Abstract : This work deals with developing suitable attitude control algorithm for a small low Earth orbit satellite of minimum cost and complexity. The proposed attitude control system deals with a combination of passive and active control methods. Passive control is represented by boom deployment to ensure Earth pointing with accuracy (of _ 50 ). Active control method is accomplished by the use of a set of mutually perpendicular coils called magnetorquer mounted on the principal axes of the spacecraft. The interaction between external magnetic field of the Earth and the magnetic field generated in the coil produces a mechanical torque, which is used to correct the attitude. The proposed control system is divided into three phases Detumbling phase, Boom deployment phase and Liberation phase. The magnetic field generated by the coils disturbs the reading of the magnetometer and because these measurements are important for attitude control and other applications, the need for the attitude determination system arises. The attitude determination system uses measurements from the magnetometer and sun sensor data applied to an extended Kalman filter. The Kalman filter is a set of mathematical equations that usually deal with the extraction of a signal from noisy measured data. The filter can be considered a powerful device when added to the attitude control system because it provides accuracy to the control process as it can support estimations of past, present, and even future states, it can do so even when the precise nature of the modeled system is unknown [12]. Linear and extended Kalman filters were used to estimate the attitude parameters of the system, the filters were tested using MATLAB program and they showed good estimation of both kinematic angles and angular velocity. An experimental setup of a magnetic attitude control system was utilized, a PD controller and a pulse width modulator were tested practically to control the current applied to the coils, a sun sensor can detect the new attitude and the error can be minimized using feedback control.