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IEEE-RAS International Conference on Humanoid Robots

作者： Xuechao Chen Yuhang Zhou Qiang Huang Zhangguo Yu Gan Ma Libo Meng Chenglong Fu Key Laboratory of Intelligent Control and Decision of Complex System China Ministry of Education Key Laboratory of Biomimetic Robots and Systems China Intelligent Robotics Institute Beijing Institute of Technology Beijing China Department of Mechanical Engineering Tsinghua University Beijing

ISBN: (纸本)9781479971756

Both disturbance rejection and human-like motions, like toe-off and heel-strike, are important for a biped robot to enhance its performance. However, the required motions for them may influence each other, which is why few studies consider them simultaneously. This paper presents a method to realize stable walking with toe-off and heel-strike even when the robot experiences disturbances. We propose a walking controller which can constrain the desired ground reaction force. On the one hand, the controller can adjust the torso acceleration to make the supporting leg compliant with the external disturbances on the torso. On the other hand, it can rotate the supporting foot by adjusting the ZMP to an appropriate location. The linear inverted pendulum is utilized to generate the CoM trajectory and the foot placement. Meanwhile, its ZMP can be predefined as required so that the toe-off and heel-strike can be achieved by the controller. The effectiveness of the proposed method is demonstrated by simulations.

关键词： Legged locomotion Foot Torso Robot kinematics Acceleration Joints

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Distributed simulation system hierarchical design model based on quotient space granular computation

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Zidonghua Xuebao/Acta Automatica Sinica 2010年第7期36卷 923-930页

作者： Chen, Jie Wu, Di Zhang, Juan Department of Automation Beijing Institute of Technology Beijing 100081 China Education Ministry Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China VALORIA Laboratory Department of Computer Science and Technology University of South Brittany Vannes Cedex 56017 France

To answer the problem of ambiguous design levels for large-scale distributed simulation systems, this paper proposes a hierarchical system model based on the quotient space theory. This model consists of a system global design level, an architecture level, and a execution structure level to solve the problem of diverse levels on system design. Furthermore, we deeply analyze the relationship between the granules of different levels in both horizontal and vertical directions, and integratedly consider simulation tasks, resources and services. Finally, the model is verified based on a real simulation system design example, and the results illustrate that the flexibility and reusability of the system can be improved with the application of the hierarchical design model. Copyright © 2010 Acta Automatica Sinica. All rights reserved.

关键词： systems analysis

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Event-triggered Consensus control of Heterogeneous Multi-agent systems: Model- and Data-based Analysis

arXiv

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arXiv 2022年

作者： Wang, Xin Sun, Jian Wang, Gang Chen, Jie The School of Automation The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

This article deals with model- and data-based consensus control of heterogenous leader-following multi-agent systems (MASs) under an event-triggering transmission scheme. A dynamic periodic transmission protocol is developed to significantly alleviate the transmission frequency and computational burden, where the followers can interact locally with each other approaching the dynamics of the leader. Capitalizing on a discrete-time looped-functional, a model-based consensus condition for the closed-loop MASs is derived in form of linear matrix inequalities (LMIs), as well as a design method for obtaining the distributed controllers and event-triggering parameters. Upon collecting noise-corrupted state-input measurements during open-loop operation, a data-driven leader-following MAS representation is presented, and employed to solve the data-driven consensus control problem without requiring any knowledge of the agents' models. This result is then extended to the case of guaranteeing an H∞ performance. A simulation example is finally given to corroborate the efficacy of the proposed distributed event-triggering scheme in cutting off data transmissions and the data-driven design method. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

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Leader-Following Consensus of Discrete-Time Linear Multi-Agent systems with Communication Noises

Leader-Following Consensus of Discrete-Time Linear Multi-Age...

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第三十四届中国控制会议

作者： Yunpeng Wang Long Cheng Hongming Wang Zeng-Guang Hou Min Tan Hongnian Yu State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology China North Vehicle Research Institute Faculty of Science and Technology Bournemouth University

ISBN: (纸本)9781467374439

This paper studies the leader-following consensus problem of discrete-time generic linear multi-agent systems. Agents share their states with their neighbors via a noisy communication network. An algorithm is proposed for the leader-following consensus problem where the time-varying gain is employed to attenuate noises. Different from most previous results where all agents have to use the same time-varying gain, each agent can have its own time-varying gain. Sufficient conditions for solving the mean square leader-following consensus problem are obtained: 1) the communication topology graph has a spanning tree;2) the summation of every time-varying gain from zero to infinite is infinite;3) all time-varying gains are infinitesimal of the same order as time goes to infinity;and 4) all roots of a so-called "parameter polynomial" are inside the unit circle. Finally, a simulation example is given to verify the theoretical results.

关键词： Multi-Agent system,Leader-following consensus,Mean square,Communication noise.

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Power system state estimation via feasible point pursuit: Algorithms and Cramér-rao bound

Power system state estimation via feasible point pursuit: Al...

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作者： Wang, Gang Zamzam, Ahmed S. Giannakis, Georgios B. Sidiropoulos, Nicholas D. State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Department of Electrical and Computer Engineering University of Virginia CharlottesvilleVA22904 United States

Accurately monitoring the system's operating point is central to the reliable and economic operation of an autonomous energy grid. Power system state estimation (PSSE) aims to obtain complete voltage magnitude and angle information at each bus given a number of system variables at selected buses and lines. Power flow analysis amounts to solving a set of noise-free power flow equations, and is cast as a special case of PSSE. Physical laws dictate quadratic relationships between available quantities and unknown voltages, rendering general instances of power flow and PSSE nonconvex and NP-hard. Past approaches are largely based on gradient-type iterative procedures or semidefinite relaxation (SDR). Due to nonconvexity, the solution obtained via gradient-type schemes depends on initialization, while SDR methods do not perform as desired in challenging scenarios. This paper puts forth novel feasible point pursuit (FPP)-based solvers for power flow analysis and PSSE, which iteratively seek feasible solutions for a nonconvex quadratically constrained quadratic programming reformulation of the weighted least-squares (WLS). Relative to the prior art, the developed solvers offer superior numerical performance at the cost of higher computational complexity. Furthermore, they converge to a stationary point of the WLS problem. As a baseline for comparing different estimators, the Cramér-Rao lower bound is derived for the fundamental PSSE problem in this paper. Judicious numerical tests on several IEEE benchmark systems showcase markedly improved performance of our FPP-based solvers for both power flow and PSSE tasks over popular WLS-based Gauss-Newton iterations and SDR approaches. © 1991-2012 IEEE.

关键词： state estimation

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Online reinforcement learning control by direct heuristic dynamic programming: from time-driven to event-driven

arXiv

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arXiv 2020年

作者： Zhao, Qingtao Si, Jennie Sun, Jian Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing100081 China Department of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States

In this paper time-driven learning refers to the machine learning method that updates parameters in a prediction model continuously as new data arrives. Among existing approximate dynamic programming (ADP) and reinforcement learning (RL) algorithms, the direct heuristic dynamic programming (dHDP) has been shown an effective tool as demonstrated in solving several complex learning control problems. It continuously updates the control policy and the critic as system states continuously evolve. It is therefore desirable to prevent the time-driven dHDP from updating due to insignificant system event such as noise. Toward this goal, we propose a new event-driven dHDP. By constructing a Lyapunov function candidate, we prove the uniformly ultimately boundedness (UUB) of the system states and the weights in the critic and the control policy networks. Consequently we show the approximate control and cost-to-go function approaching Bellman optimality within a finite bound. We also illustrate how the event-driven dHDP algorithm works in comparison to the original time-driven dHDP. Copyright © 2020, The Authors. All rights reserved.

关键词： Learning algorithms

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Anti-skid foot design for a humanoid robot

Anti-skid foot design for a humanoid robot

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IEEE International Conference on Robotics and Biomimetics

作者： Haotian She Weimin Zhang Hulin Huang Zhangguo Yu Xuechao Chen Qiang Huang Ministry of Education under Grant 2014CX02004 Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (纸本)9781479973989

Stable walking of bipedal humanoid is an crucial and challenge issue of research in bipedal robots. And the structure of shoe sole plays a significant role in preventing someone from slipping in human life. The humanoid robot foot often skid while the robot is walking fast, and it may cause serious harmfulness. This study presents some foot pads for humanoid robot to improve its stability and reliability. First, anti-skid foot for a humanoid robot is proposed in this paper. Second, the material and pattern of foot pads are selected. Finally, the better foot pads are chosen by several experiments and the effectiveness of the new foot pads is confirmed by comparison experiments.

关键词： Foot Legged locomotion Humanoid robots Footwear Friction Rubber

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Data-Driven Model for Detection, Isolation and Accommodation of Faulty Angle of Attack Sensor Measurements in Fixed Winged Aircraft

Data-Driven Model for Detection, Isolation and Accommodation...

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Chinese control and decision Conference, CCDC

作者： Bemnet Wondimagegnehu Mersha Hongbin Ma School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665478977

Ethiopian Airlines’ Boeing 737-8 MAX nosedived and crashed shortly after takeoff on March 10, 2019, at Ejere Town, south of Addis Ababa. A faulty angle of attack (AOA) sensor was the cause of the crash. Many airplane accidents have been linked to faulty AOA sensors in the past. The majority of the AOA sensor fault detection, isolation, and accommodation (SFDIA) literature relied on linear model-driven techniques, which are not suitable when the system’s model is uncertain, complex, or nonlinear. Traditional multilayer perceptron (MLP) models have been employed in data-driven models in the literature and the effectiveness of deep learning-based data-driven models has not been investigated. In this work, a data collection and processing method that ensures the collected data is not monotonous and a data-driven model for AOA SFDIA is proposed. The proposed model uses a deep learning-based recurrent neural network (RNN) to accommodate for faulty AOA measurement under flight conditions with faulty AOA measurement, faulty total velocity measurement, and faulty pitch rate measurement. Conventional residual analysis with a fixed threshold is used to detect and isolate faulty AOA sensors. The proposed and benchmark models are trained with the adaptive momentum estimation (Adam) algorithm. We show that the proposed model effectively detects, isolates, and accommodates faulty AOA measurements when compared to other data-driven benchmark models. The method is able to detect and isolate faulty AOA sensors with a detection delay of 0.5 seconds for ramp failure and 0.1 seconds for step failure.

关键词： Adaptation models Recurrent neural networks Atmospheric modeling Fault detection Transportation Benchmark testing Velocity measurement

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Cooperative Pollution Supervising and Neutralization with Multi-actuator-sensor Network

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Acta Automatica Sinica 2011年第1期37卷 107-113页

作者： Wei SUN Li-Hua DOU Hao FANG School of Automation Beijing Institute of Technology Beijing 100081 P.R. China Key Laboratory of Complex System Intelligent Control and Decision (Beijing Institute of Technology) Ministry of Education Beijing 100081 P.R. China

The present work considers a scenario that a multi-actuator-sensor network neutralizes poisonous gas and tracks the pollution sources in a bounded area. A novel algorithm is proposed to minimize the system information uncertainty while reaching balance on the workload of actuators. The method combines the centroidal Voronoi tessellations (CVT) with a consensus strategy. The CVT of the region insures a local optimal position configuration of the actuators, thus the sensing uncertainty can be minimized. The consensus algorithm utilizes the connection information among actuators, and helps them to reach a common workload. The consensus component will be terminated or suppressed when the workload is averaged. The consensus component may postpone the realization of CVT configuration. But it could be viewed as a perturbation that helps the actuators jump out of the local optimal CVT configuration. As a result, the information uncertainty may be further reduced. Comparison is drawn between the pure CVT algorithm and the method with consensus strategy. Simulations validated the proposed approach.

关键词： Voronoi tessellation position configuration workload assignment multi-agent system

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Real-time terrain estimation based on multi-scale radial basis function for unmanned ground vehicle

Real-time terrain estimation based on multi-scale radial bas...

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International Conference on Information and Automation (ICIA)

作者： Yi Yang Zhili Wang Xinghe Li Mengyin Fu Beijing Institute of Technology Beijing China Nanjing University of Science and Technology Nanjing China School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

ISBN: (纸本)9781509041039

Accurate terrain estimation is essential for unmanned ground vehicle (UGV) to achieve autonomous navigation. However, some existing approaches are difficult to reconstruct the 3D surface in real-time because of serious amount of computation. A method of environmental terrain estimation based on multi-scale radial basis function with a 3D lidar mounted on a moving vehicle was proposed in this paper. By combining kernel template with terrain grid map, the approach is applicable to the non-uniform density distribution of laser point cloud with the increasing detection range and improves the efficiency of calculation. What's more, the estimation of culverts and trees will be more accurate if treat the point cloud in separate layers for suspended obstacles problem. All terrain estimation approaches were verified with good performance in an interactive system, which is set up with Virtual Robot Experimentation Platform (VREP) and actual vehicle.

关键词： Three-dimensional displays Estimation Laser radar Kernel Lasers Surface reconstruction Real-time systems

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