Research Of Artificial Immune Mechanism And It's Application In The Robot Control

The natural immune system is a very comlpex system with several organs, many tissues and billions of cells and molcules, the main roles of the biologic immune system are to recognize and eliminate foreign antigens (e.g., bacteria, virus, etc), and to act as a defensive barrier. From an information-processing perspective, the immune system is a highly parallel and distributed intelligent system that has learning, recognition, memory, and associative retrieval capabilities, for many field projects have instructive. In recent years, the artificial immune system (AIS), inspired by biologic immune system, has sprung up since it provides a powerful capability of information process and a novel paradigm of solving problem. Now they have been widely applied in many other areas and multi-objective optimization problems.This paper first introduced the robot and its control of the development process, followed by introduction of the immune system, clonal selection theory and typical applications, the immune system and in accordance with the principles of clonal selection, the artificial immune algorithm was improved, a choice based on memory Cloning The artificial immune algorithm for antibodies in the evolution of populations at the same time, the memory is to focus on clonal selection operation, imitating a more comprehensive selection process of cloning, the better to maintain the diversity of population, while improving the convergence rate. In a number of test function, will improve with the traditional method of genetic algorithm, the experimental results show that the improved algorithm can solve the more complex multi-peak search problems and find solutions closer to the optimal solution, and has a good convergence rate. Subsequently, the algorithm will be applied to improve the multi-objective function optimization, has also made good results.Finally, the degree of freedom dynamic model of the robot system for the study, focusing on the optimization of based on artificial immune nonlinear PID control strategy in the robot motion control on the use of numerical simulation of the proposed strategy for the effectiveness of control.