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A Survey of Output Feedback Robust MPC for Linear Parameter Varying systems

IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1717-1751页

作者： Xubin Ping Jianchen Hu Tingyu Lin Baocang Ding Peng Wang Zhiwu Li the Department of Automation School of Electro-Mech-anical EngineeringXidian UniversityXi’an 710071China the Ministry of Education Key Laboratory for Intelligent Networks and Network Security School of Automation Science and EngineeringFaculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China the State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing 100854China the College of Automation Chongqing University of Posts and TelecommunicationsChongqing 400065China the Information and Navigation College Air Force Engineering UniversityXi’an 710077China IEEE the School of Electro-Mechanical Engineering Xidian UniversityXi’an 710071 the Institute of System Engineering Macao University of Science and TechnologyMacao SARChina

For constrained linear parameter varying(LPV)systems,this survey comprehensively reviews the literatures on output feedback robust model predictive control(OFRMPC)over the past two decades from the aspects on motivations,main contributions,and the related *** to the types of state observer systems and scheduling parameters of LPV systems,different kinds of OFRMPC approaches are summarized and *** extensions of OFRMPC for LPV systems to other related uncertain systems are also *** methods of dealing with system uncertainties and constraints in different kinds of OFRMPC optimizations are *** issues on OFRMPC optimizations for LPV systems are ***,the future research directions on OFRMPC for LPV systems are suggested.

关键词： Linear parameter varying(LPV)systems model predictive control(MPC) output feedback robust control

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Requirement-Oriented TT&C Method for Satellite Based on BDS-3 Short-Message Communication system

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Space(Science & Technology) 2023年第1期3卷 311-324页

作者： Chao Li Peijie Liu Shiyuan Fu Yiwen Jiao Wei Zhang Department of Electronic and Optical Engineering Space Engineering UniversityBeijingChina Key Laboratory of Intelligent Space TT&C and Operation(Space Engineering University) Ministry of EducationBeijingChina State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System LuoyangChina Xi’an Satellite Control Center Xi’anChina

With the increasing number of satellites being launched in China,the demand for Telemetry,Tracking,and Command(TT&C)resources is also *** of the global coverage and resource requirements of TT&C management,this paper proposes a TT&C scheme based on the Global Short-Message Communication system(GSMCS)of the BeiDou-3 Navigation Satellite system(BDS-3).The system composition,workflow,and functions of satellite TT&C are analyzed using the GSMCS of *** the coverage analysis of the Medium Earth Orbit(MEO)constellation of BDS-3,scheme’s applicability is pointed out,and the correctness of the analysis results is verified via *** value range of the link distance is derived by calculating the range of the distance variation between any 2 satellites in the BDS-3 MEO constellation and combining the intersatellite routing *** calculation results show that the response time range of the autonomous request management application of in-orbit satellites based on the GSMCS of BDS-3 is 1.407 to 2.448 *** can meet the requirements of TT&C service.

关键词： Message Command service

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Adaptive Deep Reinforcement Learning for Critical Boundary Scenario Generation 43

Adaptive Deep Reinforcement Learning for Critical Boundary S...

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43rd Chinese control Conference, CCC 2024

作者： Zhou, Junjie Wang, Lin Wang, Xiaofan Meng, Qiang Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai202400 China Ministry of Education of China Key Laboratory of System Control and Information Process Shanghai202400 China National University of Singapore Department of Civil and Environmental Engineering Singapore117576 Singapore Shanghai Institute of Technology School of Electrical and Electronic Engineering Shanghai202400 China

ISBN: (纸本)9789887581581

Critical boundary scenarios play a vital role in the comprehensive testing of autonomous vehicles, as they can significantly expedite testing processes and reduce economic and time costs. To tackle the intricate, multidimensional, and diverse nature of intelligent driving scenarios, this paper proposes an innovative bi-level adaptive deep reinforcement learning (BADRL) approach aimed at generating authentic and diverse critical boundary scenarios. Leveraging naturalistic driving data, background agents are trained to exhibit naturalistic and realistic driving behaviors using a neural-based naturalistic driving behavior model. To address the intricacies of multi-interaction, high-dimensional environments, the scenario complexity model is introduced to evaluate the relative complexity between the traffic environment and the tested autonomous vehicle in real time. By integrating the scenario complexity model, the naturalistic driving behavior learning, intelligent driving testing, and critical boundary scenario generation are concatenated together to form a closed loop. BADRL facilitates the upper-level neural network in learning to adaptively increase the complexity of test scenarios, which are then fed into lower-level models to optimize the behavior of principal traffic participants, thereby generating naturalistic and critical boundary test scenarios. Extensive simulations were carried out to verify the efficacy of the BADRL technique in complex intersection environments. Results indicate that the BADRL approach boosts the efficiency of critical boundary scenario generation by approximately 10% compared to the state-of-the-art method. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Deep reinforcement learning

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Analytic Mechanism for the Cumulative Effect of Wind Power Fluctuations from Single Wind Farm to Wind Farm Cluster

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CSEE Journal of Power and Energy systems 2022年第5期8卷 1290-1301页

作者： Gang Mu Fangze Wu Xiaoping Zhang Ziheng Fu Bai Xiao Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China Department of Electronic Electrical and Systems EngineeringSchool of EngineeringUniversity of BirminghamBirmingham B152TTU.K

The use of wind power is rapidly growing worldwide as a means of reducing carbon emissions for the energy *** has the world’s largest wind power installation and multiple large-scale wind farm clusters,each comprising dozens of wind *** the planning and operation of the power system,it is important to understand the power fluctuation characteristics of wind farm *** studies demonstrate that the relative power fluctuation of a wind farm cluster is less than that of a single wind *** this decreasing trend a random occurrence or does it have a regular pattern?This scientific question is addressed by investigating the mechanism of the cumulative effect of a wind farm *** this study,a cumulative model is proposed by examining the spatiotemporal relationships of wind power variations and wind farm *** gain function and critical cumulative frequency are defined as the foundations to analytically describing the cumulative *** investigating the cumulative effect mechanism,the relationship between power fluctuation and spatiotemporal parameters of the wind farm cluster are *** power fluctuation of a cluster can be predicted using the cumulative model even before it is completely *** mechanism of the cumulative effect is validated on the basis of the data of two actual wind farm clusters.

关键词： Analytic mechanism cumulative effect evolution regularity wind farm cluster wind power fluctuation

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Automatic Detection of Myotonia using a Sensory Glove with Resistive Flex Sensors and Machine Learning Techniques 6

Automatic Detection of Myotonia using a Sensory Glove with R...

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6th IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd4.0 and IoT 2023

作者： Cesarini, Valerio Costantini, Giovanni Amato, Federica Errico, Vito Pietrosanti, Luca Calado, Alexandre Luis Massa, Roberto Frezza, Erica Irrera, Fernanda Manoni, Alessandro Saggio, Giovanni University of Rome Tor Vergata Department of Electronic Engineering Rome Italy Polytechnic University of Turin Department of Control and Computer Engineering Turin Italy University of Rome Tor Vergata Department of Systems Medicine Rome Italy University of Rome la Sapienza Department of Information Engineering Electronics and Telecommunications Rome Italy

ISBN: (纸本)9798350396577

This paper deals with the automatic detection of Myotonia from a task based on the sudden opening of the hand. Data have been gathered from 44 subjects, divided into 17 controls and 27 myotonic patients, by measuring a 2-point articulation of each finger thanks to a calibrated sensory glove equipped with a Resistive Flex Sensor (RFS). RFS gloves are proven to be reliable in the analysis of motion for myotonic patients, which is a relevant task for the monitoring of the disease and subsequent treatment. With the focus on a healthy VS pathological comparison, customized features were extracted, and several classifications entailing motion data from single fingers, single articulations and aggregations were prepared. The pipeline employed a Correlation-based feature selector followed by a SVM classifier. Results prove that it's possible to detect Myotonia, with aggregated data from four fingers and upper/lower articulations providing the most promising accuracies (91.1%). © 2023 IEEE.

关键词： Machine learning

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Study on Applying Median Cancellation Adaptive Clutter Suppression Interference Algorithm to Airborne Radar 3

Study on Applying Median Cancellation Adaptive Clutter Suppr...

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3rd International Conference on Neural Networks, Information and Communication engineering, NNICE 2023

作者： Li, Zhe Zhao, Juan Lu, Shanshan Xi'an Electronic Engineering Research Institute General System Designing Department No.3 Xi'an China Sixth Sector Xi'an Modern Control Technology Research Institute Xi'an China Xi'an Electronic Engineering Research Institute Basic Research Department No.4 Xi'an China

ISBN: (纸本)9798350335972

Clutter Suppression Interference (CSI) is a common radar signal processing method, which efficiently suppresses ground clutter interference in radar received echoes and can greatly improve the signal-to-noise ratio of airborne synthetic aperture radar ground motion target indication (SAR/GMTI). However, the implementation of the clutter suppression algorithm in engineering is difficult because of the large number of filtering power coefficients to be calculated in real time. Based on this research background, this paper models the ground clutter of airborne radar, analyzes the principles and performance of three clutter suppression algorithms, CSI, ACSI and median cancellation ACSI, and performs engineering implementation. From the engineering experimental results, it can be seen that all three algorithms can improve the airborne radar signal-to-noise ratio and thus improve the recognition capability of moving targets, among which the median pair cancellation ACSI algorithm has the lowest false alarm probability and the greatest performance improvement. © 2023 IEEE.

关键词： Synthetic aperture radar

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Development of a Bio-inspired Tailless FWMAV with High-Frequency Flapping Wings Trajectory Tracking control

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Journal of Bionic engineering 2024年第5期21卷 2145-2166页

作者： Qingcheng Guo Chaofeng Wu Yichen Zhang Feng Cui Wu Liu Xiaosheng Wu Junguo Lu National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai Jiao Tong UniversityShanghai200240China Department of Micro/Nano Electronics School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai200240China Department of Automation Shanghai Jiao Tong UniversityShanghai200240China The Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China

The development of a tailless Flapping Wing Micro Aerial Vehicle(FWMAV)inspired by the hummingbird is presented in this *** implementing mechanical simplifications,it is possible to use planar machining technology for manufacturing of the FWMAV’s body,greatly reducing assembly ***,studies on flapping wing aircraft are limited to open-loop wing kinematics *** this work,an instantaneous closed-loop wing trajectory tracking control system is introduced to minimize wings’trajectory tracking *** control system is based on Field-Oriented control(FOC)with a loop shaping compensation technique near the flapping *** frequency analysis,the loop shaping compensator ensures the satisfactory bandwidth and performance for the closed-loop flapping *** implement the proposed controller,a compact autopilot board integrated with FOC hardware is designed,weighing only 2.5 *** utilizing precise wing trajectory tracking control,the hummingbird-inspired FWMAV demonstrates superior ability to resist external disturbances and exhibits reduced attitude tracking errors during hovering flight compared to the open-loop wing motion.

关键词： Flapping Wing Micro Aerial Vehicle(FWMAV) Bio-inspired robotics Trajectory control Loop shaping compensator Field-Oriented control(FOC)

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Synthesis of Dynamic Virtual-Inertia for Microgrid system Applications

Synthesis of Dynamic Virtual-Inertia for Microgrid System Ap...

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2025 International Conference on Intelligent control, Computing and Communications, IC3 2025

作者： Justo, Jackson J. Demidova, Galina Lukichev, Dmitry Poliakov, Nikolai Makolo, Peter Bansal, Ramesh C. Itmo University Faculty of Control System and Robotics Saint-Petersburg Russia University of Dar es Salaam Department of Electrical Engineering P.O. Box 33335 Dar es Salaam Tanzania United Republic of University of Sharjah Depatment of Electrical Engineering Sharjah United Arab Emirates University of Pretoria Department of Electric Electronic and Computer Engineering Pretoria South Africa

ISBN: (纸本)9798331527495

During the last two decades, interest in grid integrated renewable energy sources (RERs) into the electrical power grids has significantly grown. The motive being a promising strategy to reduce greenhouse gas emissions generated by conventional power plants (CPPs) and hence environmental consequences, decrease losses in distribution lines to improve power system supply efficiency and reliability to consumers. As a result, several CPPs are being replaced by RERs such as solar PV system, wind energy, micro hydro-turbine, fuel cell, and small gas power plants. These are installed close to customers on low-voltage and medium-voltage sites to reduce losses in the network and improve power quality, overall efficiency and reliability. However, grid-connected RERs via inverter decreases system inertia due to decrease in CPPs with rotating mass serving as an immediate natural response to frequency deviations following network disturbances. Therefore, this paper presents the design of dynamic virtual-inertia control (DVIC) scheme. The developed DVIC incorporates the mechanism to adjust active and reactive demand in response to any frequency and voltage variations to ensure system stability. To validate the suitability of the presented technique, MATLAB/Simulink model is developed and simulated under various operating scenarios. Using the results obtained simulation study, it is evidently the proposed DVIC shows improved performance is achieved than when no inertia control system applied. © 2025 IEEE.

关键词： Solar fuels

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Extended NNs-Based Adaptive Event-Triggered Asymptotic control for Nonlinear systems Against Actuator Faults 7

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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7th International Symposium on Autonomous systems, ISAS 2024

作者： Liu, Shanlin Zhang, Yingwei Zhao, Xudong Wang, Hesheng Northeastern University College of Information Science and Engineering Shenyang China Northeastern University State Laboratory of Synthesis Automation of Process Industry Shenyang China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350363173

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent. © 2024 IEEE.

关键词： Approximation algorithms

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Optimal Power system Scheduling Considering Uncertainty-Induced Generation Unit Output Curtailment 25

Optimal Power System Scheduling Considering Uncertainty-Indu...

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25th IEEE China Conference on system Simulation Technology and its Application, CCSSTA 2024

作者： Hu, Wei Mi, Ning Zhong, Hailiang Chen, Weihan Ma, Kun Geng, Tianxiang Wang, Yun Su, Bo Yang, Long Tsinghua University State Key Laboratory of Power System and Generation Equipment Department of Electrical Engineering Beijing China Dispatching Control Center State Grid Ningxia Electric Power Co. Ltd. Yinchuan China Tsinghua University Department of Electrical Engineering and Applied Electronic Technology Beijing China

ISBN: (纸本)9798350366600

Under the call of the national 'dual carbon' goals, the growth of the proportion of new energy generation has become an inevitable trend in energy structure adjustment. The 'static parameter' model, which traditional thermal power units rely on, can no longer accurately reflect their output uncertainty, urgently requiring a new optimization scheduling strategy to cope with this change. This study proposes an optimized scheduling model for power generation systems that considers the output curtailment and unplanned outages of thermal power units. It employs non-parametric kernel density estimation techniques to model the uncertainty of thermal power unit output and uses chance constraints to define the fluctuation range of generation output and the system's reliability. The model adopts a scenario generation method based on Copula theory to construct output scenarios and further employs reduction techniques to optimize the number of scenarios. Moreover, this paper introduces Conditional Value at Risk as a key indicator to measure the cost of system uncertainty risk, thereby providing a more comprehensive perspective in risk assessment. Simulation experiments on the IEEE 30-node standard system demonstrate that compared to traditional optimization scheduling models relying on static parameters, the proposed model can more effectively balance the output fluctuations of different thermal power units, significantly reducing the risk of curtailment due to supply shortages. This study offers a new theoretical basis and practical guidance for optimizing the scheduling of power systems under the context of large-scale integration of new energy and economic fluctuations. © 2024 IEEE.

关键词： Chance Constraints Conditional Value at Risk Output Curtailment Scenario Generation

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