Based On Improved Chaos Mapping Particle Swarm Optimization Algorithm And Its Application On Optimization Of Antenna Parameters

Chaos,relativity and quantum are also called the three major sciences of the 20 th century.Its advent makes people explore the mysteries of the universe and provide a new breakthrough.People can use certain methods to describe the natural phenomena that seem to be disorderly and chaotic in life.They can even control chaotic systems to make chaos become orderly and chaos tend to be regular.The chaotic sequence has good pseudo-randomness,is very sensitive to the initial value,and has the characteristics of fast divergence.It has a broad application prospect in the emerging intelligent optimization algorithms.Non-linear programming is a matter of mathematical programming,and mathematical programming is an old topic.In the 20 th century,the rapid development of computer technology provided hardware conditions for the emergence of many new nonlinear optimization algorithms.Many scholars have linked these concepts with the disciplines of mathematics,physics,and mechanics,and have developed various stochastic algorithms,including simulated annealing,genetic algorithms,and particle swarm algorithms.Among them,the particle swarm algorithm is an algorithm that simulates the behavior of a biological population to find food.Due to its easy implementation and powerful search capabilities,particle swarm optimization has become a research focus of many scholars.In this paper,the initial population in the particle swarm optimization algorithm is selected by chaotic mapping.In order to select the initial population quickly,rationally and without missing,this paper improves the traditional logistics mapping.Firstly,it proposes an improved logistics mapping(ILM),that is,the probability density from the mapping,in view of the inhomogeneous distribution characteristics of the logistics mapping traversal characteristics.The function starts by deriving the homogenizer formula to improve the mapping properties.Through simulation analysis,the data generated by the logistics map added to the regulator tends to be evenly distributed throughout the value interval.Further,in order to effectively improve the divergence rate of chaotic maps,cascade iterations are adopted to improve the chaotic dynamic equations.By analyzing the Lyapunov exponent of cascaded chaotic systems,it is proved that the cascading method can effectively improve the divergence speed of the system.Thirdly,this dissertation deeply studies the applicability of the ergodicity of chaotic systems in practical applications,and finds that its ergodicity is based on a global perspective.When taking a finite-length chaotic sequence,its ergodicity is limited.In a specific application,a determination condition should be set.Particle swarm optimization algorithm has its own initial population selection without regularity,it is easy to fall into local extremes and other defects in the late iteration,and the improved chaotic sequence has the characteristics of rapid divergence,strong ergodicity,and high randomness.In this paper,the particle swarm optimization algorithm is optimized based on the above improved chaotic sequence,and a homogenized cascaded chaotic particle swarm algorithm(ICPSO)is obtained.By performing linear transformation on the improved logistics sequence to initialize the particle position information and initial velocity information,the distribution of the particles is randomized and the variable's value space can be traversed.At the same time,the chaos of the optimal value in the population of particles in each iteration makes the particles “mutate”,thereby ensuring the diversity of particles in the iterative process.Finally,this paper applies the improved chaotic particle swarm optimization(ICPSO)algorithm to optimize the antenna parameters design.Using the MATLAB Antenna Toolbox to model the half-wave dipole antenna operating at 300 MHz and analyze its S11 diagram,then optimize the length and width of the antenna arm using the optimization algorithm to find the center frequency that can make the antenna work.The parameter size close to the expected frequency point,through the experimental simulation,found that the ICPSO algorithm has a good effect on the optimization of the half-wave dipole antenna and has high efficiency.