Impact of sensorless neural direct torque control in a fuel cell traction system

Abstract

<span>Due to the reliability and relatively low cost and modest maintenance requirement of the induction machine make it one of the most widely used machines in industrial applications. The speed control is one of many problems in the traction system, researchers went to new paths instead the classical controllers as PI controller, they integrated the artificial intelligent for its yield. The classical DTC is a method of speed control by using speed sensor and PI controller, it achieves a decoupled control of the electromagnetic torque and the stator flux in the stationary frame, besides, the use of speed sensors has several drawbacks such as the fragility and the high cost, for this reason, the specialists went to propose an estimators as Kalman filter. The fuel cell is a new renewable energy, it has many applications in the traction systems as train, bus. This paper presents an improved control using DTC by integrate the neural network strategy without use speed sensor (sensorless control) to reduce overtaking and current ripple and static error in the system because the PI controller has some problems like this; and reduce the cost with use a renewable energy as fuel cell.</span>

Feedforward neural network emulation of a PID continuous-time controller for quadcopter attitude digital control

“…The equations of motion for a quadcopter are typically stated in an inertial frame, which utilizes a rotation matrix R [23], for the following reasons: − The inertia matrix is not related to time. − The symmetry of the quadcopter body can be used to simplify the equations.…”

“…Intelligent controllers utilizing artificial intelligence and neural networks can greatly improve automation systems [23]. The neural network acquires knowledge through training and stores it through synaptic weights, which connect neurons.…”

Efficient detection of faults and false data injection attacks in smart grid using a reconfigurable Kalman filter

“…Figure 3 depicts the control system alongside the KF entrenched on the approximation of the vector of state & detector in order to do the identification of errors [12], [13]. The (9) represents the KF technique where = [ 1 0 0 1 ] , from in (8) it can be represented in simplest form and it is given in (10).…”

Optimized Kalman filters for sensorless vector control induction motor drives

“…Field orientation control induction motor (FOCIM) drives are widely used in high performance industrial applications when high torque and speed response are required [1], [2]. Furthermore, the main advantage of FOCIM drives is decupling control between torque and flux as separately excited direct current (DC) motor [2], [3].…”