Genetic Algorithms in Engineering Systems
Genetic Algorithms in Engineering Systems
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
Classical and fuzzy-genetic autopilot design for unmanned aerial vehicles
Applied Soft Computing
Fuzzy sliding mode autopilot design for nonminimum phase and nonlinear UAV
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications
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A multi-objective evolutionary algorithm is used to determine the membership function distribution within the outer loop control system of a non-linear missile autopilot using lateral acceleration control. This produces a design that meets objectives related to closed loop performance such as: steady state error, overshoot, settling and rising time. The evolutionary algorithm uses non-dominated sorting for forming a Pareto front of possible solutions. This paper shows that fuzzy controllers can be produced for engineering problems, with the multi-objective algorithm allowing the designer the freedom to choose solutions and investigate the properties of very complex systems.