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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31-40 订阅

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Observer-based Optimal Adaptive control for Multi-motor Driving Servo System 9

Observer-based Optimal Adaptive Control for Multi-motor Driv...

引用

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

作者： Hu, Shuangyi Ren, Xuemei Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

ISBN: (纸本)9781728159225

In this paper, an improved optimal sliding mode control strategy is proposed for multi-motor driving servo system. Some states of multi-motor drive system are not measurable and there exists unknown nonlinearity. To solve this problem, the disturbance observer and extended state observer are both applied to estimate the unknown states and nonlinearity. Based on optimal control theory, the optimal sliding surface is selected to guarantee the optimal dynamic performance of the sliding mode of the system. the effectiveness of designed control methods is illustrated by simulation results.

关键词： Disturbance observer Extended state observer Optimal sliding surface Multi-motor driving servo system

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Active disturbance rejection control for a quadrotor UAV 9

Active disturbance rejection control for a quadrotor UAV

引用

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

作者： Wang, Zhikai Huang, Deqing Huang, Tianpeng Qin, Na Southwest Jiaotong Univ Sch Elect Engn Chengdu 611756 Peoples R China

ISBN: (纸本)9781728159225

the design of robust tracking control for a quadrotor is an important and challenging problem nowadays. In the paper, an active disturbance rejection control (ADRC) technique is developed for attitude and altitude tracking of a quadrotor unmanned aerial vehicle (UAV) system subject to external disturbances. the nonlinear dynamics model of quadrotor is first obtained by Newton-Euler formula. then, the control law, consisting of tracking differentiator (TD), extended state observers (ESO) and state error feedback (SEF) is designed. Finally, numerical simulations and experimental tests are conducted to illustrate the effectiveness of the proposed control strategy

关键词： Quadrotor active disturbance rejection control disturbance experiment

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Robust Adaptive control for DC-DC Buck Converters with Load Fluctuation 9

Robust Adaptive Control for DC-DC Buck Converters with Load ...

引用

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

作者： Yang, Cheng-Wei Jin, Xiao-Zheng HeFei Univ Technol Sch Elect Engn & Automat Hefei 230000 Peoples R China Qilu Univ Technol Sch Comp Sci & Technol Shandong Acad Sci Jinan 250353 Peoples R China

ISBN: (纸本)9781728159225

this paper mainly develops a robust adaptive tracking control scheme to counter effects caused by load fluctuation and external disturbances. An adaptive controller based on appropriate control strategy and adaptive law is presented based on Lyapunov stability theory. the output voltage asymptotic tracking of the buck converters is obtained even under the influence of load fluctuation and external disturbances. Simulation results also reveal the availability of the proposed adaptive control scheme.

关键词： DC-DC buck converter adaptive control load fluctuation

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A Deep Reinforcement learning Approach to the Flexible Flowshop Scheduling Problem with Makespan Minimization 9

A Deep Reinforcement Learning Approach to the Flexible Flows...

引用

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

作者： Zhu, Jialin Wang, Huangang Zhang, Tao Tsinghua Univ Dept Automat Beijing 100036 Peoples R China

ISBN: (纸本)9781728159225

Recent work has demonstrated the efficiency of deep reinforcement learning (DRL) in making optimization decisions in complex systems. Compared with other DRL algorithms, the proximal policy optimization (PPO) has higher stability and lower complexity. the typical flexible flowshop scheduling problem (FFSP) with identical parallel machines is an NP-hard problem. this paper is the first case to utilize PPO to solve the problem with makespan minimization. the particular state, action and reward function are designed for the FFSP to follow the Markov property. the efficiency of PPO is evaluated on the wafer pickling instance and random instances with different scales. the results show that PPO can always provide satisfactory solutions within a reasonable computational time.

关键词： Deep Reinforcement learning Proximal Policy Optimization Flexible Flowshop Scheduling Makespan

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Adaptive NN Finite-Time Tracking control for PMSM with Full State Constraints 9

Adaptive NN Finite-Time Tracking Control for PMSM with Full ...

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

作者： Yang, Jin-Zi Li, Yuan-Xin Liaoning Univ Technol Coll Informat Coll Sci Jinzhou 121001 Peoples R China

ISBN: (纸本)9781728159225

this paper proposes a finite-time adaptive tracking control scheme for permanent magnet synchronous motors (PMSM) with full state constraints. In order to deal with full state constraints, the nonlinear transformation function is first introduced to transform the constraint problem into a non-constraint problem. then, we will provide a tracking differentiator that get the differentiation of the virtual control laws. At the same time, the neural networks (NN) are employed to approximate unknown nonlinearities. Finally, simulation results are given to validate the proposed control scheme.

关键词： Backstepping design adaptive neural control PMSM full-state constraints finite-time

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A Multi-Label Method of State Partition and Fault Diagnosis Based on Binary Relevance Algorithm 9

A Multi-Label Method of State Partition and Fault Diagnosis ...

引用

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

作者： Li, Fengying Ma, Xin Wang, Youqing Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China Shandong Univ Sci & Technol Qingdao 266590 Shandong Peoples R China

ISBN: (纸本)9781728159225

Prognostics and health management (PHM) is an important topic of rolling bearing, so partition of healthy stage and different degree of fault states are equally important as fault types. this study uses a multi-label learning method, Binary Relevance (BR) algorithm, for fault diagnosis of bearing data based on both of states partition and fault types judgment. the Binary Relevance algorithm simplifies the classification process by transforming the multi-classification problem into multiple binary classification problems. Using extreme learning machine ensures the classification speed and effect. By comparative experiments on XJTU-SY bearing datasets, the effectiveness of our method is proved to be superior.

关键词： Multi-label learning Binary Relevance state partition fault diagnosis

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Finite-Time Annular Domain Stability and Stabilization of Discrete-Time Stochastic systems 9

Finite-Time Annular Domain Stability and Stabilization of Di...

引用

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

作者： Yan, Zhiguo Lv, Qingfeng Hu, Guolin Du, Mingjun Qilu Univ Technol Shandong Acad Sci Sch Elect Engn & Automat Jinan 250353 Peoples R China Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China

ISBN: (纸本)9781728159225

this paper discusses the problems of the finite-time annular domain stability (FTAD-stability) and stabilization of discrete-time stochastic systems (DTSS). First, a definition of FTAD-stability for DTSS is given and a stability criterion is also proposed. Second, we respectively give some sufficient conditions for the existence of state feedback controller (SFC), static output feedback controller (SOFC) and dynamic output feedback controller (DOFC). Finally, a numerical example is utilized to show the effectiveness of proposed method.

关键词： Discrete-time stochastic systems finite-time stability (FTS) linear matrix inequality (LMI)

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Fault Diagnosis of Wind Motor based on Convolutional Neural Network 9

Fault Diagnosis of Wind Motor based on Convolutional Neural ...

引用

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

作者： Liu, Xinyang Wang, Yakun Yin, Hui Wang, Zhenhua Shen, Yi Harbin Inst Technol Sch Astronaut Harbin 150001 Peoples R China

ISBN: (纸本)9781728159225

this paper studies the fault diagnosis of wind motors, which is an important way to improve the safety and reliability of wind motors. It is non-trivial to extract the fault features from the original vibration signals by the traditional methods. We propose a novel method to improve the fault diagnosis performances of wind motors. First, the Wigner-Ville distribution method is used to generate the time-frequency images of the vibration signals in different speed ranges of the motor, which is helpful for fault features extraction. then, we use the convolutional neural network, an important tool in the field of deep learning, to extract the fault features from the time-frequency images. Finally, simulation results based on the measurement data of an actual wind motor are provided to demonstrate the effectiveness of the proposed method.

关键词： wind motor time-frequency deep learning convolutional neural network fault detection

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RRT Based Obstacle Avoidance Path Planning for 6-DOF Manipulator 9

RRT Based Obstacle Avoidance Path Planning for 6-DOF Manipul...

引用

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

作者： Han, Ben Liu, Shan Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China

ISBN: (纸本)9781728159225

Obstacle avoidance path planning is an important research topic in robot operation. As a complex system with multiple inputs and multiple outputs, highly nonlinear and strong coupling, the manipulator cannot be directly regarded as a particle in Cartesian space, so many path planning algorithms for mobile robots cannot be directly extended to manipulators. In this issue, based on the rapidly-exploring random tree algorithm, this paper proposed an improved path planning method. the path is searched in the joint space of the manipulator, collision detection is performed in Cartesian space by solving forward kinematics, and then the Bezier curve is used to smooth the path. the experimental results indicate that the proposed method can effectively plan a smooth, collision-free and less expensive path.

关键词： Manipulator Path Planning Obstacle Avoidance Bezier Curves

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data driven control for a Class of Nonlinear systems with Stochastic Fading Channels 9

Data Driven Control for a Class of Nonlinear Systems with St...

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

作者： Yu, Wei Bu, Xuhui Yin, Yanling Liang, Jiaqi Henan Polytech Univ Sch Elect Engn Jiaozuo 454000 Henan Peoples R China

ISBN: (纸本)9781728159225

this paper investigates the data driven model free adaptive control (MFAC) problem for a class of non-affine nonlinear systems with stochastic fading channels. Firstly, the phenomenon of signal fading is regarded as an independent stochastic process occurring at the output side, which has known mathematical expectations. Using an innovative linearization method, the considered non-affine system is converted into a linear model with a time-varying parameter called PPD and the MFAC controller is redesigned by utilizing the faded outputs. the stability of the system is analyzed rigorously and the influence of incomplete signal transmission on system convergence is explored. Finally, a numerical example shows the validity of the presented strategies.

关键词： data driven model free adaptive control fading channels stability analysis

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