Journal of Intelligent Manufacturing

, Volume 30, Issue 8, pp 2819–2833 | Cite as

Industrial feedforward control technology: a review

  • Lu LiuEmail author
  • Siyuan Tian
  • Dingyu Xue
  • Tao Zhang
  • YangQuan Chen


In the control field, most of the research papers focus on feedback control, but few of them have discussed about feedforward control. Therefore, a review of the most commonly used feedforward control algorithms in industrial processes is necessary to be carried out. In this paper, in order to benefit researchers and engineers with different academic backgrounds, two most representative kinds of feedforward controller design algorithms and some other typical industrial feedforward control benchmarks are presented together with their characteristics, application domains and informative comments for selection. Moreover, some frequently concerned problems of feedforward control are also discussed. An industrial data driven example is presented to show how feedforward controller works to improve system performance and achieve the maximum economic profits.


Feedforward control Industrial application Disturbance rejection Reference tracking Temperature control 



The authors would thank Lam Research Corporation for the on-line data provided. The authors would also thank Editor-in-Chief, Associate Editor and anonymous reviewers for their useful comments and efforts to improve this paper.


  1. Abilov, A. G., Zeybek, Z., Tuzunalp, O., & Telatar, Z. (2002). Fuzzy temperature control of industrial refineries furnaces through combined feedforward/feedback multivariable cascade systems. Chemical Engineering and Processing, 41(1), 87–98.Google Scholar
  2. Abukhalifeh, H., Dhib, R., & Fayed, M. (2005). Model predictive control of an infrared-convective dryer. Drying Technology, 23(3), 497–511.Google Scholar
  3. Adam, E., & Marchetti, J. L. (2004). Designing and tuning robust feedforward controllers. Computers & Chemical Engineering, 28(9), 1899–1911.Google Scholar
  4. Ali, S. S. A., Al Sunni, F. M., Shafiq, M., & Bakhashwain, J. M. (2010). U-model based learning feedforward control of MIMO nonlinear systems. Electrical Engineering, 91(8), 405–415.Google Scholar
  5. Altmann, W. (2005). Practical process control for engineers and technicians. Newnes.Google Scholar
  6. Anderson, B. D., & Moore, J. B. (2007). Optimal control: Linear quadratic methods. Courier Corporation.Google Scholar
  7. Ang, W. T., Khosla, P. K., & Riviere, C. N. (2007). Feedforward controller with inverse rate-dependent model for piezoelectric actuators in trajectory-tracking applications. IEEE/ASME Transactions on Mechatronics, 12(2), 134–142.Google Scholar
  8. Anibal Valenzuela, M., Bentley, J. M., Aguilera, P. C., & Lorenz, R. D. (2007). Improved coordinated response and disturbance rejection in the critical sections of paper machines. IEEE Transactions on Industry Applications, 43(3), 857–869.Google Scholar
  9. Barkefors, A., & Sternad, M. (2014). Design and analysis of linear quadratic Gaussian feedforward controllers for active noise control. IEEE Press, pp. 1777–1791.Google Scholar
  10. Bartroli, A., Perez, J., & Carrera, J. (2010). Applying ratio control in a continuous granular reactor to achieve full nitritation under stable operating conditions. Environmental Science & Technology, 44(23), 8930–8935.Google Scholar
  11. Brosilow, C., & Joseph, B. (2002). Techniques of model-based control. Englewood cliffs: Prentice Hall.Google Scholar
  12. Buehner, M. R., & Young, P. M. (2015). Robust adaptive feedforward control and achievable tracking for systems with time delays. International Journal of Control, 88(4), 768–782.Google Scholar
  13. Chen, S. S. (1992). Intelligent control of semiconductor manufacturing processes. In Proceedings of IEEE international conference on fuzzy systems. IEEE, pp. 101–108.Google Scholar
  14. Chen, Y., & Moore, K. L. (2001). Frequency domain adaptive learning feedforward control. In Proceedings of 2001 IEEE international symposium on computational intelligence in robotics and automation. IEEE, pp. 396–401.Google Scholar
  15. Chiu, C. S. (2006). Mixed feedforward/feedback based adaptive fuzzy control for a class of MIMO nonlinear systems. IEEE Transactions on Fuzzy Systems, 14(6), 716–727.Google Scholar
  16. Choi, J. Y., & Do, H. M. (2001). A learning approach of wafer temperature control in a rapid thermal processing system. IEEE Transactions on Semiconductor Manufacturing, 14(1), 1–10.Google Scholar
  17. Chue, J. M., & Hugunin, T. D. (2010). Feedforward compensation for fly height control in a disk drive, Nov. 23 US Patent 7,839,595.Google Scholar
  18. Cori, R., & Maffezzoni, C. (1984). Practical-optimal control of a drum boiler power plant. Automatica, 20(2), 163–173.Google Scholar
  19. Corripio, A. B. (2000). Tuning of industrial control systems. Instrument Society of America.Google Scholar
  20. Dang, C., Tong, X., Huang, J., Wang, Q., & Zhang, H. (2017). Qpr and duty ratio feedforward control for vienna rectifier of HVDC supply system. IEEE Transactions on Electrical and Electronic Engineering.Google Scholar
  21. De xin, G., & Hou peng, D. (2011). Optimal disturbance rejection via feedforward-PD for MIMO systems with external sinusoidal disturbances. Procedia Engineering, 15, 459–463.Google Scholar
  22. Elliott, S. J. (2000). Optimal controllers and adaptive controllers for multichannel feedforward control of stochastic disturbances. IEEE Transactions on Signal Processing, 48(4), 1053–1060.Google Scholar
  23. Elliott, S. J., & Sutton, T. J. (1996). Performance of feedforward and feedback systems for active control. IEEE Transactions on Speech and Audio Processing, 4(3), 214–223.Google Scholar
  24. Ferreres, G., & Roos, C. (2005). Efficient convex design of robust feedforward controllers. In Proceedings of the 44th IEEE conference on decision and control. IEEE, pp. 6460–6465.Google Scholar
  25. Fujimoto, H., Hori, Y., Yamaguchi, T., & Nakagawa, S. (2000). Proposal of seeking control of hard disk drives based on perfect tracking control using multirate feedforward control. In Proceedings of the 6th international workshop on advanced motion control. IEEE, pp. 74–79.Google Scholar
  26. Fujimoto, H., Hori, Y., & Kawamura, A. (2001). Perfect tracking control based on multirate feedforward control with generalized sampling periods. IEEE Transactions on Industrial Electronics, 48(3), 636–644.Google Scholar
  27. Gagnon, E., Pomerleau, A., & Desbiens, A. (1998). Simplified, ideal or inverted decoupling? ISA Transactions, 37(4), 265–276.Google Scholar
  28. Ghosh, R., & Narayanan, G. (2007). Generalized feedforward control of single-phase pwm rectifiers using disturbance observers. IEEE Transactions on Industrial Electronics, 54(2), 984–993.Google Scholar
  29. Gonzalez, C. (1995). Fuel blending system method and apparatus. Nov. 28, US Patent 5,469,830.Google Scholar
  30. Goodwin, G. C., Graebe, S. F., & Salgado, M. E. (2001). Control system design (Vol. 240). New Jersey: Prentice Hall.Google Scholar
  31. Gross, E., Tomizuka, M., & Messner, W. (1994). Cancellation of discrete time unstable zeros by feedforward control. Journal of Dynamic Systems, Measurement, and Control, 116(1), 33–38.Google Scholar
  32. Hägglund, T. (2001). The blend stationa new ratio control structure. Control Engineering Practice, 9(11), 1215–1220.Google Scholar
  33. Hori, Y., Sawada, H., & Chun, Y. (1999). Slow resonance ratio control for vibration suppression and disturbance rejection in torsional system. IEEE Transactions on Industrial Electronics, 46(1), 162–168.Google Scholar
  34. Ho, W. K., Tay, A., Chen, M., & Kiew, C. M. (2007). Optimal feed-forward control for multizone baking in microlithography. Industrial & Engineering Chemistry Research, 46(11), 3623–3628.Google Scholar
  35. Isermann, R. (2013). Digital control systems. Berlin: Springer.Google Scholar
  36. Ismail, H., Ishak, N., Tajjudin, M., Rahiman, M. H. F., & Adnan, R. (2012). Adaptive feedforward zero phase error tracking control with model reference for high precision xy table, In Proceedings of the 4th international conference on intelligent and advanced systems (ICIAS), vol. 2. IEEE, pp. 526–530.Google Scholar
  37. Jain, N., Otten, R. J., & Alleyne, A. G. (2010). Decoupled feedforward control for an air-conditioning and refrigeration system. In Proceedings of American control conference, pp. 5904–5909.Google Scholar
  38. Jiang, Y., Zhu, Y., Yang, K., Hu, C., & Yu, D. (2015). A data-driven iterative decoupling feedforward control strategy with application to an ultraprecision motion stage. IEEE Transactions on Industrial Electronics, 62(1), 620–627.Google Scholar
  39. Jinzenji, A., Sasamoto, T., Aikawa, K., Yoshida, S., & Aruga, K. (2001). Acceleration feedforward control against rotational disturbance in hard disk drives. IEEE Transactions on Magnetics, 37(2), 888–893.Google Scholar
  40. Johansson, B. (2003). Feedforward control in dynamic situations, Ph.D. dissertation, Linköping University.Google Scholar
  41. Kaibel, G. (1987). Distillation columns with vertical partitions. Chemical Engineering & Technology, 10(1), 92–98.Google Scholar
  42. Karer, G., Mui, G., krjanc, I., & Zupani, B. (2011). Feedforward control of a class of hybrid systems using an inverse model. Mathematics and Computers in Simulation, 82(3), 414–427.Google Scholar
  43. Kempf, C. J., & Kobayashi, S. (1999). Disturbance observer and feedforward design for a high-speed direct-drive positioning table. IEEE Transactions on Control Systems Technology, 7(5), 513–526.Google Scholar
  44. Kim, H., Lee, K., Jeon, B., & Song, C. (2010). Quick wafer alignment using feedforward neural networks. IEEE Transactions on Automation Science and Engineering, 7(2), 377–382.Google Scholar
  45. Klančar, G., & Škrjanc, I. (2007). Tracking-error model-based predictive control for mobile robots in real time. Robotics and Autonomous Systems, 55(6), 460–469.Google Scholar
  46. Ko, P. J., Wang, Y. P., & Tien, S. C. (2013). Inverse-feedforward and robust-feedback control for high-speed operation on piezo-stages. International Journal of Control, 86(2), 197–209.Google Scholar
  47. Kusama, A., Nakamachi, I., Shigihara, K., Amemori, H., Miyata, Y., & Iwamoto, T. (1986). Air fuel ratio control system for furnace. Apr. 29, US Patent 4,585,161.Google Scholar
  48. Lee, H. S., & Tomizuka, M. (1996). Robust motion controller design for high-accuracy positioning systems. IEEE Transactions on Industrial Electronics, 43(1), 48–55.Google Scholar
  49. Li, M., Zhu, Y., Yang, K., Hu, C., & Mu. H. (2016). An integrated model-data based zero phase error tracking feedforward control strategy with application to an ultra-precision wafer stage. IEEE Transactions on Industrial Electronics, pp. 1–1.Google Scholar
  50. Li, H., Jeong, S. K., & You, S. S. (2009). Feedforward control of capacity and superheat for a variable speed refrigeration system. Applied Thermal Engineering, 29(5), 1067–1074.Google Scholar
  51. Malchow, F., & Sawodny, O. (2012). Model based feedforward control of an industrial glass feeder. Control Engineering Practice, 20(20), 6268.Google Scholar
  52. Marconi, L., & Isidori, A. (2000). Mixed internal model-based and feedforward control for robust tracking in nonlinear systems. Automatica, 36(7), 993–1000.Google Scholar
  53. Marlin, T. E. (2000). Process control. New York: McGraw-Hill.Google Scholar
  54. Miyazaki, T., Ohishi, K., Inomata, K., Kuramochi, K., Koide, D., & Tokumaru, D. (2004). Robust feedforward tracking control based on sudden disturbance observer and zpet control for optical disk recording system. In Proceedings of the 8th IEEE international workshop on advanced motion control. IEEE, pp. 353–358.Google Scholar
  55. Nedic, N., Stojanovic, V., & Djordjevic, V. (2015). Optimal control of hydraulically driven parallel robot platform based on firefly algorithm. Nonlinear Dynamics, 82(3), 1–17.Google Scholar
  56. O’Brien, M. J., & Broussard, J. R. (1979). Feedforward control to track the output of a forced model. In Proceedings of the 17th IEEE conference on symposium on adaptive processes. IEEE, pp. 1149–1155.Google Scholar
  57. Park, H. S., Chang, P. H., & Lee, D. Y. (1999). Continuous zero phase error tracking controller with gain error compensation. In Proceedings of the 1999 American control conference, vol. 5. IEEE, pp. 3554–3558.Google Scholar
  58. Peng, H., & Tomizuka, M. (1993). Preview control for vehicle lateral guidance in highway automation. Journal of Dynamic Systems, Measurement, and Control, 115(4), 679–686.Google Scholar
  59. Piccagli, S., & Visioli, A. (2009). An optimal feedforward control design for the set-point following of MIMO processes. Journal of Process Control, 19(6), 978–984.Google Scholar
  60. Powell, J. D., Fekete, N., & Chang, C.-F. (1998). Observer-based air fuel ratio control. IEEE Control Systems, 18(5), 72–83.Google Scholar
  61. Rong, H. J., Wei, J. T., Bai, J. M., Zhao, G. S., & Liang, Y. Q. (2015). Adaptive neural control for a class of MIMO nonlinear systems with extreme learning machine. Neurocomputing, 149, 405–414.Google Scholar
  62. Ruegsegger, S., Wagner, A., Freudenberg, J. S., & Grimard, D. S. (1999). Feedforward control for reduced run-to-run variation in microelectronics manufacturing. IEEE Transactions on Semiconductor Manufacturing, 12(4), 493–502.Google Scholar
  63. Schaper, C. D., Cho, Y. M., Park, P., Norman, S. A., Gyugyi, P., Hoffmann, G., Balemi, S., Boyd, S. P., Franklin, G., Kailath, T. et al. (1992). Modeling and control of rapid thermal processing. In Proceedings of rapid thermal and integrated processing. International Society for Optics and Photonics, pp. 2–17.Google Scholar
  64. Seborg, D. E., Mellichamp, D. A., Edgar, T. F., & Doyle, F. J. (2010). Process dynamics and control. London: Wiley.Google Scholar
  65. Seidler, R., Noll, D., & Thiers, G. (2004). Feedforward and feedback processes in motor control. Neuroimage, 22(4), 1775–1783.Google Scholar
  66. Shinskey, F. G., & Levine, W. (1996). The control handbook. CRC Press and IEEE Press.Google Scholar
  67. Shinskey, F. G. (1990). Process control systems: Application, design and tuning. NY: McGraw-Hill.Google Scholar
  68. Skogestad, S., & Morari, M. (1987). Control configuration selection for distillation columns. AIChE Journal, 33(10), 1620–1635.Google Scholar
  69. Song, G., Zhao, J., Zhou, X., & De Abreu-García, J. A. (2005). Tracking control of a piezoceramic actuator with hysteresis compensation using inverse preisach model. IEEE/ASME Transactions on Mechatronics, 10(2), 198–209.Google Scholar
  70. Stoddard, K., Crouch, P., Kozicki, M., & Tsakalis, K. (1994). Application of feedforward and adaptive feedback control to semiconductor device manufacturing. In: Proceedings of the 1994 American control conference, vol. 1. IEEE, pp. 892–896.Google Scholar
  71. Stojanovic, V., & Nedic, N. (2016). A nature inspired parameter tuning approach to cascade control for hydraulically driven parallel robot platform. Journal of Optimization Theory & Applications, 168(1), 332–347.Google Scholar
  72. Stojanovic, V., & Nedic, N. (2016). Identification of time-varying OE models in presence of non-Gaussian noise: Application to pneumatic servo drives. International Journal of Robust & Nonlinear Control, 26(18), 3974–3995.Google Scholar
  73. Stojanovic, V., & Nedic, N. (2016). Joint state and parameter robust estimation of stochastic nonlinear systems. International Journal of Robust & Nonlinear Control, 26(14), 3058–3074.Google Scholar
  74. Tan, S. C., Lai, Y., Tse, C. K., & Cheung, M. K. (2006). Adaptive feedforward and feedback control schemes for sliding mode controlled power converters. IEEE Transactions on Power Electronics, 21(1), 182–192.Google Scholar
  75. Tao, K. M., Kosut, R. L., & Aral, G. (1994). Learning feedforward control. In Proceedings of the 1994 American control conference, vol. 3. IEEE, pp. 2575–2579.Google Scholar
  76. Tao, K. M., Kosut, R. L., & Ekblad, M. (1994). Feedforward learning-nonlinear processes and adaptation. In Proceedings of the 33rd IEEE conference on decision and control, vol. 2. IEEE, pp. 1060–1065.Google Scholar
  77. Tao, K. M., Kosut, R. L., Ekblad, M., & Aral, G. (1994). Feedforward learning applied to rtp of semiconductor wafers. In Proceedings of the 33rd IEEE conference on decision and control, vol. 1. IEEE, pp. 67–72.Google Scholar
  78. Tomizuka, M. (1974). The optimal finite preview problem and its application to man-machine systems. Ph.D. dissertation, Massachusetts Institute of Technology.Google Scholar
  79. Tomizuka, M. (1987). Zero phase error tracking algorithm for digital control. Journal of Dynamic Systems, Measurement, and Control, 109(1), 65–68.Google Scholar
  80. Tomizuka, M. (1992). Feedforward digital tracking controllers for motion control applications. Advanced Robotics, 7(6), 575–586.Google Scholar
  81. Tomizuka, M. (1993). On the design of digital tracking controllers. Journal of Dynamic Systems, Measurement, and Control, 115(2B), 412–418.Google Scholar
  82. Tomizuka, M., Dornfeld, D., & Purcell, M. (1980). Application of microcomputers to automatic weld quality control. Journal of Dynamic Systems, Measurement, and Control, 102(2), 62–68.Google Scholar
  83. Tomizuka, M., & Janczak, D. (1985). Linear quadratic design of decoupled preview controllers for robotic arms. International Journal of Robotics Research, 4(1), 67–74.Google Scholar
  84. Torfs, D., De Schutter, J., & Swevers, J. (1992). Extended bandwidth zero phase error tracking control of nonminimal phase systems. Journal of Dynamic Systems, Measurement, and Control, 114(3), 347–351.Google Scholar
  85. Tsao, T. C., & Tomizuka, M. (1987). Adaptive zero phase error tracking algorithm for digital control. Journal of Dynamic Systems, Measurement, and Control, 109(4), 349–354.Google Scholar
  86. Wagner, A. B., Ruegsegger, S. M., Freudenberg, J. S., & Grimard, D. S. (1999). Interprocess run-to-run feedforward control for wafer patterning. In Proceedings of the 1999 IEEE international conference on control applications, vol. 1. IEEE, pp. 789–795.Google Scholar
  87. Wang, J., & Malakooti, B. (1992). A feedforward neural network for multiple criteria decision making. Computers & Operations Research, 19(2), 151–167.Google Scholar
  88. Wu, M. F., Lin, W. K., Ho, C.-L., Wong, D. S. H., Jang, S. S., Zheng, Y., et al. (2007). A feed-forward/feedback run-to-run control of a mixed product process: Simulation and experimental studies. Industrial & Engineering Chemistry Research, 46(21), 6963–6970.Google Scholar
  89. Yamada, M., Funahashi, Y., & Fujiwara, Si. (1997). Zero phase error tracking system with arbitrarily specified gain characteristics. Journal of Dynamic Systems, Measurement, and Control, 119(2), 260–264.Google Scholar
  90. Yamada, M., Funahashi, Y., & Riadh, Z. (1999). Generalized optimal zero phase error tracking controller design. Journal of Dynamic Systems, Measurement, and Control, 121(2), 165–170.Google Scholar
  91. Yan, M. T., & Shiu, Y. J. (2008). Theory and application of a combined feedback-feedforward control and disturbance observer in linear motor drive wire-edm machines. International Journal of Machine Tools and Manufacture, 48(3), 388–401.Google Scholar
  92. Zhou, K., Doyle, J. C., Glover, K., et al. (1996). Robust and optimal control (Vol. 40). New Jersey: Prentice hall.Google Scholar
  93. Zhou, K., & Wang, D. (2002). Unified robust zero-error tracking control of CVCF PWM converters. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 49(4), 492–501.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Lu Liu
    • 1
    Email author
  • Siyuan Tian
    • 2
  • Dingyu Xue
    • 3
  • Tao Zhang
    • 2
  • YangQuan Chen
    • 4
  1. 1.School of Marine Science and TechnologyNorthwestern Polytechnical UniversityXi’anChina
  2. 2.Lam Research CorporationFremontUSA
  3. 3.Department of Information Science and EngineeringNortheastern UniversityShenyangChina
  4. 4.Mechatronics, Embedded Systems and Automation (MESA) Lab, School of EngineeringUniversity of CaliforniaMercedUSA

Personalised recommendations