For the inverted pendulum stabilization problem (whose implementation is also treated in the present paper) one simplified solution is to linear along the desired equilibrium point and apply the pole placement technique or the linear quadratic regulator (LQR). Such real-time control systems were implemented in [7,8,9] using a host computer with Matlab/Simulink (real time workshop RTW)and interface boards with 8 or 10 bits convertors. An adaptive LQR state controller was tested in [10] for an optimal balancing of an inverted pendulum. The adaptation method is based on the N2 norm of the state vector and the controller behaves as a gain scheduling controller and, therefore, the convergence of the proposed adaptive controller is guaranteed. The control algorithm and data acquisition and visualization were realized with Matlab/Simulink, and Real-Time xPC target products on a personal computer with 12-bit AD/DA converter board. In [5] a sliding mode control SMC method based on Ackermann’s formula is developed on a hardware platform with microcontrollers.