scholarly journals Novel Online Optimized Control for Underwater Pipe-Cleaning Robots

2020 ◽  
Vol 10 (12) ◽  
pp. 4279
Author(s):  
Yanhu Chen ◽  
Siyue Liu ◽  
Jinchang Fan ◽  
Canjun Yang
Keyword(s):  
Control Method ◽  
Fuzzy Controller ◽  
Imaging System ◽  
Bat Algorithm ◽  
Offshore Platforms ◽  
Operational Environment ◽  
Underwater Robots ◽  
Reference Path ◽  
Cleaning Robot ◽  
Vision Localization

Due to the particularity of the jacket structure of offshore platforms and the complexity of the marine environment, there have been few effective localization and autonomous control methods for underwater robots that are designed for cleaning tasks. To improve this situation, a fusion bat algorithm (BA) online optimized fuzzy control method using vision localization was developed based on the constraints of the underwater operational environment. Vision localization was achieved based on images from a catadioptric panoramic imaging system. The features of the pipe edge and the boundary of the area covered by biofouling were obtained by image processing and feature extraction. The feature point chosen as the “highest” point of the boundary was calculated by projection transformation to generate the reference path. The specialized fuzzy controller was designed to drive the robot to track the reference path, and an improved bat algorithm with dynamic inertia weight and differential evolution method was developed to optimize the scale factors of the fuzzy controller online. The control method was simulated and further implemented on an underwater pipe-cleaning robot (UPCR), and the results indicate its rationality and validity.

scholarly journals Robust control method for bionic gait of machine legs based on time delay feedback

2018 ◽  
Vol 173 ◽  
pp. 02009
Author(s):  
Lu Xing-Hua ◽  
Huang Peng-Fen ◽  
Huang Wei-Peng
Keyword(s):  
Time Delay ◽  
Robust Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Delayed Feedback Control ◽  
Accurate Estimation ◽  
Gait Control ◽  
Robot Leg ◽  
Correlation Parameters ◽  
Robotic Leg

The bionic machine leg is disturbed by the joint during the walking process, which is easy to produce time delay, which causes the robustness of the control of the machine leg is not good. In order to improve the robustness of the bionic gait control of the machine leg, a robust control method for the bionic gait of the machine leg based on time - delay feedback is proposed. The gait correlation parameters of robot leg are collected by sensor array, and the dynamic model of bionic gait is constructed. The fuzzy controller of bionic gait of robot leg is constructed by using time-delay coupling control method. The delayed feedback control error compensation method of machine leg correction is taken to improve the steady control performance of the robotic leg, reduce the steady-state error, improve the robustness of the control machine leg. The simulation results show that this method is robust to the bionic gait control of the machine leg. The output error of the gait parameter can quickly converge to zero, and the accurate estimation of the attitude parameter is stronger.

scholarly journals Interval Type-2 Neural Fuzzy Controller-Based Navigation of Cooperative Load-Carrying Mobile Robots in Unknown Environments

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4181 ◽  
Author(s):  
Chun-Hui Lin ◽  
Shyh-Hau Wang ◽  
Cheng-Jian Lin
Keyword(s):  
Mobile Robots ◽  
Control Method ◽  
Fuzzy Controller ◽  
Bee Colony ◽  
Load Carrying ◽  
Navigation Control ◽  
Interval Type ◽  
Navigation Method ◽  
Neural Fuzzy

In this paper, a navigation method is proposed for cooperative load-carrying mobile robots. The behavior mode manager is used efficaciously in the navigation control method to switch between two behavior modes, wall-following mode (WFM) and goal-oriented mode (GOM), according to various environmental conditions. Additionally, an interval type-2 neural fuzzy controller based on dynamic group artificial bee colony (DGABC) is proposed in this paper. Reinforcement learning was used to develop the WFM adaptively. First, a single robot is trained to learn the WFM. Then, this control method is implemented for cooperative load-carrying mobile robots. In WFM learning, the proposed DGABC performs better than the original artificial bee colony algorithm and other improved algorithms. Furthermore, the results of cooperative load-carrying navigation control tests demonstrate that the proposed cooperative load-carrying method and the navigation method can enable the robots to carry the task item to the goal and complete the navigation mission efficiently.

Energy Management System Optimal Strategy for Pure Electric Vehicle Based on the Dynamic Programming

2014 ◽  
Vol 556-562 ◽  
pp. 1472-1475 ◽  
Author(s):  
Bing Dong ◽  
Yan Tao Tian ◽  
Chang Jiu Zhou
Keyword(s):  
Dynamic Programming ◽  
Fuzzy Control ◽  
Electric Vehicle ◽  
Energy Management ◽  
Management System ◽  
Control Method ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Energy Management System ◽  
Fuzzy Control Strategy

This thesis puts forward one optimal adaptive fuzzy control method based on the pure electric vehicle energy management system of the fuzzy control which has been founded already. By adding an optimizing researching model based on the conventional fuzzy control strategy, the thesis can pick up the valuable control rules based on the dynamic programming theory and also can adjust the parameter of the fuzzy controller automatically according to the system operating. These can make the sum of the energy loss reduce to the min. The experiment points out that this method makes the vehicle possess good economic performance in the same driving cycle.

scholarly journals Study of the Intelligent Behavior of a Maximum Photovoltaic Energy Tracking Fuzzy Controller

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3263 ◽  
Author(s):  
Gul Tchoketch Kebir ◽  
Cherif Larbes ◽  
Adrian Ilinca ◽  
Thameur Obeidi ◽  
Selma Tchoketch Kebir
Keyword(s):  
Fuzzy Logic ◽  
Control Method ◽  
Fuzzy Controller ◽  
Power Converter ◽  
Climatic Conditions ◽  
Maximum Power ◽  
Maximum Speed ◽  
Special Choice ◽  
Photovoltaic Generators ◽  
Inputs And Outputs

The Maximum Power Point Tracking (MPPT) strategy is commonly used to maximize the produced power from photovoltaic generators. In this paper, we proposed a control method with a fuzzy logic approach that offers significantly high performance to get a maximum power output tracking, which entails a maximum speed of power achievement, a good stability, and a high robustness. We use a fuzzy controller, which is based on a special choice of a combination of inputs and outputs. The choice of inputs and outputs, as well as fuzzy rules, was based on the principles of mathematical analysis of the derived functions (slope) for the purpose of finding the optimum. Also, we have proved that we can achieve the best results and answers from the system photovoltaic (PV) with the simplest fuzzy model possible by using only 3 sets of linguistic variables to decompose the membership functions of the inputs and outputs of the fuzzy controller. We compare this powerful controller with conventional perturb and observe (P&O) controllers. Then, we make use of a Matlab-Simulink® model to simulate the behavior of the PV generator and power converter, voltage, and current, using both the P&O and our fuzzy logic-based controller. Relative performances are analyzed and compared under different scenarios for fixed or varied climatic conditions.

scholarly journals Control system design of duct cleaning robot capable of overcoming L and T-shaped ducts

2020 ◽  
Vol 9 (2) ◽  
pp. 123
Author(s):  
Myeong In Seo ◽  
Woo Jin Jang ◽  
Junhwan Ha ◽  
Kyongtae Park ◽  
Dong Hwan Kim
Keyword(s):  
Control Method ◽  
Estimation Algorithm ◽  
Location Estimation ◽  
Positional Error ◽  
Cleaning Robot ◽  
Communication Module ◽  
Duct Cleaning Robot ◽  
Robot Position ◽  
Uwb Communication ◽  
Duct Cleaning

This study introduces the control method of duct cleaning robot that enables real-time position tracking and self-driving over L-shaped and T-shaped duct sections. The developed robot has three legs and is designed to flexibly respond to duct sizes. The position of the robot inside the duct is identified using the UWB communication module and the location estimation algorithm. Although UWB communication has relatively large distance error within the metal, the positional error was reduced by introducing appropriate filters to estimate the robot position accurately. TCP/IP communication allows commands to be sent between the PC and the robot and to receive live images of the camera attached to the robot. Using Haar-like and classifiers, the robot can recognize the type of duct that is difficult to overcome, such as L-shaped and T-shaped duct, and it moves successfully inside the duct according to the corresponding moving algorithms.

Sensorless Control for PMLSM Based on Fuzzy Sliding Mode Observer

2014 ◽  
Vol 556-562 ◽  
pp. 2270-2273
Author(s):  
Hua Cai Lu ◽  
Juan Ti ◽  
Yi Ming Yuan ◽  
Li Sheng Wei
Keyword(s):  
Boundary Layer ◽  
Control Method ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Sensorless Control ◽  
Sliding Mode Observer ◽  
Mode Function ◽  
Fuzzy Sliding Mode ◽  
The Difference ◽  
Current Error

In this paper, a new sensorless control method is proposed for a permanent magnet linear synchronous motor based on Fuzzy sliding mode observer, which combines the advantages of sliding mode observer and Fuzzy controller respectively. The difference between the current estimated value and the actual current value is regarded as sliding mode function; sliding mode function (current error) and variation of the error are used as the input of fuzzy controller, and the width of the boundary layer as the output, adjusting the width of the boundary layer dynamically in real time. The simulation results show that Fuzzy sliding mode observer is able to find a balance between soft chattering and steady-state error, keep the system robustness and control precision.

Chaotic Gyros Synchronization

2011 ◽  
pp. 183-209
Author(s):  
M. Roopaei ◽  
M. J. Zolghadri ◽  
B. S. Ranjbar ◽  
S. H. Mousavi ◽  
H. Adloo ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Dead Zone ◽  
Control Input ◽  
Mode Control ◽  
Fuzzy Sliding Mode ◽  
Robust Adaptive ◽  
Fuzzy Parameter

In this chapter, three methods for synchronizing of two chaotic gyros in the presence of uncertainties, external disturbances and dead-zone nonlinearity are studied. In the first method, there is dead-zone nonlinearity in the control input, which limits the performance of accurate control methods. The effects of this nonlinearity will be attenuated using a fuzzy parameter approximator integrated with sliding mode control method. In order to overcome the synchronization problem for a class of unknown nonlinear chaotic gyros a robust adaptive fuzzy sliding mode control scheme is proposed in the second method. In the last method, two different gyro systems have been considered and a fuzzy controller is proposed to eliminate chattering phenomena during the reaching phase of sliding mode control. Simulation results are also provided to illustrate the effectiveness of the proposed methods.

Cost Analysis and Fuzzy Control for Collapsible Container Usage Based on Closed-Loop Supply Chain Model

2017 ◽  
Vol 139 (8) ◽  
Author(s):  
Xinyan Ou ◽  
Jorge Arinez ◽  
Qing Chang ◽  
Guoxian Xiao
Keyword(s):  
Mathematical Model ◽  
Fuzzy Control ◽  
Closed Loop ◽  
Control Method ◽  
Fuzzy Controller ◽  
Accurate Estimation ◽  
Chain Model ◽  
Market Demand ◽  
Total Cost ◽  
Logistic Cost

In the last decade, global competition has forced manufacturers to optimize logistics. The implementation of collapsible containers provides a new perspective for logistics cost savings, since using collapsible containers reduces the frequency of shipping freight. However, optimization of logistic cost is complicated due to the interactions in a system, such as market demand, inventory, production throughput, and uncertainty. Therefore, a systematic model and accurate estimation of the total cost and system performance are of great importance for decision making. In this paper, a mathematical model is developed to describe deterministic and stochastic scenarios for a closed-loop container dynamic flow system. The uncertainties in a factory and a supplier are considered in the model. The performance evaluation of the collapsible container system and total cost estimation are provided through model analysis. Furthermore, fuzzy control method is proposed to monitor the processing rate of the supplier and the factory and to adjust the rate of the supplier operation then further reduce the logistic cost. A case study with a matlab simulation is presented to illustrate the accuracy of the mathematical model and the effectiveness of the fuzzy controller.

Modeling and Simulation of Nonlinear Networked Control System Based on Fuzzy Control

2012 ◽  
Vol 426 ◽  
pp. 368-371
Author(s):  
Sheng Li Song ◽  
Y. Chen ◽  
S.J. Huang ◽  
L.H Yang ◽  
R. He
Keyword(s):  
Control System ◽  
Nonlinear Problem ◽  
Control Method ◽  
Fuzzy Controller ◽  
Good Control ◽  
Networked Control System ◽  
Networked Control ◽  
Packet Dropout ◽  
Data Packet Dropout ◽  
Nonlinear Networked Control System

In the nonlinear networked control system (NCS), the conventional control method is difficult to achieve good control performance, due to the nonlinear problem associated with the disturbance factors, such as network induced time delay and data packet dropout. Considering this situation, this paper is aimed to propose a nonlinear networked control system based on T-S fuzzy model, which does not rely on specific network parameters or mathematical model. The nonlinear problem and the uncertainties of network can be both processed by the designed fuzzy controller. Then this approach is applied to nonlinear motor servo system, simulation of the example model is implemented in Matlab/Simulink associated with True Time toolbox. The results show that the proposed method not only is convenient for modeling, but also upgrade the performance of control system.

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