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Primal-dual Learning for the Model-free Risk-constrained Linear Quadratic Regulator 3

Primal-dual Learning for the Model-free Risk-constrained Lin...

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3rd Annual conference on Learning for Dynamics and control (L4DC)

作者： Zhao, Feiran You, Keyou Tsinghua Univ Dept Automat Beijing Peoples R China Tsinghua Univ BNRist Beijing Peoples R China

Risk-aware control, though with promise to tackle unexpected events, requires a known exact dynamical model. In this work, we propose a model-free framework to learn a risk-aware controller of a linear system. We formulate it as a discrete-time infinite-horizon LQR problem with a state predictive variance constraint. Since its optimal policy is known as an affine feedback, i.e., u*(x) =-Kx + l, we alternatively optimize the gain pair (K;l) by designing a primal-dual learning algorithm. First, we observe that the Lagrangian function enjoys an important local gradient dominance property. Based on it, we then show that there is no duality gap despite the non-convex optimization landscape. Furthermore, we propose a primal-dual algorithm with global convergence to learn the optimal policy-multiplier pair. Finally, we validate our results via simulations.

关键词： Risk-aware control Policy optimization Reinforcement learning Optimal control Constrained Markov decision process

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Research on a new improved UAV anti-jamming and optimization model 3

Research on a new improved UAV anti-jamming and optimization...

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3rd International conference on Computer Science and Communication Technology, ICCSCT 2022

作者： Zhang, Longqing Zhang, Xinwei Yang, Lei Tian, Liwei Chen, Yungui Zhang, Yanghong Li, Peipei Guangdong University of Science and Technology Guangdong Dongguan523083 China

ISBN: (纸本)9781510661240

In complex environments, UAV wireless sensing networks suffer from path loss, incomplete channels, swarm access security and other problems, and the signal fading and packet loss rates are very obvious. In order to solve the problem of user control data security, this paper gives full play to the characteristics of blockchain technology and builds a blockchain-based UAV cluster anti-interference communication network in UAV cluster applications to achieve anti-interference performance. Meanwhile, Markov decision process is used to optimize and realize the research of UAV air-ground integrated radio wave anti-interference. © 2022 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Research on ToB/ToC Capacity Synergy in 5G Wireless networks 25

Research on ToB/ToC Capacity Synergy in 5G Wireless Networks

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Proceedings of the 2025 3rd International conference on Communication networks and Machine Learning

作者： Kai Tang Ning Ma Wenyan Jin Bo Zhang Ganbei Wang China Mobile Communications Group Co. Ltd. Beijing China China Mobile Group Design Institute Co. Ltd. Beijing China China Mobile Group Design Institute Co. Ltd. Wuhan Hubei China

ISBN: (纸本)9798400713231

The rapid expansion of 5G wireless networks has enabled extensive coverage, driving significant growth in 5G ToB (To Business) services. While substantial progress has been made in optimizing 5G ToC (To Consumer) capacity, research on the synergistic capacity management between ToB and ToC domains remains limited. Unlike the ToC sector, ToB applications typically demand low latency, large uplink bandwidth, and high reliability. These distinct requirements of ToB and ToC applications pose significant challenges to the integration of ToB and ToC services in current wireless networks. To enhance the versatility of 5G networks across both ToC and ToB sectors, it is crucial to explore and develop a synergistic capacity strategy that can accommodate the concurrent demands of ToC and ToB scenarios. This strategy aims to achieve dual optimization, ensuring efficient network resource allocation and quality of service for both ToB and ToC users.

关键词： Resource control

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Evaluation and optimization Strategies for Reactive Power Compensation in Distribution networks Based on Scheduling Domain

Evaluation and Optimization Strategies for Reactive Power Co...

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Energy, Power and Electrical Technology (ICEPET), International conference on

作者： Zhenyong Niu Jinbo Huang Dongxu Li Guangzhou Power Supply Bureau Guangdong Power Grid Co. Ltd Guangzhou China

ISBN: (数字)9798350352658

ISBN: (纸本)9798350352665

With access to massive distributed power sources and the increasing demand for voltage stability from the user side, the demand for precise voltage regulation in the distribution network has also increased. Currently, the main means of voltage regulation at the feeder level are through adjusting the reactive power compensation at the head end of the feeder. However, due to the fact that the control objective of reactive power compensation at the head end only considers the voltage at the head end of the feeder itself, it cannot meet the voltage regulation needs of other nodes in the feeder. As a result, the problem of uneven voltage at the beginning and end of the feeder line, as well as repeated occurrences of low voltage at the end, can occur. In response to this issue, this article establishes a voltage scheduling domain model for the first node of the feeder based on the consistency and synchronization of voltage changes between the first end of the feeder and other nodes, taking into account the voltage operation status of the entire node of the feeder. This model serves as the control objective for reactive power compensation switching at the first end, and utilizes the correlation between the historical reactive power compensation switching amount and the voltage of the first node in the feeder to calculate the sensitivity of reactive power voltage at the first end of the feeder, Then, a practical control strategy for feeder reactive power compensation is proposed based on the comprehensive scheduling domain and sensitivity. Finally, the useless voltage control strategy was validated using a certain feeder line as an example. Proved the effectiveness of this strategy.

关键词： Reactive power Low voltage Sensitivity Distribution networks Switches control systems Stability analysis

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4G LTE Experience: Reference Signal Received Power, Noise Ratio and Quality 3

4G LTE Experience: Reference Signal Received Power, Noise Ra...

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3rd East Indonesia conference on Computer and Information Technology, EIConCIT 2021

作者： Putra, Gubtha Mahendra Budiman, Edy Malewa, Yonatan Cahyadi, Dedy Taruk, Medi Hairah, Ummul Universitas Mulawarman Dept. of Informatics Samarinda Indonesia

ISBN: (纸本)9781665405140

Currently, Indonesia has just entered the 4G technology stage so that 5G technology will look very far away, although it cannot be denied that 5G technology will come whether Indonesia is ready or not, therefore this study was held to help describe the current condition of Indonesia's 4G network and is expected to provide input in determining steps and Indonesia's 5G roadmap going forward. This study aims to evaluate the quality of video streaming over the 4G LTE network based on the quality of experience parameters of RSRP, RSRQ and SNR of mobile operators. The walk-Test measurement method was used for data collection (morning, evening, night). The performance evaluation results of 4G LTE mobile operators show that the weak value of the RSRP, RSRQ, and SNR values obtained at a point have experienced a decrease in signal strength, this is due to the propagation loss that occurs. The presence of buildings, trees, network density and weather cause propagation such as reflection, diffraction, and scattering. In addition, the distance from the transmitter to the receiver is also a factor that causes a decrease in the signal strength received from the user's device. Therefore, the results of the evaluation serve as a reference for further optimization actions to support the improvement of the 4G LTE network by service providers so that users experience satisfying 4G LTE network services. © 2021 IEEE.

关键词： Quality control

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Divide and Cache: A Novel control Plane Framework for Private 5G networks

Divide and Cache: A Novel Control Plane Framework for Privat...

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Consumer Communications and networking conference, CCNC IEEE

作者： Taeho Park Hochan Lee Heewon Kim Subin Han Taeyun Kim Sangheon Pack School of Electrical Engineering Korea University Seoul

To support a wide range of vertical services in fifth-generation (5G), a concept of private 5G has gained a great attention. Even though several deployment models for private 5G have been reported in the literature, they have not fully utilized the benefit of modularized control plane (CP) network functions (nfs) for better performance and cost efficiency. In addition, their qualitative and quantitative analysis has not been conducted yet. In this paper, we propose a novel CP framework for private 5G dubbed divide and cache (D&C). In D&C, the dependency and frequency of CP nfs are first analyzed based on the 3rd generation partnership project (3GPP) specification. Based on the analysis results, nfs are split into on-premise and edge/public clouds to balance the tradeoff between performance and cost. Also, a new nf called nf profile cache function (nfPCF) is built in on-premise to mitigate the signaling overhead. We implemented D&C over a private 5G testbed using an open-source software (i.e., free5GC). Evaluation results demonstrate that D&C can achieve 19% lower deployment cost at the expense of slightly increased latency compared to the existing model.

关键词： Costs 5G mobile communication Statistical analysis Dynamic scheduling Noise measurement 3GPP Open source software

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ICECIE 2021 - 2021 International conference on Electrical, control and Instrumentation Engineering, conference Proceedings

ICECIE 2021 - 2021 International Conference on Electrical, C...

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3rd IEEE International conference on Electrical, control and Instrumentation engineering, ICECIE 2021

ISBN: (纸本)9781665449663

The proceedings contain 50 papers. The topics discussed include: closed-loop dual comparator and its applications;an initial value selection method based on hybrid de-newton for energy flow calculation of the electricity-gas integrated energy system;an extensive survey on intrusion detection systems: datasets and challenges for modern scenario;implication of diverse modalities for electrical load forecasting;the effect of single tuned filter on coordinated planning in increasing power quality in radial distribution system;harmonic mitigation through enhancement network reconfiguration technique on coordinated planning using hybrid particle swarm optimization in radial distribution system;and non-intrusive load monitoring for high power consuming appliances using neural networks.

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Adaptive Power control with Improved Genetic Algorithm to Enhance QoS Performance in Vehicular Communication Systems

Adaptive Power Control with Improved Genetic Algorithm to En...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International conference on

作者： A. Aranganathan Dalia Al-Tarazi S. Bharath Durga Devi Jayant Giri S. Ravi Department of ECE Sathyabama Institute of Science and Technology Chennai India Department of Architecture Engineering Faculty of Engineering Zarqa University Zarqa Jordan College of Engineering University of Business and Technology Jeddah Saudi Arabia Department of ECE Rajalakshmi Institute of Technology Chennai India Department of CSE Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College Chennai India Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur India Division of Research and Development Lovely Professional University Phagwara India Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Background: Vehicular Ad hoc networks (VANETs) play a crucial role in intelligent transportation systems since they enable vehicles to communicate instantaneously. Elevated mobility and dynamic settings create difficulties for dependable data transmission, resulting in longer delays and packet loss. Method used: An Advanced Genetic Algorithm-based Vehicular Ad hoc Routing (AIGAV) model that leverages meta-heuristic optimization to enhance routing decisions in VANETs. It utilizes GPS for live navigation and modifies routes as required. This optimization reduces congestion and distributes network load more evenly for improved packet forwarding. Results: The AIGAV model exceeds the performance in crucial efficacy aspects. It enhanced data success rates (95.25%), remarkable throughput (521.41 Kbps), and minimal routing overhead (254.18 packets), and decreased data loss rates. Conclusion: The AIGAV model improves the efficiency of VANET routing through dependable and adaptable communication in mobile settings. It employs optimization to enhance safer, more intelligent transportation systems for upcoming uses.

关键词： Adaptation models Metaheuristics Vehicular ad hoc networks Routing Throughput Reliability Integrated circuit modeling Genetic algorithms Load modeling Global Positioning System

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Optimal coordination of a pool of different EV charging stations

Optimal coordination of a pool of different EV charging stat...

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International conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Fabrizio Pilo Giuditta Pisano Simona Ruggeri Dept. of Electrical and Electronic Engineering University of Cagliari Cagliari Italy

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

The transport sector will contribute to the decarbonisation goals by massively replacing internal combustion engine vehicles with electric vehicles (EVs). In europe, up to 70 million EVs are expected by 2030. The diffusion of EVs will be accompanied by 50-70 million charging points connected to the distribution systems (at medium and low voltage levels). The EV charging causes power quality and operation issues, such as line overloading, voltage violations, and voltage unbalances. It will require extensive investments to develop a distribution system suited to face the electrification of heating and transportation. Using suitable control systems for optimal charging that consider charging session features and network criticalities can mitigate the impact of EVs on distribution grids and contribute to postponing or even avoiding significant investments. The paper proposes a strategy to reduce the effects of public charging on low-voltage networks. If already burdened by the increased electrification of end-use consumption and domestic vehicle charging, these networks are susceptible to significant voltage drops or overcurrents. The proposed strategy involves developing a signalling system that informs vehicle owners whether a charging station can guarantee a full charge based on current grid conditions. An Italian LV unbalanced network and charging habits in parking lots derived from the latest literature are used to demonstrate the effectiveness of the proposed approach.

关键词： Low voltage Power quality Electrification Minimization Low carbon economy Electric vehicle charging optimization Investment Vehicles Load modeling

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Deep Reinforcement Learning-Based Scheduling optimization of a Wind-solar Coupled CHP Unit System Considering Source-load Uncertainty

Deep Reinforcement Learning-Based Scheduling Optimization of...

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

作者： Baohua Wang Xinglong Gao Xianlian Wang Zhixiao Wang Li Sun Shan Hua State Key Laboratory of Low-Carbon Smart Coal-Fired Power Generation and Ultra-Clean Emission China Energy Science and Technology Research Institute Co.Ltd. Nanjing China National Energy Changzhou Power Generation Co. Ltd. Changzhou China National Engineering Research Center of Power Generation Control and Safety School of Energy and Environment Southeast University Nanjing China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

Promoting the electric-thermal decoupling in combined heat and power (CHP) units is an effective way to enhance their peak-regulation capability and facilitate the integration of renewable energy. In order to address the problems of flexibility and source-load uncertainty in the operation of the CHP unit, this paper studies the deep reinforcement learning (DRL)-based efficient scheduling problem of a wind-solar coupled CHP unit system. The problem is optimized under the objective of comprehensive income for energy supply and the constraints of safe operation and supply-demand balance. Based on system operation characteristics in uncertain environments, a Markov decision process (MDP) model is designed so as to transform the scheduling optimization into a sequential decision problem. To achieve efficient and intelligent scheduling of the CHP unit, the co-optimization of electricity and heat decisions is achieved by a continuous DRL algorithm, twin delayed deep deterministic policy gradient (TD3). Simulation results under a typical day scenario in the heating season show that TD3 algorithm can promote the consumption of renewable energy and ensure the sustainable scheduling capability of the thermal storage device while satisfying power balances. Furthermore, based on the well-trained neural network, the system exhibits near-theoretically optimal results with rapid single-step scheduling duration, effectively enhancing the system’s adaptability to uncertainty.

关键词： Renewable energy sources Uncertainty Cogeneration Electricity Simulation Transforms Scheduling

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