Adaptive Integral Backstepping Controller for PMSM with AWPSO Parameters Optimization

Abstract

This article presents an adaptive integral backstepping controller (AIBC) for permanent magnet synchronous motors (PMSMs) with adaptive weight particle swarm optimization (AWPSO) parameters optimization. The integral terms of dq axis current following errors are introduced into the control law, and by constructing an appropriate Lyapunov function, the adaptive law with the differential term and the control law with the integral terms of the current error are derived to weaken the influence of internal parameters perturbation on current control. The AWPSO algorithm is used to optimize the parameters of the AIBC. Based on the analysis of single-objective optimization and multi-objective realization process, a method for transforming multi-objective optimization with convex Prato frontier into single-objective optimization is presented. By this method, a form of fitness function suitable for parameters optimization of backstepping controller is determined, and according to the theoretical derivation and large number of simulation results, the corresponding parameters of the optimization algorithm are set. By randomly adjusting the inertia weight and changing the acceleration factor, the algorithm can accelerate the convergence speed and solve the problem of parameters optimization of the AIBC. The feasibility and effectiveness of the proposed controller for PMSM are verified by simulation and experimental studies.

Modified backstepping control of IPMSM: Experimental tests

“…The time derivative of V 3 e 1 , e 2 , e 3 ð Þresulting from the substitution of equation (24) in equation ( 23) is…”

“…Depending on Lyapunov stability theory, the control law fulfilling the convergence condition of the Lyapunov function is obtained by constructing feedback control law and the Lyapunov function at the same time. 19,20 The theory of backstepping control has been successfully applied to many engineering fields such as motor drive because it simplifies the design process, achieves the complete decoupling and global stability of the IPMSM system. 9 Traditional backstepping is successfully applied to the control of IPMSM drive systems, which greatly simplifies the design process of the general system.…”

“…21 In order to improve the control performance, the integral of the tracking error is introduced in the backstepping control. The design of an integral backstepping controller (IBC) for the IPMSM control system has been reported in Nadji et al, 22 Lin et al 23 and Wang et al 24 This work introduces an IBC that can precisely follow the speed reference trajectory of the motor in the existence of load fluctuation and parameter uncertainty. The influence of the perturbation of the load torque and the variation of motor parameters can be considerably decreased by using integral action at each step to guarantee high precision speed control.…”

“…21 In order to improve the control performance, the integral of the tracking error is introduced in the backstepping control. The design of an integral backstepping controller (IBC) for the IPMSM control system has been reported in Nadji et al, 22 Lin et al 23 and Wang et al 24…”

Magnetic levitation planar motor and its adaptive contraction backstepping control for logistics system

“…11,12 The above methods are hard to meet the requirements of dynamic and steady-state performance of the logistics transmission system under time-varying conditions. The backstepping design method 13 is a method of system identification and model building, which has nice rapidity, 14,15 no overshoot under ideal conditions, and meets the requirements of system dynamics. [16][17][18] Besides, the integration of backstepping control and contraction control does not need to linearize the system at the equilibrium point, which is helping solve the modeling problem when the system parameters are not clear.…”