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Terrain-Based Hierarchical Trajectory Planning for Low-Altitude Flight of Fixed-Wing Aircrafts 1

7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Zhong, Yuhang Han, Zhichao Peng, Yiyang Zhao, Changchun Xu, Guangtong Xu, Chao Gao, Fei State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Huzhou Institute Zhejiang University Huzhou313000 China Shanghai Aerospace Control Technology Institute Shanghai201109 China

ISBN: (数字)9789819733408

ISBN: (纸本)9789819733392

For the complex low-altitude flight mission of fixed-wing aircrafts, this paper proposes a terrain-based trajectory generation method based on hierarchical planning framework. The sampling-based path planning algorithm, rapidly-exploring random tree (RRT*), is modified to search collision-free low-altitude path according to the terrain information. Since the generated path by RRT is not dynamically feasible, the subsequent trajectory optimization step is introduced to refine the non-smooth path. In this step, an advanced numerical optimization method is used to achieve spatial optimization subject to the flight performance of fixed-wing aircrafts, which can improve the trajectory smoothness and dynamic feasibility effectively. Numerical simulations on complex terrains are conducted, and the results validate the effectiveness and efficiency of the proposed method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Fixed wings

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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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Trajectory Tracking control for Autonomous Parking Based on Adaptive Reduced-horizon Model Predictive control 19

Trajectory Tracking Control for Autonomous Parking Based on ...

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19th IEEE International Conference on Networking, Sensing and control, ICNSC 2022

作者： Cai, Minghan Wu, Weimin Zhou, Xiaoling Technology Institute of Cyber-Systems and Control Zhejiang University The State Key Laboratory of Industrial Control Hangzhou310027 China College of Control Science and Engineering Zhejiang University Hangzhou310027 China

ISBN: (纸本)9781665472432

In this paper, an adaptive reduced-horizon model predictive control is proposed for autonomous parking trajectory tracking. Given the reference trajectory, the discrete linear time varying model is obtained by linearizing and discretizing along the reference trajectory point. Furthermore, the model is reformulated into a combined incremental form. Then, a standard quadratic programming problem is established, and the optimal control strategy is obtained by solving the problem online at every time instant. Meanwhiles, the prediction horizon will reduce adaptively by solving the constrained optimization problem, and it will minimize the computation time complexity of the MPC-based controller. The actual parking scenarios are co-simulated in Simulink and Carsim, which shows the effectiveness and feasibility of the proposed method. © 2022 IEEE.

关键词： Model predictive control

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Steady-state and dynamic simulation of gas phase polyethylene process

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Chinese Journal of Chemical Engineering 2024年第11期75卷 110-120页

作者： Xiaodong Hong Wanke Chen Zuwei Liao Xiaoqiang Fan Jingyuan Sun Yao Yang Chunhui Zhao Jingdai Wang Yongrong Yang State Key Laboratory of Chemical Engineering College of Chemical and Biological EngineeringZhejiang UniversityHangzhou 310027China Engineering Research Center of Functional Materials Intelligent Manufacturing of Zhejiang Province ZJU-Hangzhou Global Scientific and Technological Innovation CenterHangzhou 311215China Ningbo Research Institute Zhejiang UniversityNingbo 315100China State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China

Gas-phase polyethylene(PE)processes are among the most important methods for PE production.A deeper understanding of the process characteristics and dynamic behavior,such as properties of PE and reactor stability,holds substantial interest for both academic researchers and *** this study,both steady-state and dynamic models for a gas-phase polyethylene process are established as a simulation platform,which can be used to study a variety of operation tasks for commercial solution polyethylene processes,such as new product development,process control and real-time *** copolymerization kinetic parameters are fitted by industrial ***,a multi-reactor series model is developed to characterize the temperature distribution within the fluidized bed *** accuracy in predicting melt index and density of the polymer,and the dynamic behavior of the developed models are verified by real plant ***,the dynamic simulation platform is applied to compare four practical control schemes for reactor temperature by a series of simulation experiments,since temperature control is important in industrial *** results reveal that all four schemes effectively track the setpoint ***,only the demineralized water temperature cascade control demonstrates excellent performance in handling disturbances from both the recycle gas subsystem and the heat exchange subsystem.

关键词： Gas-phase polyethylene process Steady state Dynamic modeling control

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The First Five Years of a Phase Theory for Complex systems and Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1728-1743页

作者： Dan Wang Wei Chen Li Qiu Division of Decision and Control Systems KTH Royal Institute of TechnologyStockholm 10044Sweden Department of Mechanics and Engineering Science&the State Key Laboratory for Turbulence and Complex Systems Peking UniversityBeijing 100871China Hong Kong University of Science and Technology Hong KongChinaand also with the Southern University of Science and TechnologyShenzhen 518055China

In this paper,we review the development of a phase theory for systems and networks in its first five years,represented by a trilogy:Matrix phases and their properties;The MIMO LTI system phase response,its physical interpretations,the small phase theorem,and the sectored real lemma;The synchronization of a multi-agent network using phase *** the end,we also summarize a list of ongoing research on the phase theory and speculate what will happen in the next five years.

关键词： Consensus and synchronization matrix phases multi-agent systems phase theory sectored real lemma small phase theorem.

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Synthesis of Decoherence-Free Modes in Linear Quantum Passive systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

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2024 IEEE International Conference on systems, Man, and cybernetics, SMC 2024

作者： Miao, Zibo Pan, Yu Gao, Qing School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Guangdong Key Laboratory of Intelligent Morphing Mechanisms Shenzhen518055 China The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique. © 2024 IEEE.

关键词： Poles

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Few Shot Object Detection Based on Graph Attention Network 4

Few Shot Object Detection Based on Graph Attention Network

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4th IEEE International Conference on Pattern Recognition and Machine Learning, PRML 2023

作者： Ding, Rou Zhang, Yu Zhejiang University of Control Science and Engineering State Key Laboratory of Industrial Control Technology Zhejiang China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Zhejiang China

ISBN: (纸本)9798350324303

Few shot object detection is a challenging task in computer vision, as it involves detecting objects from a small number of examples. This makes it difficult for traditional object detection methods to generalize well to new classes or scenes. In this paper, we propose a siamese neural network model that utilizes the power of Faster RCNN for few shot object detection. The network takes in support and query datasets and extracts both support and query features. To supplement category information between various support features, we use Pearson similarity to enhance the features and extract support prototypes. We propose a graph attention network that can perform association matching between support prototype and proposals. Through this network, we facilitate information exchange between support features and query features, which helps to supplement the information of query images. We divide the training process into two stages. In the first stage, we use a large amount of basic category data to train the basic detection ability. In the second stage, we further train our model on few shot novel class and base class mixed datasets to improve its generalization performance. Experimental results on the public Pascal VOC dataset demonstrate that our proposed method achieves state-of-The-Art few shot object detection performance. © 2023 IEEE.

关键词： Object detection

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Efficient learning of robust quadruped bounding usingpretrained neural networks

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IET cyber-systems and Robotics 2022年第4期4卷 331-338页

作者： Zhicheng Wang Anqiao Li Yixiao Zheng Anhuan Xie Zhibin Li Jun Wu Qiuguo Zhu Institute of Cyber-Systems and Control Zhejiang UniversityZhejiangChina Intelligent Robot Research Center Zhejiang LabZhejiangChina Department of Computer Science University College LondonLondonUK State Key Laboratory of Industrial Control Technology Zhejiang UniversityZhejiangChina

Bounding is one of the important gaits in quadrupedal locomotion for negotiating *** authors proposed an effective approach that can learn robust bounding gaits more efficiently despite its large variation in dynamic body *** authors first pretrained the neural network(NN)based on data from a robot operated by conventional model-based controllers,and then further optimised the pretrained NN via deep reinforcement learning(DRL).In particular,the authors designed a reward function considering contact points and phases to enforce the gait symmetry and periodicity,which improved the bounding *** NN-based feedback controller was learned in the simulation and directly deployed on the real quadruped robot Jueying Mini successfully.A variety of environments are presented both indoors and outdoors with the authors’*** authors’approach shows efficient computing and good locomotion results by the Jueying Mini quadrupedal robot bounding over uneven *** cover image is based on the Research Article Efficient learning of robust quadruped bounding using pretrained neural networks by Zhicheng Wang et al.,https://***/10.1049/csy2.12062.

关键词： legged locomotion reinforcement learning robot learning

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The TAO of Blockchain Intelligence for Intelligent Web 3.0

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IEEE/CAA Journal of Automatica Sinica 2023年第12期10卷 2183-2186页

作者： Juanjuan Li Fei-Yue Wang IEEE the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

WE are in an exciting new intelligent era where various Web 3.0 systems emerge and flourish.[1]–[3].In this new epoch,the collaboration of data and knowledge,humans and machines,actual and virtual worlds is undergoing an unprecedented diversification and community-driven transformation,unveiling an open future full of boundless ***,the value of dispersed data extends far beyond passive storage and application.

关键词： Web TAO knowledge

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A Novel Evaluation Strategy to Artificial Neural Network Model Based on Bionics

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Journal of Bionic Engineering 2022年第1期19卷 224-239页

作者： Sen Tian Jin Zhang Xuanyu Shu Lingyu Chen Xin Niu You Wang School of Mathematics and Statistics Hunan Normal UniversityChangsha410081China College of Information Science and Engineering Hunan Normal UniversityChangsha410081China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhou310058China Science and Technology on Parallel and Distributed Laboratory College of ComputerNational University of Defense TechnologyChangsha410199China Key Laboratory of Industrial Control Technology Institute of Cyber Systems and ControlZhejiang UniversityHangzhou310027China

With the continuous deepening of Artificial Neural Network(ANN)research,ANN model structure and function are improving towards diversification and ***,the model is more evaluated from the pros and cons of the problem-solving results and the lack of evaluation from the biomimetic aspect of imitating neural networks is not inclusive ***,a new ANN models evaluation strategy is proposed from the perspective of bionics in response to this problem in the ***,four classical neural network models are illustrated:Back Propagation(BP)network,Deep Belief Network(DBN),LeNet5 network,and olfactory bionic model(KIII model),and the neuron transmission mode and equation,network structure,and weight updating principle of the models are analyzed *** analysis results show that the KIII model comes closer to the actual biological nervous system compared with other models,and the LeNet5 network simulates the nervous system in ***,evaluation indexes of ANN are constructed from the perspective of bionics in this paper:small-world,synchronous,and chaotic ***,the network model is quantitatively analyzed by evaluation indexes from the perspective of *** experimental results show that the DBN network,LeNet5 network,and BP network have synchronous *** the DBN network and LeNet5 network have certain chaotic characteristics,but there is still a certain distance between the three classical neural networks and actual biological neural *** KIII model has certain small-world characteristics in structure,and its network also exhibits synchronization characteristics and chaotic *** with the DBN network,LeNet5 network,and the BP network,the KIII model is closer to the real biological neural network.

关键词： Artificial neural network(ANN) Back Propagation(BP)network Deep Belief Network(DBN) LeNet5 network Olfactory bionic model(KIII model) Small world Chaos Synchronous

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