Dissertation > Excellent graduate degree dissertation topics show

Continuous the space ant colony algorithm and industrial process control

Author: MengYan
Tutor: LiuXiYu
School: Shandong Normal University
Course: Management Science and Engineering
Keywords: Ant colony optimization Continuous space optimization Variable metric Algorithm PID controller Fitness function
CLC: TP273
Type: Master's thesis
Year: 2009
Downloads: 105
Quote: 1
Read: Download Dissertation

Abstract


Optimization is an important branch of mathematics,and a wide range of disciplines of subject. For the purpose of the actual problem, the best program can be chosen from many programs. Recently, accompanied by the rapid development of computer technology and optimized methods, all kinds of theoretical study have developed and practical applications are increasingly widespread. Ant colony algorithm has been put forward only in recent years, which is a new type of simulated evolutionary algorithm. The biggest probability will eventually approach the optimal solution of the problem after several iterations.Ant Colony Optimization Algorithm (ACO) is a new stimulated evolutionary algorithm attacking hard combinatorial optimization problems. It has showed a great deal of salient character and performed great value in its application. Choosing the analysis of character of Ant System (the basic algorithms of ant colony) as the research background, this paper focuses on the principle, the model, the behavior and its characteristics. In this paper, a kind of ACO algorithm have been proposed for solving the continuous space optimization and PID controller parameters optimization in industrial process control. Finally the results obtained via computer simulation show its validity. The main works and innovations as follows:1. The biological mechanism, the development and character of the ant colony algorithm are outline. The current situations of research and application of the ant colony algorithm is introduced. The superiority in solving combinatorial optimization problems and the shortages in solving the continuous space optimization problems are presented; in this paper, we also introduce the principle, the model, the characteristics and the management about the basic algorithms of ant colony (Ant System). And a list of improvements of continuous space optimization has been referenced and presents;2. On the foundation of summarizing and analyzing the existing research results, many details of original Ant Algorithm model have been implemented, including the number of division space, the number of searching ants and other parameters.3. Facing the limitations of the random search in the solution space, we use the certainty search method, Variable Metric Algorithm, the improved algorithm VACA has been gotten. The improved algorithm has been applied to one-dimensional and multi-dimensional continuous function optimization. Compared with the simulation results of the original ACO, the effectiveness of the approach can have been proved.4. In this paper, PID controller parameters optimization can be realized using the improved algorithm, to verify the effectiveness of its practical application. And experiments show that optimization efficiency and quality has been improved.The ant colony algorithm is a kind of stochastic explorative algorithm which has showed many excellent characteristics. It is demonstrated that the ant colony algorithm is more adaptive to the genetic algorithms and the simulated annealing algorithms which were fashionable for a time. Although some successful applications have been presented, it also has many problems for solving and making further investigation. Ant colony algorithm, which is different from other heuristic algorithm, has not formed the theory system. Parameter selection relies on more experiments and experience. It takes more time to calculate and it is prone to stagnation which shows that the algorithm in theory and practice has many problems to solve and research.

Related Dissertations

  1. Single Neuron PID Control for Electro-Hydraulic Servo Unit of Ship Rudder,U666.152
  2. PID Controller Design of Linear Systems with Time Delay Based on Parametric Space and GUI Simulation,TP273
  3. Design of Fuzzy PID Controller Based on FPGA,TP273.4
  4. Research on WSN Routing Technology with Natural Computation,TN929.5
  5. Research on Classification and Matching for Hand Vein Image,TP391.41
  6. Research and Design of Intelligent PID Controller Based on Fuzzy Neural Networks,TP273.5
  7. The Grid Task Scheduling Strategy Research Based on Ant Immune Memory Optimization Algorithm,TP393.02
  8. The Design and Key Technical Analysis of Logistics Information Platform of Heilongjiang Province,F259.2;F253.9
  9. Research and Simulation of Main Steam Pressure Control System for Supercritical Once-through Boiler,TM621.6
  10. Ant Colony Optimization and Its Application to Blind Equalization,TN911.5
  11. Study on Brushless DC Motor Velocity Adjustment Control System Based on Fuzzy PID Optimized by PSO Algorithm,TM33
  12. Research and Development of Production and Scheduling System Base on IC Production Model,F273
  13. The Control Method Research and Design of Inverted Pendulum System,TP13
  14. Design and Realization on Control System of Green Anode Production,TP273
  15. Hydraulic excavator trajectory planning and control,TU621
  16. Experimental Research on the Multi-robot Plume Tracing Algorithms,TP242
  17. Based on the angle of the knee walker functional electrical stimulation Fuzzy Control,R651.2
  18. Energy-balanced Data Gathering Algorithms in Wireless Sensor Network,TN929.5
  19. Pitch Control Servo System in Mega-watt Class Wind Turbine,TM315
  20. Unbalanced three-phase power quality problems of,TM761.1
  21. Distributed target detection in wireless sensor network research,TP212.9

CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Automatic control,automatic control system
© 2012 www.DissertationTopic.Net  Mobile