The Design and Optimization of Fuzzy Controller Based on Vibrating Mill Granularity

2012 ◽  
Vol 232 ◽  
pp. 635-638
Author(s):  
Jin Hua Zhang
Keyword(s):  
Genetic Algorithm ◽  
Main Parameter ◽  
Fuzzy Controller ◽  
Two Dimensional ◽  
Control Effect ◽  
Design And Optimization ◽  
Learning Function ◽  
Designing Method ◽  
Vibration Mill

Granularity is the main parameter of evaluating materials, from the analysis of powder producing system that made of vibration mill, the material’s size can be controlled through controlling the speed of motor. Focus on the complex nonlinear in the processing of ground breaking, the two dimensional controller is designed. Due to the subjectivity and randomness in the designing method of classic fuzzy controller, so genetic algorithm is used to put fuzzy controller some learning function in order to obtain better control effect of the system.

Study of Fuzzy Control for Intelligent Cantilever Beam Based on Genetic Algorithm

2011 ◽  
Vol 204-210 ◽  
pp. 25-30 ◽  
Author(s):  
Jing Jun Zhang ◽  
Xiao Pin Guo ◽  
Li Li He ◽  
Rui Zhen Gao
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Control ◽  
Cantilever Beam ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Fitness Function ◽  
Fuzzy Rules ◽  
Control Effect ◽  
The Core ◽  
Simulation Results

The design of fuzzy controller is the key of fuzzy control system, while the core of fuzzy controller design lies in fuzzy rules, whose performance determines the control effect of fuzzy system. General fuzzy rules are obtained from expert experience, in which much subjectivity exists. In this paper, a fuzzy controller is designed by taking an intelligent cantilever beam as the research object. And a method using the genetic algorithm to optimize fuzzy rules is proposed and the genetic coding as well as the fitness function is confirmed. Finally, the simulation model of intelligent cantilever beam is built by Matlab/Simulink, and the vibration control effects of fuzzy controller optimized by genetic algorithm are compared with those un-optimized. The simulation results indicate that the vibration amplitude of intelligent cantilever beam has a significant decrease and the vibration decay rate has a significant increase after the fuzzy rules optimized.

Research of Genetic Algorithm Controller Based Fuzzy Neural Network in Vacuum Pre-Cooling Freshness-Keeping Machine

2014 ◽  
Vol 926-930 ◽  
pp. 3545-3549
Author(s):  
Ke Liang Zhou ◽  
Qiong Tan ◽  
Jian He
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Pid Controller ◽  
Fuzzy Neural Network ◽  
Fuzzy Controller ◽  
Control Object ◽  
Bp Algorithm ◽  
Control Effect ◽  
Fuzzy Neural ◽  
The Difference

The control object is the temperature of pre-cooling machine, combined the advantage of neural network and genetic algorithm (GA). Adopting GA controller based fuzzy neural network. The controller doing the fuzzy reasoning to the difference of given temperature and sample temperature. GA does the offline training to the Connection weights and Membership function of fuzzy neural network, then uses BP algorithm to do further adjust online for parameters. Simulation result shows that the new controller achieves better control effect compared with traditional PID controller, fuzzy controller.

A quantitative measure of the degree of output controllability for output regulation control systems: Concept, approach, and applications

2021 ◽  
pp. 107754632110201
Author(s):  
Yaping Xia ◽  
Ruiyu Li ◽  
Minghui Yin ◽  
Yun Zou
Keyword(s):  
Structural Parameters ◽  
Quantitative Measure ◽  
Output Regulation ◽  
State Regulation ◽  
Control Effect ◽  
Pendulum System ◽  
Design And Optimization ◽  
Inverted Pendulum System ◽  
State Regulator ◽  
Output Controllability

Currently, many research studies reveal that for state regulator problems, the higher the degree of controllability is, the better the control effect likely is. Note that for the output regulator problems, the control performance is often evaluated by outputs. This article hence generalizes the concept and applications of degree of controllability to the case of output regulator. To this end, a kind of degree of output controllability is presented. Furthermore, simulations on wind turbines and the inverted pendulum system demonstrate that better control effect may be achieved by increasing the degree of output controllability measure. These results imply that similar to the case of degree of controllability for state regulation control, the degree of output controllability measure is likely a feasible candidate index for the design and optimization of the structural parameters of controlled plants in the case of output regulation control.

A newly combined code-designing method of two-dimensional signature codes for OCDMA system

2009 ◽  
Vol 5 (5) ◽  
pp. 372-375 ◽  
Author(s):  
Chuan-qi Li ◽  
Qing Xia ◽  
Yuan Zhang ◽  
Yuan-yuan Zhou
Keyword(s):  
Two Dimensional ◽  
Designing Method

Two-dimensional nesting system based on hybrid genetic algorithm

2009 ◽  
Vol 14 (1) ◽  
pp. 60-64
Author(s):  
Qingming Wu ◽  
Wei Yang ◽  
Qiang Zhang ◽  
Junjie Zhou
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Two Dimensional

Comparative studies of the set up of two-dimensional pneumatic arm systems by muscle and rotational actuators

2007 ◽  
Vol 221 (5) ◽  
pp. 743-748 ◽  
Author(s):  
Y-T Wang ◽  
R-H Wong ◽  
J-T Lu
Keyword(s):  
Control Systems ◽  
Fuzzy Controller ◽  
Control Algorithms ◽  
Two Dimensional ◽  
Pneumatic Control ◽  
Learning Mechanism ◽  
Set Up ◽  
And Control ◽  
Self Learning ◽  
System Characteristics

As opposed to traditional pneumatic linear actuators, muscle and rotational actuators are newly developed actuators in rotational and specified applications. In the current paper, these actuators are used to set up two-dimensional pneumatic arms, which are used mainly to simulate the excavator's motion. Fuzzy control algorithms are typically applied in pneumatic control systems owing to their non-linearities and ill-defined mathematical model. The self-organizing fuzzy controller, which includes a self-learning mechanism to modify fuzzy rules, is applied in these two-dimensional pneumatic arm control systems. Via a variety of trajectory tracking experiments, the present paper provides comparisons of system characteristics and control performances.

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