A Novel Neural Dynamics Controller for Weakening the Chaos of Permanent Magnet Synchronous Generator and Its Extended Application
针对永磁同步发电机系统出现混沌时的不稳定问题，提出一种自适应预定义时间鲁棒零化神经动力学控制器，利用投影同步削弱混沌，并应用于安全通信，保证信号及时性和通信抗干扰性。
The permanent magnet synchronous generator (PMSG) system becomes unstable when unpredicted chaos appears, and current approaches do not take how to lessen this chaos phenomenon into account. Motivated by the ability of projective synchronization (PS) to adjust the chaotic system trajectory, this research aims to use PS to reduce the chaos in PMSG system. For better control in the time estimation of PS and the robustness of systems, an adaptive predefined-time robust zeroing neural dynamic controller (APTRZNDC) for the PS between PMSG systems is proposed. In the process, an adaptive parameter determined by the system error is designed with the demand for higher convergence factor in the case of large error. In addition, a nonlinear activation function contributed to the predefined-time synchronization is created, making the upper bound of synchronization time independent of system initial states and parameters, except for a single predefined parameter. Moreover, essential theorems for the predefined-time PS and robustness under the APTRZNDC are supplied and validated. And better robustness of PMSG system with the APTRZNDC is demonstrated when compared with other controllers. Furthermore, the APTRZNDC is applied in secure communication via the PS of PMSG systems, which guarantees both the timeliness of signals and the immunity of communication.