Joint parameters identification for redundant manipulators based on fuzzy theory and genetic algorithm

2003 ◽  
Author(s):  
Yangmin Li ◽  
Xiaoping Liu ◽  
Zhaoyang Peng ◽  
Yugang Liu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Theory ◽  
Parameters Identification ◽  
Redundant Manipulators ◽  
Joint Parameters

The identification of joint parameters for modular robots using fuzzy theory and a genetic algorithm

Robotica ◽  
2002 ◽  
Vol 20 (5) ◽  
pp. 509-517 ◽  
Author(s):  
Yangmin Li ◽  
Xiaoping Liu ◽  
Zhaoyang Peng ◽  
Yugang Liu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Dynamic Characteristics ◽  
Fuzzy Theory ◽  
Dynamic Control ◽  
Modular Robots ◽  
Optimal Solutions ◽  
Modular Robot ◽  
Redundant Robot ◽  
Joint Parameters

SummaryThis paper discusses a technique for identifying the joint parameters of a modular robot in order to study the dynamic characteristics of the whole structure and to realise dynamic control. A method for identifying the joint parameters of the structure applying fuzzy logic combined with a genetic algorithm has been studied using a 9-DOF modular redundant robot. A Genetic Algorithm was used in the fuzzy optimisation, which helped to avoid converging to locally optimal solutions and made the results identified much more reasonable. The joint parameters of a 9-DOF modular redundant robot have been identified.

scholarly journals Cable Tension Adjustment Based upon Fuzzy Theory and Genetic Algorithm.

2000 ◽  
pp. 143-151
Author(s):  
Masakatsu KANEYOSHI ◽  
Hitoshi FURUTA ◽  
Hiroshi TANAKA
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Theory ◽  
Cable Tension

Transformer Fault Diagnosis Based on Improved Quantum Genetic Algorithm and BP Network

2010 ◽  
Vol 29-32 ◽  
pp. 1543-1549 ◽  
Author(s):  
Jie Wei ◽  
Hong Yu ◽  
Jin Li
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fault Diagnosis ◽  
Bp Neural Network ◽  
Fuzzy Theory ◽  
Back Propagation ◽  
Gas Analysis ◽  
Bp Network ◽  
Quantum Genetic Algorithm ◽  
Transformer Fault

Three-ratio of the IEC is a convenient and effective approach for transformer fault diagnosis in the dissolved gas analysis (DGA). Fuzzy theory is used to preprocess the three-ratio for its boundary that is too absolute. As the same time, an improved quantum genetic algorithm IQGA (QGASAC) is used to optimize the weight and threshold of the back propagation (BP). The local and global searching ability of the QGASAC approach is utilized to find the BP optimization solution. It can overcome the slower convergence velocity and hardly getting the optimization of the BP neural network. So, aiming at the shortcoming of BP neural network and three-ratio, blurring the boundary of the gas ratio and the QGASAC algorithm is introduced to optimize the BP network. Then the QGASAC-IECBP method is proposed in this paper. Experimental results indicate that the proposed algorithm in this paper that both convergence velocity and veracity are all improved to some extent. And in this paper, the proposed algorithm is robust and practical.

Actuator hysteresis modeling and compensation with an adaptive search space based genetic algorithm

2021 ◽  
Author(s):  
Che-Hang Cliff Chan
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Search Space ◽  
Parameters Identification ◽  
Experimental Results ◽  
Adaptive Search ◽  
Real Coded Genetic Algorithm ◽  
Hysteresis Modeling ◽  
Convergence Performance ◽  
Solution Accuracy

The thesis presents a Genetic Algorithm with Adaptive Search Space (GAASS) proposed to improve both convergence performance and solution accuracy of traditional Genetic Algorithms(GAs). The propsed GAASS method has bee hybridized to a real-coded genetic algorithm to perform hysteresis parameters identification and hystereis invers compensation of an electromechanical-valve acuator installed on a pneumatic system. The experimental results have demonstrated the supreme performance of the proposed GAASS in the search of optimum solutions.

Joint Parameters Identification of a Structure With Large Number of Discrete Joints

2003 ◽  
Author(s):  
J. H. Wang ◽  
S. C. Chuang
Keyword(s):  
Frequency Response ◽  
Dynamic Behavior ◽  
Error Function ◽  
Parameters Identification ◽  
New Method ◽  
Response Functions ◽  
Traditional Methods ◽  
Measured Frequency Response ◽  
Joint Parameters ◽  
Better Than

The joint parameters of a structure with a large number of discrete joints generally are very difficult to identify accurately. The difficulty is due to the fact that the dynamic behavior of a structure becomes more complex with more number of joints. A new identification method which uses the measured frequency response functions (FRFs) to identify the joint parameters is proposed in this work to overcome this difficulty. The new method uses an error function to select different best data to identify different joints so that the accuracy of the identification can be improved. The accuracy of the new method and other two traditional methods is compared in this work. The results show that the accuracy of the proposed new method is far better than other two previous methods. The proposed new method has special advantage when (1) the number of joints is large, (2) the orders of magnitude of the joint parameters are different significantly.

Trajectory Generation for Redundant Manipulator using Virus-Evolutionary Genetic Algorithm with Subpopulations

1997 ◽  
Vol 1 (2) ◽  
pp. 155-161
Author(s):  
Takemasa Arakawa ◽  
◽  
Toshio Fukuda ◽  
Naoyuki Kubota ◽  
Keyword(s):  
Genetic Algorithm ◽  
Genetic Information ◽  
Energy Optimization ◽  
Trajectory Generation ◽  
Redundant Manipulators ◽  
Redundant Manipulator ◽  
Theory Of Evolution ◽  
Evolutionary Genetic ◽  
Generation Problem ◽  
Virus Theory

In this paper, we apply a virus-evolutionary genetic algorithm with subpopulations (VEGAS) to a trajectory generation problem for redundant manipulators through energy optimization. VEGAS is based on the virus theory of evolution and VEGAS has some subpopulations that usually evolve independently. In the same subpopulation, a virus infects host individuals. And a virus sometimes immigrates from one subpopulation to another. The genetic information from one subpopulation propagates in another subpopulation only through immigration of the virus. The energy-optimized collision-free trajectory was found successfully using VEGAS.

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