标题:Multiobjective control for nonlinear stochastic Poisson jump-diffusion systems via T-S fuzzy interpolation and Pareto optimal scheme
作者:Wu, Chien-Feng ;Chen, Bor-Sen ;Zhang, Weihai
作者机构:[Wu, Chien-Feng ;Chen, Bor-Sen ] Department of Electrical Engineering, National Tsing Hua University, Hsinchu; 30013, Taiwan;[Zhang, Weihai ] The Coll 更多
通讯作者:Chen, BorSen
来源:Fuzzy Sets and Systems
出版年:2020
卷:385
页码:148-168
DOI:10.1016/j.fss.2019.02.020
摘要:Unlike the conventional mixed H2/H control design method, this study provides a multiobjective fuzzy control design method for nonlinear stochastic Poisson jump-diffusion systems to simultaneously achieve optimal cost and robustness performance in the Pareto optimal sense via the proposed evolutionary algorithm. For a nonlinear stochastic Poisson jump-diffusion system, the Poisson jumps cause its system behaviors to change intensely and discontinuously. To design an efficient controller for a nonlinear stochastic jump-diffusion system is much more difficult. On the other hand, the H2 and H performance indices generally conflict with each other and can be regarded as a multiobjective optimization problem (MOP). It is not easy to directly solve this MOP, owing to (i) the Pareto front of the MOP is difficult to obtain through direct calculation; (ii) the MOP is a Hamilton-Jacobi-Inequalities (HJIs)-constrained MOP. To address these issues, we use Takagi-Sugeno (T-S) interpolation scheme to transform the HJIs-constrained MOP into a linear matrix inequality (LMI)-constrained MOP. Then, we employ the proposed LMI-constrained multiobjective optimization evolutionary algorithm (LMI-constrained MOEA) to efficiently search for the Pareto optimal solution, from which the designer can select one kind of design according to their preference. Finally, a design example is given to illustrate the design procedure and to verify our results.
© 2019 Elsevier B.V.
收录类别:EI
资源类型:期刊论文
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