Recently, unmanned aerial vehicle (e.g. quadcopter) has been used in many applications, e.g., search-and-rescue missions, because of its capabilities, e.g. vertical takeoff and landing. To achieve these missions, we need to design a suitable control system to stabilize and control quadcopter to track a desired flight trajectory. In this paper, we proposed a comparative simulation between a classical and optimal controllers implemented on a quadcopter model. Moreover, this paper discusses obstacles avoidance using path planning by Particle Swarm Optimization. Implementation of these linear controllers requires linearization the nonlinear quadcopter model around a steady state flight condition. The simulation results shows that the optimal controller LQR has an efficient performance compared to classical controller PID.