A HYBRID INTELLIGENT CONTROL FRAMEWORK WITH REAL-TIME VALIDATION FOR INDUCTION MOTOR DRIVES
DOI:
https://doi.org/10.59277/RRST-EE.2026.1.8Keywords:
Backstepping, Radial basis function neural networks, Higher-order non-singular terminal sliding-mode control, Harris hawks’ optimization, Chaotic Lévy flightsAbstract
This paper proposes a hybrid speed–current control framework for high-performance induction motor drives under field-oriented control. The outer speed loop combines Backstepping, Radial Basis Function neural approximation, and high-order sliding mode compensation, where Backstepping provides a Lyapunov-based nonlinear structure, the RBF network estimates lumped uncertainties online, and the HOSM term ensures finite-time disturbance rejection and fast convergence. An enhanced Harris Hawks Optimization with chaotic Lévy flights is employed to optimally tune the controller parameters. In the inner loop, a Higher-Order Non-Singular Terminal Sliding Mode controller regulates stator currents, guaranteeing finite-time tracking, reduced chattering, and robustness against parameter variations and inverter nonlinearities. Lyapunov analysis confirms uniform ultimate boundedness of the speed loop and finite-time convergence of the current loop. The effectiveness of the proposed strategy is verified through MATLAB/Simulink simulations and real-time implementation on the OPAL-RT OP5707XG platform, demonstrating superior dynamic performance and disturbance rejection compared with PI- and conventional sliding-mode-based schemes.
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