کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4948481 | 1439613 | 2016 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Event-based input-constrained nonlinear Hâ state feedback with adaptive critic and neural implementation
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In this paper, the continuous-time input-constrained nonlinear Hâ state feedback control under event-based environment is investigated with adaptive critic designs and neural network implementation. The nonlinear Hâ control issue is regarded as a two-player zero-sum game that requires solving the Hamilton-Jacobi-Isaacs equation and the adaptive critic learning (ACL) method is adopted toward the event-based constrained optimal regulation. The novelty lies in that the event-based design framework is combined with the ACL technique, thereby carrying out the input-constrained nonlinear Hâ state feedback via adopting a non-quadratic utility function. The event-based optimal control law and the time-based worst-case disturbance law are derived approximately, by training an artificial neural network called a critic and eventually learning the optimal weight vector. Under the action of the event-based state feedback controller, the closed-loop system is constructed with uniformly ultimately bounded stability analysis. Simulation studies are included to verify the theoretical results as well as to illustrate the event-based Hâ control performance.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 214, 19 November 2016, Pages 848-856
Journal: Neurocomputing - Volume 214, 19 November 2016, Pages 848-856
نویسندگان
Ding Wang, Chaoxu Mu, Qichao Zhang, Derong Liu,