Command Filtered Adaptive Fuzzy Control for Induction Motors With Iron Losses and Stochastic Disturbances via Reduced-Order Observer
Jinpeng Yu, Qing‐Guo Wang, Guangna Wang, Panpan Ma, Jiapeng Liu
Abstract
This brief presents a fuzzy adaptive tracking control method based on command filtering and reduced-order observer for induction motor (IM) with iron losses and stochastic disturbances. Firstly, the rotor position and angular velocity of IM are estimated by a reduced-order observer. Then, the stochastic nonlinear functions are approximated by the fuzzy logic systems. In addition, the complexity of computation in traditional backstepping design is overcome by exploiting the command filtered technique. The results of the simulation and experiment shown that the presented control method can track the desired signal effectively.
Topics & Concepts
Control theory (sociology)BacksteppingObserver (physics)Fuzzy logicInduction motorComputationControl engineeringRotor (electric)Nonlinear systemComputer scienceMathematicsAdaptive controlEngineeringControl (management)Artificial intelligenceAlgorithmElectrical engineeringMechanical engineeringPhysicsVoltageQuantum mechanicsAdaptive Control of Nonlinear SystemsSensorless Control of Electric MotorsMagnetic Bearings and Levitation Dynamics