Multiobjective evolutionary algorithm for designing fuzzy-based missile guidance laws

In this paper, a strength Pareto evolutionary algorithm based approach is proposed for designing a multistage fuzzy-based guidance law which consists of three fuzzy controllers. Each of these controllers is activated in a region of the interception. The distribution of the membership functions and the rules are obtained by solving a nonlinear constrained multiobjective optimization problem where final time, energy consumption, and miss distance are treated as competing objectives. A hierarchical clustering technique is implemented to provide the decision maker with a representative and manageable Pareto-optimal set without destroying the characteristics of the trade-off front. Moreover, a fuzzy-based mechanism is employed to extract the best compromise solution over the trade-off curve. The simulation results show that the proposed design technique was able to generate a missile guidance law which has better performance than the classical proportional guidance law.