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Group Hybrid Coordination control of Multi-Agent systems With Time-Delays and Additive Noises

IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 737-748页

作者： Chuanjian Li Xiaofeng Zong School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China IEEE

A new kind of group coordination control problemgroup hybrid coordination control is investigated in this *** group hybrid coordination control means that in a whole multi-agent system(MAS)that consists of two subgroups with communications between them,agents in the two subgroups achieve consensus and containment,*** MASs with both time-delays and additive noises,two group control protocols are proposed to solve this problem for the containment-oriented case and consensus-oriented case,*** developing a new analysis idea,some sufficient conditions and necessary conditions related to the communication intensity betw een the two subgroups are obtained for the following two types of group hybrid coordination behavior:1)Agents in one subgroup and in another subgroup achieve weak consensus and containment,respectively;2)Agents in one subgroup and in another subgroup achieve strong consensus and containment,*** is revealed that the decay of the communication impact betw een the two subgroups is necessary for the consensus-oriented ***,the validity of the group control results is verified by several simulation examples.

关键词： Additive noises consensus control containment control group hybrid coordination control multi-agent systems(MASs) time-delays

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Adaptive control for Stochastic Nonlinear systems with Input Saturation Based on Multi-dimensional Taylor Network 20

Adaptive Control for Stochastic Nonlinear Systems with Input...

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20th IEEE International Conference on Mechatronics and automation, ICMA 2023

作者： Zheng, Xiao-Yi Yan, Hong-Sen Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University School of Automation Nanjing210096 China

ISBN: (纸本)9798350320831

For stochastic nonlinear systems with input saturation, few of the existing control methods use a suitable auxiliary system to solve input saturation problem, and most of them are for deterministic systems. In this study, according to the backstepping approach and the Lyapunov stability theorem, utilizing multi-dimensional Taylor network (MTN), an adaptive controller is presented to secure that all closed-loop signals keep bounded in probability, in which MTN is implemented to approach the uncertain function during the controller design. Moreover, the impact raised by input saturation is mitigated by designing an appropriate auxiliary system, in which the order of the auxiliary system is the same as that of the controlled system. Furthermore, unlike the majority of prior findings, the final output signal could be constrained in a mean quartic sense by an explicit expression of the input saturation error (the difference between the control signal and the saturation input) and the parameters used for design. Finally, the efficiency of the suggested control methodology is confirmed by providing an example. © 2023 IEEE.

关键词： Stochastic systems

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LSTM-TD3-based control for delayed drone combat strategies 19th

LSTM-TD3-based control for delayed drone combat strategies

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19th Chinese Intelligent systems Conference, CISC 2023

作者： Ji, Bingyu Wang, Jun Zhang, Hailin Zhang, Ya School of Automation Southeast University Nanjing210096 China Key Laboratory Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9789819968817

Reinforcement learning has made great achievements in the field of game confrontation, and military rendition intelligence is also imminent. In this paper, we propose a game confrontation game model based on LSTM and deep reinforcement learning for the red and blue sides of the drones in the delayed *** action buffer pair is added to the original battlefield environment to create a large latency environment, a TD3 algorithm is designed to join LSTM to predict the state trend, and a historical data pool is built using PER. The training results in the simulation platform show that the model has a significant improvement in effectiveness in the large latency environment, with a 0.22 improvement in battle damage ratio and a 34.76% improvement in win rate over the original model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Reinforcement learning

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Efficient temporal alignment network for smoke detection

Efficient temporal alignment network for smoke detection

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2023 Jiangsu Annual Conference on automation, JACA 2023

作者： Li, Weitai Lu, Xiaobo Cao, Yichao School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781839539848

Smoke is a distinctive feature of pre-fire combustion and it is critical to prevent fires by detecting smoke. Previous work has demonstrated that deep learning methods have a wide range of applications in the field of smoke detection. However, existing methods still have some problems, i.e., it is difficult to balance the relationship between accuracy and speed. In order to solve the existing problems, we proposed Efficient Temporal Alignment Network (ETAN) for Video Smoke Detection. Feature Aggregation Module (FAM) was designed to extract the dynamic features between frames, and we proposed Recursive Memory Feature Update (RMFU) module to maintain the features of past frames and fuse the current features to boost detection performance. Finally, experiments demonstrated that the proposed method improved about 3.8 mAP compared with base detector with little increase in the number of parameters, and outperformed all the single-frame detection methods with the same amount of parameters. Compared with video smoke detection methods, the detection achieved close to the same accuracy while 6.1 times faster than multi-frame methods. © The Institution of engineering & Technology 2023.

关键词： Smoke

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Non-Smooth Speed control of Switched Reluctance Motor Based on Generalized Proportional Integral Observer 42

Non-Smooth Speed Control of Switched Reluctance Motor Based ...

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42nd Chinese control Conference, CCC 2023

作者： Yin, Qingzhao Tian, Zheng Li, Shihua School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9789887581543

This paper investigates the speed regulation control of switched reluctance motor (SRM) systems. To improve the antidisturbance performance of SRM, a composite non-smooth control strategy is proposed. First, the structure of SRM is analyzed, and a simplified nonlinear model is obtained based on a segmented representation of the varying phase inductance. A virtual control function is introduced to represent the nonlinear part of the torque equation, whose inverse function is cascaded to linearized the nonlinear model. Second, a generalized proportional integral observer (GPIO) is constructed to estimate the lumped disturbance of the system, which is used for feedforward compensation design. Finally, a composite speed controller is designed based on a combination of finite time proportional feedback and feed-forward compensation based on GPIO (FTP+GPIO). The speed error closed-loop system can be regarded as a first-order finite time control system with bounded disturbances. Strict analysis shows that the proposed scheme can improve the anti-disturbance performance of the closed-loop system. The effectiveness of the proposed method is verified by simulation results. Moreover, it is compared with proportional feedback combining feed-forward compensation (P+GPIO) method and proportional integral (PI) control method. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Closed loop systems

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Obstacle-circumventing adaptive control of a four-wheeled mobile robot subjected to motion uncertainties

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Frontiers of Mechanical engineering 2023年第3期18卷 123-143页

作者： Yiming YAN Shuting WANG Yuanlong XIE Hao WU Shiqi ZHENG Hu LI School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China

To achieve the collision-free trajectory tracking of the four-wheeled mobile robot(FMR),existing methods resolve the tracking control and obstacle avoidance *** the synergistic robustness and smooth navigation of mobile robots subjected to motion uncertainties in a dynamic environment using this non-cooperative processing method is *** address this challenge,this paper proposes an obstacle-circumventing adaptive control(OCAC)***,a novel anti-disturbance terminal slide mode control with adaptive gains is formulated,incorporating specified control laws for different *** formulation guarantees rapid convergence and simultaneous chattering *** introducing sub-target points,a new sub-target dynamic tracking regression obstacle avoidance strategy is presented to transfer the obstacle avoidance problem into a dynamic tracking one,thereby reducing the burden of local path searching while ensuring system stability during obstacle *** experiments demonstrate that the proposed OCAC method can strengthen the convergence and obstacle avoidance efficiency of the concerned FMR system.

关键词： four-wheeled mobile robot obstacle-circumventing adaptive control adaptive anti-disturbance terminal sliding mode control sub-target dynamic tracking regression obstacle avoidance

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Anti-disturbance Low Speed Regulation control of PMSMs Using Modified Extended State Observer Based on Rotor Position

Anti-disturbance Low Speed Regulation Control of PMSMs Using...

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2024 Jiangsu Annual Conference on automation, JACA 2024

作者： Xu, Lei Mao, Linxuan Li, Shihua School of Electronic Science and Engineering Southeast University Nanjing210096 China School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

A modified extended state observer (ESO) based rotor position algorithm is proposed for improving low speed regulation control performance. The speed signal is often obtained by differentiating the position signal. However, the position signal of encoder with quantization errors results in crawling and shaking at low speeds. Considering quantization error as a type of noise limited their own accuracy, the environmental influences like mechanical vibration and electromagnetic interference also lead to noise in rotor position. The modified ESO method incorporated a Kalman filter (KF) is proposed to reduce the negative impact of noise. Due to differential amplification noise, the position signal is used instead of traditional speed signal for observers design because of its undesirable characteristics at low speed. The modified ESO based on rotor position is used to estimate both speed signal and disturbances to enhance the low speed performance in the presence of disturabances and measurement noise. The friction model is embedded for above integrated structure due to its nonliearity at low speeds. Considering the negative effects of measurement noise and disturbance at low speeds, it has verified that the proposed algorithm has better dynamic and steady-state performance and anti-disturbance ability through simulation. © The Institution of engineering & Technology 2024.

关键词： State estimation

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Vision-Based Quadrotor Rapid Landing control with An Uncooperative Platform: An Alternating Predictive Observer Approach

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-13页

作者： Shao, Liren Guo, Zeyu Yang, Jun Li, Shihua School of Automation Key Laboratory of Measurement and Control of CSE Ministry of Education Southeast University China Department of Aeronautical and Automotive Engineering Loughborough University Loughborough U.K

The challenge of allowing a quadrotor to land quickly on an unknown moving platform using visual cues is addressed. A position-based visual servoing (PBVS) framework is designed that utilises the relative position data captured by the onboard camera to ensure a successful landing. The inherent limitation imposed by the camera's low sampling rate, which hampers the update and transfer rate of control commands, is mitigated by introducing an alternating predictive observer (APO). This observer inputs rapid actual or virtual position information into the control system. Actual relative positions are used for observer design when available from the camera, whereas virtual relative positions, predicted by the quadrotor model, are used when direct sampling is unattainable. This approach enables a process that alternates between prediction and observation, allowing for the design of a sampled-data controller that updates at a fast rate, commensurate with the APO. The robustness of the proposed PBVS-APO controller is exhibited, requiring no prior knowledge of the platform's dynamics. Validation through numerical simulations and experiments confirms the high control bandwidth and the rapid landing efficacy of the control strategy. IEEE

关键词： Cameras

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Self-supervised Depth Completion with Adaptive Online Adaptation 23

Self-supervised Depth Completion with Adaptive Online Adapta...

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7th International Conference on Machine Learning and Soft Computing, ICMLSC 2023

作者： Chen, Yang Tan, Yang Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9781450398633

Although depth completion has achieved remarkable performance relying on deep learning in recent years, these models tend to suffer a performance degradation when exposed to new environments. Online adaptation, where the model is trained in a self-supervised manner during testing, seems a promising technique to alleviate the drop. However, continuous online adaptation may cause the model to over-adapt and miss the optimal parameters, resulting in oscillation or even degradation of the model performance, in addition to wasting computational resources. Therefore, this paper proposes an adaptive online adaptation framework to make model adaptively trigger online adaptation when encountering novel environments and stop adaptation when model has adapted to the current environment. In detail, we design a trigger to detect the familiarity of model to the current scenario based on image similarity and then launch online adaptation when the scenario is novel. Besides, we elaborate a stopper to monitor the error between prediction and depth input and convert online adaptation to inference when online adaptation does not bring improvement for model. Experimental results demonstrate that our method improves the accuracy of model prediction and increases average running speed of the model on each frame in online adaptation. © 2023 ACM.

关键词： Deep learning

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Optimal Strategy for Aircraft Pursuit-evasion Games via Self-play Iteration

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Machine Intelligence Research 2024年第3期21卷 585-596页

作者： Xin Wang Qing-Lai Wei Tao Li Jie Zhang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing100049China Institute of Systems Engineering Macao University of Science and TechnologyMacao999078China

In this paper,the pursuit-evasion game with state and control constraints is solved to achieve the Nash equilibrium of both the pursuer and the evader with an iterative self-play *** the condition where the Hamiltonian formed by means of Pontryagin’s maximum principle has the unique solution,it can be proven that the iterative control law converges to the Nash equilibrium ***,the strong nonlinearity of the ordinary differential equations formulated by Pontryagin’s maximum principle makes the control policy difficult to figured *** the system dynamics employed in this manuscript contains a high dimensional state vector with *** practical applications,such as the control of aircraft,the provided overload is ***,in this paper,we consider the optimal strategy of pursuit-evasion games with constant constraint on the control,while some state vectors are restricted by the function of the *** address the challenges,the optimal control problems are transformed into nonlinear programming problems through the direct collocation ***,two numerical cases of the aircraft pursuit-evasion scenario are given to demonstrate the effectiveness of the presented method to obtain the optimal control of both the pursuer and the evader.

关键词： Differential games pursuit-evasion games nonlinear control optimal control Nash equilibrium solution

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