Research On Particle Swarm Optimization Algorithm And Its Application In Array Antenna

Particle swarm optimization (PSO) algorithm is a kind of heuristic optimization algorithm based on swarm iteration. It has become a new hotspot in the area of computation intelligence for the rapid convergence and simple implementation. Recent research has drawn attention to in-depth theoretical study and improvement due to its incomplete theoretical basis and premature convergence. We has made a deep study on convergence and stability of PSO, and then proposed a parameter choice strategy to enhance its dynamic characteristic in this thesis. Catfish-PSO algorithm is proposed to enhance the overall search ability and the convergence rate. The major research work can be summarized as follows:The convergence conditions and the state values are derived from Routh stability criterion and final value theorem. Based on the analysis of iterative process,we find that the particle positions are expected to converge to the optimal positions all the time when the accelerating factor is 2, and keep high concentration all through the whole optimization process when the acceleration factor is 1.85. To enhance the system stability, a universal strategy of parameter selection is proposed and its effectiveness is showed through functions tests. At the same time, a nonlinear function of decreasing inertia weight is presented to enhance the convergence efficiency by adjusting descending index.The effect of characteristic roots distribution on convergence trajectory of paticles is studied using linear discrete-time system analysis method in control theory. We find that the system output is the attenuation oscillation pulse sequence which will benefit to optimization when characteristic roots are complex. The dynamic behavior of the particle in convergence domain is theoretically explained applying theory of dynamic analysis in discrete-time systems. And we point out for the first time that the critical factors affecting the modulus value and the phase angle of the complex characteristic roots are the maximum overshoot and angular frequency of damped oscillation. Then the principle of parameters selection about PSO is proposed in order to improve the system dynamic characteristics. The principle is not only match the conditions of mean square convergence proposed by M. Jiang, but also match the best value program proposed by Fern′andez Mart′inez, and it is proved to be effective by simulation tests.A new algorithm of Catfish-PSO is proposed to enhance the global search ability and the convergence ability, and also to avoid premature convergence. The two concepts of deviation threshold and collision strength are used to adjust the exploration and exploitation ability of Catfish-PSO algorithm in order to optimize its performance. The effect of deviation threshold and collision strength on Catfish-PSO is studied using different trial functions. The new algorithm provides a new way of thinking to improve the performance of PSO algorithm.Smart antenna can improve the spectrum utilization efficiency and play an important role in mobile communications and other modern communications; moreover, the antenna synthesis becomes the core technology of smart antenna. The application of the new algorithm to the low-sidelobe pattern synthesis is presented.