Abstract
Recently, the Indirect Field Oriented Control (IFOC) scheme for Induction Motors (IM) has gained wide acceptance in high performance applications. The IFOC has remarkable characteristics of decoupling torque and flux along with an easy hardware implementation. However, the detuning limits the performance of drives due to uncertainties of parameters. Conventionally, the use of a Proportional Integral Differential (PID) controller has been very frequent in variable speed drive applications. However, it does not allow for the operation of an IM in a wide range of speeds. In order to tackle these problems, optimal, robust, and adaptive control algorithms are mostly in use. The work presented in this paper is based on new optimal, robust, and adaptive control strategies, including an Adaptive Proportional Integral (PI) controller, sliding mode control, Fuzzy Logic (FL) control based on Steepest Descent (SD), Levenberg-Marquardt (LM) algorithms, and Hybrid Control (HC) or adaptive sliding mode controller to overcome the deficiency of conventional control strategies. The main theme is to design a robust control scheme having faster dynamic response, reliable operation for parameter uncertainties and speed variation, and maximized torque and efficiency of the IM. The test bench of the IM control has three main parts: IM model, Inverter Model, and control structure. The IM is modelled in synchronous frame using d q modelling while the Space Vector Pulse Width Modulation (SVPWM) technique is used for modulation of the inverter. Our proposed controllers are critically analyzed and compared with the PI controller considering different conditions: parameter uncertainties, speed variation, load disturbances, and under electrical faults. In addition, the results validate the effectiveness of the designed controllers and are then related to former works.
Highlights
Induction Machines (IM) have a wide use in industries for different processes due to their high performance
The dynamic behavior of adaptive Proportional Integral (PI), Fuzzy Logic Control (FLC) based on LM, FLC based on Steepest Descent (SD), and Sliding Mode Control (SMC)
The FLC based on LM algorithm, FLC based on SD technique, SMC, and Hybrid Control (HC) (Adaptive Sliding Mode Controller (ASMC)) provided
Summary
Induction Machines (IM) have a wide use in industries for different processes due to their high performance. The PID control scheme is widely utilized in industries because of the ease of design, low cost, and simple control structure [8] This scheme is unable to provide perfect control for uncertainty, disturbances, and highly non-linear systems. Non-linear control is used to tackle the parameter variation problem and enhance the performance of Indirect Field Oriented Control (IFOC) IM These control methods include adaptive and robust control [9,10], variable structure control [11], Sliding Mode Control (SMC) [12,13], Fuzzy Logic Control (FLC) [14,15], Neural Network (NN) [16,17], Hybrid Controller (HC) [18], a genetic algorithm based on supervisory control [19], Model Reference Systems (MRAS) control [20], and optimal control [21].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
