Model Based Control of Disturbance Forces for Pitch Plane Stability of a Tractor with Implement

Anche, Gurudatta M.; Devika, K. B.; Subramanian, Shankar C.

doi:10.1109/codit.2019.8820586

Cited by 2 publications

(1 citation statement)

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“…The model accuracy was found to improve by 31% with the use of a second order model. The systematic procedure followed to obtain second-order model parameters was reported [29], and the model obtained is given by,…”

Section: System Modellingmentioning

confidence: 99%

Robust Pitching Disturbance Force Attenuation for Tractor Considering Functional Constraints

2020

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Tractors are attached with function-specific implements with the help of an electro-hydraulic hitch system, to carry out various farm operations. Forces arising during travel with the lifted implement on uneven terrain, generate disturbance forces on the hitch system. In this study, the electro-hydraulic system was controlled such that the disturbance forces are attenuated. A second order transfer function model of the hitch system was obtained using experimental data. In order to account for the nonlinearities in the system, an advanced Sliding Mode Controller with Power Rate Exponential Reaching Law was developed to control the hitch system to attenuate the disturbance forces. Variation in system parameters due to change of implements was taken into account by making the system adaptive using a Recursive Least Squares (RLS) parameter estimator, which was used to estimate and update the system parameters in the controller. Position regulation was incorporated to prevent the implement from reaching its mechanical limits. Valve deadzone and operating input limits were incorporated into this design. Also, considering the presence of two valves to supply fluid to the same cylinder, a trigger logic was developed to suitably choose the valve to be operated. The controller was found to provide an average disturbance force attenuation of 82.9% while being robust to a random variation in each parameter up to ±80%.

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Section: System Modellingmentioning

confidence: 99%