In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE （differential evolution） algorithm and exploitation capability of Nelder-...In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE （differential evolution） algorithm and exploitation capability of Nelder-Mead simplex method is presented （HISADE-NMS）. The DE has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters as number of particles （NP）, scaling factor （F） and crossover control （CR）, which are kept fixed throughout the entire evolutionary process. However, these control parameters are very sensitive to the setting of the control parameters based on their experiments. The value of control parameters depends on the characteristics of each objective function, therefore, we have to tune their value in each problem that mean it will take too long time to perform. In the new manner, we present a new version of the DE algorithm for obtaining self-adaptive control parameter settings. Some modifications are imposed on DE to improve its capability and efficiency while being hybridized with Nelder-Mead simplex method. To valid the robustness of new hybrid algorithm, we apply it to solve some examples of structural optimization constraints.展开更多
Safety-critical applications such as the independently driving systems of electric vehicle （EV） require a high degree of reliability. The controller area network （CAN） is used extensively in the control sectors. A...Safety-critical applications such as the independently driving systems of electric vehicle （EV） require a high degree of reliability. The controller area network （CAN） is used extensively in the control sectors. A new real-time and reliable scheduling algorithm based on time-triggered scheduler with a focus on the CAN-based distributed control systems for independently driving EV is exploited. A distributed control network model for a dual-wheel independendy driving EV is established. The timing and reliabili- ty analysis in the worst case with the algorithm is used to evaluate the predictability and dependability and the simulation based on the algorithm with CANoe software is designed. The results indicate the algorithm is more predicable and dependable.展开更多
文摘In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE （differential evolution） algorithm and exploitation capability of Nelder-Mead simplex method is presented （HISADE-NMS）. The DE has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters as number of particles （NP）, scaling factor （F） and crossover control （CR）, which are kept fixed throughout the entire evolutionary process. However, these control parameters are very sensitive to the setting of the control parameters based on their experiments. The value of control parameters depends on the characteristics of each objective function, therefore, we have to tune their value in each problem that mean it will take too long time to perform. In the new manner, we present a new version of the DE algorithm for obtaining self-adaptive control parameter settings. Some modifications are imposed on DE to improve its capability and efficiency while being hybridized with Nelder-Mead simplex method. To valid the robustness of new hybrid algorithm, we apply it to solve some examples of structural optimization constraints.
基金Supported by the National High Technology Research and Development Programme of China （No. （2008AA11 A146 ）, China Postdoctoral Science Foundation （20090450298）.
文摘Safety-critical applications such as the independently driving systems of electric vehicle （EV） require a high degree of reliability. The controller area network （CAN） is used extensively in the control sectors. A new real-time and reliable scheduling algorithm based on time-triggered scheduler with a focus on the CAN-based distributed control systems for independently driving EV is exploited. A distributed control network model for a dual-wheel independendy driving EV is established. The timing and reliabili- ty analysis in the worst case with the algorithm is used to evaluate the predictability and dependability and the simulation based on the algorithm with CANoe software is designed. The results indicate the algorithm is more predicable and dependable.
