基于2型模糊集小脑模型的DC/DC变换器控制系统

随着新能源行业的不断发展,DC/DC变换器越来越多地被运用于各行各业,而DC/DC变换器在负载的效率直接影响到整个系统的效率。因此针对DC/DC变换器,以BUCK电路为例,设计了一种基于滑模区间的2型模糊小波的小脑模型关节控制器(T2WFCMAC)的控制系统。该系统包括主控制器和鲁棒补偿控制器。主控制器是T2WFCMAC,用于模拟理想控制器,鲁棒补偿控制器用于补偿主控制器和理想控制器之间的逼近误差。为了提高控制系统的鲁棒性,采用滑动模态超平面,利用梯度下降法得到了T2WFCMAC参数调整的自适应律。通过李雅普诺夫函数来验证控制系统的稳定性。最后,通过搭建试验平台,验证该方法在负载电阻变化情况下是否比传统PID控制和普通模糊控制更加有效。

DC/DC Converters Design Using a Type-2 Wavelet Fuzzy Cerebellar Model Articulation Controller

With the development of new energy industry,more and more DC/DC converters are used in all walks of life,and the efficiency of DC/DC converters directly affects the efficiency of the whole system when the load or voltage changes.In this paper,for DC/DC converter,taking BUCK circuit as an example,a control system of cerebellar model joint controller based on sliding mode interval 2 fuzzy wavelet is designed.The system consists of a master controller and a robust compensation controller.The main controller is T2WFCMAC,which is used to simulate the ideal controller,and the robust compensation controller is used to compensate the approximation error between the main controller and the ideal controller.In order to improve the robustness of the control system,sliding mode hyperplane is adopted,and the adaptive law of parameter adjustment of T2WFCMAC is obtained by gradient descent method.The stability of the control system is verified by Lyapunov function.Finally,the experimental platform is built to verify whether this method is more effective than the traditional PID control and the fuzzy control when the load resistance changes.