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Hyperchaos synchronization using univariate impulse control

Physical Review E 2019年第5期100卷 052215-052215页

作者： Kun Tian Chao Bai Hai-Peng Ren Celso Grebogi Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an 710048 China School of Mechatronics Engineering Xi'an Technological University Xi'an 710048 China Institute for Complex System and Mathematical Biology SUPA University of Aberdeen AB24 3UE United Kingdom

Rössler and Chen systems with time delay are shown to be hyperchaotic, which exhibits a more complex dynamics, including multiple positive Lyapunov exponents and infinite dimension. The hyperchaos has better application potential where hyperchaos synchronization is concerned. Univariate impulse control requires smaller perturbation to the response system, thus promising better performance. However, synchronization of two hyperchaotic systems using this control method is a challenging task due to the difficulty to guarantee synchronization stability using a minimum number of manipulated variables. In this paper, a univariate impulse control method is proposed for the synchronization of two hyperchaotic dynamics generated by time delay. A theorem is developed and proved to provide the sufficient conditions for the synchronization of time delay systems using the univariate impulse control. The upper bound of the impulse interval is proved to guarantee the asymptotic synchronization. Simulation and circuit experiment show the correctness of the analysis and the feasibility of the proposed method.

关键词： control & applications of chaos Synchronization

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

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IEEE International Conference on Robotics and Biomimetics

作者： Muyang Hou Zhenya Lei Haidong Hu Zhong Wang Yong Wang Le Xie Hesheng Wang Department of Automation Shanghai Jiao Tong University Shanghai China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Beijing Institute of Control Engineering Beijing China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant; on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A* which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion.

关键词： Hands Trajectory tracking Trajectory planning Service robots Stability analysis Safety Mobile robots Resource management Splines (mathematics) Trajectory optimization

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Short-Term Load Forecasting for Buildings Based on Dynamic Weighted edRVFL Model

Short-Term Load Forecasting for Buildings Based on Dynamic W...

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Chinese Automation Congress (CAC)

作者： Junwei Xie Meng Yuan Zhezhuang Xu Chi Liu Yuxiong Xia Department of Fujian Province College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Fuzhou China Fujian Huading Intelligent Manufacturing Technology Co. Ltd Fuzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Short-term load forecasting of buildings plays a key role in demand management, however, when dealing with massive data, the prevalent practice of training and testing the system as a whole overlooks pattern variations inside data and potentially limits predictive performance. To address this issue, this paper proposes an ensemble deep random vector functional link (edRVFL) model that combines adaptive ensemble clustering and dynamic weighting strategy for load forecasting of an industrial building. Firstly, the adaptive ensemble clustering that combines ordering points to identify the clustering structure and K nearest neighbor is employed to determine the electricity load usage patterns. Subsequently, the improved particle swarm optimization algorithm is applied to adjust the weights of load curves in different typical day scenarios. Finally, a dynamic weighting strategy is designed to dynamically assign model weights to two clusters, where one matches the type of predicted load pattern for the day being forecasted and another for the cluster of the previous day. The experiment in a real building verifies the effectiveness of the proposed algorithm, which has higher prediction accuracy than other comparison algorithms including one-week interval and different ensemble clustering.

关键词： Adaptation models Load forecasting Heuristic algorithms Buildings Clustering algorithms Predictive models Prediction algorithms Vectors Forecasting Load modeling

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Autocorrelation Invariance Property of Chaos for Wireless Communication

arXiv

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arXiv 2022年

作者： Yin, Hui-Ping Ren, Hai-Peng Grebogi, Celso Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'An710048 China Institute for Complex Systems and Mathematical Biology University of Aberdeen AB24 3UE United Kingdom

A new feature of the chaotic signal generated by chaotic shape-forming filter (CSF) is uncovered in this work. We find that, the autocorrelation function (ACF) of the transmitting signal generated by CSF keeps the same as that of the base function of CSF, no matter what information is encoded. We derive the analytical equation to describe the relation between the ACF of the received signal and the wireless channel parameters using the ACF of the transmitted signal as prior knowledge revealed by the finding in this work. This new property can be utilized together with different wireless communication systems to improve the system performance. Specially, to demonstrate the improvement, channel state information (CSI) is identified using the chaotic baseband wireless communication as a paradigm. Two significant benefits by using the new property are 1) the CSI can be identified without the probe information known to the receiver as done in the conventional wireless communication systems, which improves the bandwidth efficiency, especially in the time-varying channel;2) the correlation operation is insensitive to the channel noise, which improves the identification accuracy as compared to the commonly used methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Channel state information

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ESNet: evolution and succession network for high-resolution salient object detection 24

ESNet: evolution and succession network for high-resolution ...

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Proceedings of the 41st International Conference on Machine Learning

作者： Hongyu Liu Runmin Cong Hua Li Qianqian Xu Qingming Huang Wei Zhang Institute of Information Science Beijing Jiaotong University & Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing China School of Control Science and Engineering Shandong University & Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Computer Science and Technology Hainan University Hainan China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

Preserving details and avoiding high computational costs are the two main challenges for the High-Resolution Salient Object Detection (HRSOD) task. In this paper, we propose a two-stage HRSOD model from the perspective of evolution and succession, including an evolution stage with Low-resolution Location Model (LrLM) and a succession stage with High-resolution Refinement Model (HrRM). The evolution stage achieves detail-preserving salient objects localization on the low-resolution image through the evolution mechanisms on supervision and feature; the succession stage utilizes the shallow high-resolution features to complement and enhance the features inherited from the first stage in a lightweight manner and generate the final high-resolution saliency prediction. Besides, a new metric named Boundary-Detail-aware Mean Absolute Error (MAEBD) is designed to evaluate the ability to detect details in high-resolution scenes. Extensive experiments on five datasets demonstrate that our network achieves superior performance at real-time speed (49 FPS) compared to state-of-the-art methods. Our code is publicly available at: https://***/rmcong/ESNet_ICML24.

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Artificial intelligence enhances the performance of chaos-based wireless communication

arXiv

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arXiv 2019年

作者： Ren, Hai-Peng Zhao, Hong-Er Bai, Chao Yin, Hui-Ping Grebogi, Celso Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xian710048 China Institute for Complex Systems and Mathematical Biology University of Aberdeen AB24 3UE United Kingdom

Some new findings for chaos-based wireless communication systems have been identified recently. First, chaos has proven to be the optimal communication waveform because chaotic signals can achieve the maximum signal to noise ratio at receiver with the simplest matched filter. Second, the information transmitted in chaotic signals is not modified by the multipath wireless channel. Third, chaos properties can be used to relief inter-symbol interference (ISI) caused by multipath propagation. Although recent work has reported the method of obtaining the optimal threshold to eliminate the ISI in chaos-based wireless communication, its practical implementation is still a challenge. By knowing the channel parameters and all symbols, especially the future symbol to be transmitted in advance, it is almost an impossible task in the practical communication systems. Owning to Artificial intelligence (AI) recent developments, Convolutional Neural Network (CNN) with deep learning structure is being proposed to predict future symbols based on the received signal, so as to further reduce ISI and obtain better bit error rate (BER) performance as compared to that used the existing sub-optimal threshold. The feature of the method involves predicting the future symbol and obtaining a better threshold suitable for time variant channel. Numerical simulation and experimental results validate our theory and the superiority of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Signal to noise ratio

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Radio-wave communication with chaos

arXiv

引用

arXiv 2018年

作者： Ren, Hai-Peng Zheng, Wu-Yun Grebogi, Celso Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Institute for Complex System and Mathematical Biology SUPA University of Aberdeen AberdeenAB243UE United Kingdom

The invariance of the Lyapunov exponent of a chaotic signal as it propagates along a wireless transmission channel provides a theoretical base for the application of chaos in wireless communication. In additive Gaussian channel, the chaotic signal is proved to be the optimal coherent communication waveform in the sense of using the very simple matched filter to obtain the maximum signal-to-noise ratio. The properties of chaos can be used to reduce simply and effectively the Inter-Symbol Interference (ISI) and to achieve low bit error rate in the wireless communication system. However, chaotic signals need very wide bandwidth to be transmitted in the practical channel, which is difficult for the practical transducer or antenna to convert such a broad band signal. To solve this problem, in this work, the chaotic signal is applied to a radio-wave communication system, and the corresponding coding and decoding algorithms are proposed. A hybrid chaotic system is used as the pulse-shaping filter to obtain the baseband signal, and the corresponding matched filter is used at the receiver, instead of the conventional low-pass filter, to maximize the signal-to-noise ratio. At the same time, the symbol judgment threshold determined by the chaos property is used to reduce the Inter-Symbol Interference (ISI) effect. Simulations and virtual channel experiments show that the radio-wave communication system using chaos obtains lower bit error rate in the multi-path transmission channel compared with the traditional radio-wave communication system using Binary Phase Shift keying (BPSK) modulation technology and channel equalization. Copyright © 2018, The Authors. All rights reserved.

关键词： Matched filters

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Differentiator-Based Adaptive H∞ Tracking control of Fully Actuated Systems

Differentiator-Based Adaptive H∞ Tracking Control of Fully ...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Yuxin Feng Zhiqiang Li Yang Liu Zhaoshui He Hongyi Li School of Automation and Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of Technology Guangzhou China School of Automation and Electronics Engineering Qingdao University of Science and Technology Qingdao China School of Automation Guangdong University of Technology Guangzhou China Key Laboratory for IoT Intelligent Information Processing and System Integration of Ministry of Education Guangzhou China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This article addresses an adaptive tracking control problem for uncertain high-order fully actuated (HOFA) systems with unknown parameters and disturbances. Under the framework of backstepping, the unknown parameter is estimated and the external disturbance is handled by using adaptive control and H ∞ technique, respectively. Moreover, the Levant differentiator is employed to reduce the computation burden. Additionally, the boundedness of signals in the closed-loop system is proven using the Lyapunov theory. Finally, the effectiveness of the proposed scheme is validated through the simulation study.

关键词： Backstepping Manipulators Stability analysis Closed loop systems Adaptive control Lyapunov methods

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Ascl: Accelerating Semi-Supervised Learning Via Contrastive Learning

SSRN

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SSRN 2024年

作者： Liu, Haixiong Li, Zuoyong Wu, Jiawei Zeng, Kun Hu, Rong Zeng, Wei Fujian Provincial Key Laboratory of Big Data Mining and Applications School of Computer Science and Mathematics Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Data Science Minjiang University Fuzhou350121 China School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Guangdong Shenzhen518107 China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University Wuyishan354300 China School of Physics and Mechanical and Electrical Engineering Longyan University Longyan364012 China

SSL(Semi-supervised learning) is widely used in machine learning, which leverages labeled and unlabeled data to improve model performance. SSL aims to optimize class mutual information, but noisy pseudo-labels introduce false class information due to the scarcity of labels. Therefore, these algorithms often need significant training time to refine pseudo-labels for performance improvement iteratively. To tackle this challenge, we propose a novel plug-and-play method named ASCL(Accelerating Semi-Supervised Learning via Contrastive Learning). This method combines contrastive learning with uncertainty-based selection for performance improvement and accelerates the convergence of SSL algorithms. Contrastive learning initially emphasizes the mutual information between samples as a means to decrease dependence on pseudo-labels. Subsequently, it gradually turns to maximizing the mutual information between classes, aligning with the objective of semi-supervised learning. Uncertainty-based selection provides a robust mechanism for acquiring pseudo-labels. The combination of the contrastive learning module and the uncertainty-based selection module forms a virtuous cycle to improve the performance of the proposed model. Extensive experiments demonstrate that ASCL outperforms state-of-the-art methods in terms of both convergence efficiency and performance. In the experimental scenario where only one label is assigned per class in the CIFAR-10 dataset, the application of ASCL to Pseudo-label, UDA (Unsupervised Data Augmentation for Consistency Training), and Fixmatch benefits substantial improvements in classification accuracy. Specifically, the results demonstrate notable improvements in respect of 16.32%, 6.9%, and 24.43% when compared to the original outcomes. Moreover, the required training time is reduced by almost 50%. © 2024, The Authors. All rights reserved.

关键词： image classification

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Micro Channel for Analyzing Mechanical Adaption of Cancer Cell

Micro Channel for Analyzing Mechanical Adaption of Cancer Ce...

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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Pengyun Li Xiaoming Liu Xiaoqing Tang Masaru Kojima Jian Huang Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and the Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Osaka University 1-3 Machikaneyama Toyonaka Osaka Japan Key Laboratory of Ministry of Education for Image Processing and Intelligent Control the School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781728150734

ISBN: (纸本)9781728150741

It was reported that cancer cells could biologically respond and adapt to the confined environment during migration in extracellular matrix (ECM). But it is not clearly studied that how cancer cells respond and adapt to confined environment in mechanical way. Thus, in this study, we designed and fabricated a kind of one-layer micro channel to mimic confined environment for analyzing mechanical adaption of cell. This micro channel could apply sequential mechanical stresses on a number of cells with high throughput, and the time of cells passing through five rows of micro channels were used to evaluate their adaptability to the sequential and confined space. In experiments, each cell suffered 20 times of mechanical stresses after passing through 20 squeezing channels arranged in 5 rows. We observed the sequential squeezing processes under microscope and investigated the passing time using a high-speed camera. The preliminary results indicated that cancer cells could pass through and adapt to the confined environment faster than normal cells.

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