Active Disturbance Rejection Control (ADRC) emerged as a promising control solution in various engineering domains. However, increased ADRC order makes it difficult to implement and tune in practice. On the other hand, Reduced-order ADRC (RADRC) structure solves this issue with the appropriate tuning of its parameters to achieve the desired performance. This paper aims to develop analytical tuning rules for RADRC for processes approximated as First-order plus dead-time models (FOPDT). These rules meet the conflicting goals of tracking and disturbance rejection restricted by robustness specification. The tuning rules are derived based on a multi-stage approach. In the first stage, the tuning problem is formulated as a multi-objective optimization problem with appropriate constraints. A Multi-objective Quasi-Oppositional Rao-1 (MOQO-Rao-1) Algorithm solves the optimization problem to produce a collection of Pareto-optimal solutions (alternatives) in the second stage. In the third stage, using the Best-Worst based PROMETHEE method, the best one is chosen among the available options. Finally, using linear regression, analytical tuning rules are developed. Separate tuning rules are proposed for lag-dominated and dead-time dominated cases. Simulation experiments on benchmark industrial processes are performed, and the findings assess the efficacy of the suggested tuning rules relative to the methods recently published. The proposed tuning rules are experimentally validated to assess their applicability in the practical scenario. Besides, the closed-loop system’s stability with the suggested tuning rules is confirmed by the small-gain theorem and the dual-locus process.

主动抗扰控制 (ADRC) 成为各种工程领域中一种很有前途的控制解决方案。然而，增加的 ADRC 阶数使得在实践中难以实施和调整。另一方面，降阶 ADRC (RADRC) 结构通过适当调整其参数来解决此问题，以实现所需的性能。本文旨在为近似为一阶加死区时间模型 (FOPDT) 的过程开发 RADRC 的分析调整规则。这些规则满足了鲁棒性规范限制的跟踪和干扰抑制的冲突目标。调整规则是基于多阶段方法得出的。在第一阶段，调整问题被表述为具有适当约束的多目标优化问题。多目标准对立 Rao-1 (MOQO-Rao-1) 算法解决了优化问题，以在第二阶段生成一组帕累托最优解（替代方案）。在第三阶段，使用基于最佳-最差的 PROMETHEE 方法，从可用选项中选择最好的一个。最后，使用线性回归，开发了分析调整规则。针对滞后主导和死区时间主导的情况提出了单独的调整规则。对基准工业过程进行了模拟实验，结果评估了建议的调整规则相对于最近发布的方法的有效性。建议的调整规则经过实验验证，以评估它们在实际场景中的适用性。除了，