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Game players of different skills expect different challenge levels in game to be filled with enjoyment and fulfillment. Thus intelligent game opponent can be made adaptive to match different player strategies and different player skills. Traditional difficulty adjustment setting the status of the opponent often fills players with a feeling of being cheated, which cannot perfectly satisfy the player...
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...
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...
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...
Since the characteristics of time-delay, nonlinear and uncertain model structure, and in order to control temperature in greenhouse better, a fuzzy neural network PID control is presented in this paper. The intelligent controller can adjust the parameters according to the variation of system characteristics even if the system model is unknown, and meet the requests of real-time control. The approach...
A neural network (NN)-based intelligent adaptive controller that introduces a new concept of intelligent supervisory loop is proposed. The scheme consists of an online radial basis-function NN (RBFNN) in parallel with a model reference adaptive controller (MRAC) and uses a growing dynamic RBFNN to augment MRAC. Updating of the RBFNN width, center, and weight characteristics is performed such that...
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