scholarly journals The Tractor-Cart System Controller with Fuzzy Logic Rules

2020 ◽  
Vol 10 (15) ◽  
pp. 5223
Author(s):  
Nadia Delavarpour ◽  
Sulaymon Eshkabilov ◽  
Thomas Bon ◽  
John Nowatzki ◽  
Sreekala Bajwa
Keyword(s):  
Fuzzy Logic ◽  
Hydraulic Drive ◽  
Adaptive Controller ◽  
Boundary Region ◽  
Guidance System ◽  
Crop Damage ◽  
Set Constraints ◽  
Steering Torque ◽  
Control Principle ◽  
System Controller

Post-planting operations (e.g., fertilizing, cover crop planting) with a tractor and towed cart in standing crop (e.g., corn) are challenging. Tractor and cart should be kept within a certain boundary region to avoid crop damage. An automatic guidance system on the tractor is the solution of the issue; however, tractor’s auto-guidance does not guarantee the cart clear and exact following of the tractor. There is insufficient research in automatic control of a towed cart. Therefore, this research was undertaken to design a controller to manage lateral and longitudinal positions of a tractor-towed cart. A novel fuzzy logic based adaptive controller algorithm is proposed to control tractor-cart system steering with additional steering torque for the cart, ensuring that the entire system follows the desired trajectory within the set constraints. A hydraulic drive design for the cart was developed with a control principle to closely follow the tractor’s path and minimize damage to the plants. The proposed steering algorithm and designed controller were validated with interchangeable trajectory patterns via simulations in MATLAB/Simulink. The results demonstrated that the performances of the designed hydraulic drive and the accuracy of the proposed control algorithm were appropriate to steer the towed-cart with minimal damages on plant rows.

scholarly journals A fuzzy logic algorithm derived mechatronic concept prototype for crop damage avoidance during eco-friendly eradication of intra-row weeds

2020 ◽  
Vol 4 ◽  
pp. 116-126
Author(s):  
Satya Prakash Kumar ◽  
V.K. Tewari ◽  
Abhilash K. Chandel ◽  
C.R. Mehta ◽  
Brajesh Nare ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Crop Damage ◽  
Fuzzy Logic Algorithm ◽  
Damage Avoidance

scholarly journals Experimental simplified rule of self tuning fuzzy logic-model reference adaptive speed controller for induction motor drive

2020 ◽  
Vol 20 (3) ◽  
pp. 1653
Author(s):  
M.Z. Ismail ◽  
M.H.N. Talib ◽  
Z. Ibrahim ◽  
J. Mat Lazi ◽  
Z. Rasin
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Adaptive Controller ◽  
Tuning Parameter ◽  
Model Reference ◽  
Wide Range ◽  
Speed Performance ◽  
Self Tuning ◽  
Model Reference Adaptive

<span>Fuzzy logic controller (FLC) has shown excellent performance in dealing with the non-linearity and complex dynamic model of the induction motor. However, a conventional constant parameter FLC (CPFL) will not be able to provide–good coverage performance for a wide speed range operation with a single tuning parameter. Therefore, this paper proposed a self tuning mechanism FLC approach by model reference adaptive controller (ST-MRAC) to continuously allow to adjust the parameters. Due to real time hardware application, the dominant rules selection method for simplified rules has been implemented as part of the reducing computational burden. Experiment results validate a good performance of the ST-MRAC compared to the CPFL for the   speed performance in terms of the wide range of operations and disturbance showed remarkable performance.</span>

Adaptive Backstepping Control of the Gripping Process of Heavy Manipulators

2017 ◽  
Author(s):  
Lixin Yang ◽  
Xianmin Zhang
Keyword(s):  
Tracking Control ◽  
Hydraulic Drive ◽  
Adaptive Controller ◽  
Drive System ◽  
Uncertain Parameters ◽  
Backstepping Method ◽  
Nonlinear Characteristics ◽  
Cylinder Model ◽  
Stability Principle ◽  
The Stability

A valve-controlled asymmetrical cylinder model was established to study the gripping hydraulic drive system of the grip device of heavy manipulator. Due to the strong nonlinear characteristics and uncertain parameters of the model, the Lyapunov stability principle was used to design a multistage inversion adaptive controller based on backstepping method and by introducing the virtual control parameter. The simulation results reveal that the tracking control and adaptive of uncertain parameters are very effective, which confirm that the designed controller can guarantee the stability of the closed-loop clamping hydraulic drive system.

Decentralized fuzzy linguistic control of multiple robotic manipulators with guaranteed global stability

2019 ◽  
Vol 20 (1) ◽  
pp. 185-204
Author(s):  
Yongqing Fan ◽  
Wenqing Wang ◽  
Xiangkui Jiang ◽  
Zhen Li
Keyword(s):  
Fuzzy Logic ◽  
Global Stability ◽  
Fuzzy Controller ◽  
Robot Manipulators ◽  
Design Method ◽  
Robotic Manipulators ◽  
Adaptive Controller ◽  
Fuzzy Logic Systems ◽  
Approximation Accuracy ◽  
Logic Systems

Abstract A decentralized adaptive control based on human linguistic is investigated to learn human behaviors for multiple robotic manipulators. Many experts’ words or sentences can be transferred into the control actions by employing membership functions in robot systems, which can be synthesized fuzzy controller by employing reasoning mechanism. For the unknown model dynamical robot manipulators, one adjustable parameter that relates to the approximation accuracy of fuzzy logic systems is introduced at first, which be utilized to deal with the unknown dynamics of robot manipulators. Switching fuzzy adaptive controller is designed to overcome the limitation of logic structure that the number of adaptive laws only focus on fuzzy rules in conventional fuzzy logic systems. Another advantage of this design method is that the control with human linguistic extend the semi-global stability to global stability. Finally, effectiveness of the developed control design scheme has been shown in simulation example.

Predictor-corrector guidance for entry vehicle based on fuzzy logic

2017 ◽  
Vol 233 (2) ◽  
pp. 472-482
Author(s):  
Tao Wang ◽  
Hongbo Zhang ◽  
Guojian Tang
Keyword(s):  
Fuzzy Logic ◽  
Guidance System ◽  
Longitudinal Motion ◽  
Lateral Motion ◽  
Trajectory Prediction ◽  
Bank Angle ◽  
Guidance Law ◽  
Reversal Time ◽  
Lateral Error ◽  
Predictor Corrector

With the development of aerospace industry, the guidance system of an entry vehicle will be more robust, reliable and autonomous in the future. Based on fuzzy logic, the paper designs a predictor-corrector guidance law. The trajectory prediction is realized by numerical integration. The correction system is based on two fuzzy controllers, which correct the longitudinal motion and lateral motion synergistically. The error of flight range is eliminated by correcting the magnitude of bank angle. The altitude error is eliminated by correcting the attack angle. The lateral error is eliminated by regulating the reversal time of bank angle. Comparing with the traditional corrector based on Newton-Raphson iteration, the method in this paper only needs a single trajectory prediction in one correction cycle, which is favorable for on-board calculation. Moreover, the longitudinal motion and lateral motion are synergistically corrected in the predictor-corrector, which makes the method more robust and flexible.

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