Convergence analysis and application of fuzzy-HDP for nonlinear discrete-time HJB systems
In this paper, a type of fuzzy system structure is applied to heuristic dynamic programming (HDP) algorithm to solve nonlinear discrete-time Hamilton–Jacobi–Bellman (DT-HJB) problems. The fuzzy system here is adopted as a 0-order T–S fuzzy system using triangle membership functions (MFs). The conver...
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Veröffentlicht in: | Neurocomputing (Amsterdam) 2015-02, Vol.149, p.124-131 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In this paper, a type of fuzzy system structure is applied to heuristic dynamic programming (HDP) algorithm to solve nonlinear discrete-time Hamilton–Jacobi–Bellman (DT-HJB) problems. The fuzzy system here is adopted as a 0-order T–S fuzzy system using triangle membership functions (MFs). The convergence of HDP and approximability of the multivariate 0-order T–S fuzzy system is analyzed in this paper. It is derived that the cost function and control policy of HDP can be iterated to the DT-HJB solution and optimal policy. The multivariate 0-order T–S (Tanaka–Sugeno) fuzzy system using triangle MFs is proven as a universal approximator, to guarantee the convergence of the Fuzzy-HDP mechanism. Some simulations are implemented to observe the performance of the proposed method both in mathematical solution and practical issue. It is concluded that Fuzzy-HDP outperforms traditional optimal control in more complex systems. |
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ISSN: | 0925-2312 1872-8286 |
DOI: | 10.1016/j.neucom.2013.11.055 |