International Journal of Advanced Multidisciplinary Application

Model Reference Adaptive Control for Agriculture Application

Author(s):Tufan Bera, Pritam Chatterjee, Argha Maji, Ashis De

Affiliation: Department of Electronics & Communication Engineering, Gargi Memorial Institute of Technology, Kolkata, India

Page No: 33-41

Volume issue & Publishing Year: Volume 3, Issue 3, March 2026

published on: 2026/03/07

Journal: International Journal of Advanced Multidisciplinary Application.(IJAMA)

ISSN NO: 3048-9350

DOI: https://doi.org/10.5281/zenodo.18898289

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Abstract:
A new approach to adaptive model reference control, based on MIT rule is presented. Modern agricultural machines happen to work for prolonged periods of time in considerably harsh environments. This puts a higher demand on the automatic control systems and steering control in particular. Long-term machine operation leads to variance of the physical parameters of the working fluid, positive overlap in proportional valve, working temperature and machine components. In this paper we will be discussing about Model Reference Adaptive control (MRAC) which is an approach to solve real world problems related to Adaptive Control. The present research is focused on the design and application of model reference adaptive controller (MRAC) for control of steering angle of a heavy duty agriculture mobile machine through a hydraulic cylinder. The synthesized controller is based on simple integrator model of the steering cylinder and Lyapunov stability theorems. The closed-loop system achieves good performance and the adaptive gain is stabilized around its mean value too.

Keywords: Model Reference Adaptive control (MRAC), Steering, Agricultural, MIT Rule

Reference:

• 1. H. Goud and P. Swarnkar, “Signal synthesis model reference adaptive controller with artificial intelligent technique for a control of continuous stirred tank reactor”, Int. J. Chem. React. Eng., vol. 17, no. 2, pp. 1-8, Feb. 2019.
• 2. R. B. Anderson, J. A. Marshall, and J. A. L ‘Aflitto, “Constrained robust model reference adaptive control of a tilt-rotor quadcopter pulling an unmodeled cart”, IEEE Trans. Aerosp. Electron. Syst., early access, Jul. 10, 2020, doi: 10.1109/TAES.2020.3008575.
• 3. R. Nair and G. Narayanan, “Stator flux based model reference adaptive observers for sensorless vector control and direct voltage control of doubly-fed induction generator”, IEEE Trans. Ind. Appl., vol. 56, no. 4, pp. 3776-3789, Aug. 2020.
• 4. C. Y. Wu, J. Li, B. Niu, and X. P. Huang, “Switched concurrent learning adaptive control of switched systems with nonlinear matched uncertainties”, IEEE Access, vol. 8, pp. 33560-33576, Feb. 2020.
• 5. G. Song and G. Tao, “A partial-state feedback model reference adaptive control scheme”, IEEE Trans. Autom. Control, vol. 65, no. 1, pp. 44-57, Jan. 2020.
• 6. M. S. Amiri, R. Ramli, and M. F. Ibrahim, “Initialized model reference adaptive control for lower limb exoskeleton”, IEEE Access, vol. 7, pp. 167210-167220, Nov. 2019.
• 7. M. Kumar and B. Tyagi, “Design of a model reference adaptive controller(MRAC) for DC-DC boost converter for variations in solar outputs using modified MIT rule in an islanded microgrid”, in Proc. IEEE Int. Conf. Power Electron., Smart Grid Renew. Energy (PESGRE), Cochin, India,
• Jan. 2020, pp. 1-6.
• 8. E. Mathew, T. Pawar, and B. Jaganatha Pandian, “Control of a coupled CSTR process using MRAC-MIT rule”, in Proc. Innov. Power Adv. Com-put. Technol. (i-PACT), Vellore, India, Mar. 2019, pp. 1-6.
• 9. K. Narendra and L. Valavani, “Stable adaptive controller design-direct control”, IEEE Trans. Autom. Control, vol. 23, no. 4, pp. 570-583, Aug. 1978.
• 10. N.T. Nyugen, Model Reference Adaptive Control, Moffen Field, CA: Springer International Publishing, pp.83-106,2018.
• 11. Yang Y, C. Zhou etc. “Model reference adaptive robust fuzzy control for ship steering autopilot with uncertain nonlinear systems”, Applied Soft Computing, Elsevier, 2003.
• 12. Danfoss, “OSPE Steering Valve”, Technical Information, 11068682, November, 2016.