Abstract
Genetic algorithms (GAs) have been proven as robust search procedures. Numerous researchers have established the validity of GAs in optimization, machine learning and control applications. This paper presents a new intelligent control scheme using the robust sear h feature of GAs incorporating the basic idea of self-tuning regulators. The proposed controller utilized GAs to search for the changes of system parameters and to calculate the corresponding control law. The optimum parameters and control law are chosen based on the selection mechanism of GAs, which employs the square of the difference between the actual and the estimated outputs as the fitness function. The controller has an on-line parameters identification function and does not require prior knowledge or training data for learning. The proposed intelligent controller is applied to the load frequency control of a power system to investigate the effectiveness from results obtained from computer simulations, the intelligent controller has been proven to provide good system characteristics.
Published Version
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