Fuzzy proportional integral derivative control of a radiofrequency ablation temperature control system

2017 ◽  
Author(s):  
Yanyan Cheng ◽  
Qun Nan ◽  
Ruirui Wang ◽  
Tong Dong ◽  
Zhen Tian
Keyword(s):  
Control System ◽  
Radiofrequency Ablation ◽  
Temperature Control ◽  
Temperature Control System ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Proportional Integral Derivative Control ◽  
Derivative Control

Study on the visual tracking control technology of six-crawler machine

2019 ◽  
Vol 233 (17) ◽  
pp. 6051-6075
Author(s):  
Shuai Wang ◽  
Haoran Ge ◽  
Ruoding Ma ◽  
Da Cui ◽  
Xinhui Liu ◽  
...  
Keyword(s):  
Control System ◽  
Visual Tracking ◽  
Tracking Control ◽  
Control Algorithm ◽  
Least Square ◽  
Control Parameters ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Proportional Integral Derivative Control ◽  
Derivative Control

In this paper, the autonomous navigation of six-crawler machine is studied, and a visual tracking control method based on machine vision for fuzzy proportional–integral–derivative control of six-crawler machine is proposed. The steering principle of the six-crawler machine and the matching relationship between the steering angle and the speed of each crawler are introduced, and the control system is described in detail. Besides, the mathematical model for the unsteady steering is introduced to analyze the influence of deflection angle on the steering trajectory of the six-crawler machine. The image processing algorithm is programmed by LabVIEW software. After the image is fitted by graying, binary, filtering, edge detection, and least square method, the navigation line-fitting curve is obtained. The fuzzy proportional–integral–derivative control algorithm is programmed in the control system to control the six-crawler machine to drive along the navigation line. In order to obtain reasonable control parameters, a virtual prototype model of a six-crawler machine is established. In the CoLink module, the control algorithm of a six-crawler machine is established, and the co-simulation is carried out. By analyzing the simulation results, the control parameters of the fuzzy proportional–integral–derivative controller of the six-crawler machine are established. In order to verify the control effect of the visual tracking control system of the six-crawler machine, a physical prototype of the six-crawler machine is constructed and tested. The results show that the visual tracking control system of the six-crawler machine can complete the preset functions.

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.

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