Application of Genetic Algorithms in Optimal Excitation and Controller Design
| Authors: | Schoen Marco, Idaho State University, United States
Lin Feng, Indiana Institute of Technology, United States
Chinvorarat Sinchai, King Mungkut's Institute of Technology, Thailand |
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| Topic: | 1.1 Modelling, Identification & Signal Processing |
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| Session: | Experiment Design |
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| Keywords: | Identification, Genetic Algorithms, Input Signals, Intelligent Control, Controllablity |
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Abstract
Genetic Algorithms (GAs) are used in a set of covariance based optimum input signal algorithms using a proposed architecture suitable for on-line system identification. The optimal signals are computed recursively using a predictive filter. The relationships among these algorithms are investigated and compared based on a set of simulations. In addition, a nested GA is proposed for intelligent LQR controller design. The GAs are used to find the minimum distance to uncontrollability of a given system and to maximizes that minimum distance by finding the optimal coefficients in the weighting matrices of the LQR controller.
