A modification of evolutionary programming or evolution strategies for ndimensional global optimization is proposed. Based on the ergodicity and inherentrandomness of chaos, the main characteristic of the new algorith...A modification of evolutionary programming or evolution strategies for ndimensional global optimization is proposed. Based on the ergodicity and inherentrandomness of chaos, the main characteristic of the new algorithm which includes two phases is that chaotic behavior is exploited to conduct a rough search of the problem space in order to find the promising individuals in Phase I. Adjustment strategy of steplength and intensive searches in Phase II are employed. The population sequences generated by the algorithm asymptotically converge to global optimal solutions with probability one. The proposed algorithm is applied to several typical test problems. Numerical results illustrate that this algorithm can more efficiently solve complex global optimization problems than evolutionary programming and evolution strategies in most cases.展开更多
The output power of the photovoltaic （PV） array changes with the change in external environment and load. Therefore, maximum power point tracking （MPPT） technology is needed to maximize the efficiency of the PV de...The output power of the photovoltaic （PV） array changes with the change in external environment and load. Therefore, maximum power point tracking （MPPT） technology is needed to maximize the efficiency of the PV device. At present, existing methods have realized MPPT to some extent. However, the tracking precision and speed remain to be improved. In the current paper, the chaos search theory is first applied on the MPPT technology of the PV system. The chaos search algorithm based on dual carrier increases the adequacy of chaos search and overcomes the blindness of the traditional chaos search, thereby improving the search efficiency. Comparative tests show that the proposed method can quickly and accurately track the step response, and can obtain better optimization results. The simulation and experimentalresults show the effectiveness and good performance of the proposed method.展开更多
文摘A modification of evolutionary programming or evolution strategies for ndimensional global optimization is proposed. Based on the ergodicity and inherentrandomness of chaos, the main characteristic of the new algorithm which includes two phases is that chaotic behavior is exploited to conduct a rough search of the problem space in order to find the promising individuals in Phase I. Adjustment strategy of steplength and intensive searches in Phase II are employed. The population sequences generated by the algorithm asymptotically converge to global optimal solutions with probability one. The proposed algorithm is applied to several typical test problems. Numerical results illustrate that this algorithm can more efficiently solve complex global optimization problems than evolutionary programming and evolution strategies in most cases.
基金supported by the Scientific Research Foundation of State Key Laboratory of Power Transmission Equipment and System Security (No.2007DA10512709211)the Fundamental Research Funds for the Central Universities (No. CDJXS10151151)
文摘The output power of the photovoltaic （PV） array changes with the change in external environment and load. Therefore, maximum power point tracking （MPPT） technology is needed to maximize the efficiency of the PV device. At present, existing methods have realized MPPT to some extent. However, the tracking precision and speed remain to be improved. In the current paper, the chaos search theory is first applied on the MPPT technology of the PV system. The chaos search algorithm based on dual carrier increases the adequacy of chaos search and overcomes the blindness of the traditional chaos search, thereby improving the search efficiency. Comparative tests show that the proposed method can quickly and accurately track the step response, and can obtain better optimization results. The simulation and experimentalresults show the effectiveness and good performance of the proposed method.
