NDLI: The Parameter Optimization of Human-Simulated Intelligent Controller Based on Improved Genetic Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Guiqiang Chen Linjian Tang Yan Tang
Copyright Year	2009
Abstract	The human-simulated intelligent controller, using a hierarchical and multi-mode control structure, effectively solves the control difficult problems of many complex systems. But there are many parameters to be determined. In order to solve them, the paper introduces an improved genetic algorithm (IGA) which is combined with orthogonal design method. It is served as the simulation experiment platform by the cart-double pendulum. Through selected the reasonable fitness function and determined the appropriate parameters range, using the IGA, the parameters of the human-simulated intelligent controller are optimized. The simulation results show the IGA is better than the manual adjustment method. So it is proved that the IGA is more effective in solving the parameter optimization of human-simulated intelligent controller, and also promotes the more extended application space of intelligent control theory.
Starting Page	515
Ending Page	518
File Size	478276
Page Count	4
File Format	PDF
ISBN	9780769535838
DOI	10.1109/ICMTMA.2009.199
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Design methodology orthogonal design human-simulated intelligent controller Communication system control improved genetic algorithm Control systems Intelligent structures Intelligent sensors Genetic algorithms Automatic control cart-double pendulum parameter optimization Artificial intelligence Intelligent control
Content Type	Text
Resource Type	Article

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