Servo motor and motion control using digital signal processors
Servo motor and motion control using digital signal processors
Torque regulation of induction motors
Automatica (Journal of IFAC)
Control of Electrical Drives
Adaptive control of robot manipulators using fuzzy logic systems under actuator constraints
Fuzzy Sets and Systems
Adaptive control of robot manipulator using fuzzy compensator
IEEE Transactions on Fuzzy Systems
Speed control of induction motors using a novel fuzzy sliding-mode structure
IEEE Transactions on Fuzzy Systems
Adaptive neural network control for strict-feedback nonlinear systems using backstepping design
Automatica (Journal of IFAC)
Robust backstepping control of induction motors using neural networks
IEEE Transactions on Neural Networks
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In this paper, we present an adaptive tracking control for the induction motors using multi-input--multi-output fuzzy logic systems (MIMO-FLS). The rotor resistance and load torque of the system dynamics are considered to be unknown. The structure of the feedback control law is derived based on backstepping method. The unknown nonlinear functions of the controller are approximated using MIMO-FLS. An on-line parameter tuning algorithm is presented based on Lyapunov stability theorem. In the proposed control algorithm, the rotor flux measurement is not needed. Moreover, an amplitude current limitation technique is adopted to protect the motor against excessive magnitudes of stator currents. The effectiveness of the control scheme has been validated based on simulation results.