An unmanned bicycle versus linear quadratic optimal controls

The dynamic model of an unmanned bicycle was presented with linear quadratic optimal controls. An unmanned bicycle uses a dynamic equilibrium model of gravity and centrifugal force in order to control its steering on the purpose to acceleration´s control. The linear quadratic optimal controls have been designed based on linear control theory. The initial state responses from simulation for the camber angle and its estimator have shown that even they are started from difference initial conditions, but both of them have been reached the zero state rapidly. For the camber angle rate and its estimator, they reach to the zero state as well. Although, the oscillation in the transient response is occurred. Hence, it concludes that the Linear Quadratic Regulator can be replaced by Linear Quadratic Gaussian for economy.