PID模糊控制在工业控制中是最广泛的一种控制方法,在一些复杂的实际系统中,应用分数阶PID模糊控制器在整定系统参数性能上优于整数模糊控制器。分数阶模糊控制器具有较多的控制参数,这些控制参数直接影响了模糊控制器的性能。用传统的...PID模糊控制在工业控制中是最广泛的一种控制方法,在一些复杂的实际系统中,应用分数阶PID模糊控制器在整定系统参数性能上优于整数模糊控制器。分数阶模糊控制器具有较多的控制参数,这些控制参数直接影响了模糊控制器的性能。用传统的算法校准分数阶模糊控制器并不能得到最佳的参数值,而且标定参数的过程较为复杂。因此提出用灰狼优化算法(Grey Wolf Optimizer,GWO)优化分数阶模糊控制器的参数。将基于灰狼优化算法的分数阶模糊控制器优化方法与其他五种典型的基于群智能的优化方法进行了比较。实验结果表明,该方法的控制效果更好。展开更多
Internal model control （IMC） yields very good performance for set point tracking, but gives sluggish response for disturbance rejection problem. A two-degree-of-freedom IMC （2DOF-IMC） has been developed to overcom...Internal model control （IMC） yields very good performance for set point tracking, but gives sluggish response for disturbance rejection problem. A two-degree-of-freedom IMC （2DOF-IMC） has been developed to overcome the weakness. However, the setting of parameter becomes a complicated matter if there is an uncertainty model. The present study proposes a new tuning method for the controller. The proposed tuning method consists of three steps. Firstly, the worst case of the model uncertainty is determined. Secondly, the parameter of set point con- troller using maximum peak （Mp） criteria is specified, and finally, the parameter of the disturbance rejection con- troller using gain margin （GM） criteria is obtained. The proposed method is denoted as Mp-GM tuning method. The effectiveness of Mp-GM tuning method has evaluated and compared with IMC-controller tuning program （IMCTUNE） as bench mark. The evaluation and comparison have been done through the simulation on a number of first order plus dead time （FOPDT） and higher order processes. The FOPDT process tested includes processes with controllability ratio in the range 0.7 to 2.5. The higher processes include second order with underdarnped and third order with nonminimum phase processes. Although the two of higher order processes are considered as difficult processes, the proposed Mp-GM tuning method are able to obtain the good controller parameter even under process uncertainties.展开更多
文摘PID模糊控制在工业控制中是最广泛的一种控制方法,在一些复杂的实际系统中,应用分数阶PID模糊控制器在整定系统参数性能上优于整数模糊控制器。分数阶模糊控制器具有较多的控制参数,这些控制参数直接影响了模糊控制器的性能。用传统的算法校准分数阶模糊控制器并不能得到最佳的参数值,而且标定参数的过程较为复杂。因此提出用灰狼优化算法(Grey Wolf Optimizer,GWO)优化分数阶模糊控制器的参数。将基于灰狼优化算法的分数阶模糊控制器优化方法与其他五种典型的基于群智能的优化方法进行了比较。实验结果表明,该方法的控制效果更好。
基金Supported by Postgraduate Fellowship of UMP,Fundamental Research Grant Scheme of Malaysia(GRS070120)Joint Research Grant between Universiti Malaysia Pahang (UMP) and Institut Teknologi Sepuluh Nopember (ITS) Surabaya
文摘Internal model control （IMC） yields very good performance for set point tracking, but gives sluggish response for disturbance rejection problem. A two-degree-of-freedom IMC （2DOF-IMC） has been developed to overcome the weakness. However, the setting of parameter becomes a complicated matter if there is an uncertainty model. The present study proposes a new tuning method for the controller. The proposed tuning method consists of three steps. Firstly, the worst case of the model uncertainty is determined. Secondly, the parameter of set point con- troller using maximum peak （Mp） criteria is specified, and finally, the parameter of the disturbance rejection con- troller using gain margin （GM） criteria is obtained. The proposed method is denoted as Mp-GM tuning method. The effectiveness of Mp-GM tuning method has evaluated and compared with IMC-controller tuning program （IMCTUNE） as bench mark. The evaluation and comparison have been done through the simulation on a number of first order plus dead time （FOPDT） and higher order processes. The FOPDT process tested includes processes with controllability ratio in the range 0.7 to 2.5. The higher processes include second order with underdarnped and third order with nonminimum phase processes. Although the two of higher order processes are considered as difficult processes, the proposed Mp-GM tuning method are able to obtain the good controller parameter even under process uncertainties.
