Research Of Chaotic Ant Swarm Optimization Algorithm And Its Applications

Most of the existing ant-inspired optimization algorithms are based on the random mechanism of non-deterministic probability theory. However, it has been suggested by biologist Cole that an ant colony exhibits a periodic behavior, while single ant show chaotic activity patterns. The chaotic phenomenon can not be explained by the mathematical model which is built based on probability theory of Marco Dorigo et al.. And the problem of how the chaotic behavior of single ant relates to the self-organizing and foraging behaviors of the ant colony has received little attention.Inspired by the chaotic behavior of single ant and self-organizing behavior of ant colony, we integrate the chaotic dynamics of ant, swarm organization with optimization mechanism and construct a new mathematical model of swarm intelligence optimization. We analyzed the nonlinear dynamical behaviors of the developed model in detail. Now the model has been applied in some diverse fields and achieved perfect effectiveness. Thus a new theory has been formed about the swarm intelligence optimization and chaos optimization. The main work and contribution of the present thesis are as follows:Firstly, based on the theories of swarm intelligence and chaos, a new mathematical optimization algorithm model, which is called chaotic ant swarm(CAS), is given and the information exchange mechanism in an ant colony is discussed. The dynamical behavior of the model is analyzed and is applied to the problem of numerical optimization. Under the same conditions, the results of particle swarm and Kalman swarm are compared. At the same time, similarities and differences among the new model and other chaos optimization algorithms, ant colony optimization algorithm, particle swarm algorithm are analyzed.Secondly, we introduce the proposed chaotic ant swarm optimization method to solve the training problems of neural networks and the design problem of fuzzy system to match desiredinput-output data pairs. Then the corresponding fuzzy system based on CAS optimization algorithm is built and applied to the identification and adaptive control of the unknown nonlinear dynamical systems.Thirdly, the proposed CAS optimization algorithm is used for the parameters tuning of PID controller. For the constructed optimization model, the objective function is the performance index of error integrality and the constrained conditions are the range of the designing parameter, the least gain and phase margin.Lastly, through the construction of a suitable fitness function, the problem of parameter estimation of the chaotic system is converted to a problem of parameter optimization1 which1 could be solved via chaotic ant swarm algorithm. Chaotic ant swarm algorithm has the ability'of global search. A numerical simulation on the well-known Lorenz chaotic system is conducted.Numerical simulation results are provided to show the effectiveness and feasibility of the developed CAS algorithm.