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2018 Annual American control Conference, ACC 2018

作者： Fletscher, L.A. Barreiro-Gomez, J. Ocampo-Martinez, C. Maestre, J.M. Valencia Peroni, C. Facultad de Ingeniería Universidad de Antioquia UdeA Departamento de Ingeniería Electrónica y Telecomunicaciones Medellín Colombia New York University Abu Dhabi Learning Game Theory Laboratory United Arab Emirates Automatic Control Department Barcelona Spain School of Engineering Universidad de Sevilla System Engineering and Automation Department Seville Spain Universidad Nacional de Colombia Process and Energy Department Medellín Colombia

ISBN: (纸本)9781538654286

In this paper, a distributed control scheme based on population games is proposed. The controller is in charge of dealing with the energy consumption problem in a Heterogeneous Cellular Network (HetNet) powered by hybrid energy sources (grid and renewable energy) while guaranteeing appropriate quality of service (QoS) level at the same time. Unlike the conventional approach in population games, it considers both atomicity and non-anonymity. Simulation results show that the proposed population-games approach reduces grid consumption by up to about 12% compared to the traditional best-signal level association policy. © 2018 AACC.

关键词： Games Energy consumption Sociology Statistics Base stations Cellular networks Optimization"

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Fuzzy-based Tracking controller Design for Autonomous Underwater Vehicle 36

Fuzzy-based Tracking Controller Design for Autonomous Underw...

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第36届中国控制会议

作者： Hongjun Ban Xian Yang Xiaoyuan Luo Jing Yan Xinping Guan Institute of Electrical Engineering Yanshan University Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China Institute of Information Science and Engineering Yanshan University

ISBN: (纸本)9781538629185

Autonomous Underwater Vehicle（AUV） is referred as a promising device to extend human intelligences to harsh underwater *** applications of AUV demand accurate trajectory tracking,however the nonlinear and model inaccuracy constraints on AUV make it challenging to achieve tracking *** this paper,we are concerned with the trajectory tracking problem for *** AUV is assumed to be auto navigated in surge,sway,heave and *** first give the 4-DOF mathematical model of ***,the tracking control problem is formulated into T-S fuzzy *** on this,T-S fuzzy-based position and head controllers,which depend on the relative state errors between the AUV and reference,are designed for AUV to achieve the trajectory tracking ***,simulation results are presented to show the effectiveness of the proposed tracking controllers,wherein the influence of chattering problem can be reduced by compared with SMC-based controller.

关键词： Autonomous underwater vehicle（AUV） tracking target fuzzy underwater

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Preventive Soot Blowing Strategy Based on State of Health Prediction for Coal-fired Power Plant Boiler

Preventive Soot Blowing Strategy Based on State of Health Pr...

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Chinese control Conference (CCC)

作者： Yuanhao Shi Jie Wen Xiaoqiong Pang Jianfang Jia Fangshu Cui Jianchao Zeng Jingcheng Wang North University of China School of Electrical and Control Engineering Taiyuan China North University of China School of Computer Science and Technology Taiyuan China Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China

This paper seeks the optimization of soot-blowing operations for heat transfer surfaces in coal- fired power plant boiler. A preventive soot blowing strategy based on state of health prediction for heat transfer surface was proposed. The average state of health of heat transfer surface was forecasted as the threshold to draft preventive soot blowing strategy. According to the theory of renewal process, an optimization model with the system prediction interval and the threshold of preventive soot blowing operation as the optimization variables and minimize average energy losses as the target function was established. By using Particle Swarm Optimization (PSO), the optimal preventive cycle and soot-blowing threshold were obtained, and the long-run average cost rate was the lowest. The model is validated with experiment data of a 300MW coal-fired power plant boiler and the parameters of prediction model are obtained. The results can verify the feasibility of proposed strategy. It can be used as the guide for the optimization of soot blowing in coal-fired power plant to improve the energy conservation level.

关键词： Thermal engineering Radio frequency Coal Combustion Heat engines Heat transfer

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Adaptive Fault-tolerant Output Feedback control of Uncertain Nonlinear systems with Unknown High-frequency Gain Sign 29

Adaptive Fault-tolerant Output Feedback Control of Uncertain...

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第29届中国控制与决策会议

作者： Chuanjing Hou Lisheng Hu Dept.of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information ProcessingMinistry of Education of China School of Information and Electrical Engineering Shandong Jianzhu University

ISBN: (纸本)9781509046584

This article develops an adaptive control method for accommodating actuator faults in a class of unknown nonlinear systems without a priori knowledge of high-frequency *** adaptive high-gain K-filters with switching laws is proposed to suppress the nonlinearities which are dependent on the unmeasured *** the Nussbaumgain approach with backstepping design,an adaptive controller with high-gain function can be *** is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are bounded and tracking error can be made as small as desired by appropriate choice of the design *** results are presented to show the effectiveness of the proposed scheme.

关键词： Actuator failures K-filters Nonlinear systems Nussbaum-gain

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Design of Modular Humanoid Rehabilitation Robot for Apoplectic Hemiplegia 29

Design of Modular Humanoid Rehabilitation Robot for Apoplect...

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第29届中国控制与决策会议

作者： Shuai Li Jian Li Siqi Li Guodong Li Yu Mu The Bionic Robot and System Key Laboratory School of Mechatronical EngineeringBeijing Institute of Technology Key Laboratory for Intelligent Control and Decision on Complex Systems School of AutomationBeijing Institute of Technology

ISBN: (纸本)9781509046584

Stroke is mainly caused by the brain damage due to the acute cerebral vascular disease and its primary disease,which can make upper limb or lower limb on one side of the body *** rehabilitation training is the most effective way to regain the Activities of Daily Living(ADL).Based on the concept of humanoid and modular design,this paper outlines the design process of humanoid ***,kinematics and dynamics are calculated in different coordinate frames,which makes simulation and control algorithms are more complex and not intuitive,for the forked-tree structure rehabilitation robot,a modified geometric description method of DH parameters is proposed to solve the problem of inconsistent frames,the whole body Jacobian matrix of this structure is derived and used for the inverse kinematics,and the singular configurations of redundant manipulator are *** important design criteria of humanoid robot is discussed,and the realization of the mechanical design is ***,the experimental results show that the humanoid robot can effectively carry out multiple parts rehabilitation training.

关键词： Rehabilitation Robot Humanoid robot Modularity Singularity Geometric Representation

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A novel fault classification method based on neural network in smart grid

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International Journal of Electrical engineering 2018年第1期25卷 1-7页

作者： Zhang, Tong Sun, Lanxiang Liu, Jianchang Yu, Haibin College of Information Science and Engineering Northeastern University Shenyang China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control System CAS Shenyang China University of Chinese Academy of Sciences Beijing China

This paper presents a back propagation (BP) neural network method to identify fault types and phases in the smart grid with renewable sources. A fault classification method based on the BP neural network is used to identify patterns of voltage and current measured with phasor measurement unit (PMU). The voltage and current values are decomposed, and then they are used as the input matrix of the BP neural network, which identifies the fault type and fault phasor. All the common short-circuit faults occurred are analyzed, BP neural network method is proposed for fault classification in a power active distribution network. Simulation results show feasibility and usefulness of the BP neural network method, which provides good classification performances.

关键词： Smart power grids

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Trajectory Planning of Quadrotor UAV with Suspended Payload Based on Predictive control

Trajectory Planning of Quadrotor UAV with Suspended Payload ...

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第37届中国控制会议

作者： Binghan Sun Chaofang Hu Lei Cao Na Wang Yimin Zhou School of Electrical and Information Engineering Tianjin University Key Laboratory of Micro Opto-electro Mechanical System Technology Tianjin UniversityMinistry of Education Key Laboratory of System Control and Information Processing Ministry of Education School Engineering and Automation Tianjin Polytechnic University Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences

In the work of data collection,express transportation and rescue by UAV,we generally use UAVs to move the suspended payload in flight *** is fully necessary to study how to effectively suppress the swing of the suspended load and avoid known *** this paper,the kinematic equations of the quadrotor UAV and suspended payload in the three-dimensional space are analyzed.A trajectory planning method based on predictive control is proposed,and the cost function considering load swing angle and the distance between obstacle and UAV is designed and generate an optimal trajectory that meets the *** simulation results show that the proposed method can achieve the purpose of minimizing the swing angle and avoid the obstacles at the level of trajectory planning.

关键词： quadrotor UAV suspended load predictive control trajectory planning

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Soft-Sensing Estimation of Optical Density for PHA Production Using Multilayer Perceptron Neural Network

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Journal of Physics: Conference Series 2020年第1期1532卷

作者： Nor Hana Mamat Samsul Bahari Mohd Noor Azura Che Soh Farah Saleena Taip Ahmad Hazri Ab. Rashid Nur Liyana Jufika Ahmad Ishak Mohd Yusof Adida Zuraida Mohamad Control System and Signal Processing Research Centre Department of Electrical & Electronic Engineering Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor. Faculty of Electrical and Automation Engineering Technology TATI University College Teluk Kalong 24000 Kemaman Terengganu. Food and Process Department Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor. Industrial Biotechnology Research Centre SIRIM Berhad Persiaran Dato' Menteri Seksyen 2 40700 Shah Alam Selangor.

Biomass concentration is an important indicator of production rate in polyhydroxyalkanoates (PHA) fermentation process. In current practice, measurement of biomass concentration is done off-line by laboratory analysis that is unsuitable for online process monitoring and control. Soft-sensor is often used as an alternative that provides an estimate of hard to measure parameters from easy to measure process data. However, most of these studies use simulated data or data generated from mathematical model that was developed without full consideration of process and measurement uncertainty. In this study, a soft-sensor is developed from real production data for PHA fermentation in pilot-scale bioreactor with the appropriate data pre-processing techniques applied to process data that was obtained from this system. Multilayer perceptron (MLP) neural network is used to estimate biomass concentration using secondary process parameters such as dissolved oxygen (DO), temperature, pH and agitation speed as inputs. Different models are developed based on different batches of production data and various network architecture in order to study the appropriate integration of process data and network topology that gives the best model accuracy. Results indicate that the biomass soft-sensor developed using MLP-ANN provides a better estimate of biomass in comparison to radial basis function (RBF) neural network and support vector regression (SVR) methods. The developed soft-sensor can be further used in monitoring and control of production output.

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Semi-Global Output Containment control of Linear Multi-agent systems with Actuator Saturation

Semi-Global Output Containment Control of Linear Multi-agent...

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第37届中国控制会议

作者： Liangren Shi Zongli Lin Student Innovation Center and Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information Processing of the Ministry of Education Charles L. Brown Department of Electrical and Computer Engineering University of Virginia

In this paper, we study the semi-global output containment control problem of a multi-agent system in the presence of actuator saturation over a directed network. The leader and follower agents are of different dynamics, and the follower agents are affected by disturbances generated by the leader agents through directed paths in the communication topology. The control objective of the output containment control is to drive the output trajectories of the follower agents to converge to the convex hull spanned by the outputs of the leader agents in the presence of disturbances. Low gain feedback containment protocols are constructed based on the output regulation approach and distributed observers. It is shown that semi-global output containment control can be achieved by the proposed protocols, if each follower agent is connected to at least one leader agent through a directed path in the communication topology. Simulation results verify the theoretical conclusions.

关键词： Multi-agent systems output containment control output regulation low gain feedback actuator saturation

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A Cooperative Route Planning Method for Multi-UAVs Based-on the Fusion of Artificial Potential Field and B-spline Interpolation

A Cooperative Route Planning Method for Multi-UAVs Based-on ...

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Chinese control Conference (CCC)

作者： Wenbin Bai Xiande Wu Yaen Xie Yu Wang Han Zhao Kefan Chen Yong Li Yong Hao College of Aerospace and Civil Engineering Harbin Engineering University Harbin China College of Automation Harbin Engineering University Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Qian Xuesen Laboratory of Space Technology Beijing China

This paper deals with the route planning problem for multi-UAVs formation. It provides a method of improved artificial potential field by introducing a longitudinal random factor and B-spline interpolation. The longitudinal random factor is used to solve the problem of falling into local minimum, when the B-spline interpolation is used to smooth the planned route. The simulated results show that the proposed method can solve the route planning problem of multi-UAVs.

关键词： Planning Force Space missions Splines (mathematics) Interpolation Heuristic algorithms Unmanned aerial vehicles

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