Gradient‐based optimization techniques for the design of static controllers for Markov jump linear systems with unobservable modes
Gradient‐based optimization techniques for the design of static controllers for Markov jump linear systems with unobservable modes
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基于梯度的优化技术，用于设计具有不可观测模式的马尔可夫跳跃线性系统的静态控制器
DOI：
10.1002/jnm.1981
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
J. D. Val
中科院分区：
文献类型：
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作者：
A. N. Vargas;Daiane C. Bortolin;E. F. Costa;J. D. Val
本文给出了马尔可夫跃变线性系统的静态控制问题，假设控制器无法访问跃变变量。通过对10种基于梯度的优化技术的评估，我们推导出了成本的梯度表达式。用实际实验数据验证了这些方法的数值有效性。利用相应的解，设计了一种在突然断电情况下实时控制直流电机速度的方案。版权所有©2014 John Wiley & Sons， Ltd。
The paper formulates the static control problem of Markov jump linear systems, assuming that the controller does not have access to the jump variable. We derive the expression of the gradient for the cost motivated by the evaluation of 10 gradient‐based optimization techniques. The numerical efficiency of these techniques is verified by using the data obtained from practical experiments. The corresponding solution is used to design a scheme to control the velocity of a real‐time DC motor device subject to abrupt power failures. Copyright © 2014 John Wiley & Sons, Ltd.