Heuristic optimization based choice of LQR weighting matrices for a rotary inverted pendulum

被引：0
|
作者：
Nath, Krishanu [1 ]
Dewan, Lillie [1 ]
机构：
[1] NIT Kurukshetra, Dept Elect Engn, Kurukshetra, Haryana, India
来源：
PROCEEDINGS OF THE 2018 IEEE INTERNATIONAL CONFERENCE ON RECENT TRENDS IN ELECTRICAL, CONTROL AND COMMUNICATION (RTECC) | 2018年
关键词：
Linear quadratic regulator; Teaching learning-based optimization; Seeker optimization algorithm; Gravitational search algorithm;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The choice of weighting matrices of the linear quadratic regulator (LQR) is one such decision which has a great effect on the dynamics of the system. There exists a nonlinear relationship between the dynamics of plant and their numerical values. Problems where such nonlinear relation exists, heuristic have served very useful to extract a better solution. In this paper, an attempt is made for the optimal choice of LQR weighting matrices using heuristic optimization techniques for a rotary inverted pendulum such that the settling time of the system is minimized.
引用
收藏
页码：269 / 274
页数：6
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