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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321-330 订阅

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RBFNN-Based Event-Triggered data-driven Formation control for a Connected Heterogeneous Vehicle Platoon

RBFNN-Based Event-Triggered Data-Driven Formation Control fo...

引用

data driven control and learning systems (ddcls)

作者： Panpan Zhu Shangtai Jin Chenkun Yin School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

this paper presents a novel distributed data-driven control scheme for the longitudinal formation control of a connected heterogeneous vehicle (CHV) platoon. Initially, an event-triggered mechanism is devised to alleviate the computational burden on the distributed controller. Subsequently, the future pseudo-gradient (PG) vector is predicted using the radial basis function neural network (RBFNN) method, and a data-driven control scheme is developed for the coordinated formation control of the CHV platoon. Ultimately, the simulation results demonstrate that the proposed distributed RBFNN-based event-triggered data-driven control (RBFNN-ETDDC) approach effectively achieves the objective of maintaining low-spacing error formation control for the CHV platoon.

关键词： learning systems Simulation Estimation Radial basis function networks Prediction algorithms control systems Formation control

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Robust Adaptive control for Robotic Manipulator with Output Constraints

Robust Adaptive Control for Robotic Manipulator with Output ...

引用

data driven control and learning systems (ddcls)

作者： Lei Chen Xiangbin Liu Lang Zou Min Zhang School of Automation and Intelligence Beijing Jiaotong University Beijing China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

this paper investigates the control problem of robotic manipulator subjected to uncertain dynamics and output constraints. the robotic manipulator system is described as a Lagrangian system with parameterized uncertainties and external disturbances. To deal with these uncertain terms, a robust adaptive control scheme is proposed to ensure the system with desired performance. Furthermore, the Barrier Lyapunov Function is introduced into the controller design to guarantee the output of the robotic manipulators satisfy the constraints. Finally, the effectiveness of the proposed control scheme is demonstrated by a numerical simulation.

关键词： learning systems Uncertainty Numerical simulation Stability analysis Closed loop systems Adaptive control Manipulator dynamics

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controller Dynamic Linearization Based data-driven Adaptive control for a Vapor-Compression Refrigeration System

Controller Dynamic Linearization Based Data-Driven Adaptive ...

引用

data driven control and learning systems (ddcls)

作者： Jingyu Fang Xian Yu Shuangshuang Xiong College of Mechatronics and Control Engineering Shenzhen University Shenzhen School of Automation Beijing Information Science and Technology University Beijing P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

this paper applies a data-driven adaptive control method to a benchmark of vapor compression refrigeration system based on the controller dynamic linearization method. Two controllers, namely, a single-input single-output controller and an extended multiple-input multiple-output controller, are designed to track the exit temperature of the evaporator secondary flux and the refrigerant superheat at the evaporator exit, by controlling the valve opening of the evaporator, and the compressor speed. Both the controllers entirely rely on input-output data of the controlled system in the controller design. Comparative results between the applied data-driven adaptive control and the default PID control provided by the benchmark demonstrate the effectiveness of the two designed controllers.

关键词： learning systems PI control Benchmark testing Valves Temperature control Refrigeration PD control

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Finite-Time Quantized Iterative learning control for Discrete Nonlinear systems

Finite-Time Quantized Iterative Learning Control for Discret...

引用

data driven control and learning systems (ddcls)

作者： Jinyao Cheng Yongpeng Weng Hao Chen Yongchun Ma Xin Li College of Marine Electrical Engineering Dalian Maritime University Dalian P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In this paper, the finite-time iterative learning control problem for a class of non-affine nonlinear systems with data quantization is studied in the data-driven framework. Based on the quantized error signals, a finite time quantized iterative learning control (FQILC) scheme is proposed. the convergence of tracking error and the finiteness of the convergent iteration of FQILC scheme are analyzed. the findings demonstrate that employing the finite-time technique can decrease the required number of iterations for convergence and guarantee the boundedness of tracking error. the viability of the approach is confirmed by means of a simulation example.

关键词： learning systems Quantization (signal) control systems Nonlinear systems Iterative learning control Convergence

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data-driven Stealthy Sparse Attack Detection and Identification for Cyber Physical systems

Data-Driven Stealthy Sparse Attack Detection and Identificat...

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data driven control and learning systems (ddcls)

作者： Xinyang Du Zhiyu Xi School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

this paper investigates the issues of attack detection and identification in Cyber-Physical systems (CPSs) under sparse sensor and actuator attacks, focusing on systems with unknown parameters. Initially, stealthy sparse attacks are formulated utilizing input-output information and subspace identification techniques, and the most destructive attacks are established based on an attack impact index. Subsequently, a data-driven attack detection strategy is proposed based on coding principles, and a Gated Transformer is employed to identify the compromised sensors and actuators. Finally, the proposed methodologies are validated through simulations on a supersonic aircraft, with the coding-based attack detector integrated on Zynq-7000 FPGA.

关键词： learning systems Actuators Detectors Logic gates Transformers Encoding Steady-state

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data-driven Fault-Tolerant Distributed Formation control of Multiagent systems With Switching Topologies

Data-Driven Fault-Tolerant Distributed Formation Control of ...

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data driven control and learning systems (ddcls)

作者： Tianxu Zhao Xian Zhang Xin Wang Wen-Bo Xie Heilongjiang University Harbin P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In this paper, we study the problem of data-driven fault-tolerant formation control for linear multiagent systems with actuator faults in a directed communication switching topology. Initially, constructing a distributed observer to generate using the local information as a reference, the convergence of the observer under the switching topology is proved. Subsequently, we leverage reinforcement learning theory to determine the optimal control strategy, even when the parameters of the subsystems within the multi-agent network are not known. In the final step, we apply the acquired control strategy to devise a data-driven fault-tolerant controller, aimed at minimizing fault impacts as they arise. the efficiency of our proposed solution is confirmed through simulation experiments.

关键词： Fault tolerance Network topology Fault tolerant systems Optimal control Switches Reinforcement learning Observers

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Smart Soil Monitoring System With Crop and Fertilizer Recommendation Features 13

Smart Soil Monitoring System With Crop and Fertilizer Recomm...

引用

13th ieee International conference on Communication systems and Network Technologies, CSNT 2024

作者： Saha, Gourab Suvo, Shabbir Hoshen Tonmoy, Farhan Tanjim Asad, Jiad Bin Imran, Mohammed thushar Azad, Akm Abdul Malek Brac University Department of Eee Dhaka Bangladesh Brac University Control & Applications Research Center Department of Eee Dhaka Bangladesh

ISBN: (纸本)9798350305463

this paper represents the design of a portable and IoT based device for monitoring nitrogen, phosphorus, potassium, pH, and moisture of soil, along with surrounding temperature and humidity, for crops and fertilizer recommendation. the idea and execution of a wireless, portable system for assessing soil quality, recommending the optimal amount of fertilizer, and suggesting appropriate crops depending on the soil conditions are the main goals of this research project. the system is designed to have a user-friendly interface. It uses a cloud-based platform for analyzing data and implementation of machine learning models. Multiple classification-based machine learning algorithms are compared to gain better accuracy of the system. the results of the system are validated using different samples of both indoor and outdoor environments. this cost-effective design, which includes monitoring of seven parameters necessary for crop cultivation along with crop recommendation feature and fertilizer suggestion, makes it desirable for agroindustry. © 2024 ieee.

关键词： Machine learning

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Dissipative Consensus via ILC of Singular Multiagent systems

Dissipative Consensus via ILC of Singular Multiagent Systems

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data driven control and learning systems (ddcls)

作者： Meiyu Zhang Senping Tian Panpan Gu Xiangyang Li School of Automation Science and Engineering South China University of Technology Guangzhou China School of Electrical Engineering and Automation Hefei University of Technology Hefei China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In this paper, the problem of dissipative consensus iterative learning control (ILC) is studied for singular multiagent systems (MASs). Firstly, a novel ILC algorithm is designed for such singular MASs. then, under a connected communication graph, a sufficient condition is presented to make dissipative singular MASs abtain precise consensus tracking within a certain time interval. Finally, a simulation is conducted to validate the effectiveness of the proposed method.

关键词： learning systems Sufficient conditions Protocols control systems Multi-agent systems Iterative learning control Convergence

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Vehicle Formation control Based on Model-Free Adaptive Iterative learning

Vehicle Formation Control Based on Model-Free Adaptive Itera...

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data driven control and learning systems (ddcls)

作者： Ye Ren Yongqiang Xie Li Wang Honghai Ji School of Electronics & Control Engineering North China University of Technology Beijing

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In this paper, a vehicle formation control method based on model-free adaptive iterative learning is proposed for vehicles with the same turn at a road intersection. At road intersections, inconsistencies in speed and spacing between vehicles with the same turn can lead to traffic congestion. therefore, this study investigates the path planning and speed planning for vehicles with the same turn. In the case of vehicular networking, the formation control of intelligent networked vehicles with the same turn makes the vehicles travel in formation in a fast and orderly manner, thus improving the efficiency and enhancing the safety of road intersections.

关键词： learning systems Adaptation models Roads Formation control Path planning Safety Planning

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Optimal control of Stochastic systems with Wiener and Poisson Noise based on data-driven Approach

Optimal Control of Stochastic Systems with Wiener and Poisso...

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data driven control and learning systems (ddcls)

作者： Zhiguo Yan Guocui Chen Guolin Hu School of Information and Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In this paper, we investigate the optimal control problem pertaining to a specific class of continuous-time stochastic systems that incorporate both Wiener and Poisson noise. Firstly, a data-driven strategy iteration algorithm is designed, which iteratively solves the Riccati equation through online state and collected data without knowing the system coefficient matrix; Secondly, an algorithm is proposed to calculate the maximum value of Poisson intensity under a given convergence accuracy; Finally, a numerical example is employed to demonstrate the efficacy of the proposed algorithm.

关键词： learning systems Accuracy System dynamics Heuristic algorithms Stochastic systems Noise Riccati equations

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