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Design of a Stable an Intelligent Controller for a Quadruped Robot

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Abstract

Quadruped robots have increasingly been used in complex terrains where barriers and gaps exist. In this paper, a four-legged robot with intelligent controllers is designed and simulated. The designed architecture comprises 12 servo motors, three per leg, to provide considerable flexibility in movement and turning. Proportional Integral Derivative (PID) controllers and Fuzzy controllers are proposed to control and stabilize the motion of the quadruped robot. An ant colony optimization algorithm has been utilized to tune the parameters of the PID controller and the Fuzzy controller. After obtaining the optimal values of both controllers, the entire architecture is implemented using the Multibody Simscape package in MATLAB which models multidomain physical systems. The simulation results are conducted in a 3-dimensional environment and they are demonstrated in three case studies; firstly, when the system is simulated without using a controller which leads to a collapse of the quadruped robot. Secondly, when the PID controller is combined with the system, better movement is obtained. However, the quadruped is unable to complete its path and collapses after a few meters. Thirdly, when the Fuzzy controller is integrated into the designed architecture, a significant improvement is observed in terms of minimizing elapsed time and improving the overall performance of the motion. The stability of the Fuzzy controller has been examined using Lyapunov criteria to validate its overall performance. Comparisons are conducted based on control efforts and travelled distances to demonstrate the suitability and effectiveness of Fuzzy controllers over PID controllers.

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References

  1. Chwa D (2010) Tracking control of differential-drive wheeled mobile robots using a backstepping-like feedback linearization. IEEE Trans Syst Man Cybern Part A Syst Hum 40(6):1285–1295

    Article  Google Scholar 

  2. Wang H, Li B, Liu J, Yang Y, Zhang Y (2011) Dynamic modeling and analysis of Wheel Skid steered Mobile Robots with the different angular velocities of four wheels. In: The 30th Chinese control conference, pp 3919–3924

  3. Sun T, Xiang X, Su W, Wu H, Song Y (2017) A transformable wheel-legged mobile robot: design, analysis and experiment. Robot Auton Syst 98(September):30–41

    Article  Google Scholar 

  4. Li X, Gao H, Li J, Wang Y, Guo Y (2019) Hierarchically planning static gait for quadruped robot walking on rough terrain. J Robot 2019:1–12

    Article  Google Scholar 

  5. Kumar GK, Pathak PM (2013) Dynamic modelling an simulation of a four legged jumping robot with compliant legs. Robot Auton Syst 61(3):221–228

    Article  Google Scholar 

  6. Peula JM, Urdiales C, Herrero I, Sánchez-Tato I, Sandoval F (2009) Pure reactive behavior learning using case based reasoning for a vision based 4-legged robot. Robot Auton Syst 57(6–7):688–699

    Article  Google Scholar 

  7. Aiyama Y, Hara TYM, Ota J, Arai T (1999) Cooperative transportation by two four-legged robots with implicit communication. Robot Auton Syst 29(1):13–19

    Article  Google Scholar 

  8. Martins-Filho LS, Prajoux R (2000) Locomotion control of a four-legged robot embedding real-time reasoning in the force distribution. Robot Auton Syst 32(4):219–235

    Article  Google Scholar 

  9. Fukui T, Fujisawa H, Otaka K, Fukuoka Y (2019) Autonomous gait transition and galloping over unperceived obstacles of a quadruped robot with CPG modulated by vestibular feedback. Robot Auton Syst 111:1–19

    Article  Google Scholar 

  10. Lee JH, Park JH (2019) Time-dependent genetic algorithm and its application to quadruped’s locomotion. Robot Auton Syst 112:60–71

    Article  Google Scholar 

  11. Chow CK, Jacobson DH (1972) Further studies of human locomotion: postural stability and control. Math Biosci 15(1–2):93–108

    Article  Google Scholar 

  12. Hemami H, Golliday CL Jr (1977) The inverted pendulum and biped stability. Math Biosci 34(1–2):95–110

    Article  Google Scholar 

  13. Furusho J, Masubuchi M (1986) Control of a dynamical biped locomotion system for steady walking. J Dyn Syst Meas Control 108(2):111–118

    Article  Google Scholar 

  14. Hirose S (1984) A study of design and control of a quadruped walking vehicle. Int J Robot Res 3(2):113–133

    Article  Google Scholar 

  15. Liu M, Xu F, Jia K, Yang Q, Tang C (2016) A stable walking strategy of quadruped robot based on foot trajectory planning. In: 3rd international conference on information science and control engineering, pp 799–803

  16. Agrawal SP, Dagale H, Mohan N, Umanand L (2016) IONS: a quadruped robot for multi-terrain applications. Int J Mater Mech Manuf 4(1):84–88

    Google Scholar 

  17. Sprlak R, Chlebis P (2014) A study on locomotions of quadruped robot. In: International conference on advanced engineering—theory and application, pp 125–133

  18. Atique MMU, Sarker MRI, Ahad MAR (2018) Development of an 8DOF quadruped robot and implementation of Inverse Kinematics using Denavit–Hartenberg convention. Heliyon 4(12):2405–8440

    Article  Google Scholar 

  19. Moosavian SAA, Khorram M, Zamani A, Abedini H (2011) PD regulated sliding mode control of a quadruped robot. In: IEEE international conference on mechatronics and automation. IEEE, Beijing, pp 2061–2066

  20. Gor MMS, Pathak PM, Samantaray AK, Yang JM, Kwak SW (2015) Control of compliant legged quadruped robots in the workspace. Simulation 91(2):103–125

    Article  Google Scholar 

  21. Sun L, Meng M, Chen W, Liang H, Mei T (2007) Design of quadruped robot based neural network. In: International symposium on neural networks, pp 843–851

  22. Li K, Wen R (2017) Robust control of a walking robot system and controller design. In: 13th global congress on manufacturing and management, pp 947–955

  23. Bhatti J, Hale M, Iravani P, Plummer A, Sahinkaya N (2017) Adaptive height controller for an agile hopping robot. Robot Auton Syst 98:126–134

    Article  Google Scholar 

  24. Liu Q, Chen X, Han B, Luo Z, Luo X (2018) Learning control of quadruped robot galloping. J Bionic Eng 15(2):329–340

    Article  Google Scholar 

  25. Potts AS, Da Cruz JJ (2010) Kinematics analysis of a quadruped robot. In: 5th IFAC symposium on mechatronic systems, pp 261–266

  26. Gor M, Pathak P, Samantaray A (2013) Dynamic modeling and simulation of compliant legged quadruped robot. In: The 1st international and 16th national conference on machines and mechanisms, pp 7–16

  27. Zeng X, Zhang S, Zhang H, Li X, Zhou H, Fu Y (2019) Leg trajectory planning for quadruped robots with high-speed trot gait. Appl Sci 9(7):1508

    Article  Google Scholar 

  28. McMillan GK (2012) Industrial applications of PID control. In: Vilanova R, Visioli A (eds) PID control in the third millennium. Advances in industrial control. Springer, London, pp 415–461

    Chapter  Google Scholar 

  29. Meena DC, Devanshu A (2017) Genetic algorithm tuned PID controller for process control. In: International conference on inventive systems and control

  30. Solihin MI, Tack LF, Kean ML (2011) Tuning of PID controller using particle swarm optimization. In: international conference on advanced science, engineering and information technology, pp 458–461

  31. Ali RS, Aldair AA, Almousawi AK (2014) Design an optimal PID controller using artificial bee colony and genetic algorithm for autonomous mobile robot. Int J Comput Appl 100(16):8–16

    Google Scholar 

  32. Hsiao Y-T, Chuang C-L, Chien C-C (2004) Ant colony optimization for designing of PID controllers. In: International conference on robotics and automation

  33. Lakshmi Narayana KV, Kumar VN, Dhivya M, Prejila Raj R (2015) Application of ant colony optimization in tuning a PID controller to a conical tank. Indian J Sci Technol 8(S2):217

    Article  Google Scholar 

  34. Ning J, Zhang C, Sun P, Feng Y (2018) Comparative study of ant colony algorithms for multi-objective optimization. Information 10(1):1–19

    Article  Google Scholar 

  35. Lee CCC (1990) Fuzzy logic in control systems: fuzzy logic controller, Part II. IEEE Trans Syst Man Cybern 20(2):404–418

    Article  MathSciNet  Google Scholar 

  36. Almayyahi A, Wang W, Hussein A, Birch P (2017) Motion control design for unmanned ground vehicle in dynamic environment using intelligent controller. Int J Intell Comput Cybern 10(4):530–548

    Article  Google Scholar 

  37. Aldair AA, Alsaedee EB, Abdalla TY (2019) Design of ABCF control scheme for full vehicle nonlinear active suspension system with passenger seat. Iran J Sci Technol Trans Electr Eng 43:289–302

    Article  Google Scholar 

  38. Al-Mayyahi A, Ali RS, Thejel RH (2018) Designing driving and control circuits of four-phase variable reluctance stepper motor using fuzzy logic control. Electr Eng 100(2):695–709

    Article  Google Scholar 

  39. Pukdeboon C (2011) A review of fundamentals of Lyapunov theory. J Appl Sci 10(2):55–61

    MathSciNet  Google Scholar 

  40. Ogata K (1995) Discrete time control systems, 2nd edn. Prentice Hall International Inc, Upper Saddle River

    Google Scholar 

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Authors and Affiliations

  1. Department of Electrical Engineering, College of Engineering, University of Basrah, Basrah, Iraq

    Ammar A. Aldair & Auday Al-Mayyahi

  2. Department of Engineering and Design, School of Engineering and Informatics, University of Sussex, Brighton, UK

    Weiji Wang

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  1. Ammar A. Aldair
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  2. Auday Al-Mayyahi
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  3. Weiji Wang
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Correspondence to Ammar A. Aldair.

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Aldair, A.A., Al-Mayyahi, A. & Wang, W. Design of a Stable an Intelligent Controller for a Quadruped Robot. J. Electr. Eng. Technol. 15, 817–832 (2020). https://doi.org/10.1007/s42835-019-00332-5

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  • DOI: https://doi.org/10.1007/s42835-019-00332-5

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