This paper proposed a multiple-node hormone regulation neuroendocrine-proportional-integration- differential (MnHR-NEPID) controller based on adaptive safe experimentation Dynamics (ASED) for nonlinear multi-input-multi-output (MIMO) systems. In the existing neuroendocrine-PID (NEPID) controller of the single-input-single-output (SISO) system, only a single node of hormone regulation is used due to a single control variable. Meanwhile, in the MIMO system, since having many control variables, it is worth introducing an MnHR-NEPID for better controller performance by prioritizing each node's control regulation from their level of error. In particular, instead of considering its own hormone regulation, each node's hormone regulation is also generated based on the change of error from other control variables or nodes if the error of that corresponding control variable exceeds the given error threshold. Here, the relation between hormone regulation and the change of error is adopted based on the normalized Gaussian function. As a result, better prioritize control regulation with heightened control accuracy can be subsequently achieved due to interactions between multiple nodes of hormones available for the nonlinear MIMO system. The performance error and control input for several nonlinear MIMO systems were further tracked to assess the proposed controller's performance. Standard PID, NEPID, and sigmoid-based secretion rate neuroendocrine-PID (SbSR-NEPID) controllers were also compared. Thus, this simulation work has acknowledged higher accuracy within the design of an MnHR-NEPID controller, with comparatively superior objective function and total norm of error resulted in better control performance.

本文针对非线性多输入多输出 (MIMO) 系统提出了一种基于自适应安全实验动力学 (ASED) 的多节点激素调节神经内分泌比例积分微分 (MnHR-NEPID) 控制器。在现有的单输入单输出（SISO）系统的神经内分泌-PID（NEPID）控制器中，由于单个控制变量，仅使用单个激素调节节点。同时，在 MIMO 系统中，由于具有许多控制变量，因此值得引入 MnHR-NEPID，通过根据每个节点的误差水平对每个节点的控制调节进行优先级排序来获得更好的控制器性能。特别是，每个节点不考虑自身的激素调节，而是 如果相应控制变量的误差超过给定的误差阈值，则也会根据来自其他控制变量或节点的误差变化生成激素调节。这里，激素调节和误差变化之间的关系是基于归一化高斯函数采用的。因此，由于可用于非线性 MIMO 系统的激素的多个节点之间的相互作用，随后可以实现具有更高控制精度的更好的优先级控制调节。进一步跟踪了几个非线性 MIMO 系统的性能误差和控制输入，以评估所提出的控制器的性能。还比较了标准 PID、NEPID 和基于乙状结肠的分泌率神经内分泌-PID (SbSR-NEPID) 控制器。因此，