Development of an electric-driven control system for a precision planter based on a closed-loop PID algorithm

He, Xiongkui; Cui, Tongtong; Zhang, Di; Wei, Jiantao; Wang, M.; Yao, Yu; Liu, Q.; Yan, Bin; Zhao, Di; Liu, Yang

doi:10.1016/j.compag.2017.01.028

Cited by 44 publications

(26 citation statements)

References 5 publications

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“…The notable discrimination is that the overshoot of the PID control algorithm considering viscosity is higher than the PID control algorithm without considering viscosity. However, the maximum overshoot was found to be 26.1% for the four raw corn planters [47]. The minimum overshoot was 0% at 0℃ for all types of hydraulic oils.…”

Section: Preprintsmentioning

confidence: 82%

“…On the other hand, Figure 10 shows the performance of the control algorithm considering the viscosity of the hydraulic oils. The pressure of the proportional valve suddenly rose to a peak after 0.40 s, and had a 5% acceptable error band [47], as shown in Figure 10a oils (VG 32, 46, and 68), the response was a little slow compared with the other temperature levels of the hydraulic oils. It took a maximum of 0.45 s to be stable.…”

Section: Performance Of Pid Control Algorithmsmentioning

confidence: 94%

“…The higher settling time also affects the planting performance of the transplanter [46]. The steady-state error, which is another important character to control the planting depth control system, was considered to be less than 1% [47]. Therefore, the responses characteristics of both control algorithms should satisfy the boundary conditions or target values, in order to minimize the tilting problem of the automatic planting depth control system and improve the performance of transplanter.…”

Section: Performance Evaluation Of the Control Algorithmsmentioning

confidence: 99%

“…These results indicate that the PID control algorithm considering viscosity is feasible for controlling the planting depth of rice seedlings. Also, He [47] applied a PID control algorithm for four raw corn planter to control the seed plate rotation speed for the seed meter's response and planting quality. He also reported that a faster response is important for improving planting quality and accuracy.…”

Section: Preprintsmentioning

confidence: 99%

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PID Control Algorithm Based on Hydraulic Oil Viscosity for the Proportional Valve of the Planting Depth Control System

Siddique¹,

Kim²,

Kim³

et al. 2020

Preprint

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This study was conducted to develop a PID control algorithm considering viscosity for the planting depth control system of a rice transplanter using various hydraulic oils at different temperatures and to evaluate the performance of the control algorithm, and compare the performance of the PID control algorithm without considering viscosity and considering viscosity. In this study, the simulation model of the planting depth control system and a PID control algorithm were developed based on the power flow of the rice transplanter (ERP60DS). The primary PID coefficients were determined using the Ziegler–Nichols (Z–N) second method. Routh’s stability criteria were applied to optimize the coefficients. The pole and double zero points of the PID controller were also applied to minimize the sustained oscillations of the responses. The performance of the PID control algorithm was evaluated for three ISO (The International Organization for Standardization) standard viscosity grade (VG) hydraulic oils (VG 32, 46, and 68). The results show that the control algorithm considering viscosity is able to control the pressure of the proportional valve, which is associated with the actuator displacement for various types of hydraulic oils. It was noticed that the maximum pressure was 15.405 bars at 0, 20, 40, 60, 80, and 100 ℃ for all of the hydraulic oils. The settling time and steady-state errors were 0.45 s at 100 ℃ for VG 32, and 0% for all of the conditions. The maximum overshoots were found to be 17.50% at 100 ℃ for VG 32. On the other hand, the PID control algorithm without considering viscosity could not control the planting depth, because the response was slow and did not satisfy the boundary conditions. The PID control algorithm considering viscosity could sufficiently compensate for the nonlinearity of the hydraulic system and was able to perform for any of temperature-dependent viscosity of the hydraulic oils. In addition, the rice transplanter requires a faster response for accurately controlling and maintaining the planting depth. Planting depth is highly associated with actuator displacement. Finally, this control algorithm considering viscosity could be helpful in minimizing the tilting of the seedlings planted using the rice transplanter. Ultimately, it would improve the transplanter performance.

show abstract

Section: Preprintsmentioning

confidence: 82%

Section: Performance Of Pid Control Algorithmsmentioning

confidence: 94%

Section: Performance Evaluation Of the Control Algorithmsmentioning

confidence: 99%

Section: Preprintsmentioning

confidence: 99%

See 2 more Smart Citations

PID Control Algorithm Based on Hydraulic Oil Viscosity for the Proportional Valve of the Planting Depth Control System

Siddique¹,

Kim²,

Kim³

et al. 2020

Preprint

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show abstract

“…However, more systems are discrete in practical applications and the PID algorithm can be described as follows. 33,34 PID algorithm.…”

Section: Pid Algorithmmentioning

confidence: 99%

Improvements of direct current motor control and motion trajectory algorithm development for automated guided vehicle

Zhang

Wang

2019

Advances in Mechanical Engineering

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The precise control of the two-wheel independent drive motor speed of automated guided vehicle is the prerequisite for high-precision operation of its actuator. The optimization of motor control performance has been a topic of concern to researchers. First, the model identification of direct current motor is done. Second, there are two control strategies, including parallel proportional-integral-differential control strategy and the coupling proportional-integral-differential control strategy, which are researched and compared for the direct current motor control system of automated guided vehicle in dispatching the goods from one location to another with greater ease. Finally, the motion trajectory algorithm of automated guided vehicle is also proposed on the basis of kinematics theory. Besides, the above control strategies and algorithm improved for automated guided vehicle are simulated by the MATLAB tool and the experimental simulations by Kinect sensor, and the simulation results show that the coupling proportional-integral-differential control strategy is slightly better in controlling performance because of some smaller cumulative errors and the better start performance. Meanwhile, the motion trajectory algorithm of automated guided vehicle under both the control strategies can achieve different effects in different control cases.

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Design and development of Truncated Angle Variant (TAV) controller for multi-source-fed BLDC motor drive

Kanna¹,

Sasiraja²,

Winston³

2020

Electr Eng

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Development of an electric-driven control system for a precision planter based on a closed-loop PID algorithm

Cited by 44 publications

References 5 publications

PID Control Algorithm Based on Hydraulic Oil Viscosity for the Proportional Valve of the Planting Depth Control System

PID Control Algorithm Based on Hydraulic Oil Viscosity for the Proportional Valve of the Planting Depth Control System

Improvements of direct current motor control and motion trajectory algorithm development for automated guided vehicle

Design and development of Truncated Angle Variant (TAV) controller for multi-source-fed BLDC motor drive

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