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检索条件"任意字段=13th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2024"

共 716 条记录，以下是81-90 订阅

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Tracking control of Autonomous Underwater Vehicle Based on Sliding Mode Adaptive Optimal Feedback 13

Tracking Control of Autonomous Underwater Vehicle Based on S...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Miao, Baixue Lv, Chenle Lv, Yongfeng College of Electrical and Power Engineering Taiyuan University of Technology Taiyuan030024 China

ISBN: (纸本)9798350361674

To improve the tracking control of autonomous underwater vehicles, an adaptive sliding mode optimal tracking control method for linear continuous systems is proposed by combining adaptive control and sliding mode technology. the vertical state equation of an autonomous underwater vehicle is simplified according to the actual situation. Firstly, the linear sliding mode surface is designed and the state optimal feedback controller is established. then, considering the performance index function and linear quadratic value function that meet the system requirements, the Riccati equation is linearly parameterized, and an online learning algorithm driven by parameter estimation error is introduced to approximate the optimal solution of the equation. Finally, the stability of the closed-loop system and the convergence of the error are proved by Lyapunov theory. Simulation results demonstrate that the proposed method effectively achieves depth tracking control with dynamic response, high tracking accuracy, and robustness. © 2024 ieee.

关键词： Riccati equations

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data-driven Q-learning control for Nonlinear systems Involving Parallel Multi-Step Deduction 13

Data-Driven Q-Learning Control for Nonlinear Systems Involvi...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Wang, Jiangyu Wang, Ding Zhao, Mingming Qiao, Junfei Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China Beijing Institute of Artificial Intelligence Beijing University of Technology Beijing100124 China Beijing University of Technology Beijing Laboratory of Smart Environmental Protection Beijing100124 China

ISBN: (纸本)9798350361674

When facing large amounts of data, it is a challenging task to optimize policies by using all data at once. In this paper, a data-driven Q-learning scheme with parallel multi-step deduction is developed to improve learning efficiency using small batch data for discrete-time nonlinear control. Specifically, a data-driven model is established by making use of all data in advance. then, the proposed algorithm can parallel deduce the small batch data to effectively accelerate the learning process. Furthermore, we can adjust the step size of multi-step deduction to balance the utilization between data and model. the near-optimal policy can be obtained ultimately by using hybrid data from the real system and data-driven model. Finally, a torsional pendulum plant is given to demonstrate the effectiveness of the proposed method. © 2024 ieee.

关键词： Contrastive learning

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Fixed-Time Observer Based Adaptive Prescribed Performance control for Full State Feedback System with Disturbance 13

Fixed-Time Observer Based Adaptive Prescribed Performance Co...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Sun, Guofa Liang, Boyang School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China

ISBN: (纸本)9798350361674

this article proposes a fixed-time adaptive controller based on disturbance observer to optimize the disturbance resistance and dynamic performance of full state feedback system. Firstly, a fixed-time prescribed performance (PP) function is used to transform the error function, and a new control law is proposed to ensure that the tracking error converges within a fixed-time and improve the dynamic performance of considered system;Secondly, a fixed-time disturbance observer (FT-DO) is used to observe disturbance signals and compensate to improve the performance of the system;Besides, considering the uncertainty of the system, a new update law is constructed by combining neural network (NN) and fixed-time PP function;As a result, a fixed-time control scheme is obtained, to increase the robustness of the system, where commander filter is adopted to decrease complexity;Finally, the effectiveness of the method was further verified through simulation. © 2024 ieee.

关键词： State feedback

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Model-free adaptive predictive control of nonlinear sandwich systems with input constraints 13

Model-free adaptive predictive control of nonlinear sandwich...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Dong, Jianguo Liu, Jun Jiang, Xiaoqing Wang, Ziyu Luo, Huarui Shi, Zhao School of Automation Southeast University Nanjing210000 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China College of Information Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9798350361674

Since nonlinear sandwich systems with input constraints are difficult to establish their model accurately, a model-free adaptive predictive control (MFAPC) based on compact format dynamic linearization is proposed. the criterion function of MFAPC algorithm is applied to build a quadratic programming problem with input constraints. the optimal control input signal can be obtained by solving the quadratic programming problem. In order to eliminate the adverse effect of random measurement noise on solving the optimal input signal and the stability of tracking control results, the tracking differentiator is used to estimate the output measurement signal. the stability of the control algorithm is also analyzed and proved. Finally, the merit of the proposed control algorithm is verified by example test. © 2024 ieee.

关键词： Predictive control systems

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Fault Diagnosis of Hyperbolic Distributed Parameter System 13

Fault Diagnosis of Hyperbolic Distributed Parameter System

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Song, Yu Zhang, Jianxiang Institute of Intelligent Systems and Control Guangxi University of Science and Technology School of Automation Liuzhou54500 China

ISBN: (纸本)9798350361674

the problem of iterative learning control for hyperbolic distributed parameter systems with faults under sensor/actuator networks is studied. Many results have been achieved in previous studies on iterative learning control, but the problem of fault diagnosis for partial differential systems has rarely been mentioned. therefore, this paper considers for the first time the occurrence of faults in a class of hyperbolic distributed-parameter systems with fluctuation equations having Kelvin-Voigt damping and viscous damping, and gives the corresponding fault estimation algorithms. An iterative learning based fault diagnosis algorithm and fault estimator are constructed in the article. the convergence of nonlinear system faults in sensor/actuator networks is demonstrated using the principle of compressive mapping. the convergence conditions for the convergence of virtual faults to real faults are obtained through rigorous mathematical analysis. Finally, numerical simulations are carried out according to the convergence conditions, and the numerical simulation results verify the effectiveness of the fault diagnosis algorithm designed in this paper. © 2024 ieee.

关键词： Distributed parameter control systems

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An Enhanced GC-RANSAC Approach for Subway Indoor Ground Segmentation 13

An Enhanced GC-RANSAC Approach for Subway Indoor Ground Segm...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Ren, Ye Fang, Wenxuan Wang, Li Liu, Shida School of Electronics & Control Engineering North China University of Technology Beijing100043 China

ISBN: (纸本)9798350361674

Addressing the challenges of traditional LiDAR ground segmentation algorithms in processing complex subway scenes captured, an improved GC-RANSAC ground segmentation algorithm is proposed. this method initially uses the RANSAC algorithm to extract several planes. then, it calculates the slope threshold for each plane to preserve non-ground areas. Finally, the min-cut algorithm is utilized to complete the ground segmentation. Based on the quadruped robots experimental platform, empirical data from subway scenarios are collected and tested. the processing results show the proposed algorithm demonstrates excellent performance compared with other selected methods. the False Negative Rates are 0.56%, 0.84%, and 1.67% for elevators, subway station corridors, and subway station halls respectively, which meets the effectiveness requirements for quadruped robots. © 2024 ieee.

关键词： Subway stations

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Robust Stability and Stabilization of Switched Parametric Uncertain Linear systems with Infinite Subsystems 13

Robust Stability and Stabilization of Switched Parametric Un...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Zhang, Jing Liang, Kaili Zhu, Liying Jinan250353 China

ISBN: (纸本)9798350361674

this paper investigates the robust stability issues of switched parametric uncertain linear systems with infinite subsystems and their constrained dwell times. Firstly, a switching Lyapunov function is obtained by solving a family of differential Lyapunov equations and algebraic Lyapunov equations. Secondly, based on the obtained switching Lyapunov function, this paper proposes some sufficient conditions for robust globally asymptotic stability of such kind of switched systems. thirdly, by means of the proposed robust stability results, robust globally asymptotically stabilized state feedback controllers are designed for switched parameter uncertain linear systems with infinite subsystems. Finally, an illustrative example and its numerical simulations demonstrate the effectiveness of the new results given in this paper. © 2024 ieee.

关键词： State feedback

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Observer Design for Two-Dimensional Switched Discrete-Time Linear systems with Multiple Equilibrium Points 13

Observer Design for Two-Dimensional Switched Discrete-Time L...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Liang, Kaili Zhang, Jing Zhu, Liying School of Information and Automation Qilu University of Technology Shandong Academy of Sciences Jinan250353 China

ISBN: (纸本)9798350361674

this paper investigates the observer design problem for two-dimensional switched discrete-time linear systems with multiple equilibrium points. Firstly, a distributed state observer is constructed by considering that all subsystems are observable. then, a sufficient condition for the existence of a state observer is given by analyzing the nature of the solution of the error switching system via an iterative method. the results obtained indicate that the constructed state observer can quickly follow the state of the original system over time. In the end, the validity and correctness of the designed state observer are proved by numerical simulation examples. © 2024 ieee.

关键词： State estimation

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Improved D-Type Iterative learning control for Hyperbolic Time-Delay Distributed Parameter systems under Sensor/Actuator Networks 13

Improved D-Type Iterative Learning Control for Hyperbolic Ti...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Zhang, Jianxiang Gong, Weitai Institute of Intelligent Systems and Control Guangxi University of Science and Technology Liuzhou545000 China School of Automation Guangxi University of Science and Technology China

ISBN: (纸本)9798350361674

this paper investigates the problem of iterative learning control in sensor/actuator networks for hyperbolic distributed parameter systems with time delays. For systems with known delays, this study firstly proposes an improved D-type iterative learning algorithm and proves the convergence of the iterative learning control strategy for nonlinear systems with control delays based on the principle of contraction mapping. Furthermore, by examining a nonlinear hyperbolic distributed parameter system with state delays, this paper verifies the convergence of the proposed algorithm through detailed mathematical derivations. To empirically validate the effectiveness and feasibility of the proposed algorithm, the paper finally demonstrates the performance of the iterative learning control strategy based on the proposed convergence conditions through numerical simulations. the results of the numerical simulations strongly support the applicability of the designed iterative learning algorithm in controlling hyperbolic distributed parameter systems with time delays. © 2024 ieee.

关键词： Delay control systems

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Optimal Tracking control for Constrained Two-Link Robot Based on Adaptive Dynamic Programming 13

Optimal Tracking Control for Constrained Two-Link Robot Base...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Liao, Xin Wang, Kang Li, Xiaoli Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9798350361674

this paper introduces a novel state and input constrained optimal tracking control method to address limitations posed by only partially known robot system models and constrained physical variables, such as joint position, velocity, and torque during the control process. the method employs the slack function and nonquadratic function methods to effectively handle state error and input constraints, ensuring the overall stationarity and safety of the control process. Subsequently, the adaptive dynamic programming (ADP) algorithm is designed to formulate update laws for the approximating neural networks, enabling the derivation of optimal control solutions without relying on an internal dynamic model of the system. Finally, convergence and performance are validated through simulation experiments, confirming its efficacy in managing constraints and demonstrating its application perspectives in real-world scenarios. © 2024 ieee.

关键词： Robot programming

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