Precise Positioning Control Strategy of Machine Tools: A Review


  • Nur Amira Anang Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia.
  • Lokman Abdullah Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia.
  • Zamberi Jamaludin Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia.
  • Zain Retas Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia.
  • Chiew Tsung Heng Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia.
  • Syed Najib Syed Salim Faculty of Engineering Technology, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia.


Machine tools, precise positioning, nonlinear control,


In this article, a precise positioning control strategy for the nonlinearity of machine tools is thoroughly reviewed. Precise positioning is crucial in machine tools industry where nonlinear phenomenon must be considered. Therefore, this paper aims to review various techniques used to enhance the precision of nonlinearity of machine tools. In the introduction, a significant review of machine tools is discussed based on deadzone phenomenon and high bandwidth. After that, linear control strategies are reviewed involving Proportional-Integral-Derivative (PID) and Cascade P/PI controller. This is followed by nonlinear control strategies, Nonlinear PID (NPID), Adaptive NPID (ANPID), Feedforward NPID (FNPID), Adaptive Robust Controller (ARC), Nominal Characteristics Trajectory Following (NCTF) controller and lastly, the fuzzy and neural network control is then reviewed. Finally, conclusions are presented according to the past researches conducted. Further studies regarding the topic can be improved by the implementation of several additional modules such as deadzone and feedforward compensators and disturbance observer that focus on both disturbance forces such as cutting force and friction force.


Altintas, Y., A. Verl, C. Brecher, L. Uriarte, and G. Pritschow. 2011. Machine Tool Feed Drives. CIRP Annals - Manufacturing Technology. 60(2): 779–796.

Cheng, F., K.-C. Fan, J. Miao, B.-K. Li, and H.-Y. Wang. 2012. A BPNN-PID based Long-Stroke Nanopositioning Control Scheme driven by Ultrasonic Motor. Precision Engineering. 36(3): 485–493.

Ariffin, M. K. a., R. Kamaluddin, S. H. Tang, and S. B. Mohammed. 2013. Analysis of Automated G-Clip Machine Processes and Substation Process with Simulation by Using CAD Software. Materials Science Forum. 773–774 28–36.

Aggogeri, F., A. Borboni, R. Faglia, A. Merlo, and S. de Cristofaro. 2013. Precision Positioning Systems: An Overview of the State of Art. Applied Mechanics and Materials. 336–338 1170–1173.

Lin, Z., J. Fu, H. Shen, and W. Gan. 2014. A Generic Uniform Scallop Tool Path Generation Method for Five-Axis Machining of Freeform Surface. Computer-Aided Design. 56 120–132.

Pengbing, Z. and S. Yaoyao. 2014. Adaptive Sliding Mode Control of the A-Axis used for Blisk Manufacturing. Chinese Journal of Aeronautics. 27(3): 708–715.

Tang, T. D. 2014. Algorithms for Collision Detection and Avoidance for Five-Axis NC Machining: A State of the Art Review. Computer-Aided Design. 51 1–17.

Qiu, W., Y. Mizuno, M. Tabaru, and K. Nakamura. 2014. Can Lubricant Enhance the Torque of Ultrasonic Motors? An Experimental Investigation. Applied Physics Letters. 105(22): 224102.

Villegas, F. J., R. L. Hecker, M. E. Peña, D. A. Vicente, and G. M. Flores. 2014. Modeling of a Linear Motor Feed Drive including Pre-rolling Friction and Aperiodic Cogging and Ripple. The International Journal of Advanced Manufacturing Technology. 73(1–4): 267–277.

Fu, G., J. Fu, Y. Xu, and Z. Chen. 2014. Product of Exponential Model for Geometric Error Integration of Multi-Axis Machine Tools. The International Journal of Advanced Manufacturing Technology. 71(9–12): 1653–1667.

Peng, Y., Y. Peng, X. Gu, J. Wang, and H. Yu. 2015. A Review of Long Range Piezoelectric Motors using Frequency Leveraged Method. Sensors and Actuators A: Physical. 235 240–255.

Jamaludin, J., Z. Jamaludin, T. H. Chiew, and L. Abdullah. 2015. Design and Analysis of Disturbance Force Observer for Machine Tools Application. Applied Mechanics and Materials. 761 148–152.

Mayr, J., J. Jedrzejewski, E. Uhlmann, M. Alkan Donmez, W. Knapp, F. Härtig, K. Wendt, T. Moriwaki, P. Shore, R. Schmitt, C. Brecher, T. Würz, and K. Wegener. 2012. Thermal Issues in Machine Tools. CIRP Annals - Manufacturing Technology. 61(2): 771–791.

Qu, J., Y. Zhang, X. Tian, and J. Li. 2015. Wear Behavior of Filled Polymers for Ultrasonic Motor in Vacuum Environments. Wear. 322–323 108–116.

Ahmad, N. J., H. K. Ebraheem, M. J. Alnaser, and J. M. Alostath. 2011. , Adaptive Control of a DC motor with Uncertain Deadzone Nonlinearity at the Input. Chinese Control and Decision Conference (CCDC), 2011. 4295–4299.

He, Y., J. Wang, and R. Hao. 2015. Adaptive robust dead-zone compensation control of electro-hydraulic servo systems with load disturbance rejection. Journal of Systems Science and Complexity. 28(2): 341–359.

Erkorkmaz, K. and A. Kamalzadeh. 2006. High Bandwidth Control of Ball Screw Drives. CIRP Annals - Manufacturing Technology. 55(1): 393–398.

Kamalzadeh, A. and K. Erkorkmaz. 2007. Accurate tracking controller design for high-speed drives. International Journal of Machine Tools and Manufacture. 47(9): 1393–1400.

Erkorkmaz, K. and W. Wong. 2007. Rapid identification technique for virtual CNC drives. International Journal of Machine Tools and Manufacture. 47(9): 1381–1392.

Toscano, R. 2005. A simple robust PI/PID controller design via numerical optimization approach. Journal of Process Control. 15(1): 81–88.

Kiam Heong Ang, G. Chong, and Yun Li. 2005. PID control system analysis, design, and technology. IEEE Transactions on Control Systems Technology. 13(4): 559–576.

Abdullah, L., Z. Jamaludin, T. H. Chiew, N. a. Rafan, and M. Y. Yuhazri. 2012. Extensive Tracking Performance Analysis of Classical Feedback Control for XY Stage Ballscrew Drive System. Applied Mechanics and Materials. 229–231 750–755.

Singh, C. 2015. Genetic Algorithms Based PID controller Design. International Journal of Enginering Development and Research. 3(3): 2–5.

Fan, Y. H., C. E. Chen, and H. W. Liao. 2014. Design of an Optimal PID Controller by Genetic Algorithms for a Pantograph Type XY Platform. Key Engineering Materials. 625 417–422.

Laptev, I., P. Zahn, and G. Pritschow. 2015. Direct sliding mode current control of feed drives. CIRP Annals - Manufacturing Technology. 64(1): 373–376.

Mahajan, V., P. Agarwal, and H. O. Gupta. 2014. An artificial intelligence based controller for multilevel harmonic filter. International Journal of Electrical Power & Energy Systems. 58 170–180.

Liu, H., J. Wang, L. Zhang, and G. Zhao. 2014. , Trajectory tracking of hard rock tunnel boring machine with cascade control structure., in Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference, 2326–2331.

Chen, S. L., D. H. Nam, and N. Van Thanh. 2014. Synchronous Controller for Dual Servo Motor in Servo Press. Applied Mechanics and Materials. 494–495 1175–1181.

Precup, R.-E., E. M. Petriu, M.-B. Rădac, S. Preitl, L.-O. Fedorovici, and C.-A. Dragoş. 2015. Cascade Control System-Based Cost Effective Combination of Tensor Product Model Transformation and Fuzzy Control. Asian Journal of Control. 17(2): 381–391.

Strakos, P. and T. Karasek. 2015. , Adaptive model predictive control as a prospect for control of machine tools with significant flexibility., in Proceeding of the International Conference on Numerical Analysis and Applied Mathematics 2014, 2014, 830006.

Guo, K., J. Wei, J. Fang, R. Feng, and X. Wang. 2015. Position tracking control of electro-hydraulic single-rod actuator based on an extended disturbance observer. Mechatronics. 27 47–56.

Jamaludin, Z. 2008. , Disturbance Compensation for Machine Tools with Linear Motor Drives (Ph. D. Dissertation) Department Wertuigkunde Katholieke Universiteit Leuven, Belgium.

Ibrahim, M., S. N. S. Salim, M. N. Kamarudin, and A. Noordin. 2009. Real Time Cascade PI Control for Position Monitoring of DC Brushed Motor. World Academy of science. 60 983–987.

Krikelis, N. J. 1980. State feedback integral control with ‘ intelligent’ integrators. International Journal of Control. 32(3): 465–473.

Shahruz, S. M. and A. L. Schwartz. 1994. Design and optimal tuning of nonlinear PI compensators. Journal of Optimization Theory and Applications. 83(1): 181–198.

Seraji, H. 1998. Nonlinear and Adaptive Control of Force and Compliance in Manipulators. The International Journal of Robotics Research. 17(5): 467–484.

Armstrong, B., D. Neevel, and T. Kusik. 2001. New results in NPID control: Tracking, integral control, friction compensation and experimental results. IEEE Transactions on Control Systems Technology. 9(2): 399–406.

Abdullah, L., Z. Jamaludin, J. Jamaludin, M. R. Salleh, B. Abu Bakar, M. N. Maslan, T. . Chiew, and N. a. Rafan. 2013. , Design and Analysis of Self-tuned Nonlinear PID Controller for XY Table Ballscrew Drive System., in Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation, 3(3ca):, 419–422.

Dong, R. and W. Pedrycz. 2015. Approximation grid evaluation-based PID control in cascade with nonlinear gain. Journal of the Franklin Institute. 352(10): 4279–4296.

Zhang, Y., Y. G. Gong, and L. F. Chen. 2015. The Application of Intelligent Prediction Nonlinear PID Control in Nc Position Control. Int. Conf. on Artifical Intelligence and Industrial Engineering. (Aiie): 143–145.

Segovia, J. P., D. Sbarbaro, and E. Ceballos. 2004. An adaptive pattern based nonlinear PID controller. Isa Transaction. 271–281.

Nuella, I., C. Cheng, and M.-S. Chiu. 2009. Adaptive PID Controller Design for Nonlinear Systems. Industrial & Engineering Chemistry Research. 48(10): 4877–4883.

Tang, H. and Y. Li. 2015. Feedforward nonlinear PID control of a novel micromanipulator using Preisach hysteresis compensator. Robotics and Computer-Integrated Manufacturing. 34 124–132.

Bin Y., M. Al-Majed, and M. Tomizuka. 1997. High-performance robust motion control of machine tools: an adaptive robust control approach and comparative experiments. IEEE/ASME Transactions on Mechatronics. 2(2): 63–76.

Xu, L. and B. Yao. 2001. Output feedback adaptive robust precision motion control of linear motors. Automatica. 37(7): 1029–1039.

Yao, B. and L. Xu. 2002. Adaptive robust motion control of linear motors for precision manufacturing. Mechatronics. 12(4): 595–616.

Sato, K. and Y. Sano. 2014. Practical and intuitive controller design method for precision positioning of a pneumatic cylinder actuator stage. Precision Engineering. 38(4): 703–710.

Hee, W.-K., S.-H. Chong, and A. C. Amran. 2014. , Selection of PI compensator parameters for NCTF controller based on practical stability limit., in 2014 IEEE International Conference on Control System, Computing and Engineering (ICCSCE 2014), (November):, 674–679.

Maeda, G. J. and K. Sato. 2008. Practical control method for ultra-precision positioning using a ballscrew mechanism. Precision Engineering. 32(4): 309–318.

Chong, S.-H. and K. Sato. 2011. , Practical and robust control for precision positioning systems., in 2011 IEEE International Conference on Mechatronics, (April):, 961–966.

Yang, J., H. Shi, B. Feng, L. Zhao, C. Ma, and X. Mei. 2014. Applying Neural Network based on Fuzzy Cluster Pre-processing to Thermal Error Modeling for Coordinate Boring Machine. Procedia CIRP. 17 698–703.

Savran, A. and G. Kahraman. 2014. A fuzzy model based adaptive PID controller design for nonlinear and uncertain processes. ISA Transactions. 53(2): 280–288.

Kang, J., W. Meng, A. Abraham, and H. Liu. 2014. An adaptive PID neural network for complex nonlinear system control. Neurocomputing. 135 79–85.

El-Sousy, F. F. M. 2016. Intelligent mixed H2/H∞ adaptive tracking control system design using self-organizing recurrent fuzzy-wavelet-neural-network for uncertain two-axis motion control system. Applied Soft Computing. 41 22–50.

Boithias, F., M. El Mankibi, and P. Michel. 2012. Genetic algorithms based optimization of artificial neural network architecture for buildings’ indoor discomfort and energy consumption prediction. Building Simulation. 5(2): 95–106.

Raafat, S. M., R. Akmeliawati, and W. Martono. 2010. Intelligent robust control design of a precise positioning system. International Journal of Control, Automation and Systems. 8(5): 1123–1132.

Raafat, S. M. and R. Akmeliawati. 2010. , Intelligent disturbance rejection for robust tracking performance of X-Y positioning system., in 2010 IEEE International Conference on Mechatronics and Automation, 252–257.




How to Cite

Anang, N. A., Abdullah, L., Jamaludin, Z., Retas, Z., Tsung Heng, C., & Syed Salim, S. N. (2017). Precise Positioning Control Strategy of Machine Tools: A Review. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(3-2), 11–15. Retrieved from