Design and verification of slip rate control system for straight line travel of high clearance self-propelled sprayer

2021 ◽  
pp. 095440702110320
Author(s):  
Wei Li ◽  
Enrong Mao ◽  
Suiying Chen ◽  
Zhen Li ◽  
Bin Xie ◽  
...  
Keyword(s):  
Control System ◽  
Field Test ◽  
Rate Control ◽  
Control Method ◽  
Slip Rate ◽  
Threshold Value ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Speed Mode ◽  
High Clearance

A slip rate control system aimed at improving the working efficiency and driving stability of a high clearance sprayer was developed. First, the two-pump, two-anti-slip control (ASC) valve, four-motor “X” drive scheme hydraulic slip rate control system was designed, and a mathematical model of the system as well as a vehicle dynamics model were established. The system includes a slip rate control strategy, a proportional-integral-derivative control method and a fuzzy adaptive proportional-integral-derivative sprayer control method. To verify the performance of the system, a simulation model was developed using MATLAB/Simulink, and the performance of the two control methods were compared. Additionally, an actual vehicle test platform was built based on 3WPG-3000 high clearance self-propelled sprayer independently developed by the research group. The simulation results revealed that when a wheel slipped, the slip rate control system was able to control the wheel slip rate and keep it within the threshold value of 0.1, thus meeting the operating requirements of the sprayer. The field test results revealed that in field operations with a low adhesion coefficient, the system was able to maintain a nearly unchanged wheel speed in both fixed speed mode and variable speed mode, maintaining a slip rate below the target of 0.1 “when in a straight running mode” in both cases. Altogether, the results of the simulation and field test verify the stability, accuracy, and practicability of the system.

Hybrid adaptive tracking control method for mobile manipulator robot based on Proportional–Integral–Derivative technique

2021 ◽  
pp. 095440622110149
Author(s):  
Thanglong Mai
Keyword(s):  
Control System ◽  
Tracking Control ◽  
Control Method ◽  
Fuzzy Neural Networks ◽  
Mobile Manipulator ◽  
Proportional Integral Derivative ◽  
Adaptive Tracking Control ◽  
Proportional Integral ◽  
Adaptive Tracking ◽  
Manipulator Robot

In this research, an adaptive tracking control method for the nonholonomic robot system is addressed based on the hybrid Proportional–Integral–Derivative (PID) technique. The proposed hybrid PID scheme first applies the merits of the traditional PID method, with the online self-learning capability for the PID – gains, to force tracking errors to zero in the presence of uncertainties. Then, in order to improve the tracking performance, an adaptive Fuzzy Neural Networks (FNN) approximator and an adaptive robust controller type-compensator are utilized to relax the uncertainties problems of the robot control system. Moreover, the nonholonomic constraint force stability of the mobile manipulator robot is also considered by an adaptive control scheme. The design of online updating laws for the proposed controllers and FNN approximator are designed by applying the Lyapunov stability theorem. Thus, besides the improvement for tracking control performance, the stability of the proposed control system is also maintained. The effectiveness, robustness and adaptability of the proposed control strategy are verified by comparative numerical simulation results.

A new control method based on fuzzy controller, time delay estimation, deep learning, and non-dominated sorting genetic algorithm-III for powertrain mount system

2019 ◽  
Vol 26 (13-14) ◽  
pp. 1187-1198 ◽  
Author(s):  
Li-Xin Guo ◽  
Dinh-Nam Dao
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Deep Learning ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral

This article presents a new control method based on fuzzy controller, time delay estimation, deep learning, and non-dominated sorting genetic algorithm-III for the nonlinear active mount systems. The proposed method, intelligent adapter fractions proportional–integral–derivative controller, is a smart combination of the time delay estimation control and intelligent fractions proportional–integral–derivative with adaptive control parameters following the speed range of engine rotation via the deep neural network with the optimal non-dominated sorting genetic algorithm-III deep learning algorithm. Besides, we proposed optimal fuzzy logic controller with optimal parameters via particle swarm optimization algorithm to control reciprocal compensation to eliminate errors for intelligent adapter fractions proportional–integral–derivative controller. The control objective is to deal with the classical conflict between minimizing engine vibration impacts on the chassis to increase the ride comfort and keeping the dynamic wheel load small to ensure the ride safety. The results of this control method are compared with that of traditional proportional–integral–derivative controller systems, optimal proportional–integral–derivative controller parameter adjustment using genetic algorithms, linear–quadratic regulator control algorithms, and passive drive system mounts. The results are tested in both time and frequency domains to verify the success of the proposed optimal fuzzy logic controller–intelligent adapter fractions proportional–integral–derivative control system. The results show that the proposed optimal fuzzy logic controller–intelligent adapter fractions proportional–integral–derivative control system of the active engine mount system gives very good results in comfort and softness when riding compared with other controllers.

Fuzzy adaptive robust proportional–integral–derivative control optimized by the multi-objective grasshopper optimization algorithm for a nonlinear quadrotor

2020 ◽  
Vol 26 (17-18) ◽  
pp. 1574-1589
Author(s):  
Mohammad Javad Mahmoodabadi ◽  
Nima Rezaee Babak
Keyword(s):  
Control System ◽  
Sliding Surface ◽  
Proportional Integral Derivative ◽  
Adaptation Mechanism ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Grasshopper Optimization Algorithm ◽  
Proportional Integral Derivative Control ◽  
Grasshopper Optimization ◽  
Fuzzy Adaptive

Proportional–integral–derivative is one of the most applicable control methods in industry. Although it is simple and effective in most cases, it does not provide robustness against disturbances and may not perform well in cases with uncertainties and nonlinearities. In this study, a fuzzy adaptive robust proportional–integral–derivative controller is used to control a nonlinear 4 degree-of-freedom quadrotor. An adaptation mechanism is submitted to the proportional–integral–derivative controller for updating the proportional, derivative, and integral gains of proportional–integral–derivative control. Furthermore, a sliding surface is generated and submitted to the adaptation mechanism for better regulation of proportional–integral–derivative gains. Afterward, a fuzzy engine is applied to regulate the sliding surface for better performance of the adaptive proportional–integral–derivative when there are disturbance and uncertainties. The multi-objective grasshopper optimization algorithm is implemented on the control system for the regulation of the control system parameters to minimize the error and control effort of the proposed hybrid control system. Finally, the obtained results are presented for a nonlinear 4 degree-of-freedom multi-purpose (for marine, ground, and aerial maneuvers) quadrotor system designed and built in Sirjan University of Technology, Sirjan, Iran, to assure the effectiveness of this technique.

Performance-Adaptive Generalized Predictive Control-Based Proportional-Integral-Derivative Control System and Its Application

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Takao Sato ◽  
Toru Yamamoto ◽  
Nozomu Araki ◽  
Yasuo Konishi
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Pid Control ◽  
Design Method ◽  
Design Parameters ◽  
Generalized Predictive Control ◽  
Control Performance ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Proportional Integral Derivative Control

In the present paper, we discuss a new design method for a proportional-integral-derivative (PID) control system using a model predictive approach. The PID compensator is designed based on generalized predictive control (GPC). The PID parameters are adaptively updated such that the control performance is improved because the design parameters of GPC are selected automatically in order to attain a user-specified control performance. In the proposed scheme, the estimated plant parameters are updated only when the prediction error increases. Therefore, the control system is not updated frequently. The control system is updated only when the control performance is sufficiently improved. The effectiveness of the proposed method is demonstrated numerically. Finally, the proposed method is applied to a weigh feeder, and experimental results are presented.

Comparison between H2 and H∞ Optimal Control Solutions for a Combined Energy and Attitude Control System

2012 ◽  
Vol 225 ◽  
pp. 464-469 ◽  
Author(s):  
Ban Ying Siang ◽  
Renuganth Varatharajoo
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Pid Control ◽  
Attitude Control ◽  
Disturbance Rejection ◽  
Control Method ◽  
Proportional Integral Derivative ◽  
Attitude Control System ◽  
Control Option ◽  
Optimal Control Methods

The paper focuses on applying optimal control solutions to combined energy storage and attitude control system (CEACS) under different reference missions. In previous researches, the proportional-integral-derivative (PID) control method, the PID-active force control method and H2 control were tested for CEACS and achieved its mission requirement. However, problems such as the in-orbit system uncertainties affect the PID control performances. Thus, two optimal control methods, H2 and H∞ controls are proposed and tested on CEACS under different mission scenarios to improve its pitch attitude accuracy. Results show that both H2 and H∞ are able to achieve the reference mission requirement even under the influence of uncertainties (non-ideal). Moreover comparison between H2 and H∞ shows the H2 is a better control option for CEACS in terms of disturbance rejection.

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