustness are therefore enhanced. The proposed guidance law and attitude controller make the hypersonic vehicle fly along the reference trajectory even when the aileron is stuck at an unknown angle. Finally, a hypersonic benchmark platform is used to demonstrate the effectiveness of the proposed strategy.

关键词： trajectory tracking stuck aileron time-varying sliding mode

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Multiple moving objects detection based on level set and shadow information

Multiple moving objects detection based on level set and sha...

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International Conference on Measuring Technology and Mechatronics Automation

作者： Li, Jing Wang, Junzheng Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9780769542966

In multiple moving object detection, the connection between objects and shadow always leads to the failure of object detection. To solve this problem, a new object extraction algorithm using level set is proposed and applied to detect moving vehicle in intelligent monitoring of motorway. Moving information is extracted via symmetrical difference and used in the velocity function of level set. After the first segmentation, information of object location is found. According to difference between object and shadow, velocity function is modified. After the second segmentation multiple objects and their shadow are separate. Experimental results show that the proposed algorithm is able to extract accurate contour of object effectively. Its processing speed is 24 fps and accuracy rate of shadow elimination reaches 98.6%. © 2011 IEEE.

关键词： Object detection

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Unsupervised robust adaptive filtering against impulsive noise

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Journal of systems Engineering and Electronics 2012年第1期23卷 32-39页

作者： Tao Ma Jie Chen Wenjie Chen Zhihong Peng School of Automation Beijing Institute of Technology Beijing 100081 R R. China Key Laboratory of Complex System Intelligent Control and Decision （Ministry of Education） Beijing Institute of Technology Beijing 100081 P. R. China

An implementation of adaptive filtering, composed of an unsupervised adaptive filter （UAF）, a multi-step forward linear predictor （FLP）, and an unsupervised multi-step adaptive predictor （UMAP）, is built for suppressing impulsive noise in unknown circumstances. This filtering scheme, called unsupervised robust adaptive filter （URAF）, possesses a switching structure, which ensures the robustness against impulsive noise. The FLP is used to detect the possible impulsive noise added to the signal, if the signal is ＂impulse-free＂, the filter UAF can estimate the clean sig- nal. If there exists impulsive noise, the impulse corrupted samples are replaced by predicted ones from the FLP, and then the UMAP estimates the clean signal. Both the simulation and experimental results show that the URAF has a better rate of convergence than the most recent universal filter, and is effective to restrict large disturbance like impulsive noise when the universal filter fails.

关键词： adaptive filtering unsupervised form impulse insen- sitive switching structure.

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Statistical learning makes the hybridization of particle swarm and differential evolution more efficient-A novel hybrid optimizer

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Science in China(Series F) 2009年第7期52卷 1278-1282页

作者： CHEN Jie1,2,XIN Bin1,2,PENG ZhiHong1,2 & PAN Feng1,2 1 School of Automatic control,Beijing Institute of Technology,Beijing 100081,China 2 key laboratory of complex system intelligent control and decision,Ministry of Education,Beijing 100081,China 1. School of Automatic Control Beijing Institute of Technology Beijing 100081 China 2. Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics differential evolution （DE） and particle swarm optimization （PSO）. In the hybrid denoted by DEPSO, each individual in one generation chooses its evolution method, DE or PSO, in a statistical learning way. The choice depends on the relative success ratio of the two methods in a previous learning period. The proposed DEPSO is compared with its PSO and DE parents, two advanced DE variants one of which is suggested by the originators of DE, two advanced PSO variants one of which is acknowledged as a recent standard by PSO community, and also a previous DEPSO. Benchmark tests demonstrate that the DEPSO is more competent for the global optimization of multimodal functions due to its high optimization quality.

关键词： global optimization statistical learning differential evolution particle swarm optimization hybridization multimodal functions

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