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第43届中国控制会议

作者： Bin Huang Yahui Gan Fang Fang Bo Zhou Xianzhong Dai School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

To address the challenges of low position tracking accuracy and high vibrations in mechanical arms controlled by PID closed-loop systems, this paper introduces a torque feedforward control scheme based on dynamic models. The paper initially analyzes the causes of vibrations during robot motion, establishing a mathematical model to quantify the trajectory accuracy and repeatability of vibrations. Subsequently, a torque feedforward control scheme based on dynamic models is designed, and its feasibility is theoretically analyzed. In this motion control scheme, precise dynamic models are utilized to calculate and output the desired torque. The torque values are then converted into motor current values, which are superimposed on the control output of the current loop in the servo to achieve real-time torque compensation. Finally, through simulation experiments, the paper validates that the dynamics-based torque feedforward control effectively suppresses robot vibrations, enhances tracking accuracy,and improves dynamic performance. The findings demonstrate the efficacy of the proposed control strategy in addressing the challenges associated with PID-controlled robotic arm systems.

关键词： Industrial robots feedforward control vibration suppression

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Reliability Assessment of LCC-HVDC links Using Protection Devices 1

Reliability Assessment of LCC-HVDC links Using Protection De...

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1st International Conference on Renewable Solutions for Ecosystems: Towards a Sustainable Energy Transition, ICRSEtoSET 2023

作者： Hameurlaine, Abdelhadi Boukezzi, Larbi Karef, Salah Sayah, Haouari University of Djelfa Laboratory of Applied Automation & Industrial Diagnostics Djelfa Algeria University of Djelfa Materials Science and Informatics Laboratory Msil Djelfa Algeria University of Djelfa Com Laboratory of Modeling Optimization and Simulation of Real Complex Systems Djelfa Algeria University of SidiBel-Abbes Intelligent Control and Electrical Power System Laboratory SidiBel-Abbes Algeria

ISBN: (纸本)9798350346336

the DC/AC interaction and the presence of the high nonlinearity in the HVDC links, these problems needs to examine the behavior of the system in steady-state and transient conditions in order to define the great role of protection functions and control parameters. Furthermore, control and protection systems are a vital part of an HVDC system to guarantee the safety, reliability, and stability of its operation. This research aim is to provide the solutions for control and protection problems that can occur in HVDC link. In this paper, we study how we mitigate this serious malfunction of commutation failure process in the operation of HVDC converters. Indeed some protection functions like the commutation failure prevention. Furthermore, HVDC transmission systems are vulnerable to DC faults and its protection becomes ever more important with the fast growth in the number of installations. Finally, the dynamics of the studied power system including the HVDC link is thoroughly investigated through various simulation scenarios. © 2023 IEEE.

关键词： HVDC power transmission

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Global Path Planning of Unmanned Surface Vehicles Based on Deep Q Network

Global Path Planning of Unmanned Surface Vehicles Based on D...

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第43届中国控制会议

作者： Shuhao Li Yuehui Ji Junjie Liu Zhongli Bai Jiajun Hu Qiang Gao Tianjin Key Laboratory of Control Theory and Application for Complex Systems Maritime College Tianjin University of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The paper proposes an autonomous global path planning algorithm for unmanned surface vehicles(USV) in complex sea areas based on Deep Q Network(DQN).This algorithm integrates the artificial potential field method with the DQN algorithm to design action space and a new greedy *** also introduces a reward function based on potential energy and a penalty item for threat *** results demonstrate that compared to the traditional DQN algorithm,the algorithm proposed in this paper reduces training time by 35.27%,shortens path length by 8.71%,and decreases convergence iterations by 56.36%.Compared to the other three algorithms,such as Q-learning,the paths planned by the algorithm in this paper are more reasonable,smooth,and *** research results validate the practicality and effectiveness of the proposed algorithm,which has significant practical implications for the development of autonomous global path planning technology for USV.

关键词： Path planning Unmanned surface vehicles Deep Q network Artificial potential field Grid method

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Optimal Trajectory Planning and Safety-Critical control for Underactuated Overhead Cranes

Optimal Trajectory Planning and Safety-Critical Control for ...

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第43届中国控制会议

作者： Weihong Chen Zheng Tian Jun Yang Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

As a kind of heavy cargo lifting equipment,it is very important to improve transportation efficiency,save energy and strictly ensure safety for overhead ***,many traditional control strategies can not meet these needs *** this end,a composite control framework made up of optimal trajectory planning and Safety-Critical tracking controller is studied in this ***,optimal trajectories are obtained by the optimal control *** analysis is used to obtain a tractable optimal solution for overhead crane ***,control Lyapunov functions(CLFs) and high-order control barrier functions(HOCBFs) are used to track the optimal states and account for constraints with arbitrary relative degrees,*** CBF method is computationally efficient while providing safety *** results show that the proposed method is effective.

关键词： Safety-Critical control Optimal control control Barrier Functions Overhead Cranes

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Online Reentry Trajectory optimization for Hypersonic Vehicles Using Radau Pseudospectral Sequential Convex Programming

Online Reentry Trajectory Optimization for Hypersonic Vehicl...

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第43届中国控制会议

作者： Zhifei Song Junjie Liu Yuehui Ji Haobo Zhang Junchi Wang Qiang Gao Tianjin Key Laboratory of Control Theory and Application for Complex Systems Maritime College Tianjin University of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In this paper,an online trajectory optimization scheme is proposed to address the uncertainties and mission changes in hypersonic vehicle reentry trajectory *** combining Radau pseudospectral method and sequential convex programming(SCP),the discretization accuracy and solution speed of the trajectory optimization algorithm are ***,the downrange angle is used as the independent variable in the equations of motion to implement the free time trajectory optimization *** initial trajectory generation method is proposed,which makes the trajectory's terminal state close to the terminal position and thus reduces the number of algorithm optimization ***,the compensation and regularization terms are used,respectively,to maintain the feasibility of the trajectory optimization problem and to improve the convergence rate of the *** the end,the proper trajectory optimization period is set,and the interior-point method is used to solve the reentry trajectory optimization *** simulations demonstrate the validity of the algorithm and online reentry trajectory optimization scheme proposed in this paper.

关键词： Radau pseudospectral method Hypersonic vehicle Sequential convex programming Online reentry trajectory optimization

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Modified Deep Deterministic Policy Gradient Based Optimal Speed Tracking Strategy for PMSMs 13

Modified Deep Deterministic Policy Gradient Based Optimal Sp...

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13th IEEE Data Driven control and Learning systems Conference, DDCLS 2024

作者： Fan, Zhong-Xin Tang, Lintao Li, Shihua Liu, Rongjie School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Florida State University Department of Statistics TallahasseeFL32304 United States

ISBN: (纸本)9798350361674

Achieving optimal speed regulation for permanent magnet synchronous motors (PMSMs) remains a challenging task, particularly in selecting the most suitable controller to meet desired objectives. This paper considers the optimal speed tracking problem of PMSMs. We employ a reinforcement learning algorithm to obtain optimal controller with a linear form. The reinforcement learning approach incorporates a critic-actor network structure, which approximates the value function and optimal control, respectively. Specifically, a weight updating method for the critic network is introduced, where the update of the actor network is guided by the critic network. Through data collection and neural network training, dynamic acquisition of the optimal controller gain is achieved. In addition, a novel activation function is implemented in the network, leading to improved control performance concerning dataset size and reduced training time. At final, a real-world PMSM application is presented along with comparisons to demonstrate effectiveness. The desire idea of resulting optimal controllers is not only applicable to linear systems but also capable of approximating arbitrary nonlinear optimal controllers, thus offering practical engineering versatility. © 2024 IEEE.

关键词： Reinforcement learning

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Smooth and Time-optimal Improved-Bezier Trajectory Planning Based on Dynamics for Industrial Robots

Smooth and Time-optimal Improved-Bezier Trajectory Planning ...

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第43届中国控制会议

作者： Wei Cai Yahui Gan Fang Fang Bo Zhou Xianzhong Dai School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper presents a smooth and time-optimal improved-Bezier trajectory planning algorithm that addresses the avoidance of solving switching points and solves the problem of discontinuous torque on the basis of the time-optimal path parameterization(TOPP) algorithm. The proposed approach employs the TOPP-RA algorithm with a friction model, to construct the optimal velocity trajectory under the constraints of the geometric paths and joint torques. Moreover, the proposed algorithm utilizes an enhanced Bezier curve instead of the jerk constraint in the trajectory optimization model to achieve a smooth trajectory. The modified Bezier curve optimizes the peaks of the pseudo-velocity curve in the phase plane to change the discontinuity of joint torque. The proposed algorithm ensures absolute time optimality and achieve a s mooth tr ajectory. The results of the MATLAB simulation experiment on a two-link motion system indicate the validity of the proposed algorithm.

关键词： time-optimal smooth trajectory planning improved-Bezier trajectory

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DriveRP: RAG and Prompt Engineering Embodied Parallel Driving in Cyber-Physical-Social Spaces 4

DriveRP: RAG and Prompt Engineering Embodied Parallel Drivin...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Huang, Jun Ma, Hao Zhang, Tengchao Lin, Fei Ma, Siji Wang, Xiao Wang, Fei-Yue Macau University of Science and Technology Faculty of Innovation Engineering China Anhui University School of Artificial Intelligence Hefei China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China

ISBN: (纸本)9798350349252

In recent years, numerous technological advancements in Artificial Generative Intelligences (AGIs) have demonstrated significant potential to transform the intelligence acquisition mechanisms in connected autonomous vehicles (CAVs). Integrating technologies like ChatGPT into CAVs can enhance human-machine interactions. However, the emergence of such new traffic entities may introduce unforeseen hallucinations and complex risks that surpass our current understanding. To address these challenges, Retrieval-Augmented Generation (RAG) and prompt engineering technologies are being explored to enhance the reliability and safety of autonomous driving systems. RAG retrieves relevant contextual information, such as driving experiences and real-time road network status, from external databases to ensure that foundation models have access to accurate and timely data for informed decision-making. Prompt engineering optimizes the performance of large language models in autonomous driving systems by designing and refining prompts that guide the models' responses, thereby improving their relevance and accuracy in various driving scenarios. Together, these technologies enhance the robustness and trustworthiness of autonomous driving systems. This paper proposes DriveRP, a framework that integrates RAG and prompt engineering within the Descriptive-Predictive-Prescriptive Intelligence framework of Parallel Driving theory. DriveRP aims to enhance the safety and interpretability of autonomous vehicle trajectory planning, decision-making, and motion control, ultimately achieving the "6S"goals. Grounded in Digital Twins and Metaverse-embodied parallel driving theory, DriveRP provides the infrastructure and foundational intelligence for parallel driving with Multi-modal Large Lange Models(MLLMs). Additionally, the paper discusses future trends and potential research directions, focusing on the "6S"goals of parallel driving: Smart, Safe, Secure, Sensitive, Sustainable, and Serviceable. © 2

关键词： Intelligent systems

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Platform governance in the era of AI and the digital economy

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Frontiers of Engineering Management 2023年第1期10卷 177-182页

作者： Xiaolong ZHENG Gang ZHOU Daniel Dajun ZENG The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence Chinese Academy of SciencesBeijing 100190China

1 Introduction Companies that supply online services such as Twitter,Weibo,and Taobao are known as platform companies(Gorwa,2019).Many top companies offer their services through platforms and use Internet technology to facilitate economic transactions,transmit information,connect people,and make predictions(Fenwick et al.,2019).Such platforms cover all areas of society,including politics(Gillespie,2017),labor relations,cultural production(Scholz,2016;van Doorn,2017),and consumption(Nieborg and Poell,2018).The rapid development of Internet technology has increased the influence of network *** platforms have changed the rules of global business operations and influenced the global political *** some high-profile negative events,calls for strengthening the regulation of online platforms and holding them accountable have been growing(Suzor,2019).

关键词： companies services operations

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Can language models be used for real-world urban-delivery route optimization?

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The Innovation 2023年第6期4卷 92-100页

作者： Yang Liu Fanyou Wu Zhiyuan Liu Kai Wang Feiyue Wang Xiaobo Qu State Key Laboratory of Itelligent Green Vehicle and Mobility Tsinghua UniversityBeiing 100084China Jiangsu Key Laboratory of Urban ITS Jjiangsu Province Collaborative Innovation Center of Modem Urban Traffic TechnologiesSchool of TransportationSoutheast UniversityNanjing 211189China School of Vehicle and Mobilit Tsinghua UniversityBejjing 100084China Institute of Automation State Key Laboratory for Management and Control of Complex SystemsChinese Academy of SciencesBeiing 100190China

Language models have contributed to breakthroughs in interdisciplinary research,such as protein design and molecular dynamics *** this study,we reveal that beyond language,representations of other entities,such as human behaviors,that are mappable to learmable se quences can be learned by language *** compelling example is the realworld delivery route optimization *** here propose a novel approach based on the language model to optimize delivery routes on the basis of drivers'historical *** a broad range of optimizationbased approaches have been designed to optimize delivery routes,they do not capture the implicit knowledge of complex delivery operating *** model we propose integrates this knowledge in the route optimization process by learning from driving behaviors in experienced drivers.A real-world delivery route that preserves drivers'implicit behavioral patterns is first analogized to a sentence in natural *** unsupervised learning,we then learn the vector representations of words and infer the drivers'delivery chains on the basis of the tailored chain-reaction-based *** also provide insights into the fusion of language models and operations research *** our approach,language models are applied to learn drivers'delivery behaviors and infer new deliveries at the delivery zone level,while the classic traveling salesman problem(TSP)model is embedded into the hybrid framework for intra-zone *** experiments performed on real-world data from Amazon's delivery service demonstrate that the proposed approach outperforms pure optimization,supporting the effectiveness,efficiency,and extensibility of our *** a versatile approach,the proposed framework can easily be extended to various disciplines in which the data follow cert ain grammar *** anticipate that our work will serve as a stepping stone toward the understanding and application of language models in

关键词： driving breakthrough versatile

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