A novel ADP based model-free predictive control

被引:9
|
作者
Dong, Na [1 ]
Chen, Zengqiang [2 ]
机构
[1] Tianjin Univ, Sch Elect Engn & Automat, Dept Automat, Tianjin 300071, Peoples R China
[2] Nankai Univ, Dept Automat, Tianjin 300071, Peoples R China
基金
高等学校博士学科点专项科研基金;
关键词
Model-free control; SPSA; ADP; Neural network; Predictive control; Nonlinear tracking problem; NEURAL-NETWORK; SYSTEMS;
D O I
10.1007/s11071-011-0248-3
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Dynamic programming is a very useful tool in solving optimization and optimal control problems. Here, the Approximate Dynamic Programming (ADP) and the notion of neural networks based predictive control are combined with a model-free control method based on SPSA (Simultaneous perturbation stochastic approximation), and a novel ADP based model-free predictive control strategy for nonlinear systems is proposed. Dynamic programming is used to adjust the control parameters in the novel model-free control method and the notion of predictive control is introduced to modify the whole control structure. Finally, the proposed ADP based model-free predictive control strategy is applied to solve nonlinear tracking problems and the effectiveness of this novel control method is fully illustrated though simulation tests on two typical nonlinear systems.
引用
收藏
页码:89 / 97
页数:9
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