Design and Xilinx Virtex-field-programmable gate array for hardware in the loop of sensorless second-order sliding mode control and model reference adaptive system–sliding mode observer for direct torque control of induction motor drive

Abstract

This article aims first to propose an improved space vector modulation–direct torque control in order to enhance the induction motor performance using: (1) a super-twisting controller and (2) a novel model reference adaptive system based on a sliding mode observer. Second, due to the complexity of the suggested control algorithm, this article deals also with a hardware implementation on a field-programmable gate array board. Indeed, the field-programmable gate array is mainly chosen to reduce the execution time, thanks to its parallel processing which significantly improves the quality of the control system by reducing the sampling period, and consequently the delays in the control loop. Besides, the super-twisting controller is proposed to enhance the speed regulation loop which is a second-order sliding mode control technique that uses a continuous control law to prevent the chattering phenomenon induced by the first-order sliding mode control technique. Moreover, the high performance control requires information about the rotor speed which can be obtained by a sensor. Generally, the use of the speed sensor increases the system cost and size, and reduces its system reliability. Therefore, a combination between a model reference adaptive system observer and a sliding mode observer is suggested for speed estimation and overcoming the sensitivity of the classical model reference adaptive system observer against uncertainties and stator resistance variations. The performance of the proposed space vector modulation--direct torque control--super-twisting controller with the model reference adaptive system--sliding mode observer algorithm of an induction motor is verified through simulation, hardware co-simulation and experimental validation utilizing a field-programmable gate array Virtex-5-ML507 board. The performance of the suggested sensorless control method is compared also with other recent published schemes.

Novel Speed Sensorless DTC Design for a Five-Phase Induction Motor with an Intelligent Fractional Order Controller Based-MRAS Estimator

“…Recently, many sensorless DTC techniques of three-phase machines have been developed to reduce the cost and increase the reliability of electric drive systems in specific applications (El Ouanjli et al, 2022). For this, motor speed can be obtained by models using measured inputs (voltage and current) (Bahloul et al, 2019;Boztas and Aydogmus, 2022;Han and Zhang, 2019;Holakooie et al, 2018;Krim and Mimouni, 2023). In this context, several methods have been proposed in the literature, such as the adaptive Luenberger observer (LO) (Yousfi et al, 2022), the extended Kalman filter (EKF) (Boztas and Aydogmus, 2022) and the full-order sliding mode observer (Zhou et al, 2021), to ensure sensorless control of the simple three-phase motor.…”

A New Efficient Cuckoo Search MPPT Algorithm Based on a Super-Twisting Sliding Mode Controller for Partially Shaded Standalone Photovoltaic System

“…Moreover, STSMC is known for its robustness and has precise tracking with fewer errors. It also responds well to changes and is easy to design and put into action [57,59,68].…”

Design of Vector Control Strategies Based on Fuzzy Gain Scheduling PID Controllers for a Grid-Connected Wind Energy Conversion System: Hardware FPGA-in-the-Loop Verification

“…In order to overcome the limitations of DSP, FPGAs can be considered a preferred solution. The benefits of using hardware FPGAs are multiple: (i) rapid prototyping, (ii) reduced execution time due to parallel processing and (iii) ability to use too-heavy control methods as regards computing time [49]. Thus, FPGAs have been used in varied research work [49][50][51][52].…”

“…The benefits of using hardware FPGAs are multiple: (i) rapid prototyping, (ii) reduced execution time due to parallel processing and (iii) ability to use too-heavy control methods as regards computing time [49]. Thus, FPGAs have been used in varied research work [49][50][51][52]. Two main methods have been used to implement control algorithms on FPGAs, namely the Xilinx System Generator (XSG) and programming Very-high-speed integrated circuit Hardware Description Language (VHDL) [53][54][55][56].…”