Abstract: Aiming at robust control of six-phase copper rotor induction motors（SpCRIM）under uncertain

disturbances，a new backstepping control strategy based on advanced ant colony optimized（AACO）recursive

Romanovski polynomial neural network（RRoPNN）was proposed. Based on the theory of backstepping control

theory，the control law for SpCRIM was firstly designed，and an improved RRoPNN with adaptive law was proposed

to estimate the lump uncertainty in the backstepping control law. The error estimation law was then designed to

compensate the network observation error and to realize on-line parameter adjustment. In order to prevent precocity and accelerate the convergence rate of the proposed RRoPNN，an AACO algorithm was proposed to adjust the learning rate of RRoPNN connection weights. The robustness of the proposed control method was proved based on Lyapunov stability theory. Finally，the position tracking performance of the proposed controller was verified by experiments and compared with the classical PI controller and the switch function based backstepping controller. The results show that the proposed control method has better position tracking accuracy and robustness.

      Key words: six-phase induction motor ；polynomial neural network ；backstepping control ；ant colony

optimization algorithm；robust control