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检索条件"任意字段=9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020"

共 506 条记录，以下是101-110 订阅

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Robust Adaptive Repetitive control of Robotic Manipulators 9

Robust Adaptive Repetitive Control of Robotic Manipulators

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Zhu, Sheng Sun, Mingxuan Zhejiang Univ City Coll Hanghzou 310015 Zhejiang Peoples R China Zhejiang Univ Technol Hanghzou 310023 Zhejiang Peoples R China

ISBN: (纸本)9781728159225

this paper presents a robust adaptive repetitive control(RARC) method for trajectory tracking of uncertain robotic manipulators. Repetitive control is applied for periodic trajectory tracking and a sigma modification is introduced in the periodic learning laws to guarantee the robustness of the system. All the signals in the closed loop are proved to be bounded. An open-loop learning algorithm with switching s modification is designed to achieve asymptotic convergence of the tracking errors when the disturbances disappear. the simulation is made to show the effectiveness of the algorithms.

关键词： Robust Adaptive Repetitive control sigma Modification Robotic Manipulators

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A data-driven Fault Tolerant control of Singularly Perturbed systems 9

A Data-Driven Fault Tolerant Control of Singularly Perturbed...

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Liu, Lei Li, Shuangbo Han, Cunwu Yang, Ying North China Univ Technol Beijing 100144 Peoples R China Peking Univ Beijing 100871 Peoples R China

ISBN: (纸本)9781728159225

A data-driven fault tolerant control for singularly perturbed systems is presented in this paper. It is founded on the data-driven full state observer and Youla controller parameterization. Based on the multiplex observer residual generator and the identification of the parity subspace, an extended internal model control (EIMC) structure is proposed and then the design of the parameters is given accordingly. Since the system is disturbed by faults, the controller proposed in this paper can accurately track the fault parameters. At last a numerical example is given to illustrate the feasibility and effectiveness of the method.

关键词： Singularly perturbed system data-driven methods fault tolerant control Youla parametrization

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A new indirect ILC method with an iterative dynamical identification of the set-point command 9

A new indirect ILC method with an iterative dynamical identi...

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Li, Huaying Chi, Ronghu Qingdao Univ Sci & Technol Sch Automat & Elect Engn Qingdao 266061 Peoples R China

ISBN: (纸本)9781728159225

In this work, a new indirect iterative learning control (ILC) method with an iterative dynamical identification of the set-point command is proposed. the ILC law of the set-point is derived from the dynamical linearization of a nonlinear ideal ILC law. then, the estimation law of the parameter in the ILC law is derived from the optimization of a cost function. At last, simulations demonstrate the advantages of the proposed scheme.

关键词： Indirect ILC Iterative dynamical identification data-driven

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Physics-informed Recurrent Neural Networks for the Identification of a Generic Energy Buffer System 10

Physics-informed Recurrent Neural Networks for the Identific...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Lahariya, Manu Karami, Farzaneh Develder, Chris Crevecoeur, Guillaume IDLab Ghent University - Imec Ghent Belgium Ghent University Core Lab EEDT-DC Systems and Metal Engineering Dept. Electromechanical GentB-9052 Belgium

ISBN: (纸本)9781665424233

Energy storage is ubiquitous in industrial processes and comes in many forms such as material, chemical, electromechanical buffers. System identification of such energy buffers demands proper estimation/prediction of their physical quantities and unknown parameters. Once these parameters are determined, the identified model can be employed to predict the industrial process dynamics, which finally assist to build efficient control for these processes. this paper proposes physics-informed neural networks-based grey-box modeling methods for the identification of energy buffers. the underlying system dynamics are enforced on the neural network structure to ensure that the identified grey-box model follows the approximate physics. We define two novel grey-box models based on simple and recurrent neural network architectures and test these models for a generic energy buffer. Performance and training time for the proposed grey-box models are compared against a black-box baseline model. Results confirm that imposing the dynamic system's physics on the network improves the performance, and utilizing a recurrent architecture leads to a further improvement. © 2021 ieee.

关键词： Recurrent neural networks

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Variable Gain Accurate Differential Compensation control for A Class of Strict Feedback systems 9

Variable Gain Accurate Differential Compensation Control for...

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Sun, Guofa Zhang, Xingrong Qingdao Univ Technol Sch Informat & Control Engn Qingdao 266520 Peoples R China

ISBN: (纸本)9781728159225

this paper, an adaptive fuzzy controller is proposed to a class of discrete-time nonlinear systems with strict feedback. In these systems, total disturbance consists the fuzzy approximation error and unknown external disturbance. And the proposed accurate disturbance observer could track the approximation disturbance accuratly. It can be proved via the Lyapunov theorem that all signals in this closed-loop system are guaranteed to be bounded. Finally, the simulation example demonstrates the effectiveness of the proposed scheme.

关键词： Accurate disturbance observer discrete-time systems fuzzy logic system backstepping

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Aircraft control Method Based on Deep Reinforcement learning 9

Aircraft Control Method Based on Deep Reinforcement Learning

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Zhen, Yan Hao, Mingrui Sci & Technol Complex Syst Control & Intelligent Beijing 100074 Peoples R China

ISBN: (纸本)9781728159225

To address the failure of precise overload tracking and anti-interference caused by the difficulty of accurate modeling of a complex aircraft, the controller designing method based on deep reinforcement learning is studied. this paper trained the control network based on the Proximal Policy Optimization (PPO), studied the tracking control problem of the aircraft, and accurately tracked the typical command signals. Fixed-point simulation of the aircraft is performed, with results showing that, in presence of aircraft model parameter variation and external disturbance, the controller based on deep reinforcement learning can achieve accurate tracking of overload commands.

关键词： aircraft intelligent control deep reinforcement learning parameter setting trajectory tracking

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data-driven-Based Distributed Security control for Vehicle-Following Platoon 9

Data-Driven-Based Distributed Security Control for Vehicle-F...

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Che, Weiwei Deng, Chao Liu, Dan Qingdao Univ Inst Complex Sci Qingdao 266071 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

ISBN: (纸本)9781728159225

this paper proposes a data-driven-based distributed security control approach for vehicle-following platoons in the presence of denial-of-service attacks. First, distributed resilient observers are designed to estimate the trajectories of the leader-vehicle. Based on the developed observers, data-driven controllers are proposed for the vehicle-followers. Specifically, a datadriven approach is introduced to identify controller parameters without relying on the knowledge of system dynamics. Finally, a vehicle-following platoon example is provided to demonstrate the effectiveness of the data-driven-based distributed security control method.

关键词： data-driven control Distributed security control Vehicle-following platoon DoS attacks

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data-driven adaptive sliding mode controller design for nonlinear systems with prescribed performance 9

Data-driven adaptive sliding mode controller design for nonl...

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Liu, Dong Shenyang Aerosp Univ Coll Automat Shenyang 110136 Peoples R China

ISBN: (纸本)9781728159225

this paper addresses the problem of prescribed performance control for nonlinear discrete-time systems such that the tracking error is constrained to a predesigned region all the time. Moreover, a new second order sliding mode control method together with an novel transformed error strategy is proposed to guarantee the prescribed convergence rate and steady state error behavior to a predefined region all the time. Further, the designed controller depends only on the input/output data, which is more effective in the complex industrial processes. the potential of the results is illustrated on the simulation example.

关键词： data-driven control second-order sliding mode control tracking error constraint

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An Exoskeleton Robot with More Active Degree of Freedoms and Larger Range of Motion for Hand Rehabilitation 9

An Exoskeleton Robot with More Active Degree of Freedoms and...

引用

9th ieee International conference on Advanced Robotics and Mechatronics (ICARM)

作者： Sun, Xijin Liu, Mengqi Sun, Mingze Sun, Ning Li, Ke Shandong Univ Sch Control Sci & Engn Inst Intelligent Med Engn Jinan 250061 Peoples R China Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China

ISBN: (纸本)9798350385731;9798350385724

Exoskeleton robots are a useful technique for hand rehabilitation. Most current exoskeleton robots have low active degrees of freedoms (DOFs) and confined range of motion (ROM), which may constrain the hand dexterity and motion area for rehabilitation. this study aimed to develop a novel exoskeleton robot with more active DOFs and larger ROM for hand rehabilitation. the novel exoskeleton robot was designed with 22 DOFs. the mechanical structure of the exoskeleton was optimized by kinematic modeling and optimization problem construction. the ROM was evaluated using extraction of the structure optimized robot motion space envelope. the effect of the novel exoskeleton was examined by an experiment using data of brain tissue oxy-hemoglobin (HbO). this study collected brain tissue HbO concentrations without training and with the assistance of the exoskeleton robot for comparison. Results showed that the ROM of the exoskeleton was improved from 169 cm(3) to 207 cm(3). the mean and maximum concentrations of brain tissue HbO during hand motion driven by the exoskeleton were 0.0429 (mmol/L) *mm and 0.0921 (mmol/L) *mm, respectively. By contrast, the mean and maximum without exoskeleton-assistant motion were -0.0541 (mmol/L) *mm and 0.0138 (mmol/L) *mm, respectively. these results suggested that the brain tissue HbO during exoskeleton-assisted training was notably elevated compared to non-training conditions. this is a preliminary study showing the effectiveness of the novel exoskeleton robot.

关键词： Exoskeleton (Robotics)

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A Noise Mitigation Approach for Improving Position Estimate in Indoor Vehicle Navigation Using Inertial Measurement Unit 9

A Noise Mitigation Approach for Improving Position Estimate ...

引用

9th Indian control conference (ICC)

作者： Vasumathi, R. Kumar, Subhadeep Pasumarthy, Ramkrishna Bhatt, Nirav Indian Inst Technol Madras Dept Elect Engn Robert Bosch Ctr Data Sci & Artificial Intelligen Chennai 600036 India Indian Inst Technol Madras Dept Elect Engn Robert Bosch Ctr Data Sci & Artificial Intelligen Chennai 600036 India Indian Inst Technol Madras Prospect Ctr Excellence Network Syst Learning Con Chennai 600036 India Indian Inst Technol Madras Dept Biotechnol Robert Bosch Ctr Data Sci & Artificial Intelligen Prospect Ctr Excellence Network Syst Learning Con Chennai 600036 India

ISBN: (纸本)9798350395259

Accurate position estimation, especially in indoor environments, presents a formidable challenge despite significant advancements in estimation methodologies. the integration of additional sensors is often imperative to refine estimates, particularly within indoor settings. the choice of additional sensors depends on the specific applications and operational range. this study focuses on devising a position estimation framework utilizing the internal sensors such as the Inertial Measurement Unit (IMU) and wheel encoders within a scaled-down Electric Vehicle. the proposed approach entails a combination of crafting a digital filter and implementing a Kalman filter to effectively attenuate noise and errors in the IMU data, thereby enhancing the position estimate, and the methodology is validated through experiments. this work contributes to the broader discourse on advancing indoor position estimation while bypassing the need for external positioning systems.

关键词： IMU position estimation scaled electric vehicle

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