Optimization and control of an energy-efficient vibration-driven robot

Abstract

Vibration-driven robots are innovative mechanical systems that exhibit a wide range of capabilities and applications due to their simple propellers. The applications of these robots span from clearing debris after an incident, traversing pipelines for inspection and maintenance, or medical purposes. In this paper, optimization and motion control of an energy-efficient two-module vibration-driven robot are investigated. The robot contains two blocks connected by a spring as its main body, and an unbalanced rotating mass to drive the robot rectilinearly. At first, the governing dynamic equations of the robot are derived and solved using MATLAB/Simulink. Then, the dynamic model of the robot is verified by comparing the obtained results with the simulation results from MSC Adams. Subsequently, a parametric study is conducted to investigate the effect of various physical parameters of the robot on its average velocity and consumed energy. Afterward, optimization variables are determined and a proper objective function is considered. By performing an optimization process using a genetic algorithm (NSGA-II), optimal parameters of the robot are obtained. Moreover, for motion control of the optimized robot, two control schemes, PID and Fractional Order PID, are designed. To evaluate and compare the performance of the proposed controllers, parameters of both controllers are optimized using a genetic algorithm in which both tracking error and control input are minimized, simultaneously. Finally, tracking error and control effort of the mentioned controllers for motion control of the robot are compared and discussed.

Keywords

vibration-driven robot two-module single actuated energy-efficient dynamic analysis optimization proportional–integral–derivative controller fractional order proportional–integral–derivative controller

Get full access to this article

View all access options for this article.

References

Ammar

Azar

(2020) Robust path tracking of mobile robot using fractional order PID controller. In: The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019). Springer International Publishing, 4, pp. 370–381.

Angel

Viola

(2018) Fractional order PID for tracking control of a parallel robotic manipulator type delta. ISA transactions 79: 172–188.

Becker

Boerner

Lysenko

, et al. (2014) On the mechanics of bristle-bots-modeling, simulation and experiments. In: ISR/Robotik 2014; 41st international symposium on robotics, Munich, Germany, 02–03 June 2014. VDE, pp. 1–6.

Bergman

Ljungqvist

Axehill

(2020) Improved path planning by tightly combining lattice-based path planning and optimal control. IEEE Transactions on Intelligent Vehicles 6(1): 57–66.

Bolotnik

Nunuparov

Chashchukhin

(2016) Capsule-type vibration-driven robot with an electromagnetic actuator and an opposing spring: dynamics and control of motion. Journal of Computer and Systems Sciences International 55(6): 986–1000.

Bolotnik

Zeidis

Zimmermann

, et al. (2006) Dynamics of controlled motion of vibration-driven systems. Journal of Computer and Systems Sciences International 45(5): 831–840.

Chen

(2018) Locomotion of two vibration-driven modules connected by a mechanical position limiter. International Journal of Mechanical Sciences 137: 252–262.

Das

(2011) Functional Fractional Calculus. Berlin: Springer Science & Business Media.

Diao

Zhang

Fang

, et al. (2021) Bi-objective optimization for improving the locomotion performance of the vibration-driven robot. Archive of Applied Mechanics 91(5): 2073–2088.

10.

Eftekharian

Sohrabi

Fakhari

(2021) Dynamic analysis and control of a vibration-driven robot. In: The 10th International Conference on Acoustics and Vibrations, University of Tehran, Iran, p. 8.

11.

Fang

H-B

(2012a) Controlled motion of a two-module vibration-driven system induced by internal acceleration-controlled masses. Archive of Applied Mechanics 82(4): 461–477.

12.

Fang

H-B

(2012b) Dynamics of a three-module vibration-driven system with non-symmetric Coulomb’s dry friction. Multibody System Dynamics 27(4): 455–485.

13.

Fang

(2014) Stick-slip effect in a vibration-driven system with dry friction: sliding bifurcations and optimization. Journal of Applied Mechanics 81(5): 051001.

14.

Forrest

(1996) Genetic algorithms. ACM Computing Surveys (CSUR) 28(1): 77–80.

15.

Ke-Er

Jia-Chen

Qing-Ming

(2017) Centrifugal-force micro motion platform using vibration motor. In: 2017 International Conference on Computer Systems, Electronics and Control (ICCSEC). IEEE, pp. 1630–1634.

16.

Kim

Park

Y-L

(2019) A simple tripod mobile robot using soft membrane vibration actuators. IEEE Robotics and Automation Letters 4(3): 2289–2295.

17.

Lazarević

Batalov

Latinović

(2013) Fractional PID controller tuned by genetic algorithms for a three DOF's robot system driven by DC motors. IFAC Proceedings Volumes 46(1): 385–390.

18.

Lee

Park

(2015) Vimbot: design and control of a new magnet robot actuated by an external vibrating magnetic field. In: 2015 IEEE International Conference on Robotics and Automation (ICRA). IEEE, pp. 5358–5363.

19.

Liu

Neumann

, et al. (2018) Energy-efficient design and control of a vibro-driven robot. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, pp. 1464–1469.

20.

Loukanov

Vitliemov

Ivanov

(2016) Dynamics of a vibration-driven one-way moving wheeled robot. IOSR Journal of Mechanical and Civil Engineering 13(3): 14–22.

21.

Luo

Wang

Zheng

, et al. (2020) Research on path planning of mobile robot based on improved ant colony algorithm. Neural Computing and Applications 32: 1555–1566.

22.

Peng

Liu

, et al. (2019) A symplectic instantaneous optimal control for robot trajectory tracking with differential-algebraic equation models. IEEE Transactions on Industrial Electronics 67(5): 3819–3829.

23.

Peng

Bao

Huang

, et al. (2022) Chance-constrained sneaking trajectory planning for reconnaissance robots. Applied Mathematical Modelling 112: 224–237.

24.

Persson

Albohr

Mancosu

, et al. (2003) On the nature of the static friction, kinetic friction and creep. Wear 254(9): 835–851.

25.

Saadabad

Moradi

Vossoughi

(2019) Dynamic modeling, optimized design, and fabrication of a 2DOF piezo-actuated stick-slip mobile microrobot. Mechanism and Machine Theory 133: 514–530.

26.

Sattarov

Almaev

(2017) Electromagnetic worm-like locomotion system for in-pipe robots: design and vibration-driven motion analysis. In: 2017 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, pp. 1–6.

27.

Violia

Angel

LUIS

(2022) Control performance assessment of fractional-order PID controllers applied to tracking trajectory control of robotic systems. WSEAS Transactions on Systems and Control 17: 62–73.

28.

Vlachos

Papadimitriou

Papadopoulos

(2015) Vibration-driven microrobot positioning methodologies for nonholonomic constraint compensation. Engineering 1(1): 066–072.

29.

Wang

Liu

Zhang

, et al. (2019) A unified symplectic pseudospectral method for motion planning and tracking control of 3D underactuated overhead cranes. International Journal of Robust and Nonlinear Control 29(7): 2236–2253.

30.

Zimmermann

Zeidis

Bolotnik

, et al. (2009) Dynamics of a two-module vibration-driven system moving along a rough horizontal plane. Multibody system dynamics 22(2): 199–219.