A robust direct torque control (DTC) strategy for an induction motor is proposed in this study. In fact, the proposed control strategy is defined by a combination of DTC, space vector modulation (SVM), input-output feedback linearisation (IOFL), a second-order super-twisting speed controller (STSC), and sliding-mode-load torque and stator-flux observers with stator resistance estimation. First, non-linear IOFL is suggested to achieve decoupled flux and torque control, and the SVM technique is utilised to control the inverter switching frequency which decreases the torque ripples and noise. Second, to improve the speed regulation, an STSC is added to an SVM-DTC-IOFL scheme. Furthermore, the sliding mode observers of the stator flux and of the load torque are proposed in order to improve the control performances by reducing uncertainties and to prevent the effects of the stator resistance variations. Indeed, this study presents the importance of implementing the suggested SVM-DTC-IOFL using a field-programmable gate array (FPGA) circuit. The main interest of the FPGA implementation is the decrease in the control loop delay, due to the parallel processing offered by the FPGA. The performances of the proposed control algorithm are investigated by digital simulation using a Xilinx system generator tool and experimental implementation utilising FPGA-Virtex-5-ML507. Nomenclature (i sα , i sβ) stator current components (v sα , v sβ) voltage vector components (ϕ sα , ϕ sβ) stator flux vector components
This paper proposes a digital implementation of the direct torque control (DTC) of an Induction Motor (IM) with an observation strategy on the Field Programmable Gate Array (FPGA). The hardware solution based on the FPGA is caracterised by fast processing speed due to the parallel processing. In this study the FPGA is used to overcome the limitation of the software solutions (Digital Signal Processor (DSP), Microcontroller...). Also, the DTC of IM has many drawbacks such as for example; The open loop pure integration has from the problems of integration especially at the low speed and the variation of the stator resistance due to the temperature. To tackle these problems we use the Sliding Mode Observer (SMO). This observer is used estimate the stator flux, the stator current and the stator resistance. The hardware implementation method is based on Xilinx System Generator (XSG) which a modeling tool developed by Xilinx for the design of implemented systems on FPGA; from the design of the DTC with SMO from XSG we can automatically generate the VHDL code. The model of the DTC with SMO has been designed and simulated using XSG blocks, synthesized with Xilinx ISE 12.4 tool and implemented on Xilinx Virtex-V FPGA.
In this paper the hardware implementation of the direct torque control based on the fuzzy logic technique of induction motor on the Field-Programmable Gate Array (FPGA) is presented. Due to its complexity, the fuzzy logic technique implemented on a digital system like the DSP (Digital Signal Processor) and microcontroller is characterized by a calculating delay. This delay is due to the processing speed which depends on the system complexity. The limitation of these solutions is inevitable. To solve this problem, an alternative digital solution is used, based on the FPGA, which is characterized by a fast processing speed, to take the advantage of the performances of the fuzzy logic technique in spite of its complex computation. The Conventional Direct Torque Control (CDTC) of the induction machine faces problems, like the high stator flux, electromagnetic torque ripples, and stator current distortions. To overcome the CDTC problems many methods are used such as the space vector modulation which is sensitive to the parameters variations of the machine, the increase in the switches inverter number which increases the cost of the inverter, and the artificial intelligence. In this paper an intelligent technique based on the fuzzy logic is used because it is allows controlling the systems without knowing the mathematical model. Also, we use a new method based on the Xilinx system generator for the hardware implementation of Direct Torque Fuzzy Control (DTFC) on the FPGA. The simulation results of the DTFC are compared to those of the CDTC. The comparison results illustrate the reduction in the torque and stator flux ripples of the DTFC and show the Xilinx Virtex V FPGA performances in terms of execution time.
Induction machine drive based on Direct Torque Control (DTC) allows high dynamic performance with very simple hysteresis control scheme. Conventional Direct Torque Control (CDTC) suffers from some drawbacks such as high current, flux and torque ripple, difficulties in torque as well as flux control at very low speed. In this paper, we propose two intelligent approaches to improve the direct torque control of induction machine; fuzzy logic control and artificial neural networks control. We carry out a detailed comparison study between direct torque fuzzy control (DTFC), direct torque neural networks control (DTNNC) and CDTC applied to switching select voltage vector. The theoretical foundation principle, the numerical simulation procedure and the performances of both methods are also presented.
Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical vehicle. Like failures of a position sensor, a voltage sensor, and current sensors. Three-phase induction motors are the "workhorses" of industry and are the most widely used electrical machines. This paper presents a scheme for Fault Detection and Isolation (FDI). The proposed approach is a sensor-based technique using the mains current measurement. Current sensors are widespread in power converters control and in electrical drives. Thus, to ensure continuous operation with reconfiguration control, a fast sensor fault detection and isolation is required. In this paper, a new and fast faulty current sensor detection and isolation is presented. It is derived from intelligent techniques. The main interest of field programmable gate array is the extremely fast computation capabilities. That allows a fast residual generation when a sensor fault occurs. Using of Xilinx System Generator in Matlab/Simulink allows the real-time simulation and implemented on a field programmable gate array chip without any VHSIC Hardware Description Language coding. The sensor fault detection and isolation algorithm was implemented targeting a Virtex5. Simulation results are given to demonstrate the efficiency of this FDI approach.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.