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检索条件"任意字段=18th International Conference on Control Automation Robotics and Vision"

共 5310 条记录，以下是91-100 订阅

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Dynamic Proportional Integral Interval Observer-based Fault Tolerant control For Switched Systems: Application to Vehicle Lateral Dynamics 18

Dynamic Proportional Integral Interval Observer-based Fault ...

引用

18th international conference on control automation robotics and vision

作者： Nguyen, Duc To Mammar, Said Ichalal, Dalil Ait-Oufroukh, Naima Paris Saclay Univ Univ Evry Lab Comp Integrat Biol & Complex Syst IBISC F-91000 Evry France

ISBN: (纸本)9798331518509;9798331518493

this paper proposes a new approach for co-design of interval observer and Fault-Tolerant control (FTC) for uncertain switched linear systems subject to unknown but bounded disturbances and uncertainties. the lower and upper bounds of system states and fault vectors are reconstructed simultaneously by a Dynamic Proportional Integral Interval Observer (DPIIO) while a fault-tolerant tracking controller is designed to stabilize the closed-loop system and compensate for the effects of faults. the coordinate transformation method is applied to relax the common conservative conditions imposed on observer gain matrices. the observer and controller gain matrices are obtained by Linear Matrix Inequalities (LMIs) based on multiple Lyapunov function using input-to-state-stable (ISS) under average dwell time (ADT). Finally, the effectiveness of the proposed strategy is evaluated and proved through an application to lateral vehicle dynamics estimation.

关键词： Dynamic PI interval observer FTC and observer co-design switched system

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Cooperative Optimization control of Double-Integrator Multi-Agent Systems under DoS Attacks 18

Cooperative Optimization Control of Double-Integrator Multi-...

引用

18th international conference on control automation robotics and vision

作者： Yu, Guo Liu, Dan Xing, Yiyuan Liu, Yan Nanjing Tech Univ Coll Elect Engn & Control Sci Nanjing 211816 Peoples R China Nanjing Univ Informat Sci & Technol Sch Automat Nanjing 210044 Peoples R China

ISBN: (纸本)9798331518509;9798331518493

this paper is concerned with the cooperative distributed optimization problem of a specific type of double-integrator multi-agent systems affected by DoS attacks. Firstly, a structure for attack detection and topology recovery is introduced to eliminate the effects of DoS attacks. then, to estimate the state of the original system, a set of second-order homogeneous filters is designed to generate necessary state estimates. Furthermore, based on new coordinate transformations, the backstepping method is used to reconstruct the controller. According to the designed scheme, the output of each agent is able to converge to the global optimal solution. Ultimately, the feasibility of the theory is verified through simulation.

关键词： Distributed optimization multi-agent systems DoS Attacks backstepping

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An Improved Magnetic Field SLAM Algorithm Based on Iterative Extended Kalman Filter and Gaussian Process Regression 18

An Improved Magnetic Field SLAM Algorithm Based on Iterative...

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18th international conference on control automation robotics and vision

作者： Magad, Adeb Mysorewala, Muhammad King Fahad Univ Petr & Minerals Dept Control & Instrumentat Engn Dhahran 31261 Saudi Arabia King Fahad Univ Petr & Minerals Interdisciplinary Res Ctr Smart Mobil & Logist Dept Control & Instrumentat Engn Interdisciplinary Res Ctr Intelligent Mfg & Robot Dhahran 31261 Saudi Arabia

ISBN: (纸本)9798331518509;9798331518493

this paper introduces an approach for magnetic field simultaneous localization and mapping by leveraging Reduced-Rank Gaussian Process Regression. the proposed algorithm aims to improve the efficiency and accuracy of magnetic field-based localization in environments with spatial variations. the methodology involves representing the magnetic field potential as a sum of basis functions. the use of Reduced-Rank Gaussian Process Regression facilitates a streamlined representation, enabling faster computation and reduced storage requirements. then, two estimation methods are designed: an Extended Kalman Filter and Iterative Extended Kalman Filter methods to estimate the states of the dynamic model. Simulation results have demonstrated the effectiveness of the proposed approaches in estimating the true dynamic states, with slight improvement of the Iterative Extended Kalman Filter accuracy at certain magnetic field length scales, compared to the Extended Kalman Filter design.

关键词： SLAM Magnetic field IEKF EKF GP

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Federated Multi-Agent Reinforcement Learning Method for Energy Management of Microgrids 18

Federated Multi-Agent Reinforcement Learning Method for Ener...

引用

18th international conference on control automation robotics and vision

作者： Wang, Haochen Wang, Xiaowen Liu, Shuai Qin, Qianyi Xu, Liang Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China Shanghai Univ Sch Future Technol Shanghai 201900 Peoples R China

ISBN: (纸本)9798331518509;9798331518493

In the past few years, energy management strategies based on multi-agent reinforcement learning (MARL) have been an active research topic. However, existing MARL algorithms require a massive amount of data, making it challenging to ensure data privacy. To address the problem, this paper investigates FL-MARL that combines federated learning (FL) with MARL. FL allows each agent to train based on local data and only share model parameters, which means that the actual data are not shared among agents. the framework is in conjunction with a MARL algorithm: independent proximal policy optimization (IPPO). the proposed algorithm has two advantages: 1) It can protect data privacy of each agent and 2) It can adapt to large-scale and decentralized data scenarios. Finally, the performance of the algorithm is verified by simulation.

关键词： Federated learning

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Obstacle Avoidance of Multiple UAVs Based on Reinforcement Learning 18

Obstacle Avoidance of Multiple UAVs Based on Reinforcement L...

引用

18th international conference on control automation robotics and vision

作者： Mo, Weiting Li, Jinna Liaoning Petrochem Univ Sch Informat & Control Engn Fushun Peoples R China

ISBN: (纸本)9798331518509;9798331518493

Improving the obstacle avoidance capability of Unmanned Aerial Vehicles (UAVs) is crucial for maintaining their operational safety. UAVs with autonomous driving ability is the development trend of future aircraft. this paper introduces a novel UAV obstacle avoidance approach utilizing the Artificial Potential Field-Dueling Deep Q-Network (APF-Dueling DQN) method. According to the dynamic model of UAVs, the three-dimensional dynamic equation of UAVs is established, and the motion space of UAVs is constructed by combining pitch and heading angles. In order to improve the obstacle avoidance performance of UAVs, an improved Deep Reinforcement Learning (DRL) algorithm is designed, and the algorithm is used to improve the reward potential function of DQN algorithm. Simulation studies demonstrate that the APF-Dueling DQN approach surpasses the traditional DQN in performance, exhibiting robustness against local minima and yielding efficient, smooth flight paths. this underscores the efficacy of the APF-Dueling DQN in addressing UAV path planning problem.

关键词： Unmanned aerial vehicles (UAV)

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Extended Observer Form for Nonlinear System with Disturbances: Algorithm and Application 18

Extended Observer Form for Nonlinear System with Disturbance...

引用

18th international conference on control automation robotics and vision

作者： Kaparin, Vadim Simha, Ashutosh Chowdhury, Nilanjan Roy Kotta, Ulle Levron, Yoash Belikov, Juni Tallinn Univ Technol Dept Software Sci Akad Tee 21 EE-12618 Tallinn Estonia Kadet Def Syst Flight Dynam & Control Bangalore Karnataka India Tata Consultancy Serv Res Pune Maharashtra India Technion Israel Inst Technol Andrew & Erna Viterbi Fac Elect Engn IL-3200003 Haifa Israel

ISBN: (纸本)9798331518509;9798331518493

the paper addresses the problem of transforming single-output nonlinear state equations affine in disturbance into an extended observer form whose nonlinear injection part depends additionally on the derivatives of the output up to a finite order. Moreover, the considered form is affine in disturbance. Based on the earlier results a detailed algorithm is given and applied to the model of a synchronous machine connected to an infinite bus. For the system in the extended observer form a reduced-order Kalman-filter based observer can be designed such that its error dynamics is exponentially attractive and it is stable in the input-to-state sense with respect to the disturbance.

关键词： Nonlinear simulations

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Recurrent Sliding Mode-Based State Observer Design for a Subset of Nonlinear Systems 18

Recurrent Sliding Mode-Based State Observer Design for a Sub...

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18th international conference on control automation robotics and vision

作者： Atheupe, Gael P. Gurjar, Bhagyashri T. Monsuez, Bruno Renault Grp F-78280 Guyancourt France IP Paris F-78280 Guyancourt France Indian Inst Technol Dept Aerosp Engn Intelligent Syst & Control Lab Mumbai Maharashtra India Inst Poly Tech Paris IP Paris Comp Sci & Syst Engn Lab U2IS ENSTA Paris 828 Blvd Marechaux F-91120 Palaiseau France

ISBN: (纸本)9798331518509;9798331518493

this paper introduces a novel Sliding Mode-Based Observer tailored for a specific subset of nonlinear systems of order.. featuring Lipschitz nonlinearities. the study establishes stability conditions that ensure convergence of the estimation error (s) in finite time until order n, thus, providing an accurate state (s) estimation without the necessity for disturbance matching conditions. Furthermore, the study presents an extension of the scope of application of the proposed method to tackle a unique scenario characterized by a time-varying and non-invertible function of the output dynamics of the system model. the effectiveness of the proposed observer is showcased through simulation examples.

关键词： Nonlinear simulations

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Distributed Prescribed-time Optimization with Time-varying Cost: Zero-gradient-sum Scheme 18

Distributed Prescribed-time Optimization with Time-varying C...

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18th international conference on control automation robotics and vision

作者： Mao, Ningning Liu, Yuan Wang, Xiaowen Liu, Shuai Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China China Univ Petr East China Sch Geosci Qingdao 266580 Peoples R China

ISBN: (纸本)9798331518509;9798331518493

this paper proposes a zero-gradient-sum-based time-varying distributed prescribed-time optimization algorithm for single integrator dynamics. the algorithm introduces a prescribed-time sliding mode term aimed at attaining zero-gradient-sum, alongside a sliding-mode controller designed to ensure consensus among agents' states within a prescribed-time limit. Notably, the algorithm eliminates the need for initial condition constraints and local minimization. the criteria for achieving consensus and optimizing multi-agent systems are derived from optimization theory and Lyapunov stability theory. Finally, the superior convergence efficiency of the algorithm is verified through a power-sharing case study.

关键词： Distributed optimization Time-varying cost Prescribed-time convergence Zero-gradient-sum

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A Magnetic Field SLAM algorithm Based on Bayesian Filtering and Gaussian Process Regression 18

A Magnetic Field SLAM algorithm Based on Bayesian Filtering ...

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18th international conference on control automation robotics and vision

作者： Magad, Adeb Emzir, Muhammad King Fahd Univ Petr & Minerals Control & Instrumentat Engn Dept Dhahran Saudi Arabia

ISBN: (纸本)9798331518509;9798331518493

this study presents a method for simultaneously localizing and mapping magnetic fields (SLAM) via unscented Kalman filter (UKF) coupled with reduced-rank Gaussian process (GP) regression with the magnetic field measurement. the goal is to enhance the efficiency and precision of magnetic field-based localization in environments with spatial variations. the approach first involves breaking down the magnetic field potential into a series of basic functions. By employing Reduced-Rank GP Regression, the representation becomes more stream-lined, leading to quicker computations and decreased storage needs. then, two estimation techniques are compared: extended Kalman filter (EKF) and UKF filtering methods for estimating the states of the dynamic model. Simulation results indicate the effectiveness of the proposed methods in estimating the true dynamic states. Additionally, the proposed UKF design exhibits a slight improvement in accuracy at specific magnetic field length scales compared to the EKF approach.

关键词： SLAM Magnetic field EKF UKF GP

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Safety-Critical control for Underwater Vehicles with Model Uncertainties and External Disturbances 18

Safety-Critical Control for Underwater Vehicles with Model U...

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18th international conference on control automation robotics and vision

作者： Chen, Yizong Miao, Zhiqiang Zhan, Weiwei Wang, Yaonan Hunan Univ Coll Elect & Informat Engn Changsha 410082 Peoples R China Natl Engn Res Ctr Robot Visual Percept & Control Changsha 410082 Peoples R China

ISBN: (纸本)9798331518509;9798331518493

Safety is a crucial issue for underwater vehicles, which may be affected by narrow terrain and multiple obstacles. In addition, the model of the underwater vehicles are uncertain and susceptible to external disturbances such as water flow. this article utilizes model predictive control (MPC) and incremental nonlinear dynamic inversion (INDI) to design a robust control scheme for underwater vehicles. the position loop controller employs MPC to generate the required speed commands for the velocity loop controller. the velocity loop is designed with an INDI control scheme incorporating a second-order low-pass filter, effectively mitigating model uncertainties and external disturbances on the vehicles. Based on exponential control barrier functions (ECBFs), the input constraint and obstacle avoidance problems of underwater vehicles are solved. the results indicate that the proposed control scheme not only exhibits robustness but also effectively ensures safe obstacle avoidance.

关键词： Robust control

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