Optimization of RST Controller for Speed Control of Linear Induction Motor Using Genetic Algorithm

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Background: In this study, a new model of linear induction motor, along with the impact of end-effect on motor performance, is proposed. Moreover, a new strategy of control approach based on the polynomial RST controller is suggested and investigated. Objective: The proposed approach can provide a robust control strategy and overcome the limitations imposed by the proportional-integral (PI) regulator in the FOC technique. RST controller has a two-degree of freedom structure and consists of three polynomials, namely R, S and T, which are determined by the pole placement method and resolving of a Diophantine equation. Despite this, the implementation of this method is usually difficult and becomes more complicated with the complexity of the controlled plants. Methods: This study proposes the genetic algorithm (GA) optimization strategy for tuning RST controller parameters (adjust the controller coefficients) in order to achieve an adequate response time by minimizing the different objective functions, such as steady-state error, settling time, and rise time. Results: The accuracy and control performance of the proposed technique are checked and validated using Matlab /Simulink environment software tool. Simulation results reported that the proposed method (RST-GA) could provide robust solutions with perfect reference tracking and efficient disturbance rejection. Conclusion: These significant results make the proposed approach a promising technique for the design of a high-performance controller, which is highly suitable for industrial and electrical applications.