i-manager Publications

Model Predictive Control of a Serial Link Robot Manipulator

A. Srinivasan*

Department of Electronics and Instrumentation Engineering, SRM Valliammai Engineering College, Chennai, India.

Periodicity:July - December'2023
DOI : https://doi.org/10.26634/jic.11.2.20404

Abstract

This paper presents a novel approach for model predictive control dynamics applied to a two-link manipulator robot. The technique involves the initial step of linearizing the inherently nonlinear dynamic model of the robot through the application of feedback linearization control. Once the linear model is derived, a predictive control strategy is developed to enhance the robot's overall performance. To achieve this, we introduce a quadratic criterion, and the associated parameters are meticulously computed to induce specific behaviors within the closed-loop system. The primary objective of this study is to effectively control the arm robot, guiding it from an initial configuration to a desired final configuration by employing the predictive control approach, all while minimizing the quadratic criterion. The chosen criterion serves as a crucial metric in evaluating the system's response and optimizing its behavior during the control process. To validate the effectiveness of the proposed method, a series of simulation results are provided, showcasing the system's performance under various conditions. These simulations serve as empirical evidence supporting the feasibility and efficiency of the introduced model predictive control approach for the dynamics of a twolink manipulator robot. The outcomes highlight the method's potential for real-world applications and contribute to the ongoing advancement of control strategies in robotic systems.

Keywords

Two DOF Robot Arm, Dynamic Model, Nonlinear Control, Model Predictive Control.

How to Cite this Article?

Srinivasan, A. (2023). Model Predictive Control of a Serial Link Robot Manipulator. i-manager’s Journal on Instrumentation & Control Engineering, 11(2), 19-27. https://doi.org/10.26634/jic.11.2.20404

References

[1]. Gandolfo, D. C., Rossomando, F. G., Soria, C. M., & Carelli, R. O. (2019). Adaptive neural compensator for robotic systems control. IEEE Latin America Transactions, 17(04), 670-676.

[2]. Guechi, E. H., Bouzoualegh, S., Messikh, L., & Blažic, S. (2018, March). Model predictive control of a two-link robot arm. In 2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET) (pp. 409-414). IEEE.

[3]. He, Y., Zhao, B., Hou, X., Gao, P., Hu, Y., & Zhang, P. (2016). An assistant robot system for sinus surgery. Journal of Medical Devices, 10(3), 030925.

[4]. Ma, Y., Cocquempot, V., El Najjar, M. E. B., & Jiang, B. (2017). Multidesign integration based adaptive actuator failure compensation control for two linked 2WD mobile robots. IEEE/ASME Transactions on Mechatronics, 22(5), 2174-2185.

[5]. Minniti, M. V., Farshidian, F., Grandia, R., & Hutter, M. (2019). Whole-body mpc for a dynamically stable mobile manipulator. IEEE Robotics and Automation Letters, 4(4), 3687-3694.

[6]. Mori, S., Tanaka, K., Nishikawa, S., Niiyama, R., & Kuniyoshi, Y. (2019). High-speed humanoid robot arm for badminton using pneumatic-electric hybrid actuators. IEEE Robotics and Automation Letters, 4(4), 3601-3608.

[7]. Oh, S., & Kong, K. (2015). Two-degree-of-freedom control of a two-link manipulator in the rotating coordinate system. IEEE Transactions on Industrial Electronics, 62(9), 5598-5607.

[8]. Prada-Jimenez, V., Niáo-Suaréz, P. A., Portilla-Flores, E. A., & Mauledoux-Monroy, M. F. (2019). Tuning a PD+ controller by means of dynamic optimization in a mobile manipulator with coupled dynamics. IEEE Access, 7, 124712-124726.

[9]. Riul, J. A., Junior, A. G. C., & Montenegro, P. H. M. (2016). Nonlinear neural model of a robot five degrees of freedom. IEEE Latin America Transactions, 14(4), 1652-1655.

[10]. Rouzbeh, B., Bone, G. M., Ashby, G., & Li, E. (2019). Design, implementation and control of an improved hybrid pneumatic-electric actuator for robot arms. IEEE Access, 7, 14699-14713.

[11]. Schnelle, F., & Eberhard, P. (2017). Adaptive nonlinear model predictive control design of a flexible-link manipulator with uncertain parameters. Acta Mechanica Sinica, 33, 529-542.

[12]. Su, H., Qi, W., Yang, C., Aliverti, A., Ferrigno, G., & De Momi, E. (2019). Deep neural network approach in human-like redundancy optimization for anthropomorphic manipulators. IEEE Access, 7, 124207-124216.

[13]. Terry, J. S., Rupert, L., & Killpack, M. D. (2017, November). Comparison of linearized dynamic robot manipulator models for model predictive control. In 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) (pp. 205-212). IEEE.

[14]. Tognon, M., & Franchi, A. (2017). Dynamics, control, and estimation for aerial robots tethered by cables or bars. IEEE Transactions on Robotics, 33(4), 834-845.

[15]. Van Duijkeren, N., Verschueren, R., Pipeleers, G., Diehl, M., & Swevers, J. (2016, June). Path-following NMPC for serial-link robot manipulators using a pathparametric system reformulation. In 2016 European Control Conference (ECC) (pp. 477-482). IEEE.

[16]. Xin, Y., Rong, X., Li, Y., Li, B., & Chai, H. (2019). Movements and balance control of a wheel-leg robot based on uncertainty and disturbance estimation method. IEEE Access, 7, 133265-133273.

[17]. Yang, J., Sun, X., Liao, K., He, Z., & Cai, L. (2019). Model predictive control based load frequency control for power systems with wind turbine generators. IET Renewable Power Generation, 13(15), 2871-2879.

[18]. Zhao, M., Anzai, T., Shi, F., Chen, X., Okada, K., & Inaba, M. (2018). Design, modeling, and control of an aerial robot dragon: A dual-rotor-embedded multilink robot with the ability of multi-degree-of-freedom aerial transformation. IEEE Robotics and Automation Letters, 3(2), 1176-1183.

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Model Predictive Control of a Serial Link Robot Manipulator

Abstract

Keywords

How to Cite this Article?

References

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