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24th International Electronics Symposium, IES 2022

作者： Guo, Xin Li, Wei-Peng Pan, Yuan Liu, Jun Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China Xi'an University of Technology School of Automation and Information Engineering Xi'an China

ISBN: (数字)9781665489713

ISBN: (纸本)9781665489713

In order to effectively utilize the wind energy, the max power point tracking (MPPT) control method has been extensively used in the wind power system. The MPPT control in the wind power system is actually to control the power electronic converters connected with the wind turbine. However, due to the existing of the power switching devices, the converters were the typical nonlinear system. The traditional linearization modeling methods of the converters cannot represent the working process of the system accurately and the control strategies based on the linearization model of the converters only guarantee the satisfactory performance of system near the predefined working point. They were not suitable to the wind power MPPT system, which has the variable wind speeds and the variable max power points. This paper proposes a power switching control method based on a novel power switched model of the wind power MPPT system with Boost converter. The main contributions of the work are: (1) The proposed power switched model realizes the accurate description of the converter working process, which directly focus on the power states of the wind power system. (2) The proposed switching control method realizes the direct power switching control of the converter of the wind power MPPT system. The merits of the proposed method are simple control structure, no control parameter, no pulse width modulation block and strong robustness under circuit parameters uncertainty. The simulation results verify the effectiveness and the superiority of the proposed methods. © 2022 IEEE.

关键词： Wind power

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Streaming-Data-Driven Multi-Objective Optimal Operation for Ammonia-based Integrated Energy Chemical systems: An Event-Triggered Scheme 42

Streaming-Data-Driven Multi-Objective Optimal Operation for ...

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42nd Chinese control Conference, CCC 2023

作者： Li, Longyan Ning, Chao Shanghai Jiao Tong University Department of Automation Shanghai200240 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9789887581543

As an important component in the industry sector, the integrated energy chemical system is inescapably responsible for carbon reduction in addition to economic and reliability performance. We propose a novel streaming-data-driven multi-objective optimal operation for ammonia-based integrated energy chemical systems (AIECS). In the day ahead scheduling, a detailed mathematical model for AIECS is presented, upon which a multi-objective optimization considering cost, CO2 emission and reliability is established. For the intra-day operation, an event-triggered mechanism is firstly developed in the real-time operation of AIECS, and it enables the AIECS to be risk-aware just in time. By monitoring the difference between the predicted state of charge and the capacity limitations of battery, the AIECS identifies whether it is in hazardous regime. Then, the intelligent switch between certainty equivalence model predictive control and online-learning based distributionally robust model predictive control is proposed, such that their respective advantages are leveraged. Case studies demonstrate that the proposed approach guarantees the system safety, and brings good revenue. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Model predictive control

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Online-Learning-Based Distributionally Robust Motion control with Collision Avoidance for Mobile Robots

Online-Learning-Based Distributionally Robust Motion Control...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Han Wang Chao Ning Longyan Li Weidong Zhang Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Collision-free navigation is a critical issue in robotic systems as the environment is often dynamic and uncertain. This paper investigates a data-stream-driven motion control problem for mobile robots to avoid randomly moving obstacles when the probability distribution of the obstacle’s movement is partially observable through data and can be even time-varying. A data-stream-driven ambiguity set is firstly constructed from movement data by leveraging a Dirichlet process mixture model and is updated online using real-time data. Then we propose an Online-Learning-based Distributionally Robust Nonlinear Model Predictive control (OL-DR-NMPC) approach for limiting the risk of collision through considering the worst-case distribution within the ambiguity set. To facilitate solving the OL-DR-NMPC problem, we reformulate it as a finite-dimensional nonlinear optimization problem. To cope with the bilinear matrix inequality constraints in the nonlinear problem, we develop a parabolic relaxation and a sequential algorithm, by which the problem is further transformed into polynomial-time solvable surrogates. The simulations using a quadrotor model are employed to demonstrate the effectiveness and advantages of the proposed method.

关键词： Navigation Simulation Real-time systems Probability distribution Safety Mobile robots Collision avoidance

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Improved Spatial Registration Algorithm for Sensors on Multiple Mobile Platforms

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Journal of Shanghai Jiaotong university(Science) 2022年第5期27卷 638-648页

作者： LÜRunyan PENG Na WU Yi CAI Yunze Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Jiao Tong UniversityShanghai200240China Shanghai Aerospace Electronic Technology Institute Shanghai Academy of Spaceflight TechnologyShanghai201109China Alibaba(China)Co. Ltd.Hangzhou311121China

This paper focuses on the spatial registration algorithm under the earth-center earth-fixed(ECEF)coordinate system for multiple mobile *** sensor measurement biases are discussed with the attitude information of the platform into ***,the biased measurement model is ***,the maximum likelihood registration(MLR)algorithm is discussed to simultaneously estimate the measurement biases and the target ***,an improved online MLR(IMLR)algorithm is proposed through a sliding window of adaptive *** results demonstrate that the proposed IMLR algorithm effectively improves the realtime ability of the system and can approach similar estimation accuracy to the conventional MLR algorithm.

关键词： spatial registration 3D sensors improved online maximum likelihood registration(IMLR)

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Optimal Planning of Zero-Carbon Off-Grid Ammonia-Hydrogen-Based Microgrids Considering Hybrid Types of Electrolyzer Modules

Optimal Planning of Zero-Carbon Off-Grid Ammonia-Hydrogen-Ba...

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Power system and Green Energy Conference (PSGEC)

作者： Junhao Gu Longyan Li Chao Ning Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798350365573

ISBN: (纸本)9798350365580

The off-grid ammonia-hydrogen-based microgrid is recognized as a promising paradigm for industrial decarbonization. In this paper, we propose a novel planning model for off-grid ammonia-hydrogen-based microgrids, where the hydrogen is produced in a distributed manner and the ammonia is synthesized in a large-scale energy-intensive plant. In specific, the proposed planning model considers hybrid types of electrolyzer modules and systematically investigates the operational constraints of distribution networks and hydrogen storage equipment, enabling distributed flexible hydrogen production. To seamlessly bridge distributed hydrogen sources and centralized ammonia production site, the delivery of hydrogen through the transportation network is structured as a vehicle routing problem. Eventually, the effectiveness of the proposed model is validated through case studies. Simulation results show that the proposed model lowers the total system cost by 11.8% compared with the simplified scenario which uses one single type of electrolyzer.

关键词： Ammonia Costs Hydrogen Vehicle routing Production Microgrids Distribution networks Planning Numerical models Optimization

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A Simplified Economic Model Predictive control Algorithm for Soft Constrained system with Changing Economic Criteria

A Simplified Economic Model Predictive Control Algorithm for...

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第34届中国过程控制会议

作者： Xiaowen Qi Shaoyuan Li Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

To improve the economic performance of soft-constrained systems,this paper proposes a new soft-constrained Economic Model Predictive control(EMPC) approach to cope with changes in economic criteria caused by variations in raw material prices,product prices,market fluctuations,disturbances,*** the one hand,terminal states are permitted to be any admissible equilibrium *** the other hand,slack variables for soft constraints are considered in the cost stage to enhance dynamic operation *** ensure the asymptotic stability,the Lyapunov-like stability constraint is ***,the effectiveness of the proposed method is demonstrated by an isothermal stirred-tank reactor process.

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Robust Stability and Stabilization Conditions for Fractional-order systems with Distributed Delays and Polytopic Uncertainties

Robust Stability and Stabilization Conditions for Fractional...

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Chinese control and Decision Conference, CCDC

作者： Yi-Nan Chen Jun-Guo Lu Zhen Zhu Jia-Rui Zhang Qing-Hao Zhang Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

This paper investigates the robust stability and stabilization conditions for fractional-order systems with distributed delays (FOSDDs) with polytopic uncertainties. To begin with, two robust stability conditions for FOSDDs with polytopic uncertainties are formulated. Subsequently, the state feedback controllers are put forward to robustly stabilize the FOSDDs with polytopic uncertainties. The obtained results are illustrated utilizing linear matrix inequalities (LMIs). Finally, two numerical instances are provided to showcase the effectiveness of the derived conditions.

关键词： State feedback Uncertainty Robust stability Delays Linear matrix inequalities Numerical stability

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Towards Autonomous Indoor Parking: A Globally Consistent Semantic SLAM system and A Semantic Localization Subsystem

arXiv

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arXiv 2024年

作者： Sha, Yichen Zhu, Siting Guo, Hekui Wang, Zhong Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University China Dimensional Robot Shanghai China

We propose a globally consistent semantic SLAM system (GCSLAM) and a semantic-fusion localization subsystem (SF-Loc), which achieves accurate semantic mapping and robust localization in complex parking lots. Visual cameras (front-view and surround-view), IMU, and wheel encoder form the input sensor configuration of our system. The first part of our work is GCSLAM. GCSLAM introduces a novel factor graph for the optimization of poses and semantic map, which incorporates innovative error terms based on multi-sensor data and BEV (bird’s-eye view) semantic information. Additionally, GCSLAM integrates a Global Slot Management module that stores and manages parking slot observations. SF-Loc is the second part of our work, which leverages the semantic map built by GCSLAM to conduct map-based localization. SF-Loc integrates registration results and odometry poses with a novel factor graph. Our system demonstrates superior performance over existing SLAM on two real-world datasets, showing excellent capabilities in robust global localization and precise semantic mapping. Copyright © 2024, The Authors. All rights reserved.

关键词： Mapping

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A Distributed Model Predictive control for Multi-zone HVAC with Global Resource Constrained

A Distributed Model Predictive Control for Multi-zone HVAC w...

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第34届中国过程控制会议

作者： Shunjian MA Yuanyuan ZOU Shaoyuan LI Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

Heating,Ventilation and Air Conditioning(HVAC) for multi-zone buildings includes centralized plants and remote equipment to jointly regulate indoor air temperature of every zone to satisfy difference *** to the limited capacity of the total supply air in centralized equipment,two conflicts are raised when controlling indoor air temperature for all *** is between meeting diverse demands to meet user's preferences and limited global resources,and another conflict is between distributed regulation facilities and centralized air supply *** this paper,a distributed model predictive control(DMPC) with global resource constrained is proposed for multi-zone HVAC ***,a centralized MPC with energy savings and thermal comforts is formulated to balance the demands of each zone and the limited resource ***,this centralized MPC is decomposed into subsystems by dual *** Lagrange function is integrated in the resulting optimization to deal with global constraints,so that a fully distributed solvable DMPC can be solved by a distributed primal-dual *** effectiveness of the proposed method is proved by simulation examples.

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Accelerated Simulation of Master Equation for Open Quantum systems

Accelerated Simulation of Master Equation for Open Quantum S...

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第42届中国控制会议

作者： Bo Yue Yanfang Wang Shibei Xue Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

Simulation of open quantum systems is undoubtedly critical to design of quantum devices and applications of quantum technologies since dynamics of open quantum systems cannot be solved analytically in general. However, the dimension of open quantum systems grows exponentially as the number of their subsystems increases or as involving complicated environments,which reduces the computational efficiency of the simulation. In this paper, we boost numerical simulation of master equations of open quantum systems from several aspects with which the total time and the occupied memory in the simulation are significantly reduced without losing precision. Our method can be applied to the simulation of non-Markovian quantum systems described by an augmented system model as well. We conduct numerical experiments on simulation of a non-Markovian spin *** with the algorithm in a well-known toolbox, QuTiP, our method can take 26.3% time and less memory under fair conditions.

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