Improved GA And Its Application In The Tension Control Of H Profiled Bar

Genetic algorithm (GA) is a random search method based on the biological evolution. It roots in the natural selection mechanism of the survival of the fittest. It is simple, robust and can be used in the parallel computation. Its global search performance is very excellent, but GA also has some shortcomings such as slow convergence speed, easy to be premature, bad local search capability. And it can't meet the requirements of search speed and solution precision simultaneously. In order to solve these problems, great deals of research works have been done in this thesis.After the introduction of the basic principles of GA, the arithmetic characters, the arithmetic process and its application, we explain operators in detail. Then we present two important indexes: the convergence time and the convergence generation.Some improved GAs are introduced. Such as Hierarchic Genetic Algorithm (HGA), CHC algorithm, messy Genetic Algorithm (MGA), Adaptive Genetic Algorithm (AGA), Niched GA, hybrid Genetic Algorithm (HGA) and parallel Genetic Algorithm (PGA) are mainly discussed. A new improved GA is proposed to design the parameters optimization of PID controller. It can be used to overcome the shortcomings of slow-convergence, easy-premature and incapability of optimization in the local area of classical genetic algorithm. This algorithm has both the capability of optimization in the global area and the capability of optimization of the direct search methods in the local area. It can avoid premature convergence, and ensure the obtained parameters are optimal.At last, the new improved genetic algorithm proposed in this thesis is applied to H profiled bar tension control system, in order to achieve tiny tension or naught tension control. The simulation result shows the PID controller greatly improved the search speed, and it also has a good dynamicquality and stability.