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Probabilistic constrained stochastic model predictive control for Markovian jump linear systems with additive disturbance

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IFAC Proceedings Volumes 2014年第3期47卷 10469-10474页

作者： Jianbo Lu Yugeng Xi Dewei Li Lihui Cen Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 China Department of Control Engineering Central South University Changsha Hunan Province 410083 China

This paper is concerned with stochastic model predictive control for Markovian jump linear systems with additive disturbance, where the systems are subject to soft constraints on the system state and the disturbance sequence is finitely supported with joint cumulative distribution function given. By resorting to the maximal disturbance invariant set of the system, a model predictive control law is given based on a dynamic controller which is with guaranteed recursive feasibility and ensures the probabilistic constraints on the states. By optimizing the volume of the disturbance invariant set, the dynamic controller is given. The closed loop system under this control law is proven to be stable in the mean square sense. Finally, a numerical example is given to illustrate the developed results.

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Consensus of Edge Dynamics on Complex Networks

Consensus of Edge Dynamics on Complex Networks

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IEEE International Symposium on Circuits and systems

作者： Xiaofan Wang Xiaoling Wang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

ISBN: (纸本)9781479934331

Existed works on consensus in networks have been focused on reaching an agreement among states of nodes in a network. In this work, we propose a discrete-time edge consensus protocol for complex networks. By mapping the edge topology into a corresponding line graph, we prove that consensus can be achieved among the states of all edges in a connected network. Theoretical analysis and simulation results are provided to show the effectiveness of the model and the influence of network topology.

关键词： Consensus Synchronization Complex networks Edge protocol

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Swarming with mixed position and heading based neighboring interactions

Swarming with mixed position and heading based neighboring i...

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World Congress on Intelligent control and automation (WCICA)

作者： Shu Fang Xiaofan Wang Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai P. R. China

Previously, we proposed a topological-based swarming model in which agents probabilistically decide which other agents to interact with based on the proximity of positions of agents. Agents then average their direction with the directions of the agents they have interacted with. In this paper, we improve the model mentioned-above by taking the influence of similarity of directions into consideration, and the former model can be considered as a special case of this model here. We propose a probabilistic method which depends on both proximity of agents' positions and similarity of agents' moving directions. And agents are more likely to form links with those agents who carry a similar direction to theirs and those agents who are proximal to them. We show that there exits a non-zero positive lower bound of the selection probability, and the system can be connected in probability, which ensures the system's achievement of swarming. And by simulations, it is shown that the rate of getting alignment exhibit a strong correlation with the parameters of the system which are weighting factor, neighborhood size, proximity factor and similarity factor.

关键词： Convergence Probabilistic logic Biological system modeling Multi-agent systems Dynamics Mathematical model automation

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Crawling gait planning for a quadruped robot with high payload walking on irregular terrain 19

Crawling gait planning for a quadruped robot with high paylo...

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

作者： Hu, Nan Li, Shaoyuan Huang, Dan Gao, Feng Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai200240 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9783902823625

Walking on irregular terrain is usually a common task for a quadruped robot. It is however difficult to control the robot in this situation as undesirable impulse force by collision between the foot of robot and obstacles makes the robot unstable. This paper presents a hybrid Force-Posture Feedback Compensation (FPFC) controller for a quadruped robot with high payload walking on irregular terrain. In order to make the robot walk stably on irregular terrain, the proposed controller utilizes the feedback signals detected by force sensor and gyroscope to adjust every leg of the robot in real-time. The foot trajectory is scheduled based on the Bezier curve method in order to improve the stability of quadruped robot. Simulations of crawling gait on irregular terrain have been performed. The results have verified that the proposed methods have better stability and performance for walking on the irregular terrain. © IFAC.

关键词： Robot programming

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Development and learning control of a human limb with a rehabilitation exoskeleton

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IEEE Transactions on Industrial Electronics 2014年第7期61卷 3776-3785页

作者： Lu, Renquan Li, Zhijun Su, Chun-Yi Xue, Anke Institute of Information and Control Hangzhou Dianzi University Hangzhou 310018 China Key Laboratory of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China Department of Mechanical and Industrial Engineering Concordia University Montreal QC H3G 1M8 Canada

This paper describes a novel development of a lower limber exoskeleton for physical assistance and rehabilitation. The developed exoskeleton is a motorized leg device having a total of 4 DOF with hip, knee, and ankle actuated in the sagittal plane. The exoskeleton applies forces and learns the impedance parameters of both robot and human. An adaptive control scheme by incorporating learning control approaches into the exoskeleton system is developed to help the leg movement on a desired periodic trajectory and handle periodic uncertainties with known periods. The proposed control approach does not require a muscle model and can be proven to yield asymptotic stability for a nonlinear muscle model and an exoskeleton model in the presence of bounded nonlinear disturbances (e.g., spasticity and fatigue). The performance of the controller is demonstrated through closed-loop experiments on human subjects. The experiments illustrate the ability of the exoskeleton to enable the leg shank to track single and multiple period trajectories with different periods and ranges of motion. © 2013 IEEE.

关键词： Muscle

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Fault subspace selection and analysis of relative changes based reconstruction modeling for multi-fault diagnosis

Fault subspace selection and analysis of relative changes ba...

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第26届中国控制与决策会议

作者： Chunhui Zhao State Key Laboratory of Industrial Control Technology Department of Control Science and EngineeringZhejiang University Key Laboratory of System Control and Information Processing Ministry of Education

Online fault diagnosis has been a crucial task for industrial processes. Reconstruction-based fault diagnosis has been drawing special attentions as a good alternative to the traditional contribution plot. It identifies the fault cause by finding the specific fault subspace that can well eliminate alarming signals from a bunch of alternatives that have been prepared based on historical fault data. However, in practice, the abnormality may result from the joint effects of multiple faults, which thus can not be well corrected by single fault subspace archived in the historical fault library. In the present work, an aggregative reconstruction-based fault diagnosis strategy is proposed to handle the case where multiple fault causes jointly contribute to the abnormal process behaviors. First, fault subspaces are extracted based on historical fault data in two different monitoring subspaces where analysis of relative changes is taken to enclose the major fault effects that are responsible for different alarming monitoring statistics. Then, a fault subspace selection strategy is developed to analyze the combinatorial fault nature which will sort and select the informative fault subspaces that are most likely to be responsible for the concerned abnormalities. Finally, an aggregative fault subspace is calculated by combining the selected fault subspaces which represents the joint effects from multiple faults and works as the final reconstruction model for online fault diagnosis. Theoretical support is framed and the related statistical characteristics are analyzed. Its feasibility and performance are illustrated with simulated multi-faults using data from the Tennessee Eastman(TE) benchmark process.

关键词： fault subspace selection,joint fault effects,multi-fault diagnosis,reconstruction modeling,analysis of relative changes

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Coordinated obstacle avoidance with reduced interaction

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Neurocomputing 2014年 139卷 233-245页

作者： Jiaojie Li Wei Zhang Housheng Su Yupu Yang Hongtao Zhou Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Department of Measurement and Control Technology Shanghai Dian Ji University Shanghai 200240 China School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China

In this paper, we study the coordinated obstacle avoidance algorithm of multi-agent systems when only a subset of agents has obstacle dynamic information, or every agent has local interaction. Each agent can get partial measuring states information from its neighboring agent and obstacle. Coordinated obstacle avoidance here represents not only the agents moving without collision with an obstacle, but also the agents bypassing and assembling at the opposite side of the obstacle collectively, where the opposite side is defined according to the initial relative position of the agents to the obstacle. We focus on the collective obstacle avoidance algorithms for both agents with first-order kinematics and agents with second-order dynamics. In the situation where only a fixed fraction of agents can sense obstacle information for agents with first-order kinematics, we propose a collective obstacle avoidance algorithm without velocity measurements. And then we extend the algorithm to the case in switched topology. We show that all agents can bypass an obstacle and converge together, and then assemble at the opposite side of the obstacle in finite time, if the agents׳ topology graph is connected and at least one agent can sense the obstacle. In the case where obstacle information is available to only a fixed fraction of agents with second-order kinematics, we propose two collective obstacle avoidance algorithms without measuring acceleration when the obstacle has varying velocity and constant velocity. The switched topology is considered and extended next. We show that agents can bypass the obstacle with their positions and velocities approaching consensus in finite time if the connectivity of switched topology is continuously maintained. Several simulation examples demonstrate the proposed algorithms.

关键词： Obstacle avoidance Consensus Reduced interaction Circular motion Multi-agents

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Reprojection Error Based Annealed Particle Filter for Human Upper Body Pose Reconstruction

Reprojection Error Based Annealed Particle Filter for Human ...

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2014 IEEE International Conference on Service Operations and Logistics,and Informatics

作者： Xinzhuo Shi Yuncai Liu Shanghai Jiao Tong University Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information ProcessingMinistry of Education of China

3D human pose reconstruction is a key concern in computer vision area in recent *** to the deficiency of depth information,reconstructing human pose from a single image or image sequences is still a difficult and challenging *** this paper,we present an annealed particle filter algorithm based on reprojection error to recover the 3D configuration of human upper body,with the annotated joints’position in the *** addition,we make simplifications to the weak perspective projection,and the 7 camera parameters to be estimated are reduced to only *** show that our method is simple but exactly suitable for recovering articulated human upper body pose.

关键词： reprojection error annealed filter human pose reconstruction monocular image

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Performance analysis on dynamic matrix controller with single prediction strategy

Performance analysis on dynamic matrix controller with singl...

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World Congress on Intelligent control and automation (WCICA)

作者： YuTao Chen ShaoYuan Li Ning Li Department of Automation Key Laboratory of System Control and Information Processing Shanghai P.R. China Shanghai Jiao Tong University Shanghai CN

The property of single prediction predictive control in the form of dynamic matrix control is studied within internal model control framework. The sensitivity function and integral squared error are used as performance evaluation criteria in the frequency and time domain respectively, to quantitatively analyze single prediction strategy, especially on controller with the prediction and control horizon P = M = 1. We present the correlation between system performance and model mismatch in this case. The performance limitation for tracking unit step signal is obtained through derivation and simulation.

关键词： Sensitivity system performance Robustness Frequency-domain analysis Time-domain analysis Bandwidth control systems

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Improving ℒ 2 Gain Performance of Linear systems by Reset control

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IFAC Proceedings Volumes 2014年第3期47卷 6400-6405页

作者： Guanglei Zhao Dragan Nesic Ying Tan Jingcheng Wang Department of Automation Shanghai JiaoTong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Department of Electrical and Electronic Engineering University of Melbourne Parkville 3010 VIC. Australia

In this paper, new Lyapunov-based reset rules are constructed to improve ℒ 2 gain performance of linear-time-invariant (LTI) systems. By using the hybrid system framework, sufficient conditions for exponential and finite gain ℒ 2 stability are presented. It is shown that the ℒ 2 gain of the closed loop system with resets can be improved compared with the base system. Numerical example supports our results.

关键词： Hybrid system Lyapunov-based reset rules ℒ 2 gain reset controller

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