Design of differential evolution algorithm-based robust fuzzy logic power system stabiliser using minimum rule base

A review on applications of heuristic optimization algorithms for optimal power flow in modern power systems

“…The main body of the algorithm takes four or five lines of code in any programming language. Despite its simplicity, the gross performance of DE in terms of accuracy, convergence rate and robustness makes it attractive for applications to various real-world optimization problems [10][11][12], where finding an approximate solution in a reasonable amount of computational time is of considerable importance. The spatial complexity of DE is lower than that of some highly competitive real parameter optimizers.…”

Load Frequency Control in Deregulated Power System using Fuzzy C-Means

“…For a little more complex system, but for which significant data exist, model free method such as neural networks provide a powerful and robust means to reduce some uncertainty through learning, based on patterns in the available data. For the most complex system where few numerical data exist and only ambiguous or imprecise information may be available, fuzzy reasoning provides a way to understand system behavior by allowing us to interpolate approximately between observed input and output situation [24].The imprecision in fuzzy models is therefore, generally quite high. Fuzzy systems can implement crisp input and output, and produce a non-linear functional mapping just as do algorithms [14,21].…”

Adaptive Fuzzy Sliding Mode Optimum Control, Using the Fuzzy Control in Flat Robot

“…System path sliding through the sliding surface to the origin is called sliding mode. Under the given circumstances the SMC is stable against the system disorders and outer confusions (Vakula, Sudha, 2012). In practice the switching frequency limitation causes that system situations don't remain on switching surface and oscillate around that.…”