The Design of Optimal PID Control Method for Quadcopter Movement Control

Hanum Arrosida(1*), Mohammad Erik Echsony(2),

(1) State Polytechnic of Madiun
(2) State Polytechnic of Madiun
(*) Corresponding Author


Nowadays, quadcopter motion control has become a popular research topic because of its versatile ability as an unmanned aircraft can be used to alleviate human labor and also be able to reach dangerous areas or areas which is unreachable to humans. On the other hand, the Optimal PID control method, which incorporates PID and Linear Quadratic Regulator (LQR) control methods, has also been widely used in industry and research field because it has advantages that are easy to operate, easy design, and a good level of precision. In the PID control method, the main problem to be solved is the accuracy of the gain value Kp, Ki, and Kd because the inappropriateness of those value will result in an imprecise control action. Based on these problems and referring to the previous study, the optimal PID control method was developed by using PID controller structure with tuning gain parameter of PID through Linear Quadratic Regulator (LQR) method. Through the integration of these two control methods, the optimum solutions can be obtained: easier controller design process for quadcopter control when crossing the determined trajectories, steady state error values less than 5% and a stable quadcopter movement with roll and pitch angle stabilization at position 0 radians with minimum energy function.


Quadcopter; Optimal PID; Tuning Gain; Minimum energy function;

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R. Oliver, S. Y. Khoo, M. Norton, S. Adams, and A. Kouzani, “Development of a single axis tilting quadcopter,” in IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2017.

J. J. Beaman, “Non-linear quadratic gaussian controlf,” Int. J. Control, 1984.

E. Kuantama, T. Vesselenyi, S. Dzitac, and R. Tarca, “PID and Fuzzy-PID control model for quadcopter attitude with disturbance parameter,” Int. J. Comput. Commun. Control, 2017.

Z. Benic, P. Piljek, and D. Kotarski, “Mathematical Modelling of Unmanned Aerial Vehicles with Four Rotors,” Interdiscip. Descr. Complex Syst., 2016.

D. Guo, W. Yim, and K. K. Leang, “Adaptive repetitive visual-servo control of a low-flying unmanned aerial vehicle with an uncalibrated high-flying camera,” in IEEE International Conference on Intelligent Robots and Systems, 2016.

A. K. Das, S. Suresh, and N. Sundararajan, “A robust interval Type-2 Fuzzy Inference based BCI system,” in 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings, 2017.

A. Nemati and M. Kumar, “Non-linear control of tilting-quadcopter using feedback linearization based motion control,” in ASME 2014 Dynamic Systems and Control Conference, DSCC 2014, 2014.

R. Syam, “Dynamics and fuzzy logic method for controlling quadcopter,” Res. J. Appl. Sci., 2016.

Y. Cao and W. Ren, “Optimal linear-consensus algorithms: An lqr perspective,” IEEE Trans. Syst. Man, Cybern. Part B Cybern., 2010.

M. Palanisamy, H. Modares, F. L. Lewis, and M. Aurangzeb, “Continuous-time Q-learning for infinite-horizon discounted cost linear quadratic regulator problems,” IEEE Trans. Cybern., 2015.

S. L. Brunton, B. W. Brunton, J. L. Proctor, and J. N. Kutz, “Koopman invariant subspaces and finite linear representations of nonlinear dynamical systems for control,” PLoS One, 2016.

B. L. J. Gysen, T. P. J. Van Der Sande, J. J. H. Paulides, and E. A. Lomonova, “Efficiency of a regenerative direct-drive electromagnetic active suspension,” IEEE Trans. Veh. Technol., 2011.

G. K. H. S. L. Das, B. Tondu, F. Forget, J. Manhes, O. Stasse, and P. Soueres, “Controlling a multi-joint arm actuated by Pneumatic muscles with quasi-DDP optimal control,” in IEEE International Conference on Intelligent Robots and Systems, 2016.

M. Bharatheesha, W. Caarls, W. J. Wolfslag, and M. Wisse, “Distance metric approximation for state-space RRTs using supervised learning,” in IEEE International Conference on Intelligent Robots and Systems, 2014.

W. An and Y. Li, “Simulation and control of a two-wheeled self-balancing robot,” in 2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013, 2013.



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