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Mean square stability for Markov jump Boolean networks

Science China(Information Sciences) 2020年第1期63卷 190-199页

作者： Liqing WANG Mei FANG Zheng-Guang WU State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang University College of Automation Harbin Engineering University

In this paper, one of the stability definitions of Markov jump Boolean networks(MJBNs), called mean square stability(MSS), is investigated. Some necessary and sufficient conditions are presented to guarantee the MSS of such MJBNs. Moreover, one of the necessary and sufficient conditions for MSS is obtained in terms of linear programming, which implies that MSS is equivalent to global stability with probability 1 for MJBNs. Furthermore, the construction of Lyapunov function is given and also another theorem based on the Lyapunov function is derived to ensure the MSS of MJBNs. Finally, a numerical example is provided to illustrate the profits of our results.

关键词： mean square stability MSS Boolean network BN stochastic stability Markovian jump parameters semi-tensor product STP Lyapunov function

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Learning Gait-conditioned Bipedal Locomotion with Motor Adaptation*

Learning Gait-conditioned Bipedal Locomotion with Motor Adap...

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IEEE-RAS International Conference on Humanoid Robots

作者： Wandi Wei Zhicheng Wang Anhuan Xie Jun Wu Rong Xiong Qiuguo Zhu Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Zhejiang Lab Hangzhou China State Key Laboratory of Industrial Control Technology Hangzhou China

Whole body locomotion in humanoid robots remains a significant challenge due to the requirement of whole body coordination, natural bipedal walking gait, and accurate state estimation to enable them to traverse plain and uneven terrain. In this paper, we propose a learning-based humanoid locomotion controller that can adapt to disturbance and uneven terrain. We leverage the advances in rapid adaptation for quadruped locomotion control, and expend them to the humanoid robots, resulting in a well-performed whole body locomotion policy, gait-conditioned RMA without any reference trajectory during training. In simulation test, our trained policy demonstrates the ability to generalize in unseen turning tasks and showcases its robustness in more complex environment include hill and steps.

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Parameter Estimation and Tracking control of MIMO Linear systems Without Prior Knowledge of control Signs and Parameter Bounds

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IEEE Transactions on Automatic control 2024年第6期70卷 3695-3710页

作者： Xu, Yuchun Zhang, Yanjun Zhang, Ji-Feng Chinese Academy of Sciences Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Beijing100190 China Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology State Key Lab of Automation Intelligent Unmanned Systems Beijing100081 China University of Chinese Academy of Sciences School of Mathematics Sciences Beijing100149 China Zhongyuan University of Technology School of Automation and Electrical Engineering Zhengzhou450007 China Chinese Academy of Sciences Academy of Mathematics and Systems Science Beijing100190 China

Dealing with the uncertain high-frequency gain matrix, denoted as Kp, is a fundamental problem in multivariable adaptive control systems. In this paper, we propose a new solution for parameter estimation and adaptive control for a general class of multi-input multi-output discrete-time linear time-invariant systems. The proposed scheme does not require any prior knowledge of the sign or bound information of Kp, and thus, significantly relaxes the design conditions in traditional multivariable adaptive control systems. Compared with the commonly used Nussbaum gain or multi-model techniques for addressing the unknown signs of Kp, the proposed scheme does not rely on any additional design conditions or any switching mechanism, while still ensuring closed-loop stability and asymptotic output tracking. Specifically, an output feedback adaptive control law is developed based on a matrix decomposition technique, which leads to derivation of a modified estimation error model. Subsequently, a gradient-based parameter update law is formulated only relying on the non-zero condition of the leading principle minors of Kp. Through designing gain functions and stable filters, the controller is always non-singular and does not involve any causal contradiction problem. Simulation study showcases the design process and demonstrates the effectiveness of the proposed scheme. © 1963-2012 IEEE.

关键词： MIMO systems

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Non-fragile H∞ Filtering for Fuzzy Discrete-time systems with Markovian Jump and Data Loss 10

Non-fragile H∞ Filtering for Fuzzy Discrete-time Systems wi...

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10th IEEE Data Driven control and Learning systems Conference, DDCLS 2021

作者： Liang, Lun State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang Hangzhou310027 China

ISBN: (纸本)9781665424233

This paper focuses on the design of the non-fragile H∞ filtering of fuzzy discrete-time systems with Markovian jump and data loss. The system is represented by Takagi and Sugeno (T-S) fuzzy model. The imperfect information transmission from the factory to the filter is modeled by a Bernoulli random binary distribution. A non-fragile and full-order H∞ filter with additive gain variations is constructed. The sufficient conditions are derived based on mode-dependent and fuzzy-basis-dependent Lyapunov functional methods, which ensure the developed filtering error system is stochastically stable with given H∞ performance index. The usefulness and effectiveness of the filter design method is certified by a numerical case. © 2021 IEEE.

关键词： Numerical methods

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Obstacle Avoidance for Unicycle-Modelled Mobile Robots with Time-varying control Barrier Functions

arXiv

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arXiv 2023年

作者： Huang, Jihao Liu, Zhitao Zeng, Jun Chi, Xuemin Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Cruise LLC United States

In this paper, we propose a safety-critical controller based on time-varying control barrier functions (CBFs) for a robot with an unicycle model in the continuous-time domain to achieve navigation and dynamic collision avoidance. Unlike previous works, our proposed approach can control both linear and angular velocity to avoid collision with obstacles, overcoming the limitation of confined control performance due to the lack of control variable. To ensure that the robot reaches its destination, we also design a control Lyapunov function (CLF). Our safety-critical controller is formulated as a quadratic program (QP) optimization problem that incorporates CLF and CBFs as constraints, enabling real-time application for navigation and dynamic collision avoidance. Numerical simulations are conducted to verify the effectiveness of our proposed approach. Copyright © 2023, The Authors. All rights reserved.

关键词： controllers

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DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition

DeepRING: Learning Roto-translation Invariant Representation...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Sha Lu Xuecheng Xu Li Tang Rong Xiong Yue Wang State Key Laboratory of Industrial Control and Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Alibaba Group Hangzhou China

LiDAR based place recognition is popular for loop closure detection and re-localization. In recent years, deep learning brings improvements to place recognition by learnable feature extraction. However, these methods degenerate when the robot re-visits previous places with a large perspective difference. To address the challenge, we propose DeepRING to learn the roto-translation invariant representation from LiDAR scan, so that robot visiting the same place with a different perspective can have similar representations. There are two keys in DeepRING: the feature is extracted from sinogram, and the feature is aggregated by magnitude spectrum. The two steps keep the final representation with both discrimination and roto-translation invariance. Moreover, we state place recognition as a one-shot learning problem with each place being a class, leveraging relation learning to build representation similarity. Substantial experiments are carried out on public datasets, validating the effectiveness of each proposed component, and showing that DeepRING outperforms the comparative methods, especially in dataset level generalization.

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CREPES: Cooperative RElative Pose Estimation System

CREPES: Cooperative RElative Pose Estimation System

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Zhiren Xunt Jian Huang Zhehan Li Zhenjun Ying Yingjian Wang Chao Xu Fei Gao Yanjun Cao State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Huzhou Institute of Zhejiang University Huzhou China

Mutual localization plays a crucial role in multi-robot cooperation. CREPES, a novel system that focuses on six degrees of freedom (DOF) relative pose estimation for multi-robot systems, is proposed in this paper. CREPES has a compact hardware design using active infrared (IR) LEDs, an IR fish-eye camera, an ultra-wideband (UWB) module and an inertial measurement unit (IMU). By leveraging IR light communication, the system solves data association between visual detection and UWB ranging. Ranging measurements from the UWB and directional information from the camera offer relative 3-DOF position estimation. Combining the mutual relative position with neighbors and the gravity constraints provided by IMUs, we can estimate the 6-DOF relative pose from a single frame of sensor measurements. In addition, we design an estimator based on the error-state Kalman filter (ESKF) to enhance system accuracy and robustness. When multiple neighbors are available, a Pose Graph Optimization (PGO) algorithm is applied to further improve system accuracy. We conduct enormous experiments to demonstrate CREPES’ accuracy between robot pairs and a team of robots, as well as performance under challenging conditions.

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Adaptive cubature Kalman filter with the estimation of correlation between multiplicative noise and additive measurement noise

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Chinese Journal of Aeronautics 2022年第5期35卷 40-52页

作者： Quanbo GE Zhongcheng MA Jinglan LI Qinmin YANG Zhenyu LU Hong LI School of Electronics and Information Engineering Tongji UniversityShanghai 201804China Institute of Systems Science and Control Engineering School of AutomationHangzhou Dianzi UniversityHangzhou 310018China State Key Laboratory of Industrial Control Technology and the College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Jiangsu Key Laboratory of Meteorological Observation and Information Processing Nanjing University of Information Science and TechnologyNanjing 210044China Chinese Flight Test Establishment Xi’an 710089China

Mobile robots are often subject to multiplicative noise in the target tracking tasks,where the multiplicative measurement noise is correlated with additive measurement *** this paper,first,a correlation multiplicative measurement noise model is *** is able to more accurately represent the measurement error caused by the distance sensor dependence ***,the estimated performance mismatch problem of Cubature Kalman Filter(CKF)under multiplicative noise is *** improved Gaussian filter algorithm is introduced to help obtain the CKF algorithm with correlated multiplicative *** practice,the model parameters are unknown or inaccurate,especially the correlation of noise is difficult to obtain,which can lead to a decrease in filtering accuracy or even *** address this,an adaptive CKF algorithm is further provided to achieve reliable state estimation for the unknown noise correlation coefficient and thus the application of the CKF algorithm is ***,the estimated performance is analyzed theoretically,and the simulation study is conducted to validate the effectiveness of the proposed algorithm.

关键词： Adaptive CKF Correlated noise Estimation accuracy Multiplicative noise Performance analysis Target tracking

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Efficient Autonomous Exploration of Unknown Environment Using Regions Segmentation and VRP 1

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16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Xue, Chaoyu Zhao, Tianhao Xie, Anhuan Zhu, Qiuguo Wu, Jun Xiong, Rong College of Control Science and Engineering Zhejiang University Hangzhou China Polytechnic Institute Zhejiang University Hangzhou China Zhejiang Lab Hangzhou China State Key Laboratory of Industrial Control and Technology Zhejiang University Hangzhou China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

Autonomous exploration of unknown environments is a critical application scenario in robotics. However, existing studies have strived to generate an efficient tour plan that enables the robots to fully explore the environment. This is due to the greedy strategies and the lack of utilizing the information of the unexplored area. To address the above issues, we propose a new exploration strategy. Our approach involves partitioning the unexplored area into distinct regions and utilizing their estimated workload and spatial structure to construct a region graph. Subsequently, a VRP (Vehicle Routing Problem) planner allocates regions to robots and generates a global tour for each robot in a coordinated manner, which is then refined and provided to the robot’s navigation module. Experimental results demonstrate that that our method outperforms existing approaches in terms of exploration speed, total distance, and overlap ratio. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Robots

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Primitive-Planner: An Ultra Lightweight Quadrotor Planner with Time-optimal Primitives

arXiv

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arXiv 2025年

作者： Hou, Jialiang Pan, Neng Wang, Zhepei Ji, Jialin Guan, Yuxiang Gan, Zhongxue Gao, Fei Academy for Engineering and Technology Fudan University Shanghai200433 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China

It is a significant requirement for a quadrotor trajectory planner to simultaneously guarantee trajectory quality and system lightweight. Many researchers focus on this problem, but there’s still a gap between their performance and our common wish. In this paper, we propose an ultra lightweight quadrotor planner with time-optimal primitives. Firstly, a novel motion primitive library is proposed to generate time-optimal and dynamical feasible trajectories offline. Secondly, we propose a fast collision checking method with a deterministic time consumption, independent of the sampling resolution of the primitives. Finally, we select the minimum cost trajectory to execute among the safe primitives based on user-defined requirements. The propsed transformation relation between the local trajectories ensures the smoothness of the global trajectory. The planner reduces unnecessary online computing power consumption as much as possible, while ensuring a high-quality trajectory. Benchmark comparisons show that our method can generate the shortest flight time and distance of trajectory with the lowest computation overload. Challenging real-world experiments validate the robustness of our method. Copyright © 2025, The Authors. All rights reserved.

关键词： Flight paths

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