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2018 IEEE Industry Applications Society Annual Meeting, IAS 2018

作者： Nasmus Sakib Khan Shabbir, M. Le, Anh Minh Liang, Xiaodong Khan, Nahidul Li, Weixing Memorial University of Newfoundland Department of Electrical and Computer Engineering St John'sNL Canada Newfoundland and Labrador Hydro System Operation and Planning Energy Control Center St John'sNL Canada Harbin Institute of Technology Department of Electrical Engineering Harbin Hilongjiang China

ISBN: (纸本)9781538645369

Due to increasing penetration of wind power plants (WPP), power grids are facing significant power quality challenges. To achieve stable and robust power system operation, reactive power plays a vital role. Reactive power needed to compensate voltage fluctuations at the point of interconnection (POI) of the WPP varies with a short circuit ratio (SCR). The reactive power capability of a WPP is also limited and largely depends on various operating conditions. In a physical system, it is difficult to find the correlation among critical parameters for voltage control. In this paper, a data-driven voltage control approach is proposed for a grid-connected WPP. Two regression models are developed through surface fitting using MATLAB curve fitting toolbox: one model based on simulation data is to determine the required reactive power for grid voltage compensation;another model based on field measurement data is to determine the WPP reactive power characteristics. The reactive power compensation device is capacitors in the study. Two controllers, a central WPP controller and a capacitor controller, are designed, their effectiveness is validated through several case and sensitivity studies. © 2018 IEEE

关键词： Reactive power

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A New FEM-based Brain Tissue Model for Neurosurgical Simulation Using the Optimization Implicit Euler Method

A New FEM-based Brain Tissue Model for Neurosurgical Simulat...

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第37届中国控制会议

作者： Wenguo Hou Peter X.Liu Minhua Zheng Shichao Liu School of Mechanical Electronic and Control EngineeringBeijing Jiaotong University Department of System and Computer Engineering Carleton University

An accurate and computationally efficient model for the deformation of brain tissue is very important in virtual neurosurgical simulation. In this paper, we introduced a new Finite Element Method(FEM) model, which is based on optimization implicit Euler method, for brain tissue deformation. Specifically, both the anisotropic and viscoelastic properties of brain tissue are incorporated into the model, providing more realistic and accurate description of the mechanical features of brain tissue. In the meantime, the model is particularly suitable for GPU-based computing, making it possible to achieve real-time performance for neurosurgical simulation. Simulation results show that the deformation model exhibits the behaviors of anisotropy and viscoelasticity. The proposed model was implemented on a neurosurgical simulator and it showed that the deformation of brain tissue can be rendered with a relatively high degree of visual realism at a refreshment rate of 23 frames per second in a normal PC.

关键词： Brain Tissue Deformation Model Neurosurgical Simulation Optimization Implicit Euler

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control of Nonlinear Constrained Ultra-Supercritical Boiler–Turbine Units Using Offset-Free Output-Feedback Stable MPC

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IFAC-PapersOnLine 2018年第28期51卷 155-160页

作者： Chen, Chen Pan, Lei Shen, Jiong Lee, Kwang Y. Zhang, Fan Sun, Li Wu, Xiao Zhang, Junli Xue, Wenchao Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education Southeast University Nanjing210096 China Department of Electrical and Computer Engineering Baylor University One Bear Place #97356 WacoTX76798-7356 United States State Key Lab of Power System Department of Energy and Power Engineering Tsinghua University Beijing100084 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

It is extremely challenging to control ultra-supercritical boiler–turbine unit on account of its nonlinearity, coupling among multi-variables, hard input constraints, and unknown disturbances. An offset-free output-feedback stable model predictive control (MPC) (OFOF-SMPC) for nonlinear constrained ultra-supercritical boiler-turbine units is investigated. It is shown that the OFOF-SMPC is composed of a disturbance and state observer, a steady-state target calculator as well as a stable MPC, which can remove unknown disturbances from output channels and ensure the stability of the closed-loop system with input constraints. Simulation results demonstrate the effectiveness of the proposed algorithm. © 2018

关键词： Feedback

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A Gaussian Process Regression Approach for Fusion of Remote Sensing Images for Oil Spill Segmentation

A Gaussian Process Regression Approach for Fusion of Remote ...

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International Conference on Information Fusion

作者： Fodio S Longman Lyudmila Mihaylova Le Yang Department of Automatic Control and System Engineering University of Sheffield UK Department of Electrical and Computer Engineering University of Canterbury Chrischurch New Zealand

Synthetic Aperture Radar (SAR) satellite systems are very efficient in oil spill monitoring due to their capability to operate under all weather conditions. This paper presents a framework using Gaussian process (GP) to fuse SAR images of different modalities and to segment dark areas (assumed oil spill) for oil spill detection. A new covariance function; a product of an intrinsically sparse kernel and a Rational Quadratic Kernel (RQK) is used to model the prior of the estimated image allowing information to be transferred. The accuracy performance evaluation demonstrates that the proposed framework has 37% less RMSE per pixel and a compelling enhancement visually when compared with existing methods.

关键词： Oils Kernel Synthetic aperture radar Image resolution Gaussian processes Feature extraction Image segmentation

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Technical note for "A Geodesic Approach for the control of Tethered Quadrotors"

arXiv

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arXiv 2019年

作者： Nguyen, Tam W. Nicotra, Marco M. Garone, Emanuele Department of Aerospace Engineering University of Michigan 1320 Beal Avenue Ann ArborMI48109 United States Department of Electrical Computer and Energy Engineering University of Colorado Boulder 425 UCB BoulderCO80309 United States Department of Control Engineering and System Analysis Université libre de Bruxelles Av. F.D. Roosevelt 50 C.P. 165/55 Belgium

This technical note focuses on the control of a quadrotor unmanned aerial vehicle (UAV) tethered to the ground. The control objective is to stabilize the UAV to the desired position while ensuring that the cable remains taut at all times. A cascade control scheme is proposed. The inner loop controls the attitude of the UAV. The outer loop gives the attitude reference to the inner loop, and is designed so that (i) the gravity force is compensated, (ii) the cable is taut at all times, and (iii) the trajectory of the UAV follows the geodesic path. To prove asymptotic stability, small gain arguments are used. The control scheme is augmented with a reference governor to enforce constraints. Copyright © 2019, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Short term electric load forecast with artificial neural networks

arXiv

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arXiv 2018年

作者： Cristian, Vasar Iosif, Szeidert Ioan, Filip Gabriela, Prostean Department of Control System Engineering Politehnica' University from Timisoara Faculty of Automation and Computer Science Timisoara300223 Romania

This paper presents issues regarding short term electric load forecasting using feedforward and Elman recurrent neural networks. The study cases were developed using measured data representing electrical energy consume from Banat area. There were considered 35 different types of structure for both feedforward and recurrent network cases. For each type of neural network structure were performed many trainings and best solution was selected. The issue of forecasting the load on short term is essential in the effective energetic consume management in an open market environment. Copyright © 2007 IFAC Copyright © 2018, The Authors. All rights reserved.

关键词： Electric load forecasting

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A Decade of Soft Computing Approaches in Power system Investment Planning

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Journal of Physics: Conference Series 2021年第1期1878卷

作者： S B Yaakob A S F Rahman N M Mukhtar M N Yaakob N Arbaiy P-C Lin Control System Group (CSG) Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Kampus Alam UniMAP Pauh Putra 02600 Arau Perlis Malaysia Institut Pendidikan Guru Malaysia Kampus Darul Aman Bandar Darul Aman Kedah 06000 Jitra Kedah Malaysia Faculty of Computer Science and Information Technology University Tun Hussein Onn Malaysia 86400 Batu Pahat Johor Malaysia Department of Information Engineering and Computer Science Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan

This paper opens up an issue regarding to power system investment planning. In order to obtain a sustainable electricity supply, the power outage should be minimized. Maintenance cost plays as an essential element in investment planning, therefore misdirect investment should be avoided. Since soft computing can solved this problem, this paper offers a review in solving investment planning problem through such approaches. The main objective of this paper is to examine the concept and findings by the researchers in power system investment planning problem. Besides, this paper will highlight the most relevant contributions and limitations that can be improve in the other research. Finally, this paper will be pointed out some trends in power system investment planning problem.

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TransMut: a program to predict HLA-I peptide binding and optimize mutated peptides for vaccine design by the Transformer-derived self-attention model

Research Square

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Research Square 2021年

作者： Chu, Yanyi Zhang, Yan Wang, Qiankun Zhang, Lingfeng Wang, Xuhong Wang, Yanjing Wang, Jianmin Jiang, Xue Salahub, Dennis Russell Xiong, Yi Wei, Dong-Qing State Key Laboratory of Microbial Metabolism Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances Joint International Research Laboratory of Metabolic & Developmental Sciences School of Life Sciences and Biotechnology Shanghai Jiao Tong University Shanghai200030 China Department of Chemistry CMS - Centre for Molecular Simulation IQST - Institute for Quantum Science and Technology University of Calgary 2500 University Drive NW CalgaryABT2N 1N4 Canada Department of Clinical Oncology The University of Hong Kong-Shenzhen Hospital Shenzhen China School of Electrical Engineering and Computer Science University of Ottawa 75 Laurier Ave. OttawaONK1N 6N5 Canada The Ministry of Education Key Laboratory of System control and information processing Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200030 China Integrative Biotechnology & Translational Medicine Yonsei University Incheon21983 Korea Republic of Peng Cheng Laboratory Vanke Cloud City Phase I Building 8 Xili Street Nanshan District Guangdong Shenzhen518055 China

Computational prediction of the interaction between human leukocyte antigen (HLA) and peptide (pHLA) can speed up epitope screening and vaccine design. Here, we develop the TransMut framework composed of TransPHLA for pHLA binding prediction and AOMP for mutated peptide optimization, which can be generalized to any binding and mutation task of biomolecules. Firstly, TransPHLA is developed by using a Transformer-derived self-attention model to predict pHLA binding, which is significantly superior to 11 previous methods on pHLA binding prediction, neoantigen and human papilloma virus vaccine identification. For vaccine design, the AOMP program is then developed to automatically optimize mutated peptides to search for mutant peptides with higher affinity to the target HLA and with high homology to the source peptide. Among 3660 non-binding pHLAs, 3630 were successfully mutated. Of these, 94% were verified by the IEDB recommended method, and 88% have homology higher than 80% to the source peptide. © 2021, CC BY.

关键词： Peptides

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Petri Net control Method for Pipe-line systems and Its Implementation via CIF3 ⁎

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IFAC-PapersOnLine 2019年第24期52卷 261-266页

作者： YuHao Fu JiLiang Luo Huifeng Wu Jianhong Ye Yi-sheng Huang College Information Science and Engineering Huaqiao University Xiamen 361021 China College Information Science and Engineering Huaqiao University Xiamen 361021 China and also with Fujian Engineering Research Center of Motor Control and System Optimal Schedule Xiamen 361021 China Institute of Intelligent and Software Technology Hangzhou Dianzi University Hangzhou 310018 China Computer Science and Technology Huaqiao University Xiamen 361021 China and also with Fujian Provincial Key Laboratory of Data Intensive Computing Quanzhou 362000 China Department of Electrical Engineering National Ilan University Taiwan

As for a pipe-line system subjected to complex operations, an approach is proposed to synthesize the controller via Petri nets (PNs) such that the plant is run as concurrently as possible and the loads of equipments are balanced. A P-timed and labeled PN is designed to model the whole process of a pipe-line system, where tasks, including transporting material from one tank to another and cleaning tank, are represented by operational places, and level sensors amounted in tanks are represented by labels assigned to transitions. Further, monitor places are designed to resolve the conflict relations among tasks due to the shared valves and pipes. An method is presented to translate an PN controller into a CIF3 (Compositional Interchange Format) model, which can be converted into a PLC program in the CIF3 tool. A beer filtration plant is taken as an example to illustrate the approach, and its simulation experiments are carried out to verify the theoretic results.

关键词： Chemical plant Valve control Petri net CIF3

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Distributed H2-optimized Output Feedback controller Design using the ADMM

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IFAC-PapersOnLine 2017年第1期50卷 10389-10394页

作者： Eilbrecht J. Jilg M. Stursberg O. Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel Kassel 34121 Germany

This paper addresses the design of sparse, H2-optimized dynamic output feedback controllers for distributed systems. These systems consist of several physically remote subsystems, which are assumed to be controlled via local controllers. Depending on the topology of a communication network, subsets of these controllers may exchange information. In this setting, a trade-off between control performance and communication costs exists: while a network which connects more controllers increases control performance, establishing communication links also causes higher costs. In the past, the Alternating Direction Method of Multipliers (ADMM) has been applied to the design of state feedback controllers that optimize this trade-off. Due to the practical relevance of output feedback, this paper provides extensions necessary for application of the ADMM to the output feedback case. Motivated by deeper insights into the non-convex, non-smooth nature of the problem, the HANSO optimization package is applied to the controller performance optimization subproblem of the ADMM. The devised procedure is successfully applied to two example systems. © 2017

关键词： ADMM Decentralized control Distributed control Dynamic Output Feedback Optimal control

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