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第三十九届中国控制会议

作者： Yulei Pan Yongqiang Bai Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

The Correlation filtering algorithm is not effective for fast deformation and fast movement. It is easy to lose when encountering problems such as occlusion. However, it has a good advantage of dealing with situations such as motion blur and lighting changes. A tracking algorithm based on color statistical features has a good effect on the rotation and translation of *** Staple algorithm combines the two algorithms to track using complementary fusion, but it also does not handle the occlusion and other issues well. In this paper, based on the Staple algorithm, the average peak correlation energy（APCE） and the maximum response are introduced. The value is used as the tracking confidence, and a detector using a support vector machine（SVM） is *** the tracking confidence is low, the target is blocked or moved violently. At this time, the detector works,and the search area is expanded around the original area for the target. At the same time, because the traditional tracking algorithm uses a fixed learning rate to update the template, this paper uses an adaptive tracking learning rate. When the tracking confidence is low, the update speed of the target model is reduced, which can effectively deal with the occlusion deformation in the tracking process. OTB100 benchmark experiments show that this method can solve the occlusion problem during target tracking. The degree of change is robust and stability.

关键词： Target Tracking Complementary Filtering Re-detection Adaptive Learning Rate

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A new control method of quadruped robot walking on rough terrain based on linear inverted pendulum method

A new control method of quadruped robot walking on rough ter...

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IEEE International Conference on Robotics and Biomimetics

作者： Xin Li Junyao Gao Qiang Huang Haojian Lu Zhe Xu Yi Liu Intelligent Robotics Institute Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (纸本)9781479973989

This paper proposes a new method of linear inverted pendulum control, which is used to control the quadruped robot walking on regular uneven terrain such as ramp and stair, furthermore, this method can be applied to a more rugged terrain. This paper analyzes the dynamic parameters of a quadruped robot walking on the {2. terrain, which means the supporting points of the robot lie in different heights relative to the level ground. In order to ensure the same leg length, there will be energy dissipation caused by the raise of the center of mass. Therefore this paper proposes a dual length linear inverted pendulum method (DLLIPM), which not only effectively reduces the energy dissipation, but also promotes the workspace utilization. In addition, Newton-Raphson algorithm is used to optimize the linear inverted pendulum movement, which makes the movement symmetrical and smooth. Finally this paper presents simulation results with DLLIPM on a quadruped robot with 16 degrees of freedom.

关键词： Legged locomotion Foot Trajectory Mathematical model Robot sensing systems

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The Optimal Duty Cycle Model-Predictive control of PMSM Used for Satellite Payload 1

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17th Annual Conference of China Electrotechnical Society, CES 2.2.

作者： Li, Jialin Chen, Zhen Hu, Hengzai Liu, Xiangdong Bao, Liang School of Automatic Beijing Institute of Technology Beijing100081 China Key Laboratory of Drive and Control of Servo Motion System Ministry of Industry and Information Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision for Complex System Beijing100081 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (数字)9789819904082

ISBN: (纸本)9789819904075

Model-predictive control is emerging as an advanced control strategy for its feature that the state variables can be predicted according to the math model of the control system. In the PMSM drive application, conventional model-predictive control strategy induces current ripple due to the fact that the optimal voltage vector always acts on the system for the whole control period. In order to restrain the current ripple, the idea of duty cycle control is taken into MPC by inserting a zero vector into the optimal non-zero vector and regulating the duty cycle of non-zero vector. In this paper, the optimal duty cycle FSC-MPC strategy based on two different principles is investigated. Principle A is that the estimation is equal to the reference at the end of control cycle, and principle B is that the area under trace of the estimation is equal to that of reference. The calculation of duty based on the two different principles and the flow chart of the strategy are introduced in detail. Finally, the effectiveness of the optimal duty cycle FSC-MPC is firstly verified by the simulation, and then verified by the experimental results, which is implemented on the PMSM driver of the DQ-1 satellite payload. © 2.2., Beijing Paike Culture Commu. Co., Ltd.

关键词： Model predictive control

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Observer-based output feedback control of networked control {2.s with non-uniform sampling and time-varying delay

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International Journal of systems Science 2017年第14期48卷 3118页

作者： Meng, Su Chen, Jie Sun, Jian Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing P.R. China

This paper investigates the problem of observer-based output feedback control for networked control {2.s with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two sub{2.s in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop {2.. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.

关键词： Non-uniform sampling time-varying delay networked control systems output feedback control stability

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Extension of SGMF Using Gaussian Sum Approximation for Nonlinear/Non-Gaussian Model and Its Application in Multipath Estimation

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Acta Automatica Sinica 2013年第1期39卷 1-10页

作者： Jie CHEN Lan CHENG Ming-Gang GAN Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

The multipath estimation of global navigation satellite system (GNSS) signal is actually the state estimation of nonlinear/non-Gaussian systems. The extension of sliced Gaussian mixture filter (ESGMF) based on Gaussian sum approximation is proposed for the state estimation of nonlinear/non-Gaussian state space, and the probability density function (PDF) expression of states is derived recursively for a time varying system. Resampling is applied to the prediction PDF to reduce the complexity of Bayesian inference. The simulation result of multipath estimation with ESGMF shows that the ESGMF algorithm performs better in accuracy than the algorithms based on particle filter (PF) and extended Kalman filter (EKF).

关键词： Non-Gaussian noise Gaussian sum probability density function (PDF) sliced Gaussian mixture filter (SGMF) multipath estimation

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Research on Path Planning of Mobile Robot Based on DWA-IMP-A∗ Algorithm 42

Research on Path Planning of Mobile Robot Based on DWA-IMP-A...

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42.d Chinese control Conference, CCC 2.2.

作者： Liu, Zhi Zhang, Lin Wang, Shoukun Niu, Tianwei Xu, Yongkang Cao, Jin School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology Beijing100081 China

ISBN: (纸本)9789887581543

Path planning is one of the most critical links in mobile robots. Its timeliness, security and accessibility are crucial to the development and wide application of mobile robots. However, in solving the problem of path planning, the most popular A∗ algorithm has some problems, such as heuristic function cannot be estimated accurately, node redundancy, path is not smooth, and obstacle avoidance cannot be achieved in real time. To solve these problems, A fusion algorithm of improved A∗ combined with reverse path and dynamic window method (DWA-IMP-A∗) was proposed. The algorithm refines the heuristic function by incorporating the reverse path. The node optimization algorithm is used to further reduce the path length. The generated trajectories are smoothed by cubic spline interpolation. At the same time, it is integrated with the improved DWA algorithm to improve the efficiency and safety of robot path planning. The algorithm takes ROS mobile robot as the carrier and is tested under typical road conditions. Compared with A∗ algorithm, the planning time is reduced by 54.6% and the path length is reduced by 6.37%. Experimental results verify the effectiveness and robustness of the algorithm. The research results have certain reference significance for the path planning of various types of mobile robots and the research of driverless vehicles. © 2.2. Technical Committee on control Theory, Chinese Association of Automation.

关键词： Motion planning

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Group Behaviour control Based on Aggregation and Dilation

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IFAC Proceedings Volumes 2008年第2期41卷 6072-6077页

作者： Bin Xin Jie Chen Li-Hua Dou Zhi-Hong Peng Department of Automatic Control School of Information Science and Technology Beijing Institute of Technology Beijing 100081 Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education China

The phenomenon of aggregation and dilation(A&D) widely exists in nature. The mechanism behind it is regarded as the effect of some kind of attraction and repulsion(A&R). A&R control becomes a popular and promising way of controlling the structure and distribution of a group composed of several and even numerous individuals. This paper presents the concepts of aggregation, dilation and group evolution criticality based on group variance. We investigate the relationship between different levels of A&D as a foundation for the introduction of A&D analysis. The applications of A&D analysis and A&R control in several researches, including population-based optimization and group behavior control about multi-agent, are given in the form of simulation experiments.

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Optimal data integrity attack on actuators in Cyber-Physical systems

Optimal data integrity attack on actuators in Cyber-Physical...

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American control Conference

作者： Guangyu Wu Jian Sun The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology China

ISBN: (纸本)9781467386838

The security issues are of prime importance for Cyber-Physical systems (CPSs). Most existing works mainly investigate the secure control schemes against malicious attackers. This article analyzes how to design an data integrity attack scheme from the viewpoint of an attacker. The formulation of our approach is basically similar to the one of conventional optimal control method, with different prerequisites and solutions. An output feedback control system under data integrity attacks on actuators is considered in this article. Our work is aimed at constructing an optimal feedback attack law to maximize the error between the attacked system's output and the healthy system's output. Numerical examples are presented to demonstrate the effectiveness of the proposed method.

关键词： Actuators Cyber-physical systems Optimal control Computer crime Jamming actuators Computer crime Cyber-physical systems jamming Data Quality Optimal control Feedback control systems

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Policy iteration based Q-learning for linear nonzero-sum quadratic differential games

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Science China(Information Sciences) 2019年第5期62卷 195-213页

作者： Xinxing LI Zhihong PENG Li LIANG Wenzhong ZHA School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Information Science Academy China Electronics Technology Group Corporation

In this paper, a policy iteration-based Q-learning algorithm is proposed to solve infinite horizon linear nonzero-sum quadratic differential games with completely unknown dynamics. The Q-learning algorithm, which employs off-policy reinforcement learning(RL), can learn the Nash equilibrium and the corresponding value functions online, using the data sets generated by behavior policies. First, we prove equivalence between the proposed off-policy Q-learning algorithm and an offline PI algorithm by selecting specific initially admissible polices that can be learned online. Then, the convergence of the off-policy Qlearning algorithm is proved under a mild rank condition that can be easily met by injecting appropriate probing noises into behavior policies. The generated data sets can be repeatedly used during the learning process, which is computationally effective. The simulation results demonstrate the effectiveness of the proposed Q-learning algorithm.

关键词： adaptive dynamic programming ADP Q-learning reinforcement learning RL linear nonzerosum quadratic differential games policy iteration PI off-policy

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Adaptive control of air delivery system for PEM fuel cell using backstepping

Adaptive control of air delivery system for PEM fuel cell us...

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作者： Li, Peng Chen, Jie Cai, Tao Zhang, Bo School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education Beijing 100081 China

ISBN: (纸本)9788995605646

The proton exchange membrane (PEM) fuel cells have attracted significant attention due to high efficiency and low pollution. The performance and lifetime of the fuel cell power system depend on the heat and water management, gas flow control and pressure regulation. This paper focuses on the oxygen excess ratio regulation for the fuel cell system to improve the performance and extend the lifetime. Firstly, a third-order model of the air delivery subsystem is introduced based on suitable assumption and simplification. Secondly, the third-order model is transformed to the non-affine nonlinear form, and the oxygen excess ratio regulation is reconsidered as load current tracking problem. Using the backstepping technique and neural network, an adaptive controller is proposed for the tracking problem and guarantees the system's stability in presence of modeling errors, external disturbances and uncertainties. Finally, the simulation illustrates the effectiveness of the adaptive controller. © 2.11 Asian control Association.

关键词： Backstepping

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