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Optimal Design of PID Controller for 2-DOF Drawing Robot Using Bat-Inspired Algorithm

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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019 (AISI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1058))

Abstract

Tuning process which is used to find the optimum values of the proportional integral derivative (PID) parameters, can be performed automatically using meta-heuristics algorithms such as BA (Bat Algorithm), PSO (Particle Swarm Optimization) and ABC (Artificial Bee Colony). This paper presented a theoretical and practical implementation of a drawing robot using BA to tune the PID controller governing the robotic arm which is a non linear system difficult to be controlled using classical control. In line with the above and in order to achieve this aim and meet high performance feedback and robust dynamic stability of the system, the PID controller is designed considering the realistic constraints. For faster tuning of the controller parameters, ten individuals and five iterations have been selected. BA, ABC and PSO have been compared and it’s noticed that BA is the best choice to achieve good performance control. In the proposed design, MATLAB was used for trajectory reckoning. Afterwards, the value of coordinate position of the shape to be drawn is translated into a joint angle by applying the inverse kinematics to control the two DC motors through the ATMEGA 2560 microcontroller. The suggested technique reveals via simulations and hardware implementation the high efficiency of the applied algorithm. The PID controller approach presents an impressive stability and robustness results. The achieved results demonstrated that high performance can be obtained by tuning a PID controller using nature inspired based algorithms.

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References

  1. Abdelmalek, S., Azar, A.T., Dib, D.: A novel actuator fault-tolerant control strategy of DFIG-based wind turbines using takagi-sugeno multiple models. Int. J. Control Autom. Syst. 16(3), 1415–1424 (2018)

    Article  Google Scholar 

  2. Ammar, H.H., Azar, A.T.: Robust path tracking of mobile robot using fractional order PID controller. In: Hassanien, A.E., Azar, A.T., Gaber, T., Bhatnagar, R., Tolba, F.M. (eds.) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019), pp. 370–381. Springer, Cham (2020)

    Google Scholar 

  3. Ammar, H.H., Azar, A.T., Tembi, T.D., Tony, K., Sosa, A.: Design and implementation of fuzzy pid controller into multi agent smart library system prototype. In: Hassanien, A.E., Tolba, M.F., Elhoseny, M., Mostafa, M. (eds.) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018), pp. 127–137. Springer, Cham (2018)

    Chapter  Google Scholar 

  4. Azar, A.T., Serrano, F.E.: Adaptive decentralised sliding mode controller and observer for asynchronous nonlinear large-scale systems with backlash. Int. J. Model. Ident. Control 30(1), 61–71 (2018)

    Article  Google Scholar 

  5. Azar, A.T., Serrano, F.E.: Fractional order two degree of freedom PID controller for a robotic manipulator with a fuzzy type-2 compensator. In: Hassanien, A.E., Tolba, M.F., Shaalan, K., Azar, A.T. (eds.) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018, pp. 77–88. Springer, Cham (2019)

    Google Scholar 

  6. Azar, A.T., Ammar, H.H., Barakat, M.H., Saleh, M.A., Abdelwahed, M.A.: Self-balancing robot modeling and control using two degree of freedom PID controller. In: Hassanien, A.E., Tolba, M.F., Shaalan, K., Azar, A.T. (eds.) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018, pp. 64–76. Springer, Cham (2019)

    Google Scholar 

  7. Azar, A.T., Hassan, H., Razali, M.S.A.B., de Brito Silva, G., Ali, H.R.: Two-degree of freedom proportional integral derivative (2-DOF PID) controller for robotic infusion stand. In: Hassanien, A.E., Tolba, M.F., Shaalan, K., Azar, A.T. (eds.) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018, pp. 13–25. Springer, Cham (2019)

    Google Scholar 

  8. Azar, A.T., Ammar, H.H., de Brito Silva, G., Razali, M.S.A.B.: Optimal proportional integral derivative (PID) controller design for smart irrigation mobile robot with soil moisture sensor. In: Hassanien, A.E., Azar, A.T., Gaber, T., Bhatnagar, R., Tolba, F.M. (eds.) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019), pp. 349–359. Springer, Cham (2020)

    Google Scholar 

  9. Chopard, B., Tomassini, M.: An Introduction to Metaheuristics for Optimization. Natural Computing Series. Springer, Heidelberg (2018)

    Book  Google Scholar 

  10. Fekik, A., Denoun, H., Azar, A.T., Hamida, M.L., Zaouia, M., Benyahia, N.: Comparative study of two level and three level PWM-rectifier with voltage oriented control. In: Hassanien, A.E., Tolba, M.F., Shaalan, K., Azar, A.T. (eds.) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018, pp. 40–51. Springer, Cham (2019)

    Google Scholar 

  11. Fister, D., Fister, I., Fister, I., Afari, R.: Parameter tuning of PID controller with reactive nature-inspired algorithms. Robot. Auton. Syst. 84, 64–75 (2016)

    Article  Google Scholar 

  12. Gai, W., Qu, C., Liu, J., Zhang, J.: A novel hybrid meta-heuristic algorithm for optimization problems. Syst. Sci. Control Eng. 6(3), 64–73 (2018)

    Article  Google Scholar 

  13. Gorripotu, T.S., Samalla, H., Jagan Mohana Rao, C., Azar, A.T., Pelusi, D.: TLBO algorithm optimized fractional-order PID controller for AGC of interconnected power system. In: Nayak, J., Abraham, A., Krishna, B.M., Chandra Sekhar, G.T., Das, A.K. (eds.) Soft Computing in Data Analytics, pp. 847–855. Springer, Singapore (2019)

    Google Scholar 

  14. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of ICNN 1995 - International Conference on Neural Networks, vol. 4, pp. 1942–1948 (1995)

    Google Scholar 

  15. Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Optimization by simulated annealing. Science 220(4598), 671–680 (1983)

    Article  MathSciNet  Google Scholar 

  16. Lau, M.C., Baltes, J., Anderson, J., Durocher, S.: A portrait drawing robot using a geometric graph approach: Furthest neighbour theta-graphs. In: 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), pp. 75–79 (2012)

    Google Scholar 

  17. Megalingam, R.K., Raagul, S., Dileep, S., Sathi, S.R., Pula, B.T., Vishnu, S., Sasikumar, V., Gupta, U.S.C.: Design implementation and analysis of a low cost drawing bot for educational purpose. Int. J. Pure Appl. Math. 118(6), 213–230 (2018)

    Google Scholar 

  18. Meghni, B., Dib, D., Azar, A.T.: A second-order sliding mode and fuzzy logic control to optimal energy management in wind turbine with battery storage. Neural Comput. Appl. 28(6), 1417–1434 (2017)

    Google Scholar 

  19. Meghni, B., Dib, D., Azar, A.T., Saadoun, A.: Effective supervisory controller to extend optimal energy management in hybrid wind turbine under energy and reliability constraints. Int. J. Dyn. Control 6(1), 369–383 (2018)

    Google Scholar 

  20. Mekki, H., Boukhetala, D., Azar, A.T.: Sliding modes for fault tolerant control. In: Azar, A.T., Zhu, Q. (eds.) Advances and Applications in Sliding Mode Control systems, pp. 407–433. Springer, Cham (2015)

    Chapter  Google Scholar 

  21. Munna, M.S., Tarafder, B.K., Robbani, M.G., Mallick, T.C.: Design and implementation of a drawbot using matlab and arduino mega. In: 2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), pp. 769–773 (2017). https://doi.org/10.1109/ECACE.2017.7913006

  22. Sabir, M.M., Ali, T.: Optimal pid controller design through swarm intelligence algorithms for sun tracking system. Appl. Math. Comput. 274, 690–699 (2016)

    MathSciNet  MATH  Google Scholar 

  23. Smida, M.B., Sakly, A., Vaidyanathan, S., Azar, A.T.: Control-based maximum power point tracking for a grid-connected hybrid renewable energy system optimized by particle swarm optimization. In: Azar, A.T., Vaidyanathan, S. (ed.) Advances in System Dynamics and Control, IGI Global, pp. 58–89 (2018)

    Google Scholar 

  24. Soliman, M., Azar, A.T., Saleh, M.A., Ammar, H.H.: Path planning control for 3-omni fighting robot using PID and fuzzy logic controller. In: Hassanien, A.E., Azar, A.T., Gaber, T., Bhatnagar, R., Tolba, F.M. (eds.) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019), pp. 442–452. Springer, Cham (2020)

    Google Scholar 

  25. Srinivas, N., Deb, K.: Muiltiobjective optimization using nondominated sorting in genetic algorithms. Evol. Comput. 2(3), 221–248 (1994). https://doi.org/10.1162/evco.1994.2.3.221

    Article  Google Scholar 

  26. Yang, X.S.: A New Metaheuristic Bat-Inspired Algorithm, pp. 65–74. Springer, Heidelberg (2010)

    MATH  Google Scholar 

  27. Ziegler, J., Nichols, N.B.: Optimum settings for automatic controllers. Trans. ASME 64(8), 759–768 (1942)

    Google Scholar 

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Author information

Authors and Affiliations

  1. College of Engineering, Prince Sultan University, Riyadh, Kingdom of Saudi Arabia

    Ahmad Taher Azar

  2. Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt

    Ahmad Taher Azar

  3. School of Engineering and Applied Sciences, Nile University, 6th of October City, Giza, Egypt

    Hossam Hassan Ammar, Mayra Yucely Beb, Santiago Ramos Garces & Abdoulaye Boubakari

Authors
  1. Ahmad Taher Azar
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  2. Hossam Hassan Ammar
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  3. Mayra Yucely Beb
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  4. Santiago Ramos Garces
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  5. Abdoulaye Boubakari
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Correspondence to Ahmad Taher Azar .

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Editors and Affiliations

  1. Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. The British University in Dubai, Dubai, United Arab Emirates

    Khaled Shaalan

  3. Ain Shams University, Cairo, Egypt

    Mohamed Fahmy Tolba

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Azar, A.T., Ammar, H.H., Beb, M.Y., Garces, S.R., Boubakari, A. (2020). Optimal Design of PID Controller for 2-DOF Drawing Robot Using Bat-Inspired Algorithm. In: Hassanien, A., Shaalan, K., Tolba, M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019. AISI 2019. Advances in Intelligent Systems and Computing, vol 1058. Springer, Cham. https://doi.org/10.1007/978-3-030-31129-2_17

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