Xiao Liang, Zhao Lv, Jin Jie
Sanya Institute of Hunan University of Science and Technology, Sanya 572024, China.
School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China.
Sensors (Basel). 2025 Sep 1;25(17):5394. doi: 10.3390/s25175394.
Chaotic systems, characterized by extreme sensitivity to initial conditions and complex dynamical behaviors, exhibit significant potential for applications in various fields. Effective control of chaotic system synchronization is particularly crucial in sensor-related applications. This paper proposes a preset-time fuzzy zeroing neural network (PTCFZNN) model based on Takagi-Sugeno fuzzy control to achieve chaotic synchronization in aperiodic parameter exciting chaotic systems. The designed PTCFZNN model accurately handles the complex dynamic variations inherent in chaotic systems, overcoming the challenges posed by aperiodic parameter excitation to achieve synchronization. Additionally, field-programmable gate array (FPGA) verification experiments successfully implemented the PTCFZNN-based chaotic system synchronization control on hardware platforms, confirming its feasibility for practical engineering applications. Furthermore, experimental studies on chaos-masking communication applications of the PTCFZNN-based chaotic system synchronization further validate its effectiveness in enhancing communication confidentiality and anti-jamming capability, highlighting its important application value for securing sensor data transmission.
混沌系统以对初始条件极度敏感和复杂的动力学行为为特征，在各个领域展现出巨大的应用潜力。在与传感器相关的应用中，有效控制混沌系统同步尤为关键。本文提出了一种基于高木-关野模糊控制的预设时间模糊归零神经网络（PTCFZNN）模型，以实现非周期参数激励混沌系统中的混沌同步。所设计的PTCFZNN模型准确地处理了混沌系统中固有的复杂动态变化，克服了非周期参数激励带来的挑战以实现同步。此外，现场可编程门阵列（FPGA）验证实验在硬件平台上成功实现了基于PTCFZNN的混沌系统同步控制，证实了其在实际工程应用中的可行性。此外，对基于PTCFZNN的混沌系统同步的混沌掩盖通信应用的实验研究进一步验证了其在增强通信保密性和抗干扰能力方面的有效性，突出了其在保障传感器数据传输方面的重要应用价值。
