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The advances in clean energy technologies have made the renewable resources more attractive for distribution network operators as they are inexhaustible and non-polluting. In this paper, a comprehensive dynamic distribution network expansion planning (DDNEP) is proposed which takes into account most of the planning alternatives along with renewable and non-renewable distributed generation (DG). The...
This paper presents, a simple and robust Adaptive Neuro-Fuzzy Inference System (ANFIS) for vibration control of a Vehicle Active Suspension System (VASS) and compares with conventional Proportional, Integral and Derivative (PID) controller and an Artificial Neural Network (ANN) controller which is trained with conventional control data. The main objective is to enhance the travelling comfort to the...
For the defects of conventional direct torque control (DTC) system of switched reluctance motors (SRM), RBF neural network (RBFNN) and fuzzy adaptive PID controller are applied to direct torque control system of SRM in the paper. Switching state table is replaced by RBFNN; fuzzy adaptive PID controller is applied to the outer loop for speed adjustment. In order to verify the validity of the method,...
It is an irresistible trend of the electric power improvement for developing the smart grid, which applies a large amount of new technologies in power generation, transmission, distribution and utilization to achieve optimization of the power configuration and energy saving. As one of the key links to make a grid smarter, load forecast plays a significant role in planning and operation in power system...
This paper describes a position control of 2 degrees of freedom (DOF) XY Piezo Actuator Stage (XY PAS) with Feedforward Neural Network (FNN) and additional Particle Swarm Optimization (PSO) approach, which is used as an improved learning method for optimizing the weights of FNN rather than just the standard technique of back-propagation of errors.
This paper focuses on the study of multi-person location and tracking in a complex scene created by 3ds max. To establish the complicated relationship between the 2D-image information that is obtained through the three-camera system and the 3D information of the target, an artificial neural network is proposed. In order to overcome the shortcomings of traditional BP algorithm as being slow to converge...
In order to control the turbojet engine in the all operation condition and whole flight envelope, this paper establishes a new self-adaptive neural network control system which is conducted by a neural network controller similar to PID and an identifier based on the Elman neural network with the self-feedback. Elman network is adopted as plant model predictor to identify controlled plant on-line....
Transformer fault diagnosis based on artificial neural networks (ANN) is widely used, because ANN has essential nonlinear character, parallel processing ability and the ability of self organize and self learning. But there exist problems if we use traditional ANN method alone to diagnose transformer fault, the large input vector dimension and complex training database will cause the computation complexity...
In this paper frequency analysis of spoken Urdu numbers from dasiasifrpsila (zero) to dasianaupsila (nine) is described. Sound samples from multiple speakers were utilized to extract different features. Initial processing of data, i.e. time-slicing and normalizing and was done using a combination of Simulink and MATLAB. Afterwards, the same tools were used for calculation of Fourier descriptions and...
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