System Identification and Intelligent Control of Flexible Manipulator System

Mohsen Gol Zardian, Intan Z. Mat Darus, Mohammad Reza Miveh


Position control of flexible manipulator system is normally accompanied with tip vibration that results in degradation of performance. This paper investigates an active control strategy by applying classical PID controller to suppress unwanted vibration of flexible manipulator in presence of disturbances. The parameters of PID controller are tuned by genetic algorithm (GA) and particle swarm optimization (PSO) in the intelligent (self-tuning) manner. The results of these two optimization methods are compared toward vibration control capability, moreover; modeling of flexible manipulator is conducted by applying system identification method in which autoregressive with exogenous input (ARX) model is intended as linear model. This research can be regarded as guidance for further elaborate research on implementing optimization method particularly integrated with PID controller for flexible manipulator system modeled by system identification approach.


Flexible manipulator, System identification, Genetic algorithm (GA), particle swarm optimization (PSO), PID controller

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Abdolvand, M., & Fatehi, M. H. (2012). Model-Base Predictive Control for Vibration Suppression of a Flexible Manipulator. UKACC Internatinal Conference on Control. cardfii, uk, 3–5.

Ahmed, M.A., Nasir, A.N., Ismail, R., & Ramli, M.S. (2010). Control Strategy for Active Vibration Suppression of Flexible Robot Manipulator, Proceedings of IEEE Internatinal Conference on Information and Automation, Harbin, Chaina, 741–746.

Becedas, J., Trapero, J.R., Sira-Ramorez, H., & Feliu-Battle, V.(2007). Fast Identification Method to Control a Flexible Manipulator with Parameter Uncertainties. IEEE internatinal Conference on Robotics and Automation, Roma, Italy, 10-14

Brouwer, D., Jongc, B., & Soemers, H.M.(2010). Design and Modelling of a Six DOFsMEMS-Based Precision Manipulator. Precision Engineering, 18(2),307-319.

Gol Zardian, M., & Ayob, A. (2015). Intelligent modelling and active vibration control of flexible manipulator system. Journal of Vibroengineering, 17(4), 1879-1891.

Mute, D., Ghosh, S., &Subudhi, B. (2013). Iterative Learning Control of a Single-Link Flexible Manipulator Based on an Identified Adaptive NARX Model. Annual IEEE India Conference (INDICON), 1(1).

Nille ,O (2001). Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models. Springer Science & Business Media.

Qiu, Z., Shi, M., Wang, B., & Xie, Z. (2012). Genetic Algorithm Based Active Vibration Control for a Moving Flexible Smart Beam Driven by a Pneumatic Rod Cylinder. Journal of Sound and Vibration, 331(10), 2233-2256.

Ramos, F., & Feliu,V. (2008). New online payload identification for flexible robots, aplication to adaptive control, Juornal of Sound and Vibration. 315(1-2), 34-57.

Sekiguchi, Y., Kobayashi, Y., Tomono, Y., Watanabe, H., Toyoda, K., Hashizume, M., & Fujie, M. (2010). Development of a Tool Manipulator Driven by a Flexible Shaft for Single Port Endoscopic Surgery. Proceedings of the 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, The University of Tokyo, Tokyo, Japan, September 26-29,120–125.

Shawky, A., Zydek, D., Yehia Z., & Ordys, A. (2013). Modelling and Nonlinear Control of a Flexible-Link Manipulator. Applied Mathematical Modelling, 37(23),9591-9602.

Tavakolpour, A., Maliah, M., & Darus, I.Z.M.(2011). Modeling and Simulation of a Novel Active Vibration Control System for Flexible Structures, Wseas Transactions On Systems And Control, 6(5).

Tokhi, M.O., Mohamed, Z., & Shaheed, M.H. (2001). Dynamic Characteristic of Flexible Manipulator System, Robatica, 19, No, 571-580.

Vakil, M., Fotouhi,R., & Nikiforuk, P.N.(2009). Causal End-Effector Inversion of a Flexible Link Manipulator. Mechatronics, 19(7), 1197-1210.

Yatim, H.M., & Darus, I.Z.M. (2012). Intelligent Parametric Identification of Flexible Manipulator System . IEEE Conference On Control, System And Industrial Information(ICCSII), Bandung, Indonesia, 23-26

Zain, M., Tokhi, M.O., & Mohamed, B. (2006). Hybrid Learning Control Schemes with Input Shaping of a Flexible Manipulator System, Mechateronics, 16, 209-219.

Zarafshan, P., & Moosavian, S. A. A. (2013). Dynamics modelling and Hybrid Suppression Control of space robots performing cooperative object manipulation. Communications in Nonlinear Science and Numerical Simulation, 18(10), 2807-2824.

Ziaei, K., &Wang, D. (2009). QFT-Based Design of Force and Contact Transition Controllers for a Flexible Link Manipulator. Control Engineering Practice, 17(3), 329-344.


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