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Distributed Online Convex Optimization with Time-Varying Constraints: Tighter Cumulative Constraint Violation Bounds under Slater's Condition

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IEEE Transactions on Automatic control 2025年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Hong, Yiguang Chai, Tianyou Johansson, Karl H. National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai Institute of Intelligent Science and Technology China Ministry of Education Frontiers Science Center for Intelligent Autonomous Systems China Massachusetts Institute of Technology Lab for Information & Decision Systems CambridgeMA02139 United States Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Nanyang Technological University School of Electrical and Electronic Engineering 50 Nanyang Avenue 639798 Singapore Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online convex optimization with time-varying constraints. In this setting, a network of agents makes decisions at each round, and then only a portion of the loss function and a coordinate block of the constraint function are privately revealed to each agent. The loss and constraint functions are convex and can vary arbitrarily across rounds. The agents collaborate to minimize static network regret and network cumulative constraint violation. A novel distributed online algorithm with a vanishing stepsize is proposed and it achieves an O(Tmax {c,1-c}) static network regret bound and an O(T1-c/2) network cumulative constraint violation bound, where T is the number of rounds and c∈ (0,1) is a user-defined trade-off parameter. When Slater's condition holds (i.e, there is a point that strictly satisfies the inequality constraints), the network cumulative constraint violation bound is reduced to O(T1-c). Moreover, if the loss functions are strongly convex, then static network regret bound is reduced to O(log (T)), and the network cumulative constraint violation bound is reduced to O(√log (T)T) and O(log (T)) without and with Slater's condition, respectively. To the best of our knowledge, this paper is the first to achieve tighter (network) cumulative constraint violation bounds for (distributed) online convex optimization with time-varying constraints under Slater's condition. Finally, the theoretical results are verified through numerical simulations. © 1963-2012 IEEE.

关键词： Convex optimization

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InGaAlAs/InP MQW transistor lasers based on step-ridge waveguides

IEEE Electron Device Letters

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IEEE Electron Device Letters 2025年

作者： Liu, Yijia Qiao, Lijun Tang, Xin Liang, Song Zhang, Mingjiang Taiyuan University of Technology College of Physics and Optoelectronics Taiyuan030024 China Ministry of Education Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Shanxi Taiyuan030024 China Chinese Academy of Sciences Key Laboratory of Optoelectronic Materials and Devices Beijing100083 China University of Chinese Academy of Sciences Center of Materials Science and Optoelectronics Engineering Beijing100049 China

We propose and numerically investigate a new step-ridge-waveguide InGaAlAs/InP multi-quantum well (MQW) transistor laser (TL). The carrier nonradiative recombination centers caused by the exposed deep-ridge waveguide sidewall significantly degrade the optoelectronic performance of the TLs. The step-ridge-waveguide structure guides carriers through the center portion of the ridge waveguide, thereby effectively mitigating the effect of the nonradiative recombination defects. Simulation results show that the optoelectronic characteristics of the step-ridge TL are far better than those of the conventional deep-ridge TL, and the current amplification factor of the step-ridge TL is not affected by the laser excitation. This structure provides a new option for the simultaneous enhancement of the optoelectronic performance of TLs. © 1980-2012 IEEE.

关键词： Laser excitation

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Hybrid dynamic model of polymer electrolyte membrane fuel cell stack using variable neural network

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Journal of Beijing Institute of Technology 2012年第3期21卷 354-361页

作者：李鹏陈杰蔡涛王光辉 School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of EducationBeijing Institute of Technology

The polymer electrolyte membrane（PEM） fuel cell has been regarded as a potential alternative power source,and a model is necessary for its design,control and power management.A hybrid dynamic model of PEM fuel cell,which combines the advantages of mechanism model and black-box model,is proposed in this *** improve the performance,the static neural network and variable neural network are used to build the black-box *** static neural network can significantly improve the static performance of the hybrid model,and the variable neural network makes the hybrid dynamic model predict the real PEM fuel cell behavior with required ***,the hybrid dynamic model is validated with a 500 W PEM fuel *** static and transient experiment results show that the hybrid dynamic model can predict the behavior of the fuel cell stack accurately and therefore can be effectively utilized in practical application.

关键词： PEM fuel cell variable neural network hybrid dynamic model

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Load Prediction Model of Gas Boiler Generator Set Based on CNN-LSTM 11th

Load Prediction Model of Gas Boiler Generator Set Based on...

引用

11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024

作者： Xu, Yan Wu, Min Hu, Jie Peng, Fu-Sheng Zhang, Wen Song, Wen-Shuo Li, Hui-Hang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789819647521

With the proposal of carbon peak and carbon neutrality targets and the construction of a new power system, improving energy efficiency and reducing carbon emissions have become the key to the sustainable development of industrial boiler generator sets. However, the current load scheduling of gas boiler power plants is mainly based on manual experience, which limits achieving more efficient and stable operation. Accurate short-term load forecasting can help dispatchers to make reasonable production schedules. Therefore, this paper proposes a hybrid load forecasting model for generator sets based on convolutional neural networks combined with long short-term memory networks. First, the Isolation Forest algorithm eliminates anomalies in the historical data set. Then, variables related to unit load are selected by combining mechanistic analysis with the Spearman algorithm. Considering the multiple operating conditions and high complexity of unit loads, the CNN-LSTM network is used to fully extract the spatial and temporal characteristics to build the load prediction model. Finally, experiments are conducted using actual production data, showing that the proposed method is effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electric load dispatching

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Path Planning for Distribution Network Robots with Adaptive Simulated Annealing-Enhanced Artificial Potential Field Method 26

Path Planning for Distribution Network Robots with Adaptive ...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Zhang, Baichao Chen, Xin Chen, Jinge Li, Jinbin Wang, Xiaokai Jian, Xu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan430077 China Hubei Fangyuan Dongli Electric Power Science Research Co. Ltd Wuhan430077 China

ISBN: (纸本)9798331521950

In this paper, we propose a hybrid algorithm that combines an improved Artificial Potential Field (APF) method with the Simulated Annealing (SA) algorithm for path planning of an electric power operation robot manipulator in complex distribution grid environments. To address the unreachable target issue inherent in traditional APF, we introduce a distance regulation factor to optimize the repulsive function. This modification allows the manipulator to smoothly approach the target point as it nears, while the repulsion from obstacles gradually decreases. Additionally, to overcome the limitations of the traditional SA algorithm, such as its tendency to get trapped in local minimum solutions and its inefficiency in complex environments, we propose an adaptive temperature rise strategy. This strategy increases the temperature, enhancing the probability of escaping local optimal solutions. When the APF algorithm becomes trapped in a local optimum, the improved SA algorithm is applied to escape the local minimum. Once the local optimum is avoided, the algorithm switches back to APF to continue the path planning process. Simulation results demonstrate that the proposed improved APF-SA algorithm adapts effectively to various complex environments, achieving shorter planning times and higher success rates compared to traditional APF and SA algorithms. It successfully resolves the unreachable target and local minimum problems associated with APF. Finally, the feasibility of the proposed APF-SA fusion algorithm is validated through experiments conducted on an electric power operation robot experimental platform for distribution grid applications. © 2025 IEEE.

关键词： Motion planning

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Trajectory Tracking for Directional Drilling in Underground Coal Mine Using Robust Model Predictive control 26

Trajectory Tracking for Directional Drilling in Underground ...

引用

26th International Conference on Industrial Technology, ICIT 2025

作者： Wu, Jiajun Lu, Chengda Li, Hao Wei, Hongchao Wu, Min School of Future Technology China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Xi'an Research Institute Co. Ltd. China Coal Technology and Engineering Group Xi'an710077 China China Coal Research Institute Beijing100013 China

ISBN: (纸本)9798331521950

This paper studies the problem of trajectory tracking control for directional drilling in underground coal mine by devising a robust model predictive control method. First, a directional drilling trajectory extension model is obtained by the linearization of a drilling tool kinematic model through the Taylor series expansion in the borehole depth domain. Then, in view of the influence of the uncertainty of the drilling tool slope and external interference, a robust model predictive control method is introduced in the form of an optimal control problem. A sufficient condition is obtained to calculate the corresponding controller gain matrix on the premise of satisfying the stability of the closedloop control system and the H∞ performance index. At last, the effectiveness of our method is illustrated through simulation analysis. Compared with model predictive control, robust model predictive control directly incorporates the uncertainty of the drilling tool slope and external interference into the control design, enabling it to better adapt to the complex and variable underground coal mine environment. © 2025 IEEE.

关键词： Predictive control systems

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Trajectory synchronization of multi-cylinder electrohydraulic lift system with huge load

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Journal of Beijing Institute of Technology 2013年第2期22卷 228-234页

作者：何玉东王军政李静赵江波 Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology

A kind of four degree-of-freedom （DOF） electrohydraulic lift system is studied in this pa- per, after analyzing the motion characteristics and the mathematic model of the hydraulic cylinders, a cross-coupled synchronization method with load force and synchronization error feedback had been proposed to solve the synchronization problem encountered when realizing the needed roll and pitch attitude of the lift system. In this paper, mathematic model of asymmetric hydraulic cylinder was es- tablished and the lift system had been simplified to a dual-cylinder system. By incorporating the load force and the displacement of each cylinder, a cross-coupled synchronized control method was pro- posed to fit each cylinder＇ s tracking performance and multi-cylinder＇ s trajectory synchronization property. The proposed method not only solved the synchronization problem when multi-cylinder had a same trajectory, but also could fit the coordinated synchronization need when different trajectories of multi-cylinder were desired. Simulations and experiments on a four DOF electrohydraulic lift sys- tem with load of 100 tons verified the effectiveness of the proposed method.

关键词： hydraulic cylinder lift system trajectory synchronization

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Effective approach for outdoor obstacle detection by clustering LIDAR data context

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Journal of Beijing Institute of Technology 2016年第4期25卷 483-490页

作者：王军政乔佳楠李静 Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology

A method of environment mapping using laser-based light detection and ranging （LIDAR） is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also facilitates the detection of dynamic and hollowed-out obstacles. Essentially using this method, an improved clustering algorithm based on fast search and discovery of density peaks （CBFD） is presented to extract various obstacles in the environment map. By comparing with other cluster algorithms, CBFD can obtain a favorable number of clusterings automatically. Furthermore, the experiments show that CBFD is better and more robust in functionality and performance than the K-means and iterative self-organizing data analysis techniques algorithm （ISODATA）.

关键词： context modeling clustering algorithm based on fast search and discovery of densitypeaks（CBFD） Hull algorithm obstacle detection obstacle fusion

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Motion Planning Method for Obstacle Avoidance of 6-DOF Manipulator Based on Improved A* Algorithm

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Journal of Donghua University(English Edition) 2015年第1期32卷 79-85页

作者：汪首坤朱磊 Key Laboratory of Intelligent Control and Decision for Complex System Beijing Institute of Technology

The conventional A* algorithm may suffer from the infinite loop and a large number of search data in the process of motion planning for manipulator. To solve the problem,an improved A* algorithm is proposed in this paper by the means of selecting middle points and applying variable step segments searching during the searching process. In addition,a new method is proposed for collision detection in the workspace. In this paper,the MOTOMAN MH6 manipulator with 6-DOF is applied for motion plan. The algorithm is based on the basis of the simplification for the manipulator and obstacles by cylinder enveloping. Based on the analysis of collision detection,the free space can be achieved which makes it possible for the entire body to avoid collisions with obstacles. Compared with the Conventional A*,the improved algorithm deals with less searching points and performs more efficiently. The simulation developed in VC + + with OpenGL and the actual system experiments prove effectiveness and feasibility of this improved method.

关键词： manipulator collision detection A* algorithm variable step segments searching OpenGL

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A MILP Model and Two-Stage Heuristic Algorithm for Vehicle-Assisted Multi-Drone Inspection Routing Problem

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IET intelligent Transport systems 2025年第1期19卷

作者： Xia, Yuanqing Luo, He Dong, Rui Yin, Youlong Lin, Shizhong Wang, Guoqiang School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization & Intelligent Decision-Making Ministry of Education Hefei China Engineering Research Center for Intelligent Management of Aerospace System Anhui Province Hefei China Management Center of UAV Inspection Operation State Grid Anhui Electric Power Co. Ltd Hefei China Anhui Power Transmission & Transformation Engineering Co. Ltd Hefei China

This paper introduces a vehicle-assisted multi-drone inspection routing problem (VAMDIRP), which enables the vehicle to repeatedly traverse roads, thereby reducing task completion time. Firstly, a mixed-integer linear programming (MILP) model is constructed for the problem using a series of decision variables and auxiliary variables. The model can be solved by GUROBI for small-scale instances. Secondly, a two-stage heuristic algorithm is proposed to solve large-scale instances. Experimental results show that this algorithm improves the solution quality by an average of 20.71% and reduces the running time by an average of 60.31% compared to existing algorithms. Finally, a sensitivity analysis is conducted on relevant parameters, revealing that changes in the number and speed of drones significantly affect the solution quality. © 2025 The Author(s). IET intelligent Transport systems published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Sensitivity analysis

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