<span>This paper proposes the fractional-order proportional integral derivative (FOPID) controller, as a speed controller for permanent magnet direct current (PMDC) motor, instead of the traditional integer-order PID controller. The FOPID controller is the general form of the integer-order PID controllers, which found wide applications in all engineering fields. In this work a hybrid M-file and SIMULINK program is developed to simulate the overall system, the FOPID controller has five associated parameters. The optimum values of those parameters are found out by using particle swarm optimization technique. Simulation results show excellent command speeds tracking and superior dynamic response in conjunction with that of the integer-order PID controller. The proposed controller shows a high ability to overcome any external disturbance the system may be exposed; also, it performs a high degree of robustness to control the system in motoring and regenerative operating modes.</span>
Speed control for an I.M is a few what complex strategies; the complexity is regularly increasing in line with the required system achievement. The main forms of control strategies are scalar, direct torque, adaptive, sensorless, and vector or Field Oriented Control (FOC). The FOC method is the most efficient technique in which machine parameters: Rotor flux, unit vector, and electromagnetic torque, usually are estimated by means of using Digital Signal Processing (DSP). The Artificial Neural Network (ANN) becomes an effective tool for controlling nonlinear device in present time. This paper proposes the using of ANN instead of DSP to estimate the machine parameters in order to reduce the hardware complexity and the Electromagnetic Interference (EMI) impact. Also, it presents the PI-NN controller which is based totally on ANN. The systems simulations for both DSP and ANN are depicted. The performance of the ANN-based system gives excellent results: overshot less than 0.5%, rise time 0.514 s, steady state error less than 0.2%, settling time 0.7 s. in conjunction with that of DSPbased performance: overshot about 2%, rise time 0.64 s, steady state error less than 0.4%, settling time 0.75 s.
This paper proposes a novel method for controlling the output DC-link voltage of the Z-source inverter for adjustable speed drive applications. An adaptive neuro-fuzzy controller is used to control the DC-link. The novelty of the proposed controller is the direct feedback from the DC-link, which is a discontinuous (chopped) signal, without any additional estimation or peak detection circuits. Where, this discontinuous feedback can't be used in conventional controllers without additional circuits. Design and simulation of the proposed control system are illustrated in this paper. Simulation results give excellent performance of the Z-source inverter with ripple free DC-link voltage. The robustness of the proposed intelligent controller is demonstrated for different output voltage commands. The response of the DC-link voltage, output AC voltage, AC current and speed for 20% and 40% input voltage sag is investigated.
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