In this paper a genetic approach has been presented to the Optimal Linear Quadratic Tracking problem. In this problem control law is designed such that a cost function is minimized. The design specifications, depends on choosing weighting matrices Q and R. One must carry out a trial-and-error process to choose the weighting matrices that can satisfy the design specifications. To overcome this difficulty we employ the Genetic Algorithm (GA) to find the proper weighting matrices. A computer simulation is performed to track a desired reference trajectory in a motor-generator set as a multivariable system. This method is compared with the one proposed by Bryson and Ho.
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