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This paper presents a study that compares the efficacy of Neuro-Evolution (NE) versus Particle Swarm Optimization (PSO) for evolving Artificial Neural Network (ANN) controllers in an unsupervised adaptation process. The research objective is to ascertain which adaptive method is most appropriate for deriving agent behaviors in a competitive co-evolution pursuit-evasion task. This task requires one...
Due to the dynamic and anonymous nature of open environments, it is critically important for agents to identify trustful cooperators which work consistently as they claim. In the e-services and e-commerce communities, trust and reputation systems are applied broadly as one kind of decision support systems, and aim to cope with the consistency problems caused by uncertain trust relationships. However,...
This paper presents speed sensorless direct torque control (DTC) of induction motor using artificial intelligence (AI). The artificial neural network (ANN) MRAS-based speed estimation is used. The error between the reference model and the neural network based adaptive model is used to adjust the weights by on-line back propagation (BP) training algorithm. The speed loop regulation is carried out by...
The paper analyses in detail the application of the adaptive theory in line protection, motor protection and etc of power distribution network. With the rapid development of artificial intelligence, Artificial Neural Network (ANN) technology and Multi-agent technology has also made its application in adaptive protection. Using such adaptive protection technology to improve the defects of traditional...
In the present work an artificial neural network (ANN) based speed controller and speed estimator of PMSM (permanent magnet synchronous motor) drive is designed and simulated using SIMULINK under MATLAB and results are compared with conventional PI controller and observer based drive of PMSM. The performance of ANN based system is evaluated for various disturbances to substantiate the proposed control...
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