Aiming at the chaos problem of permanent magnet linear synchronous motor in direct-drive wave power generation system, based on the ideal chaotic model with increased rotor edge effect, the permanent magnet linear synchronous motor system chaotic system was analyzed and a new sliding mode compound chaos control strategy was proposed. This strategy compensates for the shortcomings of the sliding mode control lag and chattering by using the complementary advantages of compound control, and can correct system parameters in real time. By using Lyapunov stability criterion, it was proved that the global convergence of the system is consistent. The simulation results show that the composite chaos control strategy can rapidly disengage the chaotic state of the motor system, suppress system chattering, weaken the control overshoot phenomenon, and has strong robustness and high control precision. INDEX TERMS Blended chaos control, permanent magnet linear synchronous machine, largest Lyapunov exponents, end effect force.

To effectively solve the chaotic phenomenon problem in permanent magnet linear synchronous motor (PMLSM), this paper presents a novel control scheme combining radial basis function neural network (RBFNN), adaptive backstepping method, and particle swarm optimization (PSO) algorithm. By applying a feedback decoupling controller, a decoupled chaotic model of the PMLSM is constituted. In addition, in order to enhance the robustness of the system, the RBFNN is utilized to identify the uncertainties in PMLSM and the convergence of the overall closed-loop system, including unknown parameters is guaranteed based on the adaptive backstepping method. Moreover, the PSO is applied to promote the dynamic performance of the control system. The simulation results demonstrate the existence of chaotic phenomenon in the PMLSM. Besides, PSO-RBFNN controller that has strong robustness can make the motor out of chaos rapidly and smoothly, and identify the unknown parameters quickly and accurately.

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