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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1-10 订阅

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Proceedings of 2020 ieee 9th data driven control and learning systems conference, ddcls 2020

Proceedings of 2020 IEEE 9th Data Driven Control and Learnin...

引用

9th ieee data driven control and learning systems conference, ddcls 2020

ISBN: (纸本)9781728159225

the proceedings contain 252 papers. the topics discussed include: trajectory tracking of a quadrotor UAV based on high-order differential feedback control;nonsingular terminal sliding mode control for PMLSM based on disturbance observer;iterative learning control algorithm of consensus for discrete-time heterogeneous multi-agent systems with independent topologies;a method for analyzing the state controllability of linear discrete timevarying time-delay systems;state of charge estimation for lithium-ion batteries based on adaptive fractional extended kalman filter;data analysis and practical strategies on opioid crisis;a finite time neural network model for solving time-varying matrix inequality problem;a quality-related fault detection method based on weighted mutual information;and an edge-cloud synergy integrated security decision-making method for industrial cyber-physical systems.

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BDS/GPS data Fusion Based on McDE-PF for Aircraft Positioning and Navigation 9

BDS/GPS Data Fusion Based on McDE-PF for Aircraft Positionin...

引用

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

作者： Xue, Guangyue China Transport Telecommun & Informat Ctr Beijing 100011 Peoples R China

ISBN: (纸本)9781728159225

A novel data fusion based on McDE-PF (particle filter integrated with memetic compact differential evolution) is proposed for aviation positioning and navigation application by fusing BDS/GPS positioning data. McDE-PF is used as the local filter to process the measurements from the GNSS receivers. the flight test practical data is used to validate the effectiveness of the fusion method, Comparative simulation and experiment studies confirm the validity of the presented method.

关键词： McDE-PF GNSS BDS/GPS data Fusion

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Function Projective Synchronization of Neutral Complex Dynamic Network with Unknown Time-varying Coupling Strength 9

Function Projective Synchronization of Neutral Complex Dynam...

引用

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

作者： Yang, Ying Li, Junmin Xidian Univ Sch Math & Stat Xian 710071 Peoples R China

ISBN: (纸本)9781728159225

this paper addresses the function projective synchronization control for a class of neutral complex dynamic network with nonlinear coupling strength and unknown time-varying parameters. An adaptive controller is designed for neutral complex network with time-varying coupling strength. In addition, a sufficient condition is given to guarantee the function projective synchronization of complex dynamic networks. the simulation example demonstrates the proposed method.

关键词： Complex dynamic network function projective synchronization nonlinear coupling adaptive control

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data-driven Nearly Optimal control for Constrained Nonlinear systems 9

Data-Driven Nearly Optimal Control for Constrained Nonlinear...

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

作者： Yang, Xiong Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China

ISBN: (纸本)9781728159225

this article develops a novel data-driven policy iteration (PI) to obtain nearly optimal control of nonlinear systems with asymmetric input constraints. the data-driven PI is derived from an early established model-based PI. Owing to the datadriven PI sharing the same solution as the model-based PI, the convergence of the data-driven PI algorithm is guaranteed. the implementation of the newly developed data-driven PI algorithm relies on an actor-critic structure consisting of two kinds of neural networks (NNs). Specifically, the critic NN aims at estimating the value function and the actor NNs aim at approximating the control policies. the weight parameters used in the critic and actor NNs are determined via the least squares method together with the Monte Carlo integration technique. Finally, a nonlinear plant is provided to validate the proposed data-driven PI algorithm.

关键词： Asymmetric constraint data-driven control Optimal control policy Reinforcement learning

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Robust Adaptive Repetitive control of Robotic Manipulators 9

Robust Adaptive Repetitive Control of Robotic Manipulators

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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 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...

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

Variable Gain Accurate Differential Compensation Control for...

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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

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

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

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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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data-driven Backstepping control of Chemical Process 9

Data-Driven Backstepping Control of Chemical Process

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

作者： Gao, Jiawen Huang, Jingwen Beijing Univ Chem Technol Beijing 100029 Peoples R China

ISBN: (纸本)9781728159225

Modeling and control design of complex chemical processes are challenge tasks because of their multi-variable, time-delay and non-linear features. On the other hand, the plant dynamics are hard to characterize precisely on line when facing uncertain disturbance. In the light of this, this paper presents a data-driven backstepping control scheme for the nonlinear chemical process. Compared with other regular chemical process control schemes, the proposed scheme is independent of specific mathematical models, and free of decoupling operation, linearization, or off-line recognition and modeling. By constructing Lyapunov function and feedback control rate based on real-time data, the integral stability is guaranteed. Williams-Otto reactor example is provided to demonstrate the effectiveness and applicability of the scheme.

关键词： data-driven Backstepping control Chemical Process Williams-Otto Reactor

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