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Optimal LQI and PID Synthesis for Speed Control of Switched Reluctance Motor Using Metaheuristic Techniques
International Journal of Control, Automation and Systems ( IF 3.2 ) Pub Date : 2020-08-05 , DOI: 10.1007/s12555-019-0911-x
Darielson A. Souza , Vinícius A. de Mesquita , Laurinda L. N. Reis , Wellington A. Silva , Josias G. Batista

At present, switched reluctance motors (SRM) become very interesting for many industrial applications in variable speed control. For such systems, the linear quadratic regulator with integral action (LQI) method is commonly used when using plants in state spaces due to its robustness and easy adjustment. All methods from the linear quadratic regulator (LQR) project provide a weighting of the Q and R matrices, which are manually adjusted to achieve the desired performance. The manual fine tuning of LQI controller parameters is a difficult task that requires a high level of domain knowledge. In this work, metaheuristic algorithms are explored to design the LQI controller and a comprehensive comparison is made between these algorithms and Proportional-Integral-Derivative (PID) controller as well as to select the best technique for the LQI controller design and adjustment of the Q and R parameters in SR Motor. Simulation and experimental results on a setup prototype are shown to validate the proposed control schemes. This paper has as main contributions the weighting of the parameters of the LQI in an optimized way and adjustment of the gains of the controller more quickly and the hybrid controller (LQI + GA) becomes more powerful in the sense of a possible extension of the control of a multivariable system.

中文翻译:

基于元启发式技术的开关磁阻电机速度控制的最优LQI和PID综合

目前,开关磁阻电机 (SRM) 在变速控制的许多工业应用中变得非常有趣。对于此类系统,在状态空间中使用植物时,通常使用积分作用线性二次调节器 (LQI) 方法,因为它具有稳健性和易于调整的特点。来自线性二次调节器 (LQR) 项目的所有方法都提供了 Q 和 R 矩阵的权重,这些矩阵经过手动调整以实现所需的性能。LQI 控制器参数的手动微调是一项艰巨的任务,需要高水平的领域知识。在这项工作中,探索了元启发式算法来设计 LQI 控制器,并在这些算法和比例积分微分 (PID) 控制器之间进行了全面比较,并选择了 LQI 控制器设计和 Q 和 R 参数调整的最佳技术。 SR马达。显示了对设置原型的模拟和实验结果,以验证所提出的控制方案。本文的主要贡献在于以优化的方式对 LQI 的参数进行加权,更快地调整控制器的增益,并且混合控制器(LQI + GA)在控制可能扩展的意义上变得更加强大。多变量系统。显示了对设置原型的模拟和实验结果,以验证所提出的控制方案。本文的主要贡献在于以优化的方式对 LQI 的参数进行加权,更快地调整控制器的增益,并且混合控制器(LQI + GA)在控制可能扩展的意义上变得更加强大。多变量系统。显示了对设置原型的模拟和实验结果,以验证所提出的控制方案。本文的主要贡献在于以优化的方式对 LQI 的参数进行加权,更快地调整控制器的增益,并且混合控制器(LQI + GA)在控制可能扩展的意义上变得更加强大。多变量系统。
更新日期:2020-08-05
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