Abstract The problem of parameters uncertainty of the controlled system is one of the most challenges faces controller designers. This work proposes a combination between the Particle Swarm Optimization (PSO) method and Kharitonov's theorem in a single optimization process as a robust control design procedure against parameters uncertainty. This approach is realized by integrating various constraints functional and robustness in the controller design against uncertainty conditions, the method presents a comprehensive evaluation to validate performance and robustness. The decoupling controller is presented in this work to design the Field Oriented Control (FOC) as an efficient controller of the Induction Motor (IM). The proposed procedure works in offline mode to obtain the optimum controller's gains which having the certificate of Kharitonov's stability theorem. Simulation results demonstrate an excellent harmonize between system performance and stability in various operation conditions. A high degree of stability correlated excellent speed tracking against parameters variation is illustrated in results. A comparison study with a nominal PI-PSO simulation shows the superior performance of the proposed design in rising time and overshoot.

中文翻译：

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结合PSO和Kharitonov定理的感应电机鲁棒解耦控制器

摘要 被控系统参数的不确定性问题是控制器设计者面临的最大挑战之一。这项工作提出了粒子群优化 (PSO) 方法和 Kharitonov 定理在单个优化过程中的组合，作为针对参数不确定性的稳健控制设计程序。这种方法是通过在控制器设计中针对不确定性条件集成各种约束函数和鲁棒性来实现的，该方法提供了一个综合评估来验证性能和鲁棒性。在这项工作中提出了去耦控制器，以将磁场定向控制 (FOC) 设计为感应电机 (IM) 的有效控制器。建议的程序在离线模式下工作以获得最佳控制器' s 的增益得到了 Kharitonov 稳定性定理的证明。仿真结果表明，在各种操作条件下，系统性能和稳定性之间具有极好的协调性。结果中说明了与参数变化相关的出色速度跟踪的高度稳定性。与标称 PI-PSO 仿真的比较研究表明，所提出的设计在上升时间和过冲方面具有卓越的性能。