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第36届中国控制会议

作者： Lan Zhou Jinhua She Changzhong Pan School of Information and Electrical Engineering Hunan University of Science and Technology School of Engineering Tokyo University of Technology School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

This paper concerns disturbance rejection for a repetitive-control system（RCS） with unknown time-varying uncertainties and nonlinearity. The design of the RCS is based on the concept of equivalent input disturbance（EID）. First, an EID estimator is constructed through a state observer with dynamic coefficient matrix that effectively estimates the total effect of the uncertainties and nonlinearity on the output of the plant. Next, a robust globally uniformly ultimately bounded stability condition for the EID-based RCS is derived in the form of a linear matrix inequality. Then, the methods of designing a modified repetitive controller, a state-feedback controller, and an EID estimator are explained. Finally, simulation results demonstrate the validity of the method.

关键词： Repetitive control Equivalent Input Disturbance Disturbance Rejecting Two-dimensional System Linear Matrix Inequality

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Solving Fokker-Planck equation using deep learning

arXiv

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arXiv 2019年

作者： Xu, Yong Zhang, Hao Li, Yongge Zhou, Kuang Liu, Qi Kurths, Jürgen Department of Applied Mathematics Northwestern Polytechnical University Xi’an710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi’an710072 China Department of Engineering Mechanics Northwestern Polytechnical University Xi’an710072 China Center for Mathematical Sciences School of Mathematics and Statistics HuazhongUniversity of Science and Technology Wuhan430074 China Potsdam Institute for Climate Impact Research Potsdam14412 Germany Department of Physics Humboldt University Berlin Berlin12489 Germany

The probability density function of stochastic differential equations is governed by the Fokker-Planck (FP) equation. A novel machine learning method is developed to solve the general FP equations based on deep neural networks. The proposed algorithm does not require any interpolation and coordinate transformation, which is different from the traditional numercial methods. The main novelty of this paper is that penalty factors are introduced to overcome the local optimization for the deep learning approach, and the corresponding setting rules are given. Meanwhile, we consider a normalization condition as a supervision condition to effectively avoid that the trial solution is zero. Several numerical examples are presented to illustrate performances of the proposed algorithm, including one- and two-dimensional systems. All the results suggest that the deep learning is quite feasible and effective to calculate the FP equation. Further, influences of the number of hidden layers, the penalty factors, and the optimization algorithm are discussed in detail. These results indicate that the performances of the machine learning technique can be improved through constructing the neural networks appropriately. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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Sinter Product Rate Forecasting Based on T-S Fuzzy Model 36

Sinter Product Rate Forecasting Based on T-S Fuzzy Model

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第36届中国控制会议

作者： Qi Lei GaiWen Zhao Xin Chen Min Wu School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Through the analysis of sintering process and the relationship between sintering thermal state and sinter product rate, this paper determines the key factors influencing the sinter product rate, and proposes a method of sinter product rate forecasting based on T-S fuzzy model. Based on the extraction of the characteristic parameters of the thermal state of sintering process, the input of the model is determined. Then, the antecedent and the consequent parameters of the forecasting model are identified by the fuzzy c-means(FCM) clustering algorithm and the recursive least squares method(RLS). Finally, the T-S fuzzy model for sinter product rate forecasting is obtained. The proposed forecasting method is of value through the analysis of the forecast ing results. The forecasting results are also compared with the support vector machine(SVM) and the back propagation neural network(BPNN) methods. The results show that the proposed T-S fuzzy model can effectively improve the precision of the sinter product rate forecasting.

关键词： Sinter Product Rate Forecasting T-S Fuzzy Model Fuzzy c-means Recursive Least Squares(RLS)

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Speed control of hydraulic elevator by using PID controller and self-tuning fuzzy PID controller

Speed control of hydraulic elevator by using PID controller ...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Xian Xu Qingling Wang Key Lab of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing China

ISBN: (纸本)9781538629024

Hydraulic elevators are widely used in the world because of their simple structure, smooth running and comfortable ride, This paper presents a conventional PID controller and a self-tuning Fuzzy PID controller to control speed of elevator, their performance are compared by analyzing their step response curves, track-feature, error curves as well as ideal speed response curves. Simulation results show that Fuzzy PID controller has better control performance than the conventional PID controller. The modeling, control and simulation of the elevator system have been done using the software package MATLAB/SIMULINK.

关键词： Hydraulic systems Elevators Niobium Automobiles control systems Fuzzy logic Transfer functions

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Neural Network Adaptive Critic control With Disturbance Rejection 29

Neural Network Adaptive Critic Control With Disturbance Reje...

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第29届中国控制与决策会议

作者： Ding Wang Chaoxu Mu Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences School of Electrical and Information Engineering Tianjin University School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781509046584

A neural-network-based adaptive critic control method is established for continuous-time input-affine uncertain nonlinear systems to achieve disturbance *** present problem can be formulated as a two-player zero-sum differential game and the adaptive critic mechanism is employed to solve the minimax optimization problem.A neural network identifier is developed to reconstruct the unknown dynamical *** optimal control law and the worst-case disturbance law are designed by introducing and training a critic neural *** effectiveness of the present self-learning control method is also illustrated by a simulation experiment.

关键词： Adaptive critic control Adaptive dynamic programming Approximate dynamic programming Disturbance rejection Learning systems Neural networks Nonlinear control

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Adaptive Dynamic Programming Based Decentralized Tracking control for Unknown Large-scale systems 36

Adaptive Dynamic Programming Based Decentralized Tracking Co...

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第36届中国控制会议

作者： Bo Zhao Derong Liu Yuanchun Li Qinglai Wei Ruizhuo Song The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation Guangdong University of Technology Department of Control Science and Engineering Changchun University of Technology School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781538629185

This paper investigates decentralized tracking control（DTC） problem for unknown large-scale systems via adaptive dynamic *** DTC consists of local desired control and local tracking error *** replacing the actual states of coupled subsystems in interconnection terms with their desired states,the norm-boundedness assumption can be *** on local neural network（NN） observers,unknown subsystems can be *** helps to obtain the local desired control with corresponding desired *** establishing a proper local cost function,the local tracking error control is derived via local critic NN and the identified input gain *** the entire error caused by replacement,identification and critic NN approximation,an adaptive robust term is added to construct the robust local cost function that reflects the entire error,regulation and control ***,the asymptotic stability can be guaranteed for the closed-loop tracking system via Lyapunov stability *** demonstrate the effectiveness of the proposed DTC,simulation on a hard spring connected parallel inverted pendulum system is given.

关键词： Adaptive dynamic programming Unknown large-scale systems Decentralized tracking control Neural networks Observer

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Stability and Neimark-Sacker bifurcation analysis for single gene discrete system with delay

Stability and Neimark-Sacker bifurcation analysis for single...

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第37届中国控制会议

作者： Feng Liu Qicheng Mei Fenglan Sun Xinmei Wang Hua O Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Research Center of System Theory and Application Chongqing University of Posts and Telecommunications Department of Mechanical Engineering Boston University

The network structure and functional properties of gene regulatory system and their relationships are an important research field in systems *** this paper,a new improved model is proposed based on the study of gene expression *** model takes into account the effect of protein concentration on the gene expression,so as to obtain a new bifurcation point and improve the performance of the *** validity of the model is verified by theoretical analysis and data simulation.

关键词： Stability Neimark-Sacker bifurcation single gene discrete system delay

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Development of A Customizable Real-time Monitoring System for Networked control systems

Development of A Customizable Real-time Monitoring System fo...

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Chinese control Conference

作者： Haoran Tan Zhiwu Huang Min Wu School of Information Science and Engineering Central South University Changsha P. R. China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan P. R. China

The design and implementation of a monitoring system for networked control systems (NCSs) are introduced in this paper. The monitoring system is developed in the .NET framework using C# according to the C/S architecture which allows the user to monitor network nodes without geographical limitations. The widgets used to display come from the National Instruments (NI) suit and are integrated in the system by reconstructing it. The user is able to design a monitoring interface freely by creating and customizing widgets dynamically. During the monitoring, the display value of the widget is synchronized with parameters and signals of NCSs through receiving data asynchronously from network notes. In particular, all elements of the matrix widely used in NCSs are supported for monitoring. The functionality and feasibility of the designed monitoring system are demonstrated via a networked control experiment. In addition, the saved data can be used in data driven control and model identification.

关键词： Monitoring Graphical user interfaces control systems Communication channels Mice Protocols Real-time systems

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End-to-End Driving Activities and Secondary Tasks Recognition Using Deep Convolutional Neural Network and Transfer Learning

End-to-End Driving Activities and Secondary Tasks Recognitio...

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IEEE Intelligent Vehicles Symposium

作者： Yang Xing Jianlin Tang Hong Liu Chen Lv Dongpu Cao Efstathios Velenis Fei-Yue Wang Advanced Vehicle Engineering Centre Cranfield University JIANGSU XCMG CONSTRUCTION MACHINERY RESEARCH INSTITUTE LTD School of Mechanical and Mechatronics Engineering University of Waterloo State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781538644539

Drivers' decision and their corresponding behaviors are important aspects that can affect the driving safety, and it is necessary to understand the driver behaviors in real-time. In this study, an end-to-end driving-related tasks recognition system is proposed. Specifically, seven common driving activities are identified, which are normal driving, right mirror checking, rear mirror checking, left mirror checking, using in-vehicle video device, texting, and answering mobile phone. Among these, the first four activities are regarded as normal driving tasks, while the rest three are divided into distraction group. The images are collected using a consumer range camera, namely, Kinect. In total, five drivers are involved in the naturalistic data collection. Before training the identification model, the raw images are first segmented using a Gaussian mixture model (GMM) to extract the driver region from the background. Then, a pre-trained deep convolutional neural network (CNN) model is trained to classify the behaviors, which directly takes the processed RGB images as the input and outputs the identified label. In this work, the AlexNet is selected as the pre-trained CNN model. Then, to reduce the training cost, the transfer learning mechanism is applied to the CNN model. An average of 79% detection accuracy is achieved for the seven driving tasks. The proposed integration model can be used as a low-cost driver distraction and dangerous tasks recognition modeL.

关键词： Driver Behavior Religious Missions Transfer (Psychology) Automobile driving driving safety end-to-end Mirrors Drivers Neural network

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Stability Analysis of Discrete T-S Fuzzy systems with Time-Varying Delay Using an Extended Reciprocally Convex Matrix Inequality

Stability Analysis of Discrete T-S Fuzzy Systems with Time-V...

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Chinese control Conference (CCC)

作者： Bi-Ying Chen Fei Long Chuan-Ke Zhang Yong He Hui-Qin Xiao Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China College of Electrical and Information Engineering Hunan University of Technology Zhuzhou P. R. China

This paper concerns the stability analysis of discrete Takagi-Sugeno fuzzy systems with time-varying delays. A suitable Lyapunov-Krasovskii functional is constructed, and an extended reciprocally convex matrix inequality is used to estimate the forward difference of the functional. As a result, a less conservative stability criterion is obtained. Finally, a numerical example is given to demonstrate the advantage of the proposed method.

关键词： Delays Linear matrix inequalities Fuzzy systems Time-varying systems Stability criteria Symmetric matrices

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