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15th Annual Conference on Advances in Autonomous Robotics Systems, TAROS 2014

作者： Liang, Peidong Yang, Chenguang Wang, Ning Li, Zhijun Li, Ruifeng Burdet, Etienne Centre for Robotics and Neural Systems School of Computing and Mathematics Plymouth University United Kingdom MOE Key Lab. of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology China State Key Laboratory of Robotics and System Harbin Institute of Technology China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Department of Bioengineering Imperial College of Science Technology and Medicine London United Kingdom

ISBN: (纸本)9783319104003

This paper presents an improved method to teleoperate impedance of a robot based on surface electromyography (EMG) and test it experimentally. Based on a linear mapping between EMG amplitude and stiffness, an incremental stiffness extraction method is developed, which uses instantaneous amplitude identified from EMG in a high frequency band, compensating for non-linear residual error in the linear mapping and preventing muscle fatigue from affecting the control. Experiments on one joint of the Baxter robot are carried out to test the approach in a disturbance attenuation task, and to compare it with automatic human-like impedance adaptation. The experimental results demonstrate that the new human operated impedance method is successful at attenuating disturbance, and results similarly to as automatic disturbance attenuation, thus demonstrating its efficiency. © 2014 Springer International Publishing.

关键词： Stiffness

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A unified framework for optimality analysis of model predictive control

A unified framework for optimality analysis of model predict...

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World Congress on Intelligent control and automation (WCICA)

作者： Xin Cai Shaoyuan Li Ning Li Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai P.R. China Electrical Engineering and Computer Science Queen's University Belfast Belfast UK

As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MPC). The optimality is evaluated by comparing total performance of MPC with finite and infinite horizon optimal cost. Based on relaxed value iteration method, upper and lower bounds of optimality evaluation functions are expressed explicitly in terms of optimization horizon. These results reveal detailed characteristics on performance of closed-loop MPC systems due to using “receding horizon optimization” implementation style.

关键词： Optimal control Nonlinear systems Cost function Predictive control Predictive models

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An EMG Enhanced Impedance and Force control Framework for Telerobot Operation in Space

An EMG Enhanced Impedance and Force Control Framework for Te...

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IEEE Aerospace Conference

作者： Ning Wang Chenguang Yang Michael R. Lyu Zhijun Li Department of Computer Science and Engineering The Chinese University of Hong Kong School of Computing and Mathematics Plymouth University Key Lab of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology

ISBN: (纸本)9781479916191

Tele-operation is a merging point of modern developments in robotics and communications technologies. Both traditional applications (e.g., mining) and emerging domains (e.g., microsurgery) benefit from the advancement of tele-robotic systems. Combining a local human operator and a remote autonomous robot, the tele-robotics systems could optimally exploit both the intelligence of human operator and the automation of robot. In a tele-operation scenario, the exchange of force and position signals, i.e., haptic feedback, can greatly extend human operator's capability of conducting complicated work through the robot in a remote environment. However, long-range communications usually suffer from the time delay problem caused by the inherent characteristics of communication channels. Delayed transmission of haptic signals may lead to instability in the closed-loop telerobot control system. Although much effort has been made in the control community to overcome this difficulty, and many approaches such as wave scattering, passivity, and small gain theorem have been employed as possible solutions, stability in haptic telerobot control remains a challenge. It has been noted that the neural path of human being is also subject to transmission delay as well. We know that in the presence of time delay in sensory feedback pathways, human neural control can easily maintain stability and even to show superior manipulation skills in unstable interaction scenarios. It has been discovered and reported that the operation stability of human beings could be achieved by well adjusting the mechanical impedance, i.e., the resistance to imposed motion, which is largely contributed by the spring-like property of muscles. Being investigated in robotics community for decades, impedance control has shown great advantage in terms of safety and flexibility over conventional position or force control. However, only until very recently our attention has been attracted to transferring a human operator

关键词： impedance Electromyogram Human Robot Force Astronauts Force control muscles robotics

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Sensitivity analysis for building energy simulation model calibration via automatic differentiation

Sensitivity analysis for building energy simulation model ca...

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IEEE International Conference on Networking, Sensing and control

作者： Sisi Li MengChu Zhou Kun Deng Zhen Song Yan Lu Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Coordinated Science Laboratory University of Illinois at Urbana-Champaign Urbana IL USA Department of Automation and Control Siemens Corporation Corporate Technology Princeton NJ USA

High-fidelity building energy simulation models are established on well-known physical laws and attempt to faithfully represent a real building. The numerical solution of differential algebraic equations that interpret thermal balance of buildings is included in building energy simulation models. It thereby leads to highly discontinuous systems that involve a large number of sub-routine calls and model switches during the execution. To acquire a building energy simulation model with good quality, parameter sensitivity analysis is well-advocated since it aims to target those parameters from the parameter pool in a specific building that hold more influence on the building thermal performance than others. Since building energy simulation models are given in a large piece of program codes and encapsulate a series of sub-models, the existing sensitivity analysis is built on Monte Carlo simulation and statistics-based random sampling methods only, e.g., Monte Carlo sampling and Latin Hypercube sampling methods, which are extremely time-consuming. We propose to perform the sensitivity analysis of a first-principle high-fidelity building energy simulation model via a straightforward differential sensitivity analysis method that relies on the estimation of derivatives. A key technical challenge is that the complexity of the model prohibits the analytical differentiation, while the numerical differentiation is sensitive to step size and suffers from the truncation error. We, hence, propose to adopt an automatic differentiation method, which exploits the operator overload feature of object oriented programming language, to obtain accurate numerical estimations of derivatives in an automated and computationally efficient way.

关键词： Materials Buildings Computational modeling Mathematical model Analytical models Heating Monte Carlo methods

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Semi-randomized hashing for large scale data retrieval

Semi-randomized hashing for large scale data retrieval

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International Conference on Data Science and Advanced Analytics (DSAA)

作者： Haichuan Yang Xiao Bai Jun Zhou Peng Ren Jian Cheng Lu Bai School of Computer Since and Engineering Beihang University China School of Information and Communication Technology Griffith University Australia College of Information and Control Engineering China University of Petroleum China Institute of Automation Chinese Academy of Sciences China Department of Computer Science University of York UK

In information retrieval, efficient accomplishing the nearest neighbor search on large scale database is a great challenge. Hashing based indexing methods represent each data instance as a binary string to retrieve the approximate nearest neighbors. In this paper, we present a semi-randomized hashing approach to preserve the Euclidean distance by binary codes. Euclidean distance preserving is a classic research problem in hashing. Most hashing methods used purely randomized or optimized learning strategy to achieve this goal. Our method, on the other hand, combines both randomized and optimized strategies. It starts from generating multiple random vectors, and then approximates them by a single projection vector. In the quantization step, it uses the orthogonal transformation to minimize an upper bound of the deviation between real-valued vectors and binary codes. The proposed method overcomes the problem that randomized hash functions are isolated from the data distribution. What's more, our method supports an arbitrary number of hash functions, which is beneficial in building better hashing methods. The experiments show that our approach outperforms the alternative state-of-the-art methods for retrieval on the large scale dataset.

关键词： Vectors Euclidean distance Binary codes Training Equations Principal component analysis

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Neural Robust Adaptive Hypersonic Flight control without Back-stepping

Neural Robust Adaptive Hypersonic Flight Control without Bac...

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2014中国制导、导航与控制学术会议

作者： Shixing Wang Fuchun Sun Yongquan Zhang Bin Xu Yiwei Zhang Department of Control Engineering Naval Aeronautical and Astronautical UniversityYantaiChina Department of Computer Science and TechnologyTsinghua UniversityBeijingChina Systems Engineering Research InstituteChina State Shipbuilding Corporation School of AutomationNorthwestern Polytechnical UniversityXi''anChina

ISBN: (纸本)9781479946983

In this paper,one robust adaptive controller is proposed for hypersonic flight dynamics with high gain observer (HGO) and neural networks (NNs).For the attitude subsystem,it contains flight path angle,pitch angle and pitch *** avoid the complex back-stepping design,the dynamics are transformed into the normal feedback *** HGO estimating the newly defined states,the controller is proposed with error feedback,NN approximation and the robust *** is proved that the NN weights and filtered tracking error are guaranteed in the semiglobal *** simulation with March 15 is conducted to show the effectiveness of the proposed method.

关键词： adaptive control aerospace control neurocontrollers robust control HGO estimating NN approximation attitude subsystem complex backstepping design error feedback filtered tracking error flight path angle high gain observer hypersonic flight dynamics neural networks neural robust adaptive hypersonic flight control normal feedback form pitch angle pitch rate robust item semiglobal sense Adaptive systems Approximation methods Artificial neural networks Educational institutions Robustness Vectors Vehicle dynamics

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Network design for distributed consensus estimation over heterogeneous sensor networks

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IFAC Proceedings Volumes 2014年第3期47卷 5550-5555页

作者： Wen Yang Ling Shi Ye Yuan Xiaofan Wang Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong P. R. China Department of Engineering University of Cambridge UK Department of Automation Shanghai Jiaotong University Shanghai 200240

This paper considers distributed estimation over heterogeneous sensor networks. We propose a distributed estimation strategy based on PageRank algorithm, where the link weight depends on the edge estimation covariances. We prove that the proposed estimator obtains better estimates than one typical estimator under identical initial conditions. Motivated by the advantage of the sensors with high accuracy locating at important positions, we propose an optimal sensor deployment strategy to arrange locations for sensors in a given physical network. Numerical examples are provided to demonstrate the effectiveness of the proposed estimator, showing a better performance under the optimal sensor deployment.

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Fault diagnosis of wind energy conversion systems with sensor faults

Fault diagnosis of wind energy conversion systems with senso...

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2nd IET Renewable Power Generation Conference, RPG 2013

作者： Zhang, J.H. Xiong, J. Ren, M.F. Jiang, M. Hou, G.L. Department of Automation School of Control and Computer North China Electric Power University Beijing 102206 China

ISBN: (纸本)9781849197588

In this paper, a novel filter based fault detection and isolation strategy is presented for variable-speed wind energy conversion systems (WECSs) in the presence of sensor faults. Firstly, a nonlinear physical model of a WECS is built by integrating aerodynamic rotor, a drive train, a generator and a converter. The typical sensor faults are also modelled. Since the wind speed is usually a non-Gaussian signal, a novel filter is then presented for WECSs via improved minimum error entropy criterion. Based on the established filter, residual signals are generated, and accordingly the detection and isolation rule for the sensor faults is obtained by evaluating residual signals. Finally, the proposed fault detection and isolation scheme is applied to a WECS. Simulations results indicate the sensor faults can be detected and isolated effectively.

关键词： Failure analysis

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On Infinite Time Performance of Nonlinear Model Predictive controllers

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IFAC Proceedings Volumes 2014年第3期47卷 1916-1921页

作者： Xin Cai Shaoyuan Li Ning Li Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 P. R. China School of Electronics Electrical Engineering and Computer Science The Queen's University Belfast Belfast BT7 1NN UK

This paper addresses the problem of infinite time performance of model predictive controllers applied to constrained nonlinear systems. The total performance is compared with a finite horizon optimal cost to reveal performance limits of closed-loop model predictive control systems. Based on the Principle of Optimality, an upper and a lower bound of the ratio between the total performance and the finite horizon optimal cost are obtained explicitly expressed by the optimization horizon. The results also illustrate, from viewpoint of performance, how model predictive controllers approaches to infinite optimal controllers as the optimization horizon increases.

关键词： Model Predictive control Finite Horizon Optimal control Value Iteration Principle of Optimality

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Passive control for fuzzy system with time-delay

Passive control for fuzzy system with time-delay

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第25届中国控制与决策会议

作者： Yue Dan Liu Xiangjie Yao Xiuming School of Control and Computer Engineering North China Electric Power University Department of Automation North China Electric Power University

ISBN: (纸本)9781467355339

In this paper, a delay partitioning approach is introduced to solve problems of passivity and passification for continuous T-S fuzzy system with time delay. By constructing a Lyapunov-Krasovskii functional, delay-dependent passivity/passification performance conditions are formulated in terms of linear matrix inequalities(LMIs). Finally, a numerical example is used to illustrate the effectiveness of the proposed approaches which can futher reduce conservatism.

关键词： T-S fuzzy system delay partitioning time-delay system LMI

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