恒功率负载(constant power loads, CPL)的负阻抗特性是引起前端独立运行能够稳定的变换器带负载时却失去稳定的主要原因,由于电路状态方程的非线性,难以得到状态变量的时域解来判断系统稳定性。基于小信号线性化、以特征根的分布来评...恒功率负载(constant power loads, CPL)的负阻抗特性是引起前端独立运行能够稳定的变换器带负载时却失去稳定的主要原因,由于电路状态方程的非线性,难以得到状态变量的时域解来判断系统稳定性。基于小信号线性化、以特征根的分布来评估系统稳定性的方法,需要在平衡点处线性化并以数值方法求解特征根,且无法描述出大信号扰动时的渐近稳定范围。针对并网型三电平整流器直接带恒功率负载和以LC滤波器连接恒功率负载的2种系统,使用Takagi-Sugeno(TS)模糊推理模型方法建立考虑主电路参数和控制器参数的全阶模型,以线性矩阵不等式(linear matrix inequality,LMI)的半正定规划是否能够求解作为系统稳定判据,从而能够分析系统参数与稳定区间之间的关系。同时构造的Lyapunov备选函数能够绘制出稳定吸引域(stability domain of attraction,DOA),实现大扰动情况下的稳定性分析。仿真和实验验证了该方法的有效性和实用性。展开更多
In this paper, an approach to the control of continuous-time chaotic systems is proposed using the Takagi-Sugeno （TS） fuzzy model and adaptive adjustment. Sufficient conditions are derived to guarantee chaos control...In this paper, an approach to the control of continuous-time chaotic systems is proposed using the Takagi-Sugeno （TS） fuzzy model and adaptive adjustment. Sufficient conditions are derived to guarantee chaos control from Lyapunov stability theory. The proposed approach offers a systematic design procedure for stabilizing a large class of chaotic systems in the literature about chaos research. The simulation results on Rossler＇s system verify the effectiveness of the proposed methods.展开更多
In this paper, the global stability of Takagi-Sugeno （TS） uncertain stochastic fuzzy recurrent neural networks with discrete and distributed time-varying delays （TSUSFRNNs） is considered. A novel LMI-based stabili...In this paper, the global stability of Takagi-Sugeno （TS） uncertain stochastic fuzzy recurrent neural networks with discrete and distributed time-varying delays （TSUSFRNNs） is considered. A novel LMI-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of TSUSFRNNs. The proposed stability conditions are demonstrated through numerical examples. Furthermore, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is removed. Comparison results are demonstrated to show that the proposed method is more able to guarantee the widest stability region than the other methods available in the existing literature.展开更多
In this paper, we design a fuzzy rule-based support vector regression system. The proposed system utilizes the advantages of fuzzy model and support vector regression to extract support vectors to generate fuzzy if-th...In this paper, we design a fuzzy rule-based support vector regression system. The proposed system utilizes the advantages of fuzzy model and support vector regression to extract support vectors to generate fuzzy if-then rules from the training data set. Based on the first-order hnear Tagaki-Sugeno （TS） model, the structure of rules is identified by the support vector regression and then the consequent parameters of rules are tuned by the global least squares method. Our model is applied to the real world regression task. The simulation results gives promising performances in terms of a set of fuzzy hales, which can be easily interpreted by humans.展开更多
文摘恒功率负载(constant power loads, CPL)的负阻抗特性是引起前端独立运行能够稳定的变换器带负载时却失去稳定的主要原因,由于电路状态方程的非线性,难以得到状态变量的时域解来判断系统稳定性。基于小信号线性化、以特征根的分布来评估系统稳定性的方法,需要在平衡点处线性化并以数值方法求解特征根,且无法描述出大信号扰动时的渐近稳定范围。针对并网型三电平整流器直接带恒功率负载和以LC滤波器连接恒功率负载的2种系统,使用Takagi-Sugeno(TS)模糊推理模型方法建立考虑主电路参数和控制器参数的全阶模型,以线性矩阵不等式(linear matrix inequality,LMI)的半正定规划是否能够求解作为系统稳定判据,从而能够分析系统参数与稳定区间之间的关系。同时构造的Lyapunov备选函数能够绘制出稳定吸引域(stability domain of attraction,DOA),实现大扰动情况下的稳定性分析。仿真和实验验证了该方法的有效性和实用性。
基金Project supported by the Natural Science Foundation of Yangzhou University of China （Grant No KK0513109）.
文摘In this paper, an approach to the control of continuous-time chaotic systems is proposed using the Takagi-Sugeno （TS） fuzzy model and adaptive adjustment. Sufficient conditions are derived to guarantee chaos control from Lyapunov stability theory. The proposed approach offers a systematic design procedure for stabilizing a large class of chaotic systems in the literature about chaos research. The simulation results on Rossler＇s system verify the effectiveness of the proposed methods.
文摘In this paper, the global stability of Takagi-Sugeno （TS） uncertain stochastic fuzzy recurrent neural networks with discrete and distributed time-varying delays （TSUSFRNNs） is considered. A novel LMI-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of TSUSFRNNs. The proposed stability conditions are demonstrated through numerical examples. Furthermore, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is removed. Comparison results are demonstrated to show that the proposed method is more able to guarantee the widest stability region than the other methods available in the existing literature.
基金This paper was supported bythe National High Technology Researchand Development Programof China863program(No .2002AA412010)the Technologydevelopment Programofthe Science and Technology Ministry of China (No .2003EG113016) the key discipline construction programof Beijing Municipalcommission of education.
文摘In this paper, we design a fuzzy rule-based support vector regression system. The proposed system utilizes the advantages of fuzzy model and support vector regression to extract support vectors to generate fuzzy if-then rules from the training data set. Based on the first-order hnear Tagaki-Sugeno （TS） model, the structure of rules is identified by the support vector regression and then the consequent parameters of rules are tuned by the global least squares method. Our model is applied to the real world regression task. The simulation results gives promising performances in terms of a set of fuzzy hales, which can be easily interpreted by humans.
