Title :
Genetic approach to pole placement in linear state space systems
Author :
Cassell, Arnold ; Choi, Chiu
Author_Institution :
Electr. Eng. Program, Univ. of North Florida, Jacksonville, FL, USA
Abstract :
This paper describes a genetic approach for shaping the dynamic responses of linear state space systems through pole placement. The genetic approach generates a gain vector K. The vector K is used in state feedback for altering the poles of the system so as to meet step response requirements such as settling time and percent overshoot. To obtain the gain vector K by the proposed genetic approach, a pair of ideal, desired poles is calculate first and the corresponding gain vector K is computed based on the desired poles. That K vector is bred and mutated into a population. Each member of the population is tested for its fitness (the degree to which it matches the criteria). A new population is created each “generation” from the results of the previous iteration, until the criteria are met, or a certain number of generations have passed. Several case studies are provided in this paper to illustrate that this new approach is working.
Keywords :
genetic algorithms; iterative methods; pole assignment; state feedback; state-space methods; gain vector; genetic approach; iteration; linear state space systems; pole placement; state feedback; Application software; Eigenvalues and eigenfunctions; Genetic algorithms; Genetics; Simulation; State feedback; Vectors;
Conference_Titel :
System Theory (SSST), 2012 44th Southeastern Symposium on
Conference_Location :
Jacksonville, FL
Print_ISBN :
978-1-4577-1492-4
DOI :
10.1109/SSST.2012.6195133