Abstract
This paper describes control system for dynamic equilibrium finding of a self balancing (two-wheeled) heavy robot. Two cascade-connected Proportional-Derivative (PD) controllers are used to balance the robot and keep the desired driving speed (or standing still). A simple and efficient algorithm for tilt calculation takes data from three sensors: a gyroscope, an accelerometer and a contactless magnetic encoder. The PD controller output is combined with manual (remote) driving signals to control Electronic Speed Controllers (ESC) of two high-torque electric motors. Finally, experimental results and recommendations to cope with difficulties are discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Åström, K.J., Murray, R.M.: Feedback Systems: An Introduction for Scientists and Engineers. Princeton University Press, Princeton (2007)
Bin, H., Zhen, L.W., Feng, L.H.: The kinematics model of a two-wheeled self-balancing autonomous mobile robot and its simulation. In: International Conference on Computer Engineering and Applications, pp. 64–68 (2010)
Franklin, G.F., Powell, J.D., Emami-Naeini, A.: Feedback Control of Dynamic Systems. Pearson, London (2015)
Güner, U., Canbolat, H., Ünlütürk, A.: Design and implementation of adaptive vibration filter for MEMS based low cost IMU. In: 9th International Conference on Electrical and Electronics Engineering (ELECO), pp. 130–133 (2015)
Mahler, B., Haase, J.: Mathematical model and control strategy of a two-wheeled self-balancing robot. In: 39th Annual Conference on IECON 2013, pp. 4198–4203. Industrial Electronics Society (2013)
Majczak, M., Wawrzyński, P.: Comparison of two efficient control strategies for two-wheeled balancing robot. In: The 20th International Conference on Methods & Models in Automation & Robotics (MMAR), Międzyzdroje, Poland, pp. 745–746 (2015)
Sun, F., Yu, Z., Yang, H.: A design for two-wheeled self-balancing robot based on Kalman filter and LQR. In: International Conference on Mechatronics and Control (ICMC), pp. 612–616 (2014)
Sun, C., Lu, T., Yuan, K.: Balance control of two-wheeled self-balancing robot based on linear quadratic regulator and neural network. In: Fourth International Conference on Intelligent Control and Information Processing (ICICIP), pp. 862–867 (2013)
Teixeira, H.T., de Mattos Siqueira, V.S., Munaro, C.J.: Comparison of methods for estimation and compensation of friction applied to an inverted pendulum. In: 9th IEEE International Conference on Control and Automation (ICCA), pp. 818–822 (2011)
Yong, Q., Yanlong, L., Xizhe, Z., Ji, L.: Balance control of two-wheeled self-balancing mobile robot based on TS fuzzy model. In: International Forum on Strategic Research, pp. 406–409 (2011)
Yosi, S., Agung, N.J., Unang, S.: Tilt and heading measurement using sensor fusion from inertial measurement unit. In: International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC), pp. 193–196 (2015)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Okulski, M., Ławryńczuk, M. (2018). A Cascade PD Controller for Heavy Self-balancing Robot. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2018. AUTOMATION 2018. Advances in Intelligent Systems and Computing, vol 743. Springer, Cham. https://doi.org/10.1007/978-3-319-77179-3_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-77179-3_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-77178-6
Online ISBN: 978-3-319-77179-3
eBook Packages: EngineeringEngineering (R0)