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22nd International Conference on Electrical Machines and Systems (ICEMS)

作者： Dhulipati, Himavarsha Mukundan, Shruthi Ghosh, Eshaan Li, Ze Vidalanage, Budhika Guruwatta Tjong, Jimi Kar, Narayan C. Univ Windsor Dept Elect & Comp Engn Windsor ON Canada Univ Windsor Dept Elect & Comp Engn 1 Windsor ON Canada

ISBN: (纸本)9781728133980

Replacing half of the number of poles in a conventional surface permanent magnet synchronous machine (PMSM) reduces the use of rare earth materials delivering similar performance. However, in such a consequent pole configuration certain slot-pole numbers deliver high magnitudes of even order harmonics in the induced EMF waveforms leading to unbalanced magnetic force. Further, utilizing concentrated windings (CW) in the stator adds to this space harmonic content. In literature, slot-pole combinations were selected based on fundamental winding factor, cogging torque and net force on the machine, neglecting space harmonics content in inductance and induced EMF waveforms. Motivated by the drawbacks in the existing methods, in this paper, a novel inductance harmonics factor and EMF harmonics factor have been modelled using winding function method for a consequent pole multiphase CW PMSM. Furthermore, a gradient descent algorithm-based approach is implemented to optimally select slot-pole combination, with reduced inductance and EMF harmonics, for three-, five- and six-phase FSCW PMSM, with little prior knowledge about structural information of the machine. The inductance and induced EMF harmonics for optimal slot-pole combinations obtained from the algorithm are verified using finite element and experimental analysis.

关键词： consequent pole gradient descent algorithm fractional slot concentrated windings inductance harmonics induced EMF harmonics slot-pole combination

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Distributed Hybrid gradient algorithm with Application to Cooperative Adaptive Estimation 25

Distributed Hybrid Gradient Algorithm with Application to Co...

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Proceedings of the 25th ACM International Conference on Hybrid Systems: Computation and Control (HSCC)

作者： Maghenem, Mohamed Saoud, Adnane Loria, Antonio CNRS GIPSA Lab Grenoble France Univ Paris Saclay L2S Cent Supelec Gif Sur Yvette France CNRS L2S Gif Sur Yvette France

ISBN: (纸本)9781450391962

We address a classical identification problem that consists in estimating a vector of constant unknown parameters from a given linear input/output relationship. The proposed method relies on a network of gradient-descent-based estimators, each of which exploits only a portion of the input-output data. A key feature of the method is that the input-output signals are hybrid, so they may evolve in continuous time (i.e., they may flow), or they may change at isolated time instances (i.e., they may jump). The estimators are interconnected over a weakly-connected directed graph, so the alternation of flows and jumps combined with the distributed character of the algorithm introduce a rich behavior that is impossible to obtain using continuous- or discrete-time estimators. A condition of persistence of excitation in hybrid form ensures exponential convergence of the estimation errors. The proposed approach generalizes the existing centralized gradient-descent algorithms and yields relaxed sufficient conditions for (uniform-exponential) parameter estimation. In addition, we address the observation/identification problem for a class of hybrid systems with unknown parameters using a distributed network of adaptive observers/identifiers.

关键词： gradient descent algorithm Distributed Estimation Hybrid Systems Lyapunov Direct Method

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Feedback Control With Feedforward Sequence For Nanopositioning System 35

Feedback Control With Feedforward Sequence For Nanopositioni...

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第35届中国控制会议

作者： LIU Bin ZHU Tao ZHANG Hai-Tao CHEN Zhi Yong School of Automation and the State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Electrical Engineering and Computer Science University of Newcastle

ISBN: (纸本)9781509009107

Fast and accurate tracking of reference trajectories is highly desirable in many nanopositioning systems,such as piezoelectric tube scanner(PTS),atomic force microscopes(AFMs) and so *** this paper,notch filter is designed to attenuate the gain at resonant *** with damping controller,notch filter is designed easier and has better ***'s more,a fast control algorithm is proposed to promote response *** attain fast and accurate control,the approach that contains notch filter and fast control algorithm is used in the practice *** results have been verified in our experimental platform and show that this method has better tracking effect compared with PID control or notch filter PID control.

关键词： Nanopositioning piezoceramics notch filter gradient descent algorithm

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Micro-IMU-Based Motion Tracking System for Virtual Training 34

Micro-IMU-Based Motion Tracking System for Virtual Training

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34th Chinese Control Conference (CCC)

作者： Zhang, Yang Fei, Yunfeng Xu, Lin Sun, Guangyi Nankai Univ Inst Robot & Automat Informat Syst Tianjin Key Lab Intelligent Robot Tianjin Peoples R China Second Artillery Corps Engn Design & Res Inst Beijing Peoples R China

ISBN: (纸本)9789881563897

This paper presents the development of a low cost wireless real-time inertial body tracking system for virtual training. The system is designed to provide highly accurate human body motion capture and interactive three-dimensional (3-D) avatar steering, by combining low cost MEMS inertial measurement units (IMUs), wireless body sensor network (BSN), and Unity 3D virtual reality game engine. First, several wearable MEMS IMU sensors are placed on user's body and limbs according to human skeletal action, and each sensor performs a 9 degrees of freedom (DOF) tracking at a high-speed update rate. Second, a Zigbee-based BSN is designed to support up to 20 MEMS IMU sensor nodes data transmission at 50 Hz sampling frequency. All collected sensors' data are loaded to a Matlab-based PC program by means of serial port. In order to accurately estimate the local orientation of each IMU sensor, an optimized gradient descent algorithm is implemented. The algorithm uses a quaternion representation, which allows accelerometer and magnetometer data to be fused to compute the gyroscope measurement error as a quaternion derivative. Finally, the estimated orientation data by fusion algorithm are imported to a virtual environment, consisting of the 3-D virtual skeletal representation and the virtual scene for specific training. Experimental results indicate that the system achieves < 1 degrees static RMS error and < 2 degrees dynamic RMS error. The systems further expand the usability of low cost body tracking solution to virtual training in virtual environments.

关键词： micro inertial measurement unit (IMU) motion capture virtual training gradient descent algorithm wireless sensor network

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Temperature Controller Using the Takagi-Sugeno-Kang Fuzzy Inference System for an Industrial Heat Treatment Furnace 20th

Temperature Controller Using the Takagi-Sugeno-Kang Fuzzy In...

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20th International Conference on Computational Science and Its Applications (ICCSA)

作者： Buele, Jorge Rios-Cando, Paulina Brito, Geovanni Moreno-P, Rodrigo Salazar, Franklin W. Univ Tecnol Indoamer SISAu Res Grp Ambato 180212 Ecuador Escuela Super Politecn Chimborazo Riobamba 060155 Ecuador Univ Tecn Ambato Ambato 180103 Ecuador

ISBN: (纸本)9783030588175;9783030588168

The industrial welding industry has a high energy consumption due to the heating processes carried out. The heat treatment furnaces used for reheating equipment made of steel require a good regulator to control the temperature at each stage of the process, thereby optimizing resources. Considering dynamic and variable temperature behavior inside the oven, this paper proposes the design of a temperature controller based on a Takagi-Sugeno-Kang (TSK) fuzzy inference system of zero order. Considering the reaction curve of the temperature process, the plant model has been identified with the Miller method and a subsequent optimization based on the descending gradient algorithm. Using the conventional plant model, a TSK fuzzy model optimized by the recursive least square's algorithm is obtained. The TSK fuzzy controller is initialized from the conventional controller and is optimized by descending gradient and a cost function. Applying this controller to a real heat treatment system achieves an approximate minimization of 15 min with respect to the time spent with a conventional controller. Improving the process and integrated systems of quality management of the service provided.

关键词： Fuzzy logic controller gradient descent algorithm Heat treatment Temperature control

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Solving FDE by trigonometric neural network and its applications in simulating fractional HIV model and fractional Schrodinger equation

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MATHEMATICAL METHODS IN THE APPLIED SCIENCES 2023年第3期46卷 3132-3142页

作者： Gao, Feng Chi, Chunmei Qingdao Univ Technol Sch Sci Qingdao 266033 Peoples R China Qingdao Univ Technol Sch Informat & Control Engn Qingdao Peoples R China

In this paper, we put forward numerical algorithms to simulate fractional HIV infected CD4(+)T cell model and fractional Schrodinger equation. First, we put forward numerical algorithm to solve fractional differential systems with trigonometric neural network. Then trigonometric neural network method is used to simulate the fractional HIV infected CD4(+)T cell model. It is found that the infection equilibrium has the restriction condition for the number of virus particles released by each infected cell. Under this condition, the fractional system has a unique positive equilibrium. Second, we put forward numerical algorithm to solve fractional PDE with trigonometric neural network. Then this numerical method is used to simulate fractional Schrodinger equation, and some important results in fractional quantum mechanics are concluded by the corresponding numerical results.

关键词： fractional differential equation fractional Schrodinger equation gradient descent algorithm HIV infected CD4(+)T model trigonometric neural network

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Congestion management under deregulated fuzzy environment

Congestion management under deregulated fuzzy environment

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2nd International Conference on Electric Utility Deregulation, Restructuring and Power Technologies

作者： Padhy, NP Univ Roorkee Dept Elect Engn Roorkee 247667 Uttar Pradesh India

ISBN: (纸本)0780382374

In this paper, an efficient and practical hybrid model has been proposed for congestion management analysis for both real and reactive power transaction under deregulated fuzzy environment of power system. The proposed hybrid model determines the optimal bilateral or multilateral transaction and their corresponding load curtailment in two stages. In the first stage classical gradient descent optimal power flow algorithm has been used to determine the set of feasible curtailment strategies for different amount of real and reactive power transactions. Whereas in the second stage fuzzy decision opinion matrix has been used to select the optimal transaction strategy considering increase in private power transaction, reduction in percentage curtailment, and its corresponding change in per unit generation cost and hence profit as fuzzy variables. The performance of the proposed algorithm has been tested using modified IEEE 30 bus test system. The solutions so obtained are found to be quite encouraging and reliable refer to both utility and customers.

关键词： optimal power flow gradient descent algorithm congestion management and fuzzy decision systems

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A Contactless Insulator Contamination Levels Detecting Method Based on Infrared Images Features and RBFNN

A Contactless Insulator Contamination Levels Detecting Metho...

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Annual Meeting of the IEEE-Industry-Applications-Society (IAS)

作者： He, Hongying Luo, Diansheng Lee, Wei-Jen Zhang, Zhenyuan Cao, Yijia Lu, Tianguang Hunan Univ Changsha 410082 Hunan Peoples R China Univ Texas Arlington Arlington TX 76019 USA Univ Elect Sci & Technol China Chengdu 610054 Peoples R China Shanghai Jiao Tong Univ Shanghai 200240 Peoples R China

ISBN: (纸本)9781538645376;9781538645369

A contactless method uses infrared image features and radial basis function neural network (RBFNN) to detect contamination levels for porcelain insulators is proposed in this paper. First, theory evidence for contamination levels detection by infrared images is inferred. Then, the denoising and image segmentation is implemented to suppress the image noise and eliminate the affection of the background. Nine color moment features related to the contamination levels are extracted from the insulator images. Finally, an RBFNN is constructed to identify the contamination levels. The images features and ambient relative humidity are taken as the inputs of the RBFNN. For improve the precision of the detection, a new method based on the statistical probability of the values of each contamination feature component is proposed to select the initial hidden center parameters for RBFNN hidden nodes. An improved learning algorithm combined with the gradient descent algorithm and a random number control factor are proposed to modify the hidden center parameters and the weights vectors. Testing results show that the selected color moment features are effective on the contamination levels representation and the constructed RBFNN performs better than back propagation neural network (BPNN) and generalized regression neural network (GRNN) on contamination levels identification.

关键词： Color moment features contamination levels identification gradient descent algorithm hidden center parameters image processing infrared image insulators radial basis function neural network (RBFNN) random number control factor

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Auto lead angle algorithm for high efficiency control of BLDC Motor 17

Auto lead angle algorithm for high efficiency control of BLD...

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17th International Conference on Control, Automation and Systems (ICCAS)

作者： Jeon, Byeong-chan Park, Won-ki Lee, Sung-chul Shin, Hyun-chul Hanyang Univ Dept Convergence Syst Erica Campus Seoul South Korea Korea Elect Technol Inst SoC Platform Res Ctr Seongnam Si Gyeonggi Do South Korea

ISBN: (纸本)9788993215144

The Brushless DC motors are used in various industries such as home appliances, electric vehicles, Medical, Industrial automation equipment and so on. Because they have advantages of low noise, simple control and high power density. But, in a high-speed motor drive, current lagging which is induced by the impedance of the motor inductor reduces the motor efficiency. To solve this problem, we propose an auto lead angle control algorithm based on a gradient descent algorithm. With this algorithm, the motor current and motor Back-EMF have an identical phase angle. Thus, the efficiency of the motor can be increased. In order to verify the proposed algorithm, we implemented the hardware with FPGA and board including analog circuit. As a result, it was confirmed that the optimum lead angle was found with only one current value without various parameters, and the efficiency of the motor was improved. Also, it is confirmed that the efficiency is further increased at high load and high speed.

关键词： BLDC Motor gradient descent algorithm Lead angle FPGA Motor driver

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Path Following with Threat Avoidance Through Accelerated Model Predictive Control

Path Following with Threat Avoidance Through Accelerated Mod...

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International Conference on Autonomous Unmanned Systems (ICAUS)

作者： Fei, Bin Chang, Yuan Wang, Yanzhen Bu, Xiaoting Song, Mingwu Acad Mil Sci Beijing 100091 Peoples R China Tianjin Artificial Intelligence Innovat Ctr Tianjin 300457 Peoples R China

ISBN: (纸本)9789819904815;9789819904792;9789819904785

In this paper, we focus on the path following control of a fixed-wing UAV and investigate how to avoid pop-up threats by onboard optimization. It contains two subproblems: how to bypass threat areas in time and how to minimize deviations from the desired path. More importantly, the calculation must be completed in real-time. To address this, we design an accelerated model predictive controller with two stages. First, we incorporate multiple control objectives into the prediction model in a weighted manner. Then, by introducing the rectified linear unit penalties, it is transformed into an unconstrained problem, which is solved by gradient-based optimizers. Six state-of-the-art optimizers are compared in simulations. The results prove that the proposed control method can well deal with multiple static or moving threats, is robust to wind disturbance, and has high real-time performance.

关键词： Path following Threat avoidance gradient descent algorithm

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