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Improved dual fast gradient method for model predictive control

Hao Xia  Kang Xia  
【摘要】:A set of online optimization algorithms based on the fast gradient method had been proposed to solve the real-time model predictive control problem. This paper discusses the main characteristics of several existing algorithms first. Then by combining the advantages of each algorithm, a new improved dual fast gradient algorithm is proposed. The proposed algorithm can deal with ill-conditioned MPC problems with fast convergence speed. The memory requirement and the computational effort of the algorithm is discussed. A numerical example is used to verify the computation performance and effectiveness of the algorithm.

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