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controller Placement in Software Defined Internet of Things Using Optimization Algorithm

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Computers, Materials & Continua 2022年第3期70卷 5073-5089页

作者： Sikander Hans Smarajit Ghosh Aman Kataria Vinod Karar Sarika Sharma Department of Electrical and Instrumentation Engineering Thapar Institute of Engineering&TechnologyPatialaIndia Optical Devices and Systems CSIR-Central Scientific Instruments OrganizationSector 30-CChandigarh160030India Department of Electrical Engineering Government PolytechnicAmbala CityAmbala134003India

The current and future status of the internet is represented by the upcoming Internet of Things(IoT).The internet can connect the huge amount of data,which contains lot of processing operations and efforts to transfer the pieces of *** emerging IoT technology in which the smart ecosystem is enabled by the physical object fixed with software electronics,sensors and network ***,there are two trending technologies that take the platform i.e.,Software Defined Network(SDN)and IoT(SD-IoT).The main aim of the IoT network is to connect and organize different objects with the internet,which is managed with the control panel and data panel in the SD *** main issue and the challenging factors in this network are the increase in the delay and latency problem between the *** is more significant for wide area networks,because of the large packet propagation latency and the controller placement problem is more important in every *** the proposed work,IoT is implementing with adaptive fuzzy controller placement using the enhanced sunflower optimization(ESFO)algorithm and Pareto Optimal controller placement tool(POCO)for the placement problem of the *** order to prove the efficiency of the proposed system,it is compared with other existing methods like PASIN,hybrid SD and PSO in terms of load balance,reduced number of controllers and average latency and *** 2 controllers,the proposed method obtains 400 miles as average latency,which is 22.2%smaller than PSO,76.9%lesser than hybrid SD and 91.89%lesser than PASIN.

关键词： SD-IoT adaptive fuzzy controller enhanced sunflower optimization(ESFO) POCO placement tool controller placement problem and minimum latency

Combined indirect and direct method for adaptive fuzzy output feedback control of nonlinear system

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维普期刊数据库

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Journal of Systems Engineering and Electronics 2007年第1期18卷 120-124页

作者： Ding Quanxin Chen Haitong Jiang Changsheng Chen Zongji Coll. of Automation Engineering Beijing Univ. of Aeronautics & Astronautics Beijing 100083 P. R. China Coll. of Automation Engineering Nanjing Univ. of Aeronautics & Astronautics Nanjing 210016 P. R. China

A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.

关键词： Nonlinear control systems Non-affine Combined indirect and direct method adaptive fuzzy controller High-gain observer (HGO)

A Novel Evolutionary-fuzzy Control Algorithm for Complex Systems

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Journal of Systems Engineering and Electronics 2002年第3期13卷 52-60页

作者：王攀徐承志冯珊徐爱华 Huazhong Univ. of S&T Wuhan 430070 P. R. China Wuhan Univ. of Technology Wuhan 430070 P.R. China

This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key parameters of the adaptive control algorithm. Simulation results show that this control scheme has satisfactory performance in MIMO systems, chaotic systems and delay systems.

关键词： Modified genetic algorithm Nonlinear quantization factor adaptive fuzzy controller ITAE index Complex systems.

DSP-based adaptive fuzzy Control for a Sensorless PMSM Drive

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DSP-based Adaptive Fuzzy Control for a Sensorless PMSM Drive

adaptive fuzzy design of a rope attitude adjustment system

2009中国控制与决策会议

作者： Ying-Shieh Kung Ming-Shyan Wang Chung-Chun Huang Department of Electrical Engineering Southern Taiwan University Energy & Environment Research Laboratory Industrial Technology Research Institute

＜正＞A study on DSP-based PMSM（Permanent Magnet Synchronous Motor） drive without the encoder sensor is presented in this *** the sensorless technique,a flux angle estimator mainly constructed by a sliding mode observer is utilized to estimate the back electromotive force（EMF） and the flux angle,and indirectly compute and the rotor speed of the *** estimated values are feedback for vector control in the current loop and for speed control in the speed *** increase the performance of the speed controller,an adaptive fuzzy controller（AFC） consisted by a fuzzy controller,a reference model and an adjustable mechanism is applied;after that,the rules of the fuzzy controller can be online updated in real ***,the TMS320F2812 DSP（Digital Signal Processor） is adopted to implement the aforementioned *** a sensorless technique and an adaptive control technique into the speed controller of a PMSM drive make its performance be improved,the cost be reduced and the reliability be increased.

关键词： PMSM DSP Sliding mode observer Sensorless technique adaptive fuzzy controller

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cnki会议

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Journal of Measurement Science and Instrumentation 2019年第2期10卷 168-175页

作者： WANG Wei-shu MENG Li-fan ZHANG Zhi-dong Science and Technology on Electronic Test & Measurement Laboratory North University of ChinaTaiyuan 030051China

The attitude adjustment of rope system faces the challenging due to the difficulty in obtaining accurate three-dimensional(3D)mathematical model and solving by traditional methods.A set of adjustment systems is designed and used to investigate the automatic control for level or preset attitude adjustment of unknown weights and eccentric *** system principle and characteristics are *** 3D model is decomposed into two two-dimensional(2D)subsystems,and an adaptive fuzzy controller based on BP neural network and least squares(LSE)is *** simulation experiment uses MATLAB to train the level-adjustment data for testing algorithm,and a small load is used to verify the effectiveness of the *** experimental results show that precise attitude adjustment can be achieved within the system load range,and the response speed is *** adjustment method provides a fast and effective method for precise adjustment of the load attitude.

关键词： attitude adjustment rope system modelling adaptive fuzzy controller BP neural network