In this paper, tracking synchronization for coupled reaction-diffusion neural networks with parameter mismatches is investigated. For such a networked control system, only local neighbor information is used to compensate the mismatch characteristic termed as parameter mismatch, uncertainty or external disturbance. Different from the general boundedness hypothesis, the parameter mismatches are permitted to be unbounded. For the known parameter mismatches, parameter-dependent controller and parameter-independent adaptive controller are respectively designed. While for fully unknown network parameters and parameter mismatches, a distributed adaptive controller is proposed. By means of partial differential equation theories and differential inequality techniques, the tracking synchronization errors driven by these nonlinear controllers are proved to be uniformly ultimately bounded and exponentially convergent to some adjustable bounded domains. Finally, three numerical examples are given to test the effectiveness of the proposed controllers.

中文翻译：

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参数不匹配的耦合反应扩散神经网络的自适应跟踪同步。

本文研究了参数不匹配的耦合反应扩散神经网络的跟踪同步问题。对于这种网络控制系统，仅使用本地邻居信息来补偿被称为参数不匹配，不确定性或外部干扰的不匹配特性。与一般的有界性假设不同，参数不匹配是无界的。对于已知的参数失配，分别设计了参数相关的控制器和参数独立的自适应控制器。对于完全未知的网络参数和参数失配，提出了一种分布式自适应控制器。通过偏微分方程理论和微分不等式技术，由这些非线性控制器驱动的跟踪同步误差被证明是一致的最终有界且指数收敛于一些可调有界域。最后，给出了三个数值示例来测试所提出控制器的有效性。