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2013 IEEE International Conference on automation Science and Engineering, CASE 2013

作者： Shen, Z. Wang, K. Wang, F.-Y. State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences No. 95 Zhongguancun E. Road Beijing 100190 China Centre for Military Computational Experiments and Parallel Systems Technology College of Mechatronics Engineering and Automation National University of Defense Technology Changsha 410073 Hunan Province China

ISBN: (纸本)9781479915156

As the computing technology develops, micro-simulation becomes more and more important in the Intelligent Transportation systems (ITS) research, because it can provide detailed descriptions of the system. However, for a multi-agent systems (MAS) modelling of an ITS, the computation burden is large, as it involves the computation of the state changing of all the agents. Further, if we consider simulation based optimization, which can be simply understood as an intelligent way of running a number of micro-simulations, the computation burden is huge. Moreover, there are multiple objective optimization problems in the ITS. The Vector Ordinal Optimization (VOO) method is a powerful tool for multi-objective optimization. In this paper, we apply VOO to the problem of optimizing the stop times and delay time of an ITS. We test the method on a 4 intersection lattice road network, and on the 18 intersection road network of the Zhongguancun area of Beijing. Compared with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) method, the VOO method can achieve a speedup of factor of more than 150, with only a little sacrifice of performance. © 2013 IEEE.

关键词： Multiobjective optimization

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Generalized adaptive dynamic programming algorithm for discrete-time nonlinear systems: Convergence and stability analysis

Generalized adaptive dynamic programming algorithm for discr...

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International Conference on Information Science and Technology (ICIST)

作者： Derong Liu Qinglai Wei State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781467327626

This paper is concerned with a generalized iterative adaptive dynamic programming (ADP) algorithm for discrete-time nonlinear systems. The idea is to use iterative ADP algorithm to obtain iterative control laws which make the iterative performance index function reach the optimum. It is proved that for an arbitrary positive semi-definite function, the iterative performance index functions will converge to the optimum. For different initial functions, it shows that the convergence procedures of the iterative performance index functions are different. Stability properties of the system are analyzed in this paper to show that the iterative control can stabilize the system for suitable initial performance index functions. Admissible control properties of the iterative control laws obtained by the present generalized iterative ADP algorithm are also given in this paper.

关键词： ADP Convergence Stability Analysis Stability analysis Automatic data processing Adenosine Diphosphate Converge performance indicators Iterative control law Optimum Nonlinear systems

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Data-based vehicle adaptive cruise control: A review

Data-based vehicle adaptive cruise control: A review

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Chinese control Conference (CCC)

作者： Dongbin Zhao Bin Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

Based on the conventional cruise control, vehicle adaptive cruise control (ACC) measures the distance and the relative velocity to the preceding vehicle real time via distance sensor, computes appropriate control output with respect to throttle or brake pedal, and control the velocity or headway automatically. Under the basically security guarantee, ACC could improve the comfort and reduce fuel consumption. This paper comprehensively investigates the theory and technology for ACC of last decades. We conclude the main approach of modeling, control and optimization of ACC, and note that data-based ACC system which conforms driver character and habit has been a new trend.

关键词： Vehicles Adaptation models control systems Adaptive systems Conferences Predictive models Electronic mail

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sEMG based joint angle estimation of lower limbs using LS-SVM

sEMG based joint angle estimation of lower limbs using LS-SV...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Li, Qingling Song, Yu Hou, Zengguang Zhu, Bin Department of Mechanical Engineering China University of Mining and Technology Beijing China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Science Beijing China

ISBN: (纸本)9783642420535

In this paper, a new estimation model based on least squares support vector machine (LS-SVM) is proposed to build up the relationship between Surface electromyogram (sEMG) signal and joint angle of the lower limb. The input of the model is 2 channels of preprocessed sEMG signal. The outputs of the model are joint angles of the hip and the knee. sEMG signal is acquired from 7 motion muscles in treadmill exercise. And two channels of them are selected for dynamic angle estimation for their strong correlation with angle data. Angle estimation model is constructed by 2 independent LS-SVM based regression model with radial basis function (RBF). It is trained using part of the sample sets acquired in 10s exercise duration and test by all data. Experimental result shows proposed method has good performance on joint angles estimation based sEMG. Root mean square error (RMSE) of prediction knee and hip joint angles is 3.02° and 2.09° respectively. It provide new human-machine interface for active rehabilitation training of SCI, stroke or neurological injury patients. © Springer-Verlag 2013.

关键词： Patient rehabilitation

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An approach to remote update driver system of a robotic fish with two long fins

An approach to remote update driver system of a robotic fish...

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Chinese control Conference (CCC)

作者： Qingping Wei Shuo Wang Min Tan State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

The robotic fish with two long fins is one kind of underwater robot system imitating stingray's motion. The robotic fish generates thrust by use of two long fins located on both sides of body symmetrically. A driver control system for the motion control of fin rays is designed based on FPGA(Field Programmable Gate Array). Several kinds of motion modes can be achieved through tuning motion parameters. In order to facilitate updating control algorithm, reducing the probability of damaging the robot system and improving debugging efficiency, a solution for remote updating the driver program of the robotic fish wirelessly is proposed in this paper based on the dedicated remote system update circuitry integrated in ALTERA FPGA. In addition, a remote update system is designed in this paper. The designed control program updating system facilitates the debugging and optimization of multi-fin coordination control algorithm for the robotic fish with two long fins greatly.

关键词： Field programmable gate arrays Robot kinematics Light emitting diodes Marine animals control systems Ash

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A learning optimal control scheme for robust stabilization of a class of uncertain nonlinear systems

A learning optimal control scheme for robust stabilization o...

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Chinese control Conference (CCC)

作者： Ding Wang Derong Liu Hongliang Li Xiong Yang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing Beijing CN

In this paper, a novel learning optimal control scheme is established to design the robust controller of a class of uncertain nonlinear systems. The robust control problem is transformed into the optimal control problem by properly choosing a cost function that reflects the uncertainty, regulation, and control. Then, the online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman (HJB) equation by introducing a critic neural network. The approximate expression of the optimal control policy can be derived directly. Moreover, the closed-loop system is proved to be uniformly ultimately bounded. The equivalence of the neural-network-based HJB solution of the optimal control problem and the solution of the robust control problem is developed as well. Finally, an example is provided to verify the effectiveness of the constructed approach.

关键词： Optimal control Cost function Robust control Equations Approximation methods Nonlinear systems Uncertainty

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Consensus tracking of general linear multi-agent systems: Fast sliding-mode algorithms

Consensus tracking of general linear multi-agent systems: Fa...

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Chinese control Conference (CCC)

作者： Huiyang Liu Long Cheng Min Tan Zengguang Hou Yunpeng Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing Beijing CN

This paper solves distributed consensus tracking problems where the task is to make the multi-agent network, with each agent described by a general linear dynamics, to reach consensus with a leader whose control input is nonzero and not available to any followers. A set of sliding mode surfaces are defined and then fast sliding mode controllers are designed for both reduced order and non-reduced order cases. It is shown that all the trajectories exponentially converge to the sliding mode surfaces in a finite time if the leader has a directed path to at least one of the followers in a strongly connected and detailed balanced directed interaction graph and the leader's control input is bounded. The control Lyapunov function for exponential finite time stability, motivated by the fast terminal sliding mode control, is used to prove the reachability of the sliding mode surfaces. Simulation examples are given to illustrate the theoretical results.

关键词： Multi-agent systems Sliding mode control Trajectory Lead Manifolds Lyapunov methods Convergence

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MODULAR HIERARCHICAL FEATURE LEARNING WITH DEEP NEURAL NETWORKS FOR FACE VERIFICATION

MODULAR HIERARCHICAL FEATURE LEARNING WITH DEEP NEURAL NETWO...

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IEEE International Conference on Image Processing

作者： Xue Chen Baihua Xiao Chunheng Wang Xinyuan Cai Zhijian Lv Yanqin Shi State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing Institute of Science and Technology Information

ISBN: (纸本)9781479923427

Feature representations play a crucial role in modern face recognition systems. Most hand-crafted image descriptors usually provide low-level information. In this paper, we propose a novel feature learning method based on deep neural networks to obtain high-level, hierarchical representations for face verification. Learning proceeds in two phases. In the pre-training phase, we train Restricted Boltzmann Ma-chine(RBM) networks for each modular region in the image separately. In the fine-tuning phase, in order to develop good discriminative ability, we stack the RBM networks of each region in deep architecture and combine deep learning with side information constraints in the whole image scale. Finally, we formulate the proposed method as an appropriate optimization problem and adopt gradient descent algorithm to get the optimal solution. We evaluate our method on the LFW dataset. Representations learned from the networks achieve comparable performance (93.11%) to the state-of-art method.

关键词： deep neural networks feature learning face verification face verification Modularity Neural network image scale face recognition system Face Verification

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Design and development of vehicle license plate recognition (VLPR) system to improve parking lot management

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9th International Symposium on Linear Drives for Industry Applications, LDIA 2013

作者： Chen, Yong Hu, Bin Li, Bo He, Qing Mo, Hong Xiong, Gang College of Electric and Information Changsha University of Science and Technology Changsha 410004 China Cloud Computing Center Chinese Academy of Sciences Dongguan 523808 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Science Beijing 100190 China

ISBN: (纸本)9783037858639

In this paper, we design and develop Vehicle License Plate Recognition (VLPR) System, which is one part of comprehensive video management platform for parking lot. Combined with intelligent video analysis module, the proposed VLPR system can not only capture the license plates of those vehicles through ENTRANCE and EXIT of parking lot, but also recognize the contents of the captured license plates. In addition, the driver and passenger in the front row of the vehicle can be captured too. The capture subsystem operates well on embedded Linux environment running on Hi3516 SoC chip, and test results of the VLPR system meet the requirements of accuracy and real-time field applications. The VLPR system is easy to expand and modified for other management Information System to realize functions like personnel management, vehicle tracking, and more automatic and intelligent functions of parking lot management. © (2013) Trans Tech Publications, Switzerland.

关键词： License plates (automobile)

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Design and Kinetic Analysis of a Biomimetic Underwater Vehicle with Two Undulating Long-fins

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Acta Automatica Sinica 2013年第8期39卷 1330-1338页

作者： WEI Qing-Ping Shuo WANG Xiang DONG Liu-Ji SHANG Min TAN The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Institute of Intelligent Machines Chinese Academy of Sciences Hefei 230031 China

A biomimetic underwater vehicle propelled by two undulating long-fins is introduced in this paper. The concerned vehicle is propelled by two symmetrical undulating long-fins installed on both sides. Ten servo motors are employed to drive the long-fins and cosine wave function is employed for motor control. A real-time control system is designed for controlling the long-fins by adjusting its oscillating frequency and oscillating amplitude. An inertial measurement unit is installed to collect the accelerations and angular velocity. To obtain the relationship between oscillating frequency/amplitude and swimming performance, kinematic analysis and hydromechanic analysis are given. By dividing the long-fin into many small elements and computing the hydrodynamic force acting on each element, the instantaneous thrust generated by the long-fin is obtained. Then the average thrust of the long-fin is obtained by summing up the forces acted on the elements in one undulating period. Then swimming experiments are carried out to validate the vehicle design and kinematic analysis and hydromechanic analysis. And two swimming motion modes including marching and rotating locomotion are chosen. Finally, discussions between the swimming performance and the oscillating parameters are given.

关键词： Autonomous underwater vehicle biomimetic robot fish kinematic modeling robot control

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