optimal control of unknown continuous time linear periodic systems by adaptive dynamic programming with applications to magnetic attitude control

2021 ◽  
Author(s):  
Huaiyuan Jiang ◽  
Bin Zhou
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Continuous Time ◽  
Attitude Control ◽  
Adaptive Dynamic Programming ◽  
Periodic Systems ◽  
Adaptive Dynamic ◽  
Magnetic Attitude Control ◽  
Linear Periodic Systems ◽  
Time Linear

scholarly journals The Adaptive Dynamic Programming Toolbox

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5609
Author(s):  
Xiaowei Xing ◽  
Dong Eui Chang
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Attitude Control ◽  
Adaptive Dynamic Programming ◽  
Feedback Controls ◽  
Programming Technique ◽  
Adaptive Dynamic ◽  
Optimal Feedback ◽  
Model Free ◽  
Time Control

The paper develops the adaptive dynamic programming toolbox (ADPT), which is a MATLAB-based software package and computationally solves optimal control problems for continuous-time control-affine systems. The ADPT produces approximate optimal feedback controls by employing the adaptive dynamic programming technique and solving the Hamilton–Jacobi–Bellman equation approximately. A novel implementation method is derived to optimize the memory consumption by the ADPT throughout its execution. The ADPT supports two working modes: model-based mode and model-free mode. In the former mode, the ADPT computes optimal feedback controls provided the system dynamics. In the latter mode, optimal feedback controls are generated from the measurements of system trajectories, without the requirement of knowledge of the system model. Multiple setting options are provided in the ADPT, such that various customized circumstances can be accommodated. Compared to other popular software toolboxes for optimal control, the ADPT features computational precision and time efficiency, which is illustrated with its applications to a highly non-linear satellite attitude control problem.

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