Performance Evaluation of Balancing Bicopter using P, PI, and PID Controller

Esa Apriaskar, Fahmizal Fahmizal, Nur Azis Salim, Dhidik Prastiyanto

Abstract


Due to potential features of unmanned aerial vehicles for society, the development of bicopter has started to increase. This paper contributes to the development by presenting a performance evaluation of balancing bicopter control in roll attitude. It aims to determine the best controller structure for the balancing bicopter. The controller types evaluated are based on Ziegler-Nichols tuning method; they are proportional (P), proportional-integral (PI), and proportional-integral-derivative (PID) controllers. Root locus plot of the closed-loop balancing bicopter system is used to decide the tuning approach. This work considers a difference in pulse-width-modulation (PWM) signal between the left and right rotors as the signal control and bicopter angle in roll movement as the output. Parameters tuned by the method are Kp, Ti, and Td which is based on the ideal PID structure. The performance test utilizes rising time, settling time, maximum overshoot, and steady-state error to determine the most preferred controller. The result shows that PI-controller has the best performance among the other candidates, especially in maximum overshoot and settling time. It reaches 8.34 seconds in settling time and 3.71% in maximum overshoot. Despite not being the best in rising time and resembling PID-controller performances in steady-state error criteria, PI-controller remains the most preferred structure considering the closeness of the response to the desired value.

Keywords


Bicopter; roll attitude; ziegler-nichols; PID

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References


S. D. Kale, S. V Khandagale, S. S. Gaikwad, S. S. Narve, and P. V Gangal, “Agriculture Drone for Spraying Fertilizer and Pesticides,†Int. J. Adv. Res. Comput. Sci. Softw. Eng., vol. 5, no. 12, pp. 804–807, 2015.

Y. B. Huang, S. J. Thomson, W. C. Hoffmann, Y. Bin Lan, and B. K. Fritz, “Development and prospect of unmanned aerial vehicle technologies for agricultural production management,†Int. J. Agric. Biol. Eng., vol. 6, no. 3, pp. 1–10, 2013.

S. Amici et al., “Volcanic environments monitoring by drones, Mud Volcano case Study,†Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. Vol. XL-1/W2, 2013 UAV-g2013, vol. XL-1/W2, no. September, pp. 5–10, 2013.

E. Apriaskar, Y. P. Nugraha, and B. R. Trilaksono, “Simulation of Simultaneous Localization and Mapping Using Hexacopter and RGBD Camera,†in International Conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology, 2017, pp. 48–53.

Y. S. Chou and J. S. Liu, “A robotic indoor 3D mapping system using a 2D laser range finder mounted on a rotating four-bar linkage of a mobile platform,†Int. J. Adv. Robot. Syst., vol. 10, 2013.

Q. Galvane, J. Fleureau, F.-L. Tariolle, and P. Guillotel, “Automated Cinematography with Unmanned Aerial Vehicles,†in WICED 2016 Proceedings of the Eurographics Workshop on Intelligent Cinematography and Editing, 2016, pp. 23–30.

S. Agarwal, S. Shetty, A. Bhagat, J. Ghule, and P. S. H. Mane, “UAV based Quadcopter with Wheels,†Int. J. Sci. Res. Dev., vol. 2, no. 2, pp. 1003–1006, 2014.

R. K. Rangel and A. C. Terra, “Development of a Surveillance tool using UAV ’ s,†IEEE Aerosp. Conf., no. March 2015, pp. 1–11, 2018.

Q. Zhang, Z. Liu, J. Zhao, and S. Zhang, “Modeling and attitude control of Bi-copter,†in AUS 2016 - 2016 IEEE/CSAA International Conference on Aircraft Utility Systems, 2016, vol. 100191, pp. 172–176.

L. HreÄko, J. SlaÄka, and M. Halás, “Bicopter stabilization based on IMU sensors,†in 20th International Conference on Process Control, 2015, pp. 192–197.

G. R. Gress, “Natural Pitch Stabilization of Bicopters in Hover Using Lift-Propeller Gyroscopics,†J. Guid. Control. Dyn., vol. 41, no. 2, pp. 476–487, Feb. 2018.

J. M. Bustamante, C. A. Herrera, E. S. Espinoza, C. A. Escalante, S. Salazar, and R. Lozano, “Design and Construction of a UAV VTOL in Ducted-Fan and Tilt-Rotor Configuration,†in 2019 16th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), 2019, pp. 1–6.

Fahmizal, M. Arrofiq, E. Apriaskar, and A. Mayub, “Rigorous Modelling Steps on Roll Movement of Balancing Bicopter using Multi-level Periodic Perturbation Signals,†in 6th International Conference on Instrumentation, Control, and Automation (ICA), 2019, pp. 52–57.

M. Z. Fadel, M. G. Rabie, and A. M. Youssef, “Modeling, Simulation and Control of a Fly-by-wire Flight Control System Using Classical PID and Modified PI-D Controllers,†J. Eur. des Systèmes Autom., vol. 52, no. 3, pp. 267–276, Aug. 2019.

T. T. Hlaing, “Simulation of Ziegler-Nichols PID Tuning for Position Control of DC Servo Motor,†Int. J. Sci. Res. Publ., vol. 9, no. 7, p. p9184, Jul. 2019.

A. A. Aly and F. A. Salem, “A New Accurate Analytical Expression for Rise Time Intended for Mechatronics Systems Performance Evaluation and Validation,†Int. J. Autom. Control Intell. Syst., vol. 1, no. 2, pp. 51–60, 2015.

R. C. Dorf and R. H. Bishop, Modern Control Systems, 12th ed. New Jersey: Prentice Hall, 2011.

M. Reyad, M. Arafa, and E. A. Sallam, “An optimal PID controller for a qaudrotor system based on DE algorithm,†in 2016 11th International Conference on Computer Engineering & Systems (ICCES), 2016, pp. 444–451.

E. Susanto, A. Surya Wibowo, and E. Ghiffary Rachman, “Fuzzy Swing Up Control and Optimal State Feedback Stabilization for Self-Erecting Inverted Pendulum,†IEEE Access, vol. 8, pp. 6496–6504, 2020.

Y. Qin, G. Zhao, Q. Hua, L. Sun, and S. Nag, “Multiobjective Genetic Algorithm-Based Optimization of PID Controller Parameters for Fuel Cell Voltage and Fuel Utilization,†Sustainability, vol. 11, no. 12, pp. 1–20, Jun. 2019.

M. I. Solihin, L. F. Tack, and M. L. Kean, “Tuning of PID Controller Using Particle Swarm Optimization (PSO),†Int. J. Adv. Sci. Eng. Inf. Technol., vol. 1, no. 4, p. 458, 2011.

F. S. M. Alkhafaji, W. Z. W. Hasan, M. M. Isa, and N. Sulaiman, “A novel method for tuning PID controller,†J. Telecommun. Electron. Comput. Eng., vol. 10, no. 1–12, pp. 33–38, 2018.

A. Triwiyatno, S. Sumardi, and E. Apriaskar, “Robust fuzzy control design using genetic algorithm optimization approach: case study of spark ignition engine torque control,†Iran. J. Fuzzy Syst., vol. 14, no. 3, pp. 1–13, 2017.




DOI: https://doi.org/10.15294/jte.v11i2.23032

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