Improved Genetic Algorithm for Finite-horizon Optimal Control of Nonlinear Systems
Proceedings - 25th International Conference on Systems Engineering, ICSEng 2017
Institute of Electrical and Electronics Engineers Inc.
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Optimal control has been a very attractive and desirable feature for many dynamic and static systems, An effective online technique for finite-horizon nonlinear control problem is offered in this paper. The idea of the proposed technique is to combine the differential State Dependent Riccati equation filter algorithm and the finite-horizon SDRE technique. Genetic algorithm is used to calculate the optimal weighting matrices. Unlike the linear techniques that are used for linearized systems, the proposed technique is effective for wide range of operating points. Simulation results are given to demonstrate the effectiveness of the offered technique. © 2017 IEEE.
Improved Genetic Algorithm for Finite-horizon Optimal Control of Nonlinear Systems.
Proceedings - 25th International Conference on Systems Engineering, ICSEng 2017, 2017-January
Institute of Electrical and Electronics Engineers Inc..