Design of Linear Quadratic Regulator Based on Genetic Model Reference Adaptive Control

As the conventional control system is a controller that controls or regulates dynamics of any other process. From time to time, this may not behave appropriately online; because many factors like some variation in process itself unexpected changes environment, even undefined parameters model. To overcome problem above, an adaptive designed and implemented. This paper discusses design for ball beam with Genetic Model Reference Adaptive Control (GMRAC) mechanism MIT rule. Parameter adjustment (selection) should be done using optimization methods order obtain optimal performance, so genetic algorithm. (GA) will used as method optimum values these parameters. controller, Linear quadratic regulator (LQR) it one most popular controllers, performance proposed carried out MATLAB Simulink evaluate its effectiveness. The results show satisfactory where position tracks desired model reference.