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第43届中国控制会议

作者： Jiongzhi Qiu Yiming Fang Donliang Zhao Le Liu Nuan Shao Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Department of Environmental Engineering Hebei University of Environmental Engineering

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

To solve the trajectory tracking control problem of a rigid manipulator system in the case of unexpected actuator failure,considering the uncertainty of system parameters and bounded disturbance,an adaptive fault-tolerant tracking control strategy is proposed in this ***,an adaptive strategy is designed to estimate and compensate the effects of actuator failure and system uncertainty,and the dynamic regression matrix is extended and mixed to improve the accuracy of parameter estimation without persistency of excitation(PE),which will enhance the trajectory tracking ***,in the framework of sliding mode fault-tolerant control,combined with standard Gradient Adaptive and Dynamic Regressor Extension(GA-DRE) parameter estimation technology,a composite adaptive fault-tolerant controller is ***,theoretical analysis and numerical simulation results show that the proposed method can perform accurate parameter estimation in a finite time under the premise of matching the new conditions based on DRE additional terms,and the trajectory tracking errors of the expected positions and velocities of each joint of the manipulator can asymptotically converge to zero.

关键词： Fault-tolerant control Gradient Adaptive and Dynamic Regressor Extension(GA-DRE) Manipulator Parameter estimation Persistence of excitation(PE)

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A PD-Type Iterative Learning Algorithm for Networked control Systems with Missing Data

A PD-Type Iterative Learning Algorithm for Networked Control...

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作者： Xiaoyan Cheng Hongbin Wang Qinzhao Wang Yahui Dong the Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Weapon and Control Department Army Academy of Armored Forces

In this paper,a PD-type iterative learning control method is proposed for a class of nonlinear discrete networked control systems with measurement signal and control signal data *** and differential items of the error signal are employed in this method to modify the current control signal,which takes full advantage of the historical error *** data dropout is described as a stochastic and independent Bernoulli process with a given *** addition,the zero-order holding method is introduced at the data receivers of the controller and ***,the stability analysis and simulation results are performed to verify the convergence and effectiveness of the proposed method.

关键词： siterative learning control networked control systems data dropout nonlinear system

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Super-twisting Finite Time control for Third Order Nonlinear Systems

Super-twisting Finite Time Control for Third Order Nonlinear...

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第40届中国控制会议

作者： Xinjian Liu Jianxiong Li Zhi Li Yiming Fang Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment The Key Lab of Industrial Computer Control Engineering of Hebei Province

A novel super-twisting control method is proposed for a class of third-order systems with matched Lipschitz disturbance in this paper. The proposed method ensures finite-time convergence to the fourth-order sliding set, by using a homogeneous, continuously differentiable and strict Lyapunov function. Finally, numerical simulation results are shown to illustrate the effectiveness of the proposed method.

关键词： Third-order sliding mode Super-twisting algorithm Finite time control

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Fuzzy Q-learning obstacle avoidance algorithm of humanoid robot in unknown environment

Fuzzy Q-learning obstacle avoidance algorithm of humanoid ro...

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第37届中国控制会议

作者： Shuhuan Wen Jianhua Chen Zhen Li Ahmad B.Rad Kamal Mohammed Othman the Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University the school of Engineering Sciences Simon Fraser University

This paper proposes a fuzzy Q-learning(FQL)algorithm to solve the problem of the robot obstacle avoidance in unknown *** algorithm is used to localize the position of the *** Q-learning algorithm,optimized Q-learning algorithm,FQL algorithm are *** simulation results show that FQL algorithm has a faster learning speed than other two algorithms and the results demonstrate that the fuzzy Q-learning obstacle avoidance algorithm is effective.

关键词： FASTSLAM fuzzy logic control path planning obstacle avoidance Q-learning

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Robust predictive control for a class of uncertain discrete system with multiple state delays

Robust predictive control for a class of uncertain discrete ...

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Chinese control Conference (CCC)

作者： Jun-Cheng Zhao Yi-Ming Fang Jian-Xiong Li Key Lab of Industrial Computer Control Engineering of Hebei Province College of Electric Engineering Yanshan University Qinhuangdao 066004 China

A robust predictive control algorithm based on memory state feedback is proposed for a class of uncertain discrete time system with input constraint and multiple state delays. By introducing Lyapunov-Krasovskii function and using linear matrix inequality (LMI) method, the algorithm can convert the infinite time domain optimization problems into linear programming problems. Sufficient conditions of the existence and explicit expression for the memory state feedback controller are obtained, and the control input can satisfy constraint as well. Asymptotical stability of the closed-loop system and minimum of robust performance index can be guaranteed simultaneously. Finally, the simulation results illustrate the effectiveness of the proposed algorithm.

关键词： Robustness Predictive control Predictive models Delay Mathematical model State feedback Prediction algorithms

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YOLO-MFE: towards more accurate object detection using multiscale feature extraction 6

YOLO-MFE: towards more accurate object detection using multi...

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6th International Conference on Intelligent Computing, Communication, and Devices, ICCD 2023

作者： Li, Hui Yin, Zhenyu Fan, Chao Wang, Xiaohui School of Computer Science and Technology Shenyang University of Chemical Technology Shenyang110142 China Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China Liaoning Key Lab. of Domestic Industrial Control Platform Technology on Basic Hardware and Software Shenyang110168 China

ISBN: (数字)9781510666269

ISBN: (纸本)9781510666252

YOLOv3, as a multi-scale object detection algorithm, has a simple structure and can be detected quickly. However, during the training process, as the bottom convolutional layer contains more object detail, and the information in the underlying layer will be gradually faded out through continuous convolution. To address this, this paper adds a normalized attention mechanism behind the feature layers at different scales to further suppress insignificant features and enhance the discriminability and robustness of the features. Moreover, an improved pyramid structure is leveraged to fuse the detail of the shallow feature maps with the semantic feature information of the higher layers, aiming to improve the model performance. In particular, a YOLOv3 object detection algorithm named YOLO-MFE based on improved multi-scale feature extraction is proposed. Experimental results on the Pascal VOC dataset demonstrate that our algorithm outperforms the original YOLOv3 algorithm in terms of object detection accuracy, with a mAP on the Pascal VOC 2007 test set that is 1.66% higher. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Object detection

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Robust adaptive control for hydraulic servo position system with unmatched uncertainties

Robust adaptive control for hydraulic servo position system ...

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Chinese control Conference (CCC)

作者： Ru Chang Yi-Ming Fang Zhi-Jie Wang Hai-Bo Tian Key Lab of Industrial Computer Control Engineering of Hebei Province College of Electric Engineering Yanshan University Qinhuangdao 066004 China

To deal with the problems caused by unmatched uncertainties and external load disturbance exist in mill hydraulic servo position system, a robust adaptive controller design method is presented in this paper. The controller is composed of a state feedback controller and an adaptive compensator, the state feedback controller is obtained by solving a Riccati equation, and the compensator is obtained by estimating the upper bounds of the unknown external disturbances. It is proved that the global asymptotic stability of the resulting closed-loop system can be guaranteed. Finally, simulation results for the mill hydraulic servo position system illustrate the validity of the proposed algorithm.

关键词： Robustness Servomotors Backstepping Adaptive control Uncertainty

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Robust stabilization of nonlinear uncertain systems by dynamic output feedback

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ICIC Express Letters 2011年第7期5卷 2293-2298页

作者： Li, Jianxiong Fang, Yiming Shi, Shengli Chang, Ru Key Lab of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University No. 438 Hebei Street Qinhuangdao 066004 China

This paper proposes a constructive way to design dynamic output feedback control law to stabilize a class of nonlinear systems with unknown control coefficients. The unknown parameters are described in polytopic forms, and control parameter matrices of the dynamic controller are obtained by solving series of linear matrix inequalities in sequence. It is shown that the robust asymptotic stability of closed-loop system can be guaranteed by the proposed method. Finally, a numerical example illustrates the effectiveness of the proposed algorithm. © 2011.

关键词： Nonlinear systems

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Hydraulic System Reliability Modelling and Analysis Based on Convex Model Bayesian Network

Hydraulic System Reliability Modelling and Analysis Based on...

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2015 International Conference on Fluid Power and Mechatronics

作者： Dongning Chen Yuliang Zhang Chengyu Yao Shijun Lv Key Lab of Heavy Machinery Fluid Power Transmission and Control of Hebei Province Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

Compared with the probabilistic method, the nonprobabilistic convex model only requires a small number of samples and experiences to obtain the variation bounds of the ambiguous and imprecise parameters, and whereby makes the reliability analysis very convenient. In this paper, hydraulic lifting system reliability model is established and the reliability of the system is analyzed by convex model Bayesian network, then the reliability indices are described in the form of interval parameters. Using ellipsoid model to constrain interval model, the more accurate reliability indices are obtained. Finally the convex model Bayesian network is compared with traditional Bayesian network. All the reliability indices obtained by convex model Bayesian network provide the basis for condition-based maintenance, fault diagnosis and reliability design.

关键词： reliability analysis hydraulic system Bayesian network convex model

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Hydraulic System Reliability Modelling and Analysis Based on Convex Model Bayesian Network

Hydraulic System Reliability Modelling and Analysis Based on...

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International Conference of Fluid Power and Mechatronics

ISBN: (纸本)9781479987719

Compared with the probabilistic method, the non-probabilistic convex model only requires a small number of samples and experiences to obtain the variation bounds of the ambiguous and imprecise parameters, and whereby makes the reliability analysis very convenient. In this paper, hydraulic lifting system reliability model is established and the reliability of the system is analyzed by convex model Bayesian network, then the reliability indices are described in the form of interval parameters. Using ellipsoid model to constrain interval model, the more accurate reliability indices are obtained. Finally the convex model Bayesian network is compared with traditional Bayesian network. All the reliability indices obtained by convex model Bayesian network provide the basis for condition-based maintenance, fault diagnosis and reliability design.

关键词： Reliability analysis Hydraulic system Bayesian network Convex model

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