Designing integrated guidance law for aerodynamic missiles by hybrid multi-objective evolutionary algorithm and tabu search

In this paper, a strength Pareto evolutionary algorithm (SPEA) based approach is proposed for designing an integrated fuzzy 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 multi-objective optimization problem where final time, energy consumption, and miss distance are treated as competing objectives. Tabu search is proposed to build a library of initial feasible solutions for the multi-objective optimization algorithm. In addition, 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 with satisfactory performance with the existence of noisy measurements.